# Galactic transient sources with the Cherenkov Telescope Array

K. Abe${}^{\ref{AFFIL::JapanUTokai}}$ S.
Abe${}^{\ref{AFFIL::JapanUTokyoICRR}}$ J.
Abhir${}^{\ref{AFFIL::SwitzerlandETHZurich}}$ A.
Abhishek${}^{\ref{AFFIL::ItalyUSienaandINFN}}$ F.
Acero${}^{\ref{AFFIL::FranceCEAIRFUDAp},\ref{AFFIL::SpainFSLACIRLCNRSIAC}}$ A.
Acharyya${}^{\ref{AFFIL::USAUAlabamaTuscaloosa}}$ R.
Adam${}^{\ref{AFFIL::FranceOCotedAzur},\ref{AFFIL::FranceLLREcolePolytechnique}}$
A. Aguasca-Cabot${}^{\ref{AFFIL::SpainICCUB}}$ I.
Agudo${}^{\ref{AFFIL::SpainIAACSIC}}$ A. Aguirre-
Santaella${}^{\ref{AFFIL::UnitedKingdomICCUDurham}}$ J.
Alfaro${}^{\ref{AFFIL::ChileUPontificiaCatolicadeChile}}$ R.
Alfaro${}^{\ref{AFFIL::MexicoUNAMMexico}}$ N. Alvarez-
Crespo${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ R. Alves
Batista${}^{\ref{AFFIL::SpainIFTUAMCSIC}}$ J.-P.
Amans${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ E.
Amato${}^{\ref{AFFIL::ItalyOArcetri}}$ G.
Ambrosi${}^{\ref{AFFIL::ItalyUPerugiaandINFN}}$ F.
Ambrosino${}^{\ref{AFFIL::ItalyORoma}}$ E. O.
Angüner${}^{\ref{AFFIL::TurkeyTubitak}}$ L. A.
Antonelli${}^{\ref{AFFIL::ItalyORoma}}$ C.
Aramo${}^{\ref{AFFIL::ItalyINFNNapoli}}$ C.
Arcaro${}^{\ref{AFFIL::ItalyINFNPadova}}$ T. T. H.
Arnesen${}^{\ref{AFFIL::SpainIAC}}$ K.
Asano${}^{\ref{AFFIL::JapanUTokyoICRR}}$ Y.
Ascasibar${}^{\ref{AFFIL::SpainIFTUAMCSIC}}$ J.
Aschersleben${}^{\ref{AFFIL::NetherlandsUGroningen}}$ H.
Ashkar${}^{\ref{AFFIL::FranceLLREcolePolytechnique}}$ L. Augusto
Stuani${}^{\ref{AFFIL::BrazilIFSCUSaoPaulo}}$ D.
Baack${}^{\ref{AFFIL::GermanyUDortmundTU}}$ M.
Backes${}^{\ref{AFFIL::NamibiaUNamibia},\ref{AFFIL::SouthAfricaNWU}}$ C.
Balazs${}^{\ref{AFFIL::AustraliaUMonash}}$ M.
Balbo${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ A. Baquero
Larriva${}^{\ref{AFFIL::SpainUCMAltasEnergias},\ref{AFFIL::EcuadorUAzuay}}$ V.
Barbosa Martins${}^{\ref{AFFIL::GermanyDESY}}$ U. Barres de
Almeida${}^{\ref{AFFIL::BrazilCBPF},\ref{AFFIL::BrazilIAGUSaoPaulo}}$ J. A.
Barrio${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ L. Barrios-
Jiménez${}^{\ref{AFFIL::SpainIAC}}$ I.
Batković${}^{\ref{AFFIL::ItalyUPadovaandINFN}}$ R.
Batzofin${}^{\ref{AFFIL::GermanyUPotsdam}}$ J.
Baxter${}^{\ref{AFFIL::JapanUTokyoICRR}}$ J. Becerra
González${}^{\ref{AFFIL::SpainIAC}}$ J. Becker
Tjus${}^{\ref{AFFIL::GermanyUBochum}}$ R.
Belmont${}^{\ref{AFFIL::FranceCEAIRFUDApUParisCiteaffiliatedpersonnel}}$ W.
Benbow${}^{\ref{AFFIL::USACfAHarvardSmithsonian}}$ J.
Bernete${}^{\ref{AFFIL::SpainCIEMAT}}$ K.
Bernlöhr${}^{\ref{AFFIL::GermanyMPIK}}$ A. Berti${}^{\ref{AFFIL::GermanyMPP}}$
B. Bertucci${}^{\ref{AFFIL::ItalyUPerugiaandINFN}}$ V.
Beshley${}^{\ref{AFFIL::UkraineIAPMMLviv}}$ P.
Bhattacharjee${}^{\ref{AFFIL::FranceLAPPUSavoieMontBlanc}}$ S.
Bhattacharyya${}^{\ref{AFFIL::SloveniaUNovaGoricaCAC}}$ C.
Bigongiari${}^{\ref{AFFIL::ItalyORoma}}$ E.
Bissaldi${}^{\ref{AFFIL::ItalyPolitecnicoBari},\ref{AFFIL::ItalyINFNBari}}$ O.
Blanch${}^{\ref{AFFIL::SpainIFAEBIST}}$ J.
Blazek${}^{\ref{AFFIL::CzechRepublicFZU}}$ F.
Bocchino${}^{\ref{AFFIL::ItalyOPalermo}}$ C.
Boisson${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ J.
Bolmont${}^{\ref{AFFIL::FranceLPNHEUSorbonne}}$ G.
Bonnoli${}^{\ref{AFFIL::ItalyOBrera},\ref{AFFIL::ItalyINFNPisa}}$ A.
Bonollo${}^{\ref{AFFIL::ItalyIUSSPaviaINAF},\ref{AFFIL::ItalyUTrento}}$ P.
Bordas${}^{\ref{AFFIL::SpainICCUB}}$ Z.
Bosnjak${}^{\ref{AFFIL::CroatiaUZagreb}}$ E.
Bottacini${}^{\ref{AFFIL::ItalyUPadovaandINFN}}$ M.
Böttcher${}^{\ref{AFFIL::SouthAfricaNWU}}$ F.
Bradascio${}^{\ref{AFFIL::FranceCEAIRFUDPhP}}$ E.
Bronzini${}^{\ref{AFFIL::ItalyOASBologna}}$ A. M.
Brown${}^{\ref{AFFIL::UnitedKingdomUDurham}}$ G.
Brunelli${}^{\ref{AFFIL::ItalyOASBologna}}$ A.
Bulgarelli${}^{\ref{AFFIL::ItalyOASBologna}}$ I.
Burelli${}^{\ref{AFFIL::ItalyUUdineandINFNTrieste}}$ C. Burger-
Scheidlin${}^{\ref{AFFIL::IrelandDIAS}}$ L.
Burmistrov${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ M.
Burton${}^{\ref{AFFIL::UnitedKingdomArmaghObservatoryandPlanetarium},\ref{AFFIL::AustraliaUNewSouthWales}}$
M. Buscemi${}^{\ref{AFFIL::ItalyINFNCatania}}$ J.
Cailleux${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ A. Campoy-
Ordaz${}^{\ref{AFFIL::SpainUABandCERESIEEC}}$ B. K.
Cantlay${}^{\ref{AFFIL::ThailandUKasetsart},\ref{AFFIL::ThailandNARIT}}$ G.
Capasso${}^{\ref{AFFIL::ItalyOCapodimonte}}$ A.
Caproni${}^{\ref{AFFIL::BrazilUCidadeSPaulo}}$ R. Capuzzo-
Dolcetta${}^{\ref{AFFIL::ItalyORoma},\ref{AFFIL::ItalyURomaSapienza}}$ P.
Caraveo${}^{\ref{AFFIL::ItalyIASFMilano}}$ S.
Caroff${}^{\ref{AFFIL::FranceLAPPUSavoieMontBlanc}}$ A.
Carosi${}^{\ref{AFFIL::ItalyORoma}}$ R.
Carosi${}^{\ref{AFFIL::ItalyINFNPisa}}$ E.
Carquin${}^{\ref{AFFIL::ChileUTecnicaFedericoSantaMaria}}$ M.-S.
Carrasco${}^{\ref{AFFIL::FranceCPPMUAixMarseille}}$ E.
Cascone${}^{\ref{AFFIL::ItalyOCapodimonte}}$ F.
Cassol${}^{\ref{AFFIL::FranceCPPMUAixMarseille}}$ L.
Castaldini${}^{\ref{AFFIL::ItalyOASBologna}}$ N.
Castrejon${}^{\ref{AFFIL::SpainUAlcala}}$ A. J. Castro-
Tirado${}^{\ref{AFFIL::SpainIAACSIC}}$ D.
Cerasole${}^{\ref{AFFIL::ItalyUandINFNBari}}$ G.
Ceribella${}^{\ref{AFFIL::GermanyMPP}}$ M.
Cerruti${}^{\ref{AFFIL::FranceAPCUParisCite}}$ P. M.
Chadwick${}^{\ref{AFFIL::UnitedKingdomUDurham}}$ S.
Chaty${}^{\ref{AFFIL::FranceAPCUParisCite}}$ A. W.
Chen${}^{\ref{AFFIL::SouthAfricaUWitwatersrand}}$ M.
Chernyakova${}^{\ref{AFFIL::IrelandDCU}}$ A.
Chiavassa${}^{\ref{AFFIL::ItalyINFNTorino},\ref{AFFIL::ItalyUTorino}}$ J.
Chudoba${}^{\ref{AFFIL::CzechRepublicFZU}}$ L.
Chytka${}^{\ref{AFFIL::CzechRepublicFZU}}$ G. M.
Cicciari${}^{\ref{AFFIL::ItalyUPalermo},\ref{AFFIL::ItalyINFNCatania}}$ A.
Cifuentes${}^{\ref{AFFIL::SpainCIEMAT}}$ C. H. Coimbra
Araujo${}^{\ref{AFFIL::BrazilUFPR}}$ M.
Colapietro${}^{\ref{AFFIL::ItalyOCapodimonte}}$ V.
Conforti${}^{\ref{AFFIL::ItalyOASBologna}}$ J. L.
Contreras${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ J.
Cortina${}^{\ref{AFFIL::SpainCIEMAT}}$ A.
Costa${}^{\ref{AFFIL::ItalyOCatania}}$ H.
Costantini${}^{\ref{AFFIL::FranceCPPMUAixMarseille}}$ G.
Cotter${}^{\ref{AFFIL::UnitedKingdomUOxford}}$ P.
Cristofari${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ O.
Cuevas${}^{\ref{AFFIL::ChileUdeValparaiso}}$ Z. Curtis-
Ginsberg${}^{\ref{AFFIL::USAUWisconsin}}$ A.
D’Aì${}^{\ref{AFFIL::ItalyIASFPalermo}}$ G.
D’Amico${}^{\ref{AFFIL::NorwayUBergen}}$ F.
D’Ammando${}^{\ref{AFFIL::ItalyRadioastronomiaINAF}}$ S.
Dai${}^{\ref{AFFIL::AustraliaUWesternSydney}}$ F.
Dazzi${}^{\ref{AFFIL::ItalyINAF}}$ M. de Bony de
Lavergne${}^{\ref{AFFIL::FranceCEAIRFUDAp}}$ V. De
Caprio${}^{\ref{AFFIL::ItalyOCapodimonte}}$ G. De
Cesare${}^{\ref{AFFIL::ItalyOASBologna}}$ F. De Frondat
Laadim${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ E. M. de Gouveia Dal
Pino${}^{\ref{AFFIL::BrazilIAGUSaoPaulo}}$ B. De
Lotto${}^{\ref{AFFIL::ItalyUUdineandINFNTrieste}}$ M. De
Lucia${}^{\ref{AFFIL::ItalyINFNNapoli}}$ D. de
Martino${}^{\ref{AFFIL::ItalyOCapodimonte}}$ R. de
Menezes${}^{\ref{AFFIL::ItalyINFNTorino},\ref{AFFIL::ItalyUTorino}}$ M. de
Naurois${}^{\ref{AFFIL::FranceLLREcolePolytechnique}}$ E. de Ona
Wilhelmi${}^{\ref{AFFIL::GermanyDESY}}$ V. de
Souza${}^{\ref{AFFIL::BrazilIFSCUSaoPaulo}}$ L. del
Peral${}^{\ref{AFFIL::SpainUAlcala}}$ M. V. del
Valle${}^{\ref{AFFIL::BrazilIAGUSaoPaulo}}$ C.
Delgado${}^{\ref{AFFIL::SpainCIEMAT}}$ M.
Dell’aiera${}^{\ref{AFFIL::FranceLAPPUSavoieMontBlanc}}$ M. Della
Valle${}^{\ref{AFFIL::ItalyOCapodimonte},\ref{AFFIL::ItalyINFNNapoli}}$ D.
della Volpe${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ D.
Depaoli${}^{\ref{AFFIL::GermanyMPIK}}$ J.
Devin${}^{\ref{AFFIL::FranceLUPMUMontpellier}}$ T. Di
Girolamo${}^{\ref{AFFIL::ItalyUNapoli},\ref{AFFIL::ItalyINFNNapoli}}$ A. Di
Piano${}^{\ref{AFFIL::ItalyOASBologna},\ref{AFFIL::ItalyUModena}}$ F. Di
Pierro${}^{\ref{AFFIL::ItalyINFNTorino}}$ R. Di
Tria${}^{\ref{AFFIL::ItalyUandINFNBari}}$ L. Di
Venere${}^{\ref{AFFIL::ItalyINFNBari}}$ S.
Diebold${}^{\ref{AFFIL::GermanyIAAT}}$ R.
Dima${}^{\ref{AFFIL::ItalyUPadovaandINFN}}$ A.
Dinesh${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ J.
Djuvsland${}^{\ref{AFFIL::NorwayUBergen}}$ R. M.
Dominik${}^{\ref{AFFIL::GermanyUDortmundTU}}$ D. Dominis
Prester${}^{\ref{AFFIL::CroatiaURijeka}}$ A.
Donini${}^{\ref{AFFIL::ItalyORoma}}$ D.
Dorner${}^{\ref{AFFIL::GermanyUWurzburg},\ref{AFFIL::SwitzerlandETHZurich}}$
J. Dörner${}^{\ref{AFFIL::GermanyUBochum}}$ M.
Doro${}^{\ref{AFFIL::ItalyUPadovaandINFN}}$ C.
Dubos${}^{\ref{AFFIL::FranceIJCLab}}$ L. Ducci${}^{\ref{AFFIL::GermanyIAAT}}$
V. V. Dwarkadas${}^{\ref{AFFIL::USAUChicagoDAA}}$ J.
Ebr${}^{\ref{AFFIL::CzechRepublicFZU}}$ C.
Eckner${}^{\ref{AFFIL::SloveniaUNovaGoricaCAC},\ref{AFFIL::FranceLAPTh}}$ K.
Egberts${}^{\ref{AFFIL::GermanyUPotsdam}}$ S.
Einecke${}^{\ref{AFFIL::AustraliaUAdelaide}}$ D.
Elsässer${}^{\ref{AFFIL::GermanyUDortmundTU}}$ G.
Emery${}^{\ref{AFFIL::FranceCPPMUAixMarseille}}$ M.
Errando${}^{\ref{AFFIL::USAWashingtonU}}$ C.
Escanuela${}^{\ref{AFFIL::GermanyMPIK}}$ P.
Escarate${}^{\ref{AFFIL::ChileEscIngElec}}$ M. Escobar
Godoy${}^{\ref{AFFIL::USASCIPP}}$ J. Escudero
Pedrosa${}^{\ref{AFFIL::SpainIAACSIC}}$ P.
Esposito${}^{\ref{AFFIL::ItalyIUSSPaviaINAF},\ref{AFFIL::ItalyIASFMilano}}$ D.
Falceta-Goncalves${}^{\ref{AFFIL::BrazilEACHUSaoPaulo}}$ S.
Fegan${}^{\ref{AFFIL::FranceLLREcolePolytechnique}}$ Q.
Feng${}^{\ref{AFFIL::USAUUtah}}$ G.
Ferrand${}^{\ref{AFFIL::CanadaUManitoba},\ref{AFFIL::JapanRIKEN}}$ F.
Ferrarotto${}^{\ref{AFFIL::ItalyINFNRomaLaSapienza}}$ E.
Fiandrini${}^{\ref{AFFIL::ItalyUPerugiaandINFN}}$ A.
Fiasson${}^{\ref{AFFIL::FranceLAPPUSavoieMontBlanc}}$ M.
Filipovic${}^{\ref{AFFIL::AustraliaUWesternSydney}}$ V.
Fioretti${}^{\ref{AFFIL::ItalyOASBologna}}$ M.
Fiori${}^{\ref{AFFIL::ItalyOPadova}}$ H.
Flores${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ L.
Foffano${}^{\ref{AFFIL::ItalyIAPS}}$ L. Font
Guiteras${}^{\ref{AFFIL::SpainUABandCERESIEEC}}$ G.
Fontaine${}^{\ref{AFFIL::FranceLLREcolePolytechnique}}$ A.
Franckowiak${}^{\ref{AFFIL::GermanyUBochumPhysAst}}$ S.
Fröse${}^{\ref{AFFIL::GermanyUDortmundTU}}$ Y.
Fukazawa${}^{\ref{AFFIL::JapanUHiroshima}}$ Y.
Fukui${}^{\ref{AFFIL::JapanUNagoya}}$ S.
Funk${}^{\ref{AFFIL::GermanyUErlangenECAP}}$ A.
Furniss${}^{\ref{AFFIL::USASCIPP}}$ G.
Galanti${}^{\ref{AFFIL::ItalyIASFMilano}}$ G.
Galaz${}^{\ref{AFFIL::ChileUPontificiaCatolicadeChile}}$ C.
Galelli${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ Y. A.
Gallant${}^{\ref{AFFIL::FranceLUPMUMontpellier}}$ S.
Gallozzi${}^{\ref{AFFIL::ItalyORoma}}$ V.
Gammaldi${}^{\ref{AFFIL::SpainUniversidadSanPabloCEU},\ref{AFFIL::SpainIFTUAMCSIC}}$
M. Garczarczyk${}^{\ref{AFFIL::GermanyDESY}}$ C.
Gasbarra${}^{\ref{AFFIL::ItalyINFNRomaTorVergata}}$ D.
Gasparrini${}^{\ref{AFFIL::ItalyINFNRomaTorVergata}}$ M.
Gaug${}^{\ref{AFFIL::SpainUABandCERESIEEC}}$ A.
Ghalumyan${}^{\ref{AFFIL::ArmeniaNSLAlikhanyan}}$ F.
Gianotti${}^{\ref{AFFIL::ItalyOASBologna}}$ M.
Giarrusso${}^{\ref{AFFIL::ItalyINFNCatania}}$ J. G. Giesbrecht Formiga
Paiva${}^{\ref{AFFIL::BrazilCBPF}}$ N.
Giglietto${}^{\ref{AFFIL::ItalyPolitecnicoBari},\ref{AFFIL::ItalyINFNBari}}$
F. Giordano${}^{\ref{AFFIL::ItalyUandINFNBari}}$ M.
Giroletti${}^{\ref{AFFIL::ItalyRadioastronomiaINAF}}$ R.
Giuffrida${}^{\ref{AFFIL::ItalyOPalermo}}$ A.
Giuliani${}^{\ref{AFFIL::ItalyIASFMilano}}$ J.-F.
Glicenstein${}^{\ref{AFFIL::FranceCEAIRFUDPhP}}$ J.
Glombitza${}^{\ref{AFFIL::GermanyUErlangenECAP}}$ P.
Goldoni${}^{\ref{AFFIL::FranceAPCUParisCiteCEAaffiliatedpersonnel}}$ J. M.
González${}^{\ref{AFFIL::ChileUAndresBello}}$ M. M.
González${}^{\ref{AFFIL::MexicoUNAMMexico}}$ J. Goulart
Coelho${}^{\ref{AFFIL::BrazilUFES}}$ T.
Gradetzke${}^{\ref{AFFIL::GermanyUDortmundTU}}$ J.
Granot${}^{\ref{AFFIL::IsraelOpenUniversityofIsrael},\ref{AFFIL::USAGWUWashingtonDC}}$
R. Grau${}^{\ref{AFFIL::SpainIFAEBIST}}$ L.
Gréaux${}^{\ref{AFFIL::FranceIJCLab}}$ D. Green${}^{\ref{AFFIL::GermanyMPP}}$
J. G. Green${}^{\ref{AFFIL::GermanyMPP}}$ T.
Greenshaw${}^{\ref{AFFIL::UnitedKingdomULiverpool}}$ I.
Grenier${}^{\ref{AFFIL::FranceCEAIRFUDApUParisCiteaffiliatedpersonnel}}$ G.
Grolleron${}^{\ref{AFFIL::FranceLPNHEUSorbonne}}$ J.
Grube${}^{\ref{AFFIL::UnitedKingdomKingsCollege}}$ O.
Gueta${}^{\ref{AFFIL::ItalyCTAOBologna}}$ J.
Hackfeld${}^{\ref{AFFIL::GermanyUBochum},\ref{AFFIL::GermanyUDortmundTU}}$ D.
Hadasch${}^{\ref{AFFIL::JapanUTokyoICRR}}$ P.
Hamal${}^{\ref{AFFIL::CzechRepublicFZU}}$ W.
Hanlon${}^{\ref{AFFIL::USACfAHarvardSmithsonian}}$ S.
Hara${}^{\ref{AFFIL::JapanUYamanashiGakuin}}$ V. M.
Harvey${}^{\ref{AFFIL::AustraliaUAdelaide}}$ T.
Hassan${}^{\ref{AFFIL::SpainCIEMAT}}$ K.
Hayashi${}^{\ref{AFFIL::JapanNITSendaiNatori},\ref{AFFIL::JapanUTokyoICRR}}$
B. Heß${}^{\ref{AFFIL::GermanyIAAT}}$ L.
Heckmann${}^{\ref{AFFIL::GermanyMPP},\ref{AFFIL::AustriaUInnsbruck}}$ M.
Heller${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ J.
Hinton${}^{\ref{AFFIL::GermanyMPIK}}$ N.
Hiroshima${}^{\ref{AFFIL::JapanUTokyoICRR},\ref{AFFIL::JapanUYokohamaNational}}$
B. Hnatyk${}^{\ref{AFFIL::UkraineAstObsofUKyiv}}$ R.
Hnatyk${}^{\ref{AFFIL::UkraineAstObsofUKyiv}}$ W.
Hofmann${}^{\ref{AFFIL::GermanyMPIK}}$ D.
Horan${}^{\ref{AFFIL::FranceLLREcolePolytechnique}}$ P.
Horvath${}^{\ref{AFFIL::CzechRepublicUOlomouc}}$ T.
Hovatta${}^{\ref{AFFIL::FinlandFINCA},\ref{AFFIL::FinlandUAalto}}$ M.
Hrabovsky${}^{\ref{AFFIL::CzechRepublicUOlomouc}}$ D.
Hrupec${}^{\ref{AFFIL::CroatiaUOsijek}}$ M.
Iarlori${}^{\ref{AFFIL::ItalyCETEMPSandUandINFNAquila}}$ T.
Inada${}^{\ref{AFFIL::JapanUTokyoICRR}}$ F.
Incardona${}^{\ref{AFFIL::ItalyOCatania}}$ S.
Inoue${}^{\ref{AFFIL::JapanUChiba},\ref{AFFIL::JapanUTokyoICRR}}$ Y.
Inoue${}^{\ref{AFFIL::JapanUOsaka},\ref{AFFIL::JapanRIKEN}}$ F.
Iocco${}^{\ref{AFFIL::ItalyUNapoli},\ref{AFFIL::ItalyINFNNapoli}}$ A.
Iuliano${}^{\ref{AFFIL::ItalyINFNNapoli}}$ M.
Jamrozy${}^{\ref{AFFIL::PolandUJagiellonian}}$ P.
Janecek${}^{\ref{AFFIL::CzechRepublicFZU}}$ F.
Jankowsky${}^{\ref{AFFIL::GermanyLSW}}$ P.
Jean${}^{\ref{AFFIL::FranceIRAPUToulouse}}$ I. Jiménez
Martínez${}^{\ref{AFFIL::GermanyMPP}}$ J. Jimenez
Quiles${}^{\ref{AFFIL::SpainIFAEBIST}}$ W. Jin${}^{\ref{AFFIL::USAUCLA}}$ C.
Juramy-Gilles${}^{\ref{AFFIL::FranceLPNHEUSorbonne}}$ J.
Jurysek${}^{\ref{AFFIL::CzechRepublicFZU}}$ O.
Kalekin${}^{\ref{AFFIL::GermanyUErlangenECAP}}$ D.
Kantzas${}^{\ref{AFFIL::FranceLAPTh}}$ V.
Karas${}^{\ref{AFFIL::CzechRepublicASU}}$ H.
Katagiri${}^{\ref{AFFIL::JapanUIbaraki}}$ J.
Kataoka${}^{\ref{AFFIL::JapanUWaseda}}$ S.
Kaufmann${}^{\ref{AFFIL::UnitedKingdomUDurham}}$ D.
Kerszberg${}^{\ref{AFFIL::SpainIFAEBIST}}$ B.
Khélifi${}^{\ref{AFFIL::FranceAPCUParisCite}}$ D. B.
Kieda${}^{\ref{AFFIL::USAUUtah}}$ R.
Kissmann${}^{\ref{AFFIL::AustriaUInnsbruck}}$ T.
Kleiner${}^{\ref{AFFIL::GermanyDESY}}$ G. Kluge${}^{\ref{AFFIL::NorwayUOslo}}$
W. Kluźniak${}^{\ref{AFFIL::PolandNicolausCopernicusAstronomicalCenter}}$ Y.
Kobayashi${}^{\ref{AFFIL::JapanUChiba},\ref{AFFIL::JapanUTokyoICRR}}$ K.
Kohri${}^{\ref{AFFIL::JapanNAOJ},\ref{AFFIL::JapanKEK}}$ N.
Komin${}^{\ref{AFFIL::SouthAfricaUWitwatersrand}}$ A.
Kong${}^{\ref{AFFIL::JapanUTokyoICRR}}$ P.
Kornecki${}^{\ref{AFFIL::FranceObservatoiredeParis}}$ K.
Kosack${}^{\ref{AFFIL::FranceCEAIRFUDAp}}$ D.
Kostunin${}^{\ref{AFFIL::GermanyDESY}}$ G.
Kowal${}^{\ref{AFFIL::BrazilEACHUSaoPaulo}}$ H.
Kubo${}^{\ref{AFFIL::JapanUTokyoICRR}}$ J.
Kushida${}^{\ref{AFFIL::JapanUTokai}}$ A. La
Barbera${}^{\ref{AFFIL::ItalyIASFPalermo}}$ N. La
Palombara${}^{\ref{AFFIL::ItalyIASFMilano}}$ M.
Láinez${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ A.
Lamastra${}^{\ref{AFFIL::ItalyORoma}}$ J.
Lapington${}^{\ref{AFFIL::UnitedKingdomULeicester}}$ S.
Lazarević${}^{\ref{AFFIL::AustraliaUWesternSydney}}$ J. Lazendic-
Galloway${}^{\ref{AFFIL::AustraliaUMonash}}$ M. Lemoine-
Goumard${}^{\ref{AFFIL::FranceLP2IUBordeaux}}$ J.-P.
Lenain${}^{\ref{AFFIL::FranceLPNHEUSorbonne}}$ F.
Leone${}^{\ref{AFFIL::ItalyUCatania}}$ E.
Leonora${}^{\ref{AFFIL::ItalyINFNCatania}}$ G.
Leto${}^{\ref{AFFIL::ItalyOCatania}}$ E.
Lindfors${}^{\ref{AFFIL::FinlandUTurku}}$ I.
Liodakis${}^{\ref{AFFIL::FinlandFINCA}}$ S.
Lloyd${}^{\ref{AFFIL::UnitedKingdomUDurham}}$ S.
Lombardi${}^{\ref{AFFIL::ItalyORoma},\ref{AFFIL::ASISpaceScienceDataCenter}}$
F. Longo${}^{\ref{AFFIL::ItalyUandINFNTrieste}}$ R. López-
Coto${}^{\ref{AFFIL::SpainIAACSIC}}$ M. López-
Moya${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ A. López-
Oramas${}^{\ref{AFFIL::SpainIAC}}$ S.
Loporchio${}^{\ref{AFFIL::ItalyPolitecnicoBari},\ref{AFFIL::ItalyINFNBari}}$
J. Lozano Bahilo${}^{\ref{AFFIL::SpainUAlcala}}$ F.
Lucarelli${}^{\ref{AFFIL::ItalyORoma}}$ P. L. Luque-
Escamilla${}^{\ref{AFFIL::SpainUJaen}}$ E.
Lyard${}^{\ref{AFFIL::SwitzerlandUGenevaISDC}}$ O.
Macias${}^{\ref{AFFIL::NetherlandsUAmsterdam}}$ J.
Mackey${}^{\ref{AFFIL::IrelandDIAS}}$ G. Maier${}^{\ref{AFFIL::GermanyDESY}}$
P. Majumdar${}^{\ref{AFFIL::IndiaSahaInstitute}}$ M.
Makariev${}^{\ref{AFFIL::BulgariaINRNEBAS}}$ M.
Mallamaci${}^{\ref{AFFIL::ItalyUPalermo},\ref{AFFIL::ItalyINFNCatania}}$ D.
Mandat${}^{\ref{AFFIL::CzechRepublicFZU}}$ M.
Manganaro${}^{\ref{AFFIL::CroatiaURijeka}}$ G.
Manicò${}^{\ref{AFFIL::ItalyINFNCatania},\ref{AFFIL::ItalyUCatania}}$ P.
Marinos${}^{\ref{AFFIL::USAStanford}}$ M.
Mariotti${}^{\ref{AFFIL::ItalyUPadovaandINFN}}$ S.
Markoff${}^{\ref{AFFIL::NetherlandsUAmsterdam}}$ I.
Márquez${}^{\ref{AFFIL::SpainIAACSIC}}$ P.
Marquez${}^{\ref{AFFIL::SpainIFAEBIST}}$ G.
Marsella${}^{\ref{AFFIL::ItalyUPalermo},\ref{AFFIL::ItalyINFNCatania}}$ G. A.
Martínez${}^{\ref{AFFIL::SpainCIEMAT}}$ M.
Martínez${}^{\ref{AFFIL::SpainIFAEBIST}}$ O.
Martinez${}^{\ref{AFFIL::SpainUCMElectronica},\ref{AFFIL::SpainUPCMadrid}}$ C.
Marty${}^{\ref{AFFIL::FranceIRAPUToulouse}}$ A. Mas-
Aguilar${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ M.
Mastropietro${}^{\ref{AFFIL::ItalyORoma}}$ G.
Maurin${}^{\ref{AFFIL::FranceLAPPUSavoieMontBlanc}}$ D.
Mazin${}^{\ref{AFFIL::JapanUTokyoICRR},\ref{AFFIL::GermanyMPP}}$ S.
McKeague${}^{\ref{AFFIL::IrelandDCU}}$ D.
Melkumyan${}^{\ref{AFFIL::GermanyDESY}}$ S.
Menchiari${}^{\ref{AFFIL::SpainIAACSIC},\ref{AFFIL::ItalyOArcetri}}$ S.
Mereghetti${}^{\ref{AFFIL::ItalyIASFMilano}}$ E.
Mestre${}^{\ref{AFFIL::SpainICECSIC}}$ J.-L.
Meunier${}^{\ref{AFFIL::FranceLPNHEUSorbonne}}$ D. M.-A.
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Miceli${}^{\ref{AFFIL::ItalyINFNPadova}}$ M.
Miceli${}^{\ref{AFFIL::ItalyUPalermo},\ref{AFFIL::ItalyOPalermo}}$ M.
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Michałowski${}^{\ref{AFFIL::PolandIFJ}}$ T.
Miener${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ J. M.
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Mizote${}^{\ref{AFFIL::JapanUKonan}}$ T. Mizuno${}^{\ref{AFFIL::JapanHASC}}$
R. Moderski${}^{\ref{AFFIL::PolandNicolausCopernicusAstronomicalCenter}}$ L.
Mohrmann${}^{\ref{AFFIL::GermanyMPIK}}$ M. Molero${}^{\ref{AFFIL::SpainIAC}}$
C. Molfese${}^{\ref{AFFIL::ItalyINAF}}$ E. Molina${}^{\ref{AFFIL::SpainIAC}}$
T. Montaruli${}^{\ref{AFFIL::SwitzerlandUGenevaDPNC}}$ A.
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Moulin${}^{\ref{AFFIL::FranceCEAIRFUDPhP}}$ V. Moya
Zamanillo${}^{\ref{AFFIL::SpainUCMAltasEnergias}}$ K.
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Muraczewski${}^{\ref{AFFIL::PolandNicolausCopernicusAstronomicalCenter}}$ H.
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Nagataki${}^{\ref{AFFIL::JapanRIKEN}}$ T.
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Nava${}^{\ref{AFFIL::ItalyOBrera}}$ A.
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Nemmen${}^{\ref{AFFIL::BrazilIAGUSaoPaulo},\ref{AFFIL::USAStanford}}$ J. P.
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Živec${}^{\ref{AFFIL::SloveniaUNovaGoricaCAC}}$ J. Zuriaga-
Puig${}^{\ref{AFFIL::SpainIFTUAMCSIC}}$

_Affiliations can be found at the end of the article_<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

A wide variety of Galactic sources show transient emission at soft and hard
X-ray energies: low-mass and high-mass X-ray binaries containing compact
objects (e.g., novae, microquasars, transitional millisecond pulsars,
supergiant fast X-ray transients), isolated neutron stars exhibiting extreme
variability as magnetars as well as pulsar wind nebulae. Although most of them
can show emission up to MeV and/or GeV energies, many have not yet been
detected in the TeV domain by Imaging Atmospheric Cherenkov Telescopes. In
this paper, we explore the feasibility of detecting new Galactic transients
with the Cherenkov Telescope Array (CTA) and the prospects for studying them
with Target of Opportunity observations. We show that CTA will likely detect
new sources in the TeV regime, such as the massive microquasars in the Cygnus
region, low-mass X-ray binaries with low-viewing angle, flaring emission from
the Crab pulsar-wind nebula or other novae explosions, among others. We also
discuss the multi-wavelength synergies with other instruments and large
astronomical facilities.

###### keywords:

gamma-rays:general – transients – binaries: general – pulsars:general –
stars:novae – stars:magnetars

††pubyear: 2024††pagerange: Galactic transient sources with the Cherenkov
Telescope Array–Galactic transient sources with the Cherenkov Telescope Array

##  1 Introduction

Timing astronomy and variability studies have proven to be a powerful tool to
study extreme astrophysical processes at very high energies (VHE, E$>$ 100
GeV). The improvement of the Imaging Atmospheric Cherenkov Technique (IACT)
over the past decade has revealed new transient phenomena with variability
timescales from seconds to several weeks. The last generation of IACTs have
discovered several classes of transient TeV sources such as gamma-ray bursts
(GRBs) (MAGIC Collaboration et al., 2019; Abdalla et al., 2019), flaring
blazars associated with high-energy neutrino sources (IceCube Collaboration et
al., 2018) or Galactic novae (H. E. S. S. Collaboration et al., 2022; Acciari
et al., 2022), among others, unveiling new types of VHE emitters with highly
variable fluxes.

The Cherenkov Telescope Array (CTA) will be the next generation ground-based
observatory for VHE astronomy. It will allow the detection of gamma rays in
the 20 GeV-300 TeV domain, with two observatory sites, one in the Northern
hemisphere (CTA-N; Observatorio Roque de los Muchachos, La Palma, Spain) and
another in the Southern one (CTA-S; Paranal, Chile). It will provide an
improved sensitivity with respect to the current generation of IACTs of of
about an order of magnitude (Cherenkov Telescope Array Consortium et al.,
2019). Of special importance will be the sensitivity of CTA to short-timescale
phenomena111For CTA performance, see: https://www.cta-
observatory.org/science/ctao-performance/. CTA will have 104-105 better
sensitivity than the LAT instrument onboard the Fermi satellite for the
detection of short-duration transient events (Funk et al., 2013).

The low energy threshold of $\sim$20 GeV of the largest telescopes of the
array, the Large-Sized Telescopes (LSTs; CTA-LST Project et al., 2023) is key
for the detection of new transient sources at the lower end of the VHE regime.
This capability, together with the fast slewing response of the LSTs, which
can be re-pointed in about 20 seconds, will allow a swift reaction to
transient events. The Medium and Small Sized telescopes (MSTs and SSTs) will
also be key to understand the emission of this sources at higher energies.
Finally, since the CTA observatory will consist of two arrays located in two
hemispheres, it will provide a better and more continuous coverage of many
transient events accessible from both sites.

The core program of CTA will consist of different Key Science Projects (KSPs)
which were considered to address the science questions of CTA (see Cherenkov
Telescope Array Consortium et al., 2019 for more details). The Transients KSP
is proposed to encompass the follow-up observations of several classes of
targets such as GRBs, gravitational waves (GWs), high-energy neutrinos, core-
collapse supernovae (CCSNe) and Galactic transients.

In this paper, we focus on Galactic sources hosting compact objects whose
emission is not periodic and/or that display unexpected flaring events,
outflows or jets as described in Cherenkov Telescope Array Consortium et al.
(2019). Extragalactic transient events such as GRBs, core-collapse SNe or GWs
will be addressed in separate publications. We discuss the capabilities of CTA
to detect new transient phenomena at VHE from sources of Galactic origin,
ranging from microquasars, to pulsar-wind nebulae (PWNe) flares, to novae,
transitional millisecond pulsars or magnetars among others. For our
simulations, we have used the software packages `ctools` 222``ctools+ is a
software specifically developed for the scientific analysis of gamma-ray data,
see http://cta.irap.omp.eu/ctools/index.html (Knödlseder et al., 2016) and
`Gammapy`333 ``Gammapy— is an open-source Python package developed for gamma-
ray astronomy, see https://gammapy.org/ (Donath et al., 2023; Aguasca-Cabot et
al., 2023) with the official CTA observatory instrument response functions
(IRFs).444The IRF version ``prod3b-v2+ is the one used throughout the
manuscript, unless otherwise specified. The newest ``prod5+ version
corresponding to the Alpha Configuration, which corresponds to the first stage
of CTA observatory construction has also been tested in some science cases and
are specified in the text. For a full description of CTA observatory IRFs and
configurations see Maier et al. (2023).

The sources of our interest are described in the following Subsections
1.1-1.6. We present the sensitivity of CTA to Galactic transient detection in
Section 2 and population studies in Section 3. The simulations, analysis
results and discussion for each type of transient are collected in Section 4.
Section 5 describes the synergies with multi-wavelength and multi-messenger
astronomical facilities. The summary and final conclusions are listed in
Section 6.

###  1.1 Microquasars

Microquasars are binary systems with a compact object (NS or a BH) orbiting
around and accreting material from a companion star. The matter lost from the
star can lead to formation of an accretion disk around the compact object and
a relativistic collimated jet (Mirabel & Rodríguez, 1998).

At the moment more than 20 microquasars are known in the Galaxy (see i.e.
Corral-Santana et al., 2016). Observations demonstrated correlations between
the mass of the compact object, radio (5 GHz) and X-ray (2–10 keV)
luminosities (e.g. Falcke et al., 2004), strengthening the link between active
galactic nuclei (AGNs) and microquasars. In AGNs, jets are known to be places
of efficient particle acceleration and produce broad band non-thermal
emission. The resulting radiation can extend from radio up to the VHE band.
According to TeVCat 555http://tevcat2.uchicago.edu/ more than 65 AGNs have
been already detected by current IACTs. If similar jet production and particle
acceleration mechanisms operate in microquasars and AGNs, this might imply
that microquasars should be sources of VHE $\gamma$-ray emission as well.

Up to now, only three microquasars have been detected in the high-energy (HE,
E$>$100 MeV) domain: Cygnus X-1 (Bulgarelli et al., 2010; Sabatini et al.,
2010, 2013; Malyshev et al., 2013; Zanin et al., 2016; Zdziarski et al.,
2017), Cygnus X-3 (Tavani et al., 2009; Fermi LAT Collaboration et al., 2009;
Zdziarski et al., 2018), and SS 433 (Bordas et al., 2015; Sun et al., 2019;
Rasul et al., 2019; Xing et al., 2019; Li et al., 2020). Steady VHE emission
was detected from the interaction regions between the jet and the surrounding
nebula in SS 433 (Abeysekara et al., 2018a; H. E. S. S. Collaboration et al.,
2024). Furthermore, HAWC has announced the TeV detection of the microblazar
V4641 Sgr with 7 years of data (Tibolla, 2023). A strong hint of transient
emission was found at VHE in Cygnus X-1 (Albert et al., 2007). Strong hints of
HE emission were also found in the low-mass X-ray binary V404 Cyg during its
2015 outburst (Loh et al., 2016; Piano et al., 2017). The expectations for the
detection of both massive microquasars and low-mass X-ray binaries (LMXBs)
with CTA are presented in Sections 4.1-4.2.

The relevance for studying gamma-ray binaries and microquasars has already
been addressed by Paredes et al. (2013). In this paper, we do not focus on
gamma-ray binaries displaying periodic orbital variability, but only on
microquasars, to better investigate the potential VHE emission of this class
of binaries for which only SS 433 has been confirmed as a VHE emitter. We
discuss high-mass microquasars (Section 4.1) separately to low-mass X-ray
binaries (Section 4.2).

###  1.2 Transitional millisecond pulsars

Transitional millisecond pulsars (tMSPs) are a class of neutron star binaries
that has emerged in the last decade with the discoveries of three confirmed
systems: PSR J1023+0038 (Archibald et al., 2009a; Patruno et al., 2014a), XSS
J1227-4853 (de Martino et al., 2010; Bassa et al., 2014) and IGR J1824-2452 in
the globular cluster M28 (Papitto et al., 2013). Additionally, a handful of
candidate tMSPs have been recently discovered in the X-ray and GeV ranges (see
review by Papitto & de Martino, 2022). tMSPs alternate between a radio-loud
MSP state (RMSP, showing radio pulsations and no sign of an accretion disk)
and a sub-luminous LMXB state (forming an accretion disk and showing X-ray
pulsations). These sources are the direct link between the LMXB and the radio
MSP phases in which neutron stars are spun up to ms periods during the LMXB-
phase. Sudden transitions between the two states occur on a timescale of a few
days to weeks, and are accompanied by drastic changes across the
electromagnetic spectrum. The transition from the RMSP to LMXB state is
accompanied by brightening of optical, UV (Patruno et al., 2014b; Takata et
al., 2014), X-ray and gamma-ray (Stappers et al., 2013) emission with the
disappearance of radio pulsations. The origin of these transitions is still
debated and, for this, intense multi-wavelength campaigns are on-going to
understand the phenomenology in both the RMSP and LMXB states. tMSPs were so
far not detected in the VHE regime. The upper limits (ULs) in the VHE regime
from tMSPs are discussed in Section 4.3.

###  1.3 Pulsar wind nebulae

Pulsar wind nebulae (PWNe) are bubbles or diffuse structures of relativistic
plasma powered by a central highly-magnetized rotating neutron star (pulsar).
PWNe show three different evolution stages (see e.g. Olmi, 2023 and references
therein): a free-free expansion stage, in which there is no interaction with
the surrounding supernova remnant (SNR); a reverberation phase in which the
supernova reverse shock interacts with the PWN and a post-reverberation or bow
shock stage, in which the pulsar leaves the SNR onto the external medium,
creating a cometary-like structure. Some PWNe have been found to display TeV
halos (Abeysekara et al., 2017; Cao et al., 2023a), which are suggested to be
the result of particle escape in evolved pulsar. Recently, several PWNe have
been suggested to be PeV particle (leptons) accelerators, with the detection
of gamma rays at E$>$100 TeV (Cao et al., 2021, 2023a). The Crab nebula is the
standard candle at VHE and both the nebula and the pulsar have been
intensively studied. Pulsations have been measured up to TeV energies (Ansoldi
et al., 2016) and the nebula spectrum has been detected up to 100 TeV by IACTs
(MAGIC Collaboration et al., 2020) and recently extended to PeV (Lhaaso
Collaboration et al., 2021). Unexpectedly, the Crab nebula displays rapid
flaring emission over daily timescales at HE as reported by AGILE and Fermi-
LAT (Tavani et al., 2011; Abdo et al., 2011). The enhanced fluxes measured
over different flaring episodes were a factor three-to-six times larger than
the standard flux. So far, no signs of variability have been reported at VHE
(Mariotti, 2010; Ong, 2010; H. E. S. S. Collaboration et al., 2014; van
Scherpenberg et al., 2019). The characterization of the expected VHE emission
to be putatively detected by CTA is shown in Section 4.4.

###  1.4 Novae

Novae are thermonuclear runaway explosions on the surface of a white dwarf
star in binary systems involving a white dwarf accreting matter, often through
an accretion disc, usually from a late-type star (Gallagher & Starrfield,
1978). They are detected as transient events exhibiting huge and sudden
increase of brightness. Though novae have been studied both observationally
and theoretically for many decades, a comprehensive understanding of nova
physics is still lacking (Iben, 1982; Yaron et al., 2005). Particle
acceleration in novae was predicted before the launch of the Fermi Gamma-ray
space telescope (see Tatischeff & Hernanz, 2007). Shortly after, GeV emission
from the outburst of the symbiotic binary system V407 Cygni, comprised of a
white dwarf and an evolved red giant companion, was first detected.
Subsequently, classical novae with main sequence donor stars were also
detected (Abdo et al., 2010a; Ackermann et al., 2014).666Gomez-Gomar et al.
(1998) (and references therein) predicted gamma-ray emission from novae but of
nuclear origin, in the keV-MeV domain.  More recently, VHE emission in novae
has been predicted and searched for in a handful of sources (see e.g. Aliu et
al., 2012; Ahnen et al., 2015), with the first detection at VHE gamma rays
occurring in 2021 in the recurrent nova RS Ophiuchi (RS Oph, Acciari et al.,
2022; H. E. S. S. Collaboration et al., 2022; Abe et al., 2023).

Since the first detection at HE gamma rays from nova Cygni 2010, 19
novae777According to https://asd.gsfc.nasa.gov/Koji.Mukai/novae/latnovae.html
(as of February 2024). have been detected in this energy band (only RS Oph at
VHE) with a rate of about one outburst detection per year. All novae so far
detected at HE have been bright in the visible band ($\leq 10\,\rm{mag}$), and
the vast majority are nearby sources with distances within $5\,\rm{kpc}$
(Franckowiak et al., 2018). Non-thermal emission is expected to arise from
leptonic and hadronic interactions by particles accelerated in radiative
expanding shocks (Abdo et al., 2010a; Hernanz & Tatischeff, 2012), which can
originate from the interaction of the ejecta during the initial stage of the
outburst and the circumbinary material, or with the fast wind produced by
nuclear burning in later stages of the outburst (Abdo et al., 2010a; Ackermann
et al., 2014; Martin et al., 2018).

Based on observations of novae in the nearby M31 Galaxy, as well as binary
population synthesis models for the Milky Way, a rate of approximately 30 nova
events per year is expected (see Section 4.5). However, a significant
proportion of these will be obscured by intervening dust in the Galactic
plane. The number of nova events that will be detectable at HE and VHE gamma
rays will be further constrained by properties of the system, such as the
shock velocity and the target material density. This dependence on the
parameter space and prospects for detection of novae at VHE will be
characterised for CTA in Section 4.5.

###  1.5 Magnetars

Magnetars are isolated neutron stars in which the main energy source is the
magnetic field (e.g. Mereghetti et al. 2015; Kaspi & Beloborodov 2017, for
reviews). They are observed as pulsed X-ray sources, with typical spin periods
of a few seconds and strong spin-down rates, and/or through the detection of
short bursts and flares in the hard X-ray/soft gamma-ray range. This led to
their historical subdivision in the Anomalous X-ray Pulsars and Soft Gamma-ray
Repeater classes (Mereghetti, 2008), but it is now clear that these are just
two different manifestations of the same underlying object: a strongly
magnetized neutron star powered by magnetic energy, as proposed by Paczynski
(1992) and Duncan & Thompson (1992).

About 30 magnetars are known so far. With the exception of two sources in the
Magellanic Clouds, all of them lie in the Galactic Plane. The majority of the
magnetars are transient X-ray sources that have been discovered when they
became active, with an increase of their X-ray luminosity (from a quiescent
level of $\sim 10^{33}$ erg s-1 up to $\sim 10^{36-37}$ erg s-1), accompanied
by the emission of luminous and rapid bursts. This means that the total
Galactic population of magnetars is larger than the currently observed sample,
and more sources of this class will be known at the time of CTA observations.
Furthermore, magnetar-like behavior has recently been observed in some sources
originally presumed to be of a different kind, such as rotation-powered
(radio) pulsars (Gavriil et al., 2008; Göğüş et al., 2016), and even in the
gamma-ray binary LS I +61 303 (Torres et al., 2012; Weng et al., 2022).

For what concerns the persistent emission, magnetars have not been detected
above few hundred keV (Abdo et al., 2010b; Aleksić et al., 2013). Their X-ray
emission typically comprises a soft thermal component that dominates in the
1-10 keV range and a hard power-law component that is believed to originate
from multiple resonant scattering in the magnetosphere. The ULs in the MeV
range (Li et al., 2017) indicate a turn-off of this component implying that
their detectability is below the CTA capabilities, unless a different spectral
component is present at higher energies. On the other hand, magnetar bursts
and flares (in particular the so called Giant Flares) are potentially very
interesting targets for CTA, with the only disadvantage of their unpredictable
time of occurrence. Giant flares are extremely energetic and bright events,
reaching isotropic peak luminosities as high as a few 1047 erg s-1 for a
fraction of a second. However, they occur very rarely: only three have been
seen from local magnetars in 40 years. The high luminosity of their short ($<$
1 s) initial peaks implies that they can be detected, with properties
resembling those of short GRBs, up to distances of tens of Mpc by current hard
X-ray instruments. Indeed, a few candidate extragalactic giant flares have
been identified (Mazets et al., 2008; Frederiks et al., 2007; Svinkin et al.,
2021; Roberts et al., 2021). Of particular interest regarding CTA’s
perspective to detect giant flares is the case of the flare located in the
Sculptor galaxy (NGC 253, at 3.5 Mpc) for which Fermi-LAT observation led to
the detection of two high-energy photons with energies of 1.3 GeV and 1.7 GeV,
likely produced via synchrotron mechanism (Fermi-LAT Collaboration et al.,
2021). However, no emission from a magnetar has been yet detected at TeV
energies (Abdalla et al., 2021; López-Oramas et al., 2021). For further
discussion, see Section 4.6.

###  1.6 Other expected variable gamma-ray sources at TeV energies

In addition to the systems quoted above, it can be foreseen that CTA detects
other variable gamma-ray sources that nowadays are a mere theoretical
prediction. These include, for instance, runaway massive stars expelled from
their formation site (del Valle & Romero, 2014). The bow shocks created by
their powerful stellar winds have been proposed as sites of particle
acceleration responsible for non-thermal phenomena, so far mostly observed at
radio wavelengths. Significant gamma-ray variability is predicted on times
scales of $\sim 1$ year as the stars move across density inhomogeneities of
their surrounding medium affecting the bow shock properties.

Another kind of variable gamma-ray source based on theoretical expectations
are low-mass young stellar objects such as T-Tauri stars (del Valle et al.,
2011). Here, particle acceleration would be related to fast reconnection
events in the stellar magnetosphere. Similarly, massive young stellar objects
(MYSOs) could also produce gamma-ray emission associated with fast outflows
from accretion or supersonic ejecta (see e.g. Araudo et al., 2021 and
references therein). Recently, the MYSO S255 NIRS 3 has been suggested as the
counterpart of a HE source (de Oña Wilhelmi et al., 2023). Perspectives for
detection would be maximized at least for the closest star forming regions
(see discussion by the dedicated KSP on star-forming regions, Cherenkov
Telescope Array Consortium et al., 2019).

Supergiant Fast X-ray Transients (SFXTs; see Sidoli 2017 for a recent review)
are high-mass X-ray binaries (HMXBs) composed of an O or B type supergiant
star and a compact object; normally a neutron star (NS) is assumed, since some
of them are X-ray pulsars, although formally a black hole cannot be ruled out.
Their X-ray outbursts are rare (the duty cycle is less than 5 %, see Sidoli &
Paizis 2018). A large dynamic range of 2 to 6 orders of magnitude (Romano et
al., 2015) can be reached between quiescence and the outburst peak. Their
outbursts, that can last up to a few days, are made of short ($\sim$2 ks),
bright X-ray flares, typically reaching 1036-1037 erg s-1. The possibility
that SFXTs are MeV/TeV emitters was discussed by Walter (2007) and Sguera et
al. (2009). In particular, the latter noted the spatial proximity (positional
association within the error circles at gamma-ray energies, typically
$\leq$1∘) of some SFXTs with AGILE and EGRET transient unidentified sources.
To date, there are four unidentified gamma-ray transient sources (3EG
J1122$-$5946, AGL J1734$-$3310, 3EG J1837$-$0423, AGL J2022$+$3622/VER
J2019$+$368) which are spatially correlated with members (or candidates) of
the SFXT class: IGR J11215$-$5952 (Sguera, 2009), IGR J17354$-$3255 (Sguera,
2013), AX J1841.0$-$0536 (Sguera et al., 2009), and IGR J20188$+$3647 (Sguera,
2009). However, it is worth mentioning that no SFXT flare has ever been
simultaneously caught at both X-rays and MeV/TeV energies, implying that,
besides the spatial overlap with known SFXTs, there is no other evidence
supporting a physical association, to date.

Once CTA is operational some of these objects, and other unexpected ones, will
likely enrich the list of known Galactic transient emitters.

##  2 Sensitivity of CTA to transient detection in the Galactic plane

Figure 1:  Differential flux sensitivity, $S$, of the Southern CTA array
within 100–200 GeV for 10 min observation intervals, considering different
putative source locations along the Galactic plane. Panel (a) shows a
simulation of $F_{\text{gal}}^{>10^{-12}}$, the Galactic emission (Galactic
diffuse emission and a simulated population of Galactic sources) above a
threshold of ${10^{-12}~{}\text{erg}\;\text{cm}^{2}\;\text{s}^{-1}}$, which is
derived for different Galactic longitudes, lon, and latitudes, lat. Panel (b)
shows the corresponding CTA sensitivity. In panel (c) we present the median of
$S$ for different longitudes within the range, $-4<\text{lat}<+4$ deg, where
the shaded uncertainty region represents the $1\sigma$ variance of $S$.
Finally, panel (d) shows the relative $1\sigma$ variance, $\delta{S}$,
(compared to the median) derived for two ranges in latitude, as indicated. The
variance away from the Galactic plane ($3<|\text{lat}|<4$ deg) represents the
intrinsic statistical uncertainty of the sensitivity calculation. The variance
in the inner Galactic region ($|\text{lat}|<1$ deg) includes the intrinsic
uncertainty, as well as the additional effect of the Galactic foregrounds,
which are concentrated in this region.

CTA will have unprecedented sensitivity over a broad energy range and will
devote a large amount of time to sources in the Galactic plane, both with a
dedicated Galactic Plane Survey (GPS) (for details on the pointing strategy
and expected results see CTA Consortium, 2023) and with pointed observations
on specific targets. These are ideal capabilities for the discovery of new
Galactic transients at TeV energies.

Figure 2:  The differential flux sensitivity, $S$, of the Southern CTA array
for different energy ranges, $0.03<E_{\gamma}<200~{}\text{TeV}$, and
observation intervals, $10<t_{\text{obs}}<2\cdot 10^{4}~{}\text{sec}$. The
sensitivity is derived as the median value for various putative source
positions, considering an area of ${4~{}\text{deg}^{2}}$ close to the Galactic
centre. The bottom panels show the relative $1\sigma$ variance of the
sensitivity, $\delta{S}$, compared to the median. The variance accounts for
both the intrinsic statistical uncertainty of the sensitivity calculation, and
the degradation of performance due to the presence of steady sources.

It is then important to characterize the sensitivity of CTA in the Galactic
plane. The differential sensitivity of CTA for detecting a new source is
defined as the minimal flux of a source, multiplied by the mean energy squared
within the given energy interval, such that the source is detectable at the
$5\sigma$ significance level. It is defined within a given energy range, and
for a given observation interval or exposure. We assume a test point source
power-law spectral model,

$F(E)=P_{f}\left(\frac{E}{E_{0}}\right)^{-\gamma}$ (1)

where we set the pivot energy, ${E_{0}=1~{}\mathrm{TeV}}$, and the spectral
index, ${\gamma=2.5}$, using typical values for Galactic VHE sources. The
prefactor, Pf is varied as part of the sensitivity calculation, in order to
find the minimal flux value for a $5\sigma$ detection. In order to be
compatible with previous analyses (e.g. Fioretti et al., 2019), we also
require that the source emits at least 10 gamma-ray photons. In addition, we
validate that this number of events is larger than ${5\%}$ of the
corresponding contribution from backgrounds and foregrounds (cosmic rays;
electrons; and other gamma-ray sources that can be coincident).

We explore the performance of CTA in the Galactic plane region for various
short observation intervals. For illustration, the sensitivity of the Southern
array is shown in Fig. 1, considering different putative source locations. In
this example, we estimated the performance for short observation intervals of
10 minutes within the energy range 100–200 GeV, exploring the detection
potential of new sources in the low-energy range of CTA. We use a publicly-
available Galactic sky model, based on observations of known gamma-ray sources
and interstellar emission from cosmic-ray interactions in the Milky Way (CTA
Consortium, 2023).888Galactic sky model available at
https://zenodo.org/records/10008527 We simulate our putative transients on top
of the emission derived from this sky model, such that the latter constitutes
an additional background to the search.

As may be inferred from Fig. 1, upward fluctuations of the sensitivity
(requiring brighter transient emission for detection), are correlated with the
steady emission from Galactic sources. In the selected energy range, the flux
of the simulated Galactic foreground is mostly below the level of a few
${10^{-11}~{}\text{erg}\;\text{cm}^{-2}\;\text{s}^{-1}}$. This is of the same
order as the nominal sensitivity of the observatory in the absence of
foregrounds. Correspondingly, the overall degradation in sensitivity to
transients is not expected to be significant.

In order to verify this, we calculated $\delta{S}$, the relative variation of
the sensitivity (compared to the median value) for different Galactic
longitudes. The steady foreground sources are concentrated in the inner
Galactic region. We therefore derived $\delta{S}$ for two regions in latitude,
in order to enhance or suppress their effect. Away from the Galactic plane we
find $\delta{S}\sim 2\text{--3}\%$ which amounts to the intrinsic statistical
uncertainty of the sensitivity calculation. In the more crowded inner region,
the variation is of the order of $5\text{--}15\%$. This represents a mild
increase in the flux threshold for a new transient source to be discovered,
though only when coinciding with strong Galactic emitters.

We show the median sensitivity for various combinations of energy ranges and
observation intervals in Fig. 2. Here we consider an area of
${4~{}\text{deg}^{2}}$ next to the Galactic centre, where the steady emission
is relatively strong. The observed variation in sensitivity is mild, of the
order of $1\text{--}10\%$.

The presence of possible source variability is assessed in Section 4.1.1.
Other topics such as the study of Galactic Centre sources and interstellar
emission through observations of the Galactic Centre region and GPS and the
prospects for the CTA and its scientific results are covered in other KSPs
(see Cherenkov Telescope Array Consortium et al., 2019; CTA Consortium, 2023)

We conclude that the performance of CTA is consistent with the corresponding
nominal extragalactic sensitivity (in the absence of significant foregrounds).

##  3 Detectability of transients of unknown origin

Apart from the transient sources of clearly identifiable type, others of
unknown nature could also be serendipitously observed e.g. during a scan of
the GPS. To assess the detection capabilities of CTA for such sources we
simulate the populations of 100 generic transients. We consider the relatively
short observation time of 1 hour (compatible with the strategy defined in CTA
Consortium, 2023) during which it would be possible to detect the source and
make a decision about further observations.

We simulated the variability of each source using the following lightcurve
model:

$F(t)=\frac{2F_{0}}{\exp(\frac{t_{0}-t}{T_{r}})+\exp(\frac{t-t_{0}}{T_{d}})}$

where $T_{r}$ and $T_{d}$ stand for time rise and time decrease and $t_{0}$ is
the time at which $F=F_{0}$; we normalize the lightcurve to $F=1$ at its
maximum. Such a lightcurve describes the flux of a transient during its
growth, at peak and when it falls, allowing the simulation of observations at
each of these stages. We assume $T_{r}$, $T_{d}$ and $t_{0}$ to be in ranges
$1-86400$ s, $86400-604800$ s and $T_{d}-T_{r}$ respectively.

We used the model of Yusifov & Küçük (2004) for the radial distribution of
sources. The resulting spatial distribution is shown in Fig. 3. For
simplicity, we did not take into account the visibility constraints, assuming
that all sources are visible to either array at the time of observation.

Figure 3: Spatial distribution of sources in the simulated populations.

For each population, the parameters defining the spectrum and the lightcurve
of each source are assigned randomly for each of them, assuming a log-uniform
distribution for the prefactor and a uniform one for other parameters. The
pivot energy for all sources is 1 TeV.

Table 1: Simulated populations. We consider sources with different spectral shapes and parameters. Population | Spectrum | Prefactor | Spectral index
---|---|---|---
|  |  (ph cm-2 s-1 TeV-1) |
1 | power-law | $10^{-14}-10^{-09}$ | [-3.50, -1.50]
2 | power-law | $10^{-18}-10^{-13}$ | [-3.50, -1.50]
3 | log-parabola | $10^{-14}-10^{-09}$ | [-3.50, -1.50]
4 | power-law (Alpha) | $10^{-14}-10^{-09}$ | [-3.50, -1.50]

Four simulated populations are summarized in Table 1. They include different
spectral shapes and parameters. For each population we employed the 0.5 h IRFs
for both CTA-N and CTA-S, and also tested the Alpha configuration in the case
of population 4. Both IRF sets contain three zenith angle observation options
at 20∘, 40∘ and 60∘; and they also account for the azimuth dependence coming
from the geomagnetic field pointing direction: North, South or an average over
the azimuth direction.

For each source, we simulate the photon events list for 1 hour both for the
CTA-N and CTA-S sites with a 5.0∘ ROI centered at a source, without any other
sources within it, accounting only for the IRF background as seen in Fig. 1
and Fig. 2. The energy ranges used for both configurations at each site are
collected in Table 2. The energy dispersion effect has been also taken into
account (according to the IRFs). We then performed an unbinned maximum
likelihood fitting. The test statistic (TS) equal or higher than 25 is used as
criterion for a source detection.

Table 2: Energies (TeV) assumed in the simulations depending on the array location, configuration and zenith angle. Different energy ranges were assumed depending on the geomagnetic field (average, North, South) for CTA-N Alpha Configuration, as produced in the dedicated IRFs (Observatory & Consortium, 2021). Site |  20∘ |  40∘ |  60∘
---|---|---|---
CTA-N | 0.03-200 | 0.04-200 | 0.11-200
CTA-S | 0.03-200 | 0.04-200 | 0.11-200
CTA-N (Alpha) | 0.03-200 | 0.04-200 |  | 0.06-200 (A)
---
0.12-200 (N)
0.08-200 (S)
CTA-S (Alpha) | 0.04-200 | 0.06-200 | 0.18-200
Figure 4: Number of detected sources in populations 1 to 4 for CTA-N (blue)
and CTA-S (orange), including the Alpha configuration in population 4. From
left to right: different configurations of the geomagnetic field (North,
average and South). From top to bottom: different zenith angles (20∘, 40∘ and
60∘).

The results for all populations and observation configurations are presented
in Fig. 4. We found that in the case of having a power-law spectra and fluxes
in the range of $10^{-14}-10^{-09}$ ph cm-2 s-1 TeV-1, $73-83\%$ of sources
for 20∘ and 40∘ zenith angles and $65-74\%$ of sources for 60∘ zenith angle
will be detected, while for the population with fluxes $<10^{-13}$ ph cm-2 s-1
TeV-1, CTA will not detect any source during 1 hour of observation. In most
cases CTA-S performs marginally better than CTA-N, with the larger difference
for the North magnetic field configuration. Adding a curvature to the spectrum
does not affect the detection rate in a statistically significant way. Using
the Alpha Configuration (which corresponds to a first construction phase)
slightly decreases the detectability, which is expected due to the reduced
number of telescopes and the lack of LSTs in the CTA-S Alpha configuration
(Maier et al., 2023).

##  4 Source detection with CTA

Galactic transients that exhibit MeV-GeV emission are specially interesting to
be studied with CTA, since it is already known that non-thermal mechanisms
leading to gamma-ray production are at work. We aim at understanding whether
these sources of interest can also emit VHE radiation, which can be produced
by the same HE mechanisms and be detected as a spectral extension, or be
created by an additional component at TeV energies.

###  4.1 High-mass microquasars

The microquasars of the Cygnus region, Cyg X-3, Cyg X-1 and the system SS 433
are the only microquasars that have been detected in the HE regime, hence they
can be considered as potential targets for the CTA observatory. After the
discovery of gamma-ray emission from SS 433 above 20 TeV by HAWC (Abeysekara
et al., 2018a), the CTA observations of these microquasars will be crucial to
shed light on the physical mechanism responsible for the VHE emission in this
type of binary systems, by investigating the limits of extreme particle
acceleration in the jet.

The importance of observing this subclass of binary systems with CTA has been
previously discussed in Paredes et al. (2013). In particular, a detailed study
on a possible detection of a TeV flare from Cyg X-1 was presented in that
paper, showing conclusions similar to our findings (see Sect. 4.1.3). In this
section, we show simulations on the first microquasar detected in the VHE
regime, SS 433, and estimate the detectability both of transient and
persistent emission from Cyg X-3 and Cyg X-1. Even if the detection of
persistent emission is not the scope of this paper, we perform this additional
exercise to complement the expectations to detect microquasars with CTA. For
the case of the microquasars in the Cygnus region, we carried out several CTA
observation simulations by using the latest `prod5-v0.1` IRFs to check if
these two systems could already be detected in the first years of operation of
CTA. Almost all the simulations have been carried out in the lowest range of
energies for the CTA observatory, where the bulk of the emission from these
binary systems is expected. For each set of observations, besides the emission
from the microquasars, we simulated the main field sources of the Cygnus
region: 2HWC J2006+341 (Araya & HAWC Collaboration, 2019), VER J2016+371, VER
J2019+368 (Aliu et al., 2014b), Gamma Cygni SNR (Ackermann et al., 2017;
Abeysekara et al., 2018b), TeV J2032+4130 (emission model as detected by MAGIC
before the periastron passage of November 2017, Abeysekara et al., 2018c).
This approach also applies to the case of the LMXB V404 Cyg located in the
same region (see subsection 4.2.1).

####  4.1.1 SS 433

SS 433 is a binary system containing a supergiant star that is overflowing its
Roche lobe with matter accreting onto a compact object, either a BH or a NS
(see e.g. Margon 1984; Fabrika 2004). Two jets of ionised matter, with a bulk
velocity of approximately one quarter of the speed of light in vacuum, extend
from the binary, perpendicular to the line of sight, and terminate inside the
supernova remnant W50 (e.g. Fabrika 2004). The lobes of W50 in which the jets
terminate about 40 parsecs from the central source, are accelerating charged
particles, as it follows from radio and X-ray observations, consistent with
electron synchrotron emission (Geldzahler et al., 1980; Brinkmann et al.,
2007).

Abeysekara et al. (2018a) reported the results of the High Altitude Water
Cherenkov (HAWC) Observatory of SS 433, collected between November 2014 and
December 2017. In 1017 days of measurements with HAWC, an excess of gamma rays
with a post-trial significance of 5.4 $\sigma$ has been observed in a joint
fit of the eastern and western interaction regions (namely e1 and w1) of the
jets of SS 433. The quality of the data allow us to set only ULs on the
angular size of the emission regions, namely 0.25∘ for the east hotspot and
0.35∘ for the west hotspot at 90% confidence level. The VHE gamma-ray flux is
consistent with a hard E-2 spectrum, though current TeV flux data from HAWC
are not of sufficient significance to constrain the spectral index. The
reported HAWC flux at 20 TeV is 2.4$\times 10^{-16}$ TeV-1 cm-2 s-1 at e1, and
2.1$\times 10^{-16}$ TeV-1 cm-2 s-1 at w1. HAWC detects VHE emission from the
interaction regions up to at least 25 TeV, which is the highest energy
measured up to now from microquasars.

The SS 433 region was also observed by H.E.S.S. as part of a Galactic plane
survey, and during two further dedicated campaigns, resulting in about 200h of
observations (H. E. S. S. Collaboration et al., 2024). These observations
confirmed presence of two regions of gamma-ray emission at the positions of
the eastern and western jets, with peak statistical significances of
7.8$\sigma$ and 6.8$\sigma$, respectively. The reported fluxes at 1 TeV
(($2.30\pm 0.58)\times 10^{-13}$ TeV-1 cm-2 s-1 and ($2.83\pm 0.70)\times
10^{-13}$ TeV-1 cm-2 s-1 for the eastern and western jets correspondingly) are
inline with HAWC data taking into account the spectral slopes of
$\Gamma_{e}=2.19\pm 0.12$ and $\Gamma_{w}=2.40\pm 0.15$. Quality of the
H.E.S.S. data also allow to study the energy dependence of the source
morphology, demonstrating that while the gamma-ray emission above 10 TeV
appears only at the base of the jets, the lower-energy gamma rays have their
peak surface brightnesses at locations further along each jet, reflecting an
energy-dependent particle energy loss timescale.

Analysis of the Fermi-LAT data led to the discovery of the significant HE
gamma-ray emission from the region around SS 433 (see Bordas et al. 2015; Sun
et al. 2019; Rasul et al. 2019; Xing et al. 2019; Li et al. 2020). However,
the analysis is model dependent and can lead to very different conclusions on
the position and extension of the source. In Rasul et al. (2019), authors
report evidence at 3 $\sigma$ level for the modulation of the $\gamma$-ray
emission with the precession period of the jet of 162 days. This result
suggests that at least some of the gamma-ray emission originates close to the
base of the jet. Li et al. (2020) detected HE emission in the vicinity of SS
433 which shows periodic variation compatible with the processional period of
the jets.

Kimura et al. (2020) investigated both hadronic and leptonic scenarios for the
GeV-TeV gamma-ray emission from SS 433. They found that the existing data can
be explained by both the hadronic and leptonic models. The hadronic scenarios
predict higher-energy photons than the leptonic scenarios, and future
observations with CTA and LHAASO are needed to unravel the emission mechanism
of GeV-TeV gamma rays. A preliminary association of LHAASO sources with known
TeV sources based on their position reported in the first LHAASO catalog of
gamma-ray sources (Cao et al., 2023b) indicate the presence of 2 LHAASO
sources located at 0.26∘ and 0.15∘ from the western and eastern lobes of SS
433 correspondingly, but further observations are needed to confirm these
associations.

To test the capability of CTA to study the origin of the VHE emission from the
source we simulate the source with both the east and west lobes as extended
sources in the energy range 0.1 - 100.0 TeV. We simulate observations with 10,
30 and 50 hours of exposure time. These simulations were repeated on each of
the lobes assuming different extensions roughly corresponding to the different
characteristic scales of source morphology as observed with H.E.S.S. (H. E. S.
S. Collaboration et al., 2024) (see Table 3), to provide the expected
detectability in terms of their size. The TS and flux of each lobe was
measured for both the Northern and Southern CTA arrays, see Tables 4 and 5.

Table 3: Extension model values applied to the lobes of SS 433 that were simulated with CTA. Model | $\sigma_{w}$ | $\sigma_{e}$
---|---|---
1 | 0.001 | 0.001
2 | 0.0625 | 0.0875
3 | 0.175 | 0.125
4 | 0.26 | 0.1875
Table 4: Comparison of the detectability of the western and eastern lobes of SS 433 with varying values of source extension and exposure time for the Northern array. Model | $TS^{\rm West}_{\rm 10\,h}$ | $TS^{\rm East}_{\rm 10\,h}$ | $TS^{\rm West}_{\rm 30\,h}$ | $TS^{\rm East}_{\rm 30\,h}$ | $TS^{\rm West}_{\rm 50\,h}$ | $TS^{\rm East}_{\rm 50\,h}$
---|---|---|---|---|---|---
1 | 52.0 | 76.8 | 229.1 | 303.7 | 354.3 | 477.2
2 | 38.9 | 10.9 | 121.9 | 105.2 | 152.0 | 114.5
3 | 7.9 | 9.4 | 23.7 | 57.6 | 57.1 | 100.2
4 | 2.4 | 8.2 | 6.3 | 20.1 | 9.4 | 37.5
Table 5: Comparison of the detectability of the western and eastern lobes of SS 433 with varying values of source extension and exposure time using for the Southern array. Model | $TS^{\rm West}_{\rm 10\,h}$ | $TS^{\rm East}_{\rm 10\,h}$ | $TS^{\rm West}_{\rm 30\,h}$ | $TS^{\rm East}_{\rm 30\,h}$ | $TS^{\rm West}_{\rm 50\,h}$ | $TS^{\rm East}_{\rm 50\,h}$
---|---|---|---|---|---|---
1 | 137.4 | 184.6 | 738.8 | 821.9 | 886.3 | 1261.4
2 | 59.2 | 73.6 | 178.4 | 384.2 | 273.1 | 401.0
3 | 11.1 | 31.3 | 76.3 | 104.3 | 79.5 | 226.7
4 | 2.6 | 7.2 | 44.4 | 60.3 | 34.7 | 115.9

##### Central source emission and putative variability

Figure 5: Comparison of the relative flux errors at different exposure times
for the Northern and Southern arrays.

Figure 6: Dependence of the 1 sigma relative flux error ratio on the photon
flux for the Northern (left) and Southern (right) arrays. Different exposure
times are given by different colours as indicated in the legend.

While we do not expect to detect variability in the VHE emission coming from
the lobes, microquasars are known to have flaring emission on various
timescales coming from its central source. To test the possibility of CTA to
detect a central source and its putative variability we simulate the local
region of SS 433 with the diffuse background and the nearby MGRO 1906+06
source, where SS 433 consists of both the aforementioned lobes and a central
point source. All simulations were performed when the H.E.S.S. ULs on the
central source flux were not published yet and we assumed that the flux of
this central source is approximately half that of the western lobe, which is
roughly consistent with the ULs reported in (H. E. S. S. Collaboration et al.,
2024). The lobes and the central source were both assumed to have an index of
-2.0 and a pivot energy of 20 TeV (see Abeysekara et al., 2018a). The lobes
were given an extension that matches Model 2 as described in Table 3. Batches
of 100 simulations were run using the North and South site IRFs at multiple
different exposure times ranging from 30 minutes to 50 hours. The flux was
calculated after every simulation and the total data was compiled into
histograms for each exposure time to determine the error range of the
detections. As SS 433 could be viewed from both the north and south
hemispheres the results of error measurements from both sites were compared to
determine which can produce more sensitive detections. Fig. 5 shows the the
comparison of this flux error ratio. Obtained results demonstrate that
Southern array is better suited to study the source.

As previously mentioned, the region surrounding SS 433 does not contain many
other TeV sources and could be described as an uncrowded region. Conversely,
sources such as the gamma-ray binary LS 5039 are located in a region with
multiple nearby TeV sources (crowded region). Using the previous setup,
simulations were run for a source modelled like the central SS 433 source
located at the position of LS 5039 to determine if a crowded region would
change the results. It was found that the observed flux of the central source
and its error were very similar for both cases of a crowded and uncrowded
regions.

The procedure used to test the effectiveness of CTA on dim transient sources
can also be tested with sources of arbitrary intensity to determine what level
of variability can be observed with shorter exposures. The results of
observing sources in the same position and region of SS 433 with different
fluxes ($>1$ TeV) are shown in Fig. 6. Similarly to the simulations of the SS
433 central source at different exposures (Fig 5), the Southern array
configuration consistently produce a lower ratio between the 1 sigma error and
the input flux of the simulation. Based on the simulations run at different
fluxes, sources with a photon flux $<1\times 10^{-13}$ ph cm-2 s-1 will
require exposure times of more than 10 hours in order to detect any expected
variability. However, for sources with a flux $\geq 1\times 10^{-13}$ ph cm-2
s-1, CTA may be able to detect variability as low as $\sim 10\%$ observing
from 5 to 10 hours. At a photon flux $\geq 3\times 10^{-12}$ ph cm-2 s-1 the 1
sigma ratio gets as low as $\sim 5\%$ with exposure times of $0.5-1.0$ hour
long, meaning that even low variability may be detectable from relatively
bright sources with very short observations.

####  4.1.2 Cyg X-3

Cyg X-3 is a HMXB located at a distance of $\sim$9 kpc (Reid & Miller-Jones,
2023). The companion star is a Wolf-Rayet (WR) with a strong wind mainly
composed of helium. The nature of the compact object is still unknown,
although a black hole scenario is favored (Zdziarski et al., 2013; Antokhin et
al., 2022). The orbital period is very short, $\sim 4.8$ hours, indicating
that the compact object is very close to the WR star, totally enshrouded in
its stellar wind (orbital distance $\sim 3\times 10^{11}$ cm). The binary
system is known to produce giant radio flares (flux > 10 Jy), produced by
synchrotron processes from a relativistic jet oriented very close to the line
of sight. Transient gamma-ray activity above 100 MeV was reported for the
first time in 2009 by AGILE (Tavani et al., 2009) and Fermi-LAT (Fermi LAT
Collaboration et al., 2009). The flaring activity (typical duration: 1-2 days)
was observed in coincidence with a repetitive pattern of multi-frequency
emission (Piano et al., 2012): the gamma-ray flares have been detected (i)
during soft X-ray spectral states (around minima of the hard X-ray light
curve), (ii) in the proximity of spectral transitions, and (iii) a few days
before giant radio flares. In particular, transient gamma-ray emission was
found when the system is moving into or out of the quenched state, a spectral
state – characterized by a very low (or undetectable) flux at radio and hard
X-ray frequencies – that is known to occur a few days before major radio
flares.

The quenching activity of Cyg X-3 turns out to be a key condition for the
observed activity above 100 MeV. According to theoretical models, a simple
leptonic scenario – based on inverse Compton (IC) scattering between
electrons/positrons accelerated in the jet and seed photons from the WR
companion – can account for the flaring gamma-ray fluxes and the 4.8 h
modulation detected by Fermi-LAT during the transient activity (Dubus et al.,
2010). A simple phenomenological picture, based on dominant leptonic processes
in the jet, can account for the non-thermal emission pattern: around the
quenching, the jet would consist of plasmoids, ejected with high Lorentz
factor. This transient jet would be responsible for the HE flare (for IC
processes), produced in the proximity of the binary system ($10^{10}-10^{12}$
cm), and it would subsequently produce the major radio flares (synchrotron
processes), by moving out from the central engine (distances $>10^{14}$ cm).
MAGIC repeatedly observed Cyg X-3, both during hard and soft spectral states,
but never detected any significant VHE activity from the microquasar (Aleksić
et al., 2010).

##### Cyg X-3: transient emission

We carried out simulations by assuming two different theoretical models based
on IC processes in the jet (Piano et al., 2012; Zdziarski et al., 2018), in
order to test the possibility of a CTA detection of transient VHE gamma-rays
from Cyg X-3.

We performed a binned analysis in the energy range 100 GeV – 1 TeV with
`ctools`, by simulating observations with the Alpha Configuration of the
Northern array of the CTA observatory (IRF: `North_z20`), taking into account
the energy dispersion. A multi-source input model with the main background TeV
sources (see Section 4.1) and the CTA instrumental background
(`CTAIrfBackground`) has been considered.

In the first case, we adopted a simple power-law spectrum (see Eq. 1) inferred
from the leptonic Model A from Piano et al. (2012), where prefactor
$P_{f}=1.34\times 10^{-21}$ ph $\mathrm{cm}^{-2}$ $\mathrm{s}^{-1}$
$\mathrm{MeV}^{-1}$, index $\gamma=4.5$ and pivot energy $E_{0}=1$ TeV. The
leptonic model is based on IC scatterings between accelerated electrons in the
jet and soft seed photons from the accretion disk (X-rays) and from the
companion star (UV). We simulated 5 hour and 50 hour observations, and we
investigated the resulting simulated data, by performing a binned analysis.
The resulting spectra are shown in Fig. 7, together with the X-ray “hypersoft”
spectrum (Koljonen et al., 2010), the AGILE flaring spectrum (Piano et al.,
2012) and the MAGIC flux ULs observed during the soft states (Aleksić et al.,
2010). All the spectra (not simultaneous observations) are referred to the
same spectral state of Cyg X-3 when the transient gamma-ray activity is
detected at MeV-GeV energies (quenched state). We show the reference
theoretical model and the input simulated power-law, together with the CTA
simulated spectra. By assuming this input spectrum we found no detection with
CTA-N with 5-h observation and a weak hint of signal ($\sim$3$\sigma$) for 50
hours of observation time.

Figure 7: Multi-frequency spectral energy distribution of Cyg X-3. Black solid
curve: leptonic model A (Piano et al., 2012). Cyan solid curve: CTA input
model for the simulation. Blue points: “hypersoft” X-ray spectrum (Koljonen et
al., 2010), RXTE-PCA and RXTE-HEXTE data ($\sim$3 to $\sim$150 keV). Red
points: HE gamma-ray cumulative flaring spectrum (Piano et al., 2012), AGILE
(50 MeV – 3 GeV). Magenta points: VHE flux ULs (95% C.L.) from Aleksić et al.
(2010), MAGIC (199 GeV – 3.16 TeV). Gray points: CTA flux ULs for a simulated
observation of 5 ho. Black points: CTA spectrum for a simulated observation of
50 h.

In the second case, we assumed a different theoretical model, developed by
Zdziarski et al. (2018) in order to fit the flaring spectrum from Cyg X-3 as
detected by Fermi-LAT (cumulative spectrum of 49 1-day flares detected between
August 2008 and August 2017). The theoretical model presented in their paper
is similar to the one presented in Piano et al. (2012), but in Zdziarski et
al. (2018), the electrons in the jet scatter blackbody soft photons from the
companion star only. The orbital and geometrical parameters are similar. Also
in this case, the model is focused on the HE emission from the microquasar (E
$\leq$ 100 GeV). Thus, we assumed a simple power-law extension of the model up
to TeV energies (assuming: prefactor $P_{f}=2.15\times 10^{-19}$ ph
$\mathrm{cm}^{-2}$ $\mathrm{s}^{-1}$ $\mathrm{MeV}^{-1}$, index $\gamma=2.85$
and pivot energy $E_{0}=1$ TeV). Similarly, we simulated 5 h and 50 h
observations. The results of these simulations are shown in Fig. 8. In this
case, by assuming a harder and brighter input spectrum, we found clear
detections with CTA-N: $\sim$10$\sigma$ with 5-h observation, $\sim$30$\sigma$
with-50 h observation.

Thus, by assuming two simple power-law input spectra adapted from theoretical
leptonic models – both created ad hoc in order to account for the flaring
activity observed by AGILE and Fermi-LAT – a possible detection with CTA North
is plausible even with a few hours observations. We cannot rule out to detect
the 4.8 h orbital modulation, in the case of a prolonged TeV flare. A CTA
detection of transient VHE gamma-ray activity would represent an unprecedented
result for this elusive system, never observed at TeV energies. Nevertheless,
a CTA non-detection would give new strong constraints on theoretical models
about microquasars. The lack of a transient VHE signal from Cyg X-3,
correlated with non-thermal flaring activity, could indicate that: (i) the TeV
signal, eventually produced in the jet, is absorbed for pair production by the
companion star’s UV photons; (ii) the acceleration efficiency in the jet is
intrinsically low, the maximum energies of the jet particles are not
sufficient to generate TeV photons.

Figure 8: Gamma-ray spectral energy distribution of Cyg X-3. Black solid
curve: leptonic model (Zdziarski et al., 2018). Power-law extension of the
model up to TeV energies. Cyan solid curve: CTA input model for the
simulation. Red points: HE gamma-ray cumulative flaring spectrum (Zdziarski et
al., 2018), Fermi-LAT (50 MeV – 100 GeV). Magenta points: VHE gamma-ray flux
ULs (95% C.L.) from Aleksić et al. (2010), MAGIC (199 GeV – 3.16 TeV). Gray
points: CTA spectrum for a simulated observation of 5 h. Black points: CTA
spectrum for a simulated observation of 50 h.

####  4.1.3 Cyg X-1

Cyg X-1 is a HMXB, composed of a black hole ($M_{\rm X}=21.2\pm 2.2$
$M_{\odot}$) and a O9.7Iab supergiant companion star ($M_{\rm
opt}=40.6^{+7.7}_{-7.1}$ $M_{\odot}$, Miller-Jones et al., 2021). The system
is located at a distance of $2.22^{+0.82}_{-0.17}$ kpc (Miller-Jones et al.,
2021), and the orbital period is 5.6 days. The X-ray spectra can be accurately
modeled by hybrid Componization models (Coppi, 1999). The soft state of Cyg
X-1 is characterized by a strong disk blackbody component peaking at $kT\sim
1$ keV and a power-law tail extending up to $\sim$10 MeV, related to
Componization processes in the corona. In the hard state, the accretion disk
is truncated and the emission from the corona is dominant. In this state, the
coronal plasma is composed by a hot quasi-thermal population of electrons
($kT\sim 100$ keV) with a sharp cutoff at $\sim$200 keV. At sub-MeV energies,
the microquasar exhibits a non-thermal power-law tail with a strong linear
polarization (Laurent et al., 2011; Jourdain et al., 2012). This emission
could be ascribed either to synchrotron processes in the jet, by assuming a
very efficient particle acceleration and strong jet magnetic fields (Zdziarski
et al., 2014), or to the corona itself (Romero et al., 2014). Recent studies
investigate the physical origin of this power-law tail at sub-MeV energies,
detected during both soft and hard spectral states (Cangemi et al., 2021).
Above 100 MeV, deep observations with Fermi-LAT found evidences of persistent
emission from Cyg X-1 only during hard X-ray spectral states (Zanin et al.,
2016; Zdziarski et al., 2017). Transient HE emission was observed by AGILE
(Bulgarelli et al., 2010; Sabatini et al., 2010, 2013) on 1-2 day timescales,
in coincidence with both hard and soft X-ray spectral states. At TeV energies,
a hint of detection ($\sim$4$\sigma$) was observed by MAGIC on September 24,
2006 (Albert et al., 2007), during a hard X-ray flare of Cyg X-1.

For Cyg X-1, we investigated the possibility that CTA will detect both
transient and persistent emission from the microquasar.

##### Cyg X-1: transient emission.

In this case, we carried out a simulated short-term observation of Cyg X-1,
during a possible VHE gamma-ray flare. We simulated a 30-minute observation
with the same setup reported in Section 4.1.2: a multi-source simulation with
photon energies between 100 GeV and 1 TeV. We assumed, as input spectrum for
the simulation, the same power-law observed by MAGIC in September 24, 2006
(Albert et al. (2007); prefactor $P_{f}=2.3\times 10^{-18}$ ph
$\mathrm{cm}^{-2}$ $\mathrm{s}^{-1}$ $\mathrm{MeV}^{-1}$, index $\gamma=3.2$,
pivot energy $E_{0}=1$ TeV). We obtained an overall detection of the source at
a significance level of $\sim$38$\sigma$. The resulting spectrum is shown in
Fig. 9, together with the observed flaring spectrum observed by MAGIC. Our
results confirm that CTA will be able to detect a flare similar to the one
reported by MAGIC in 2006 in a few minute observation, with unprecedented
spectral accuracy.

Figure 9: VHE gamma-ray spectral energy distribution of Cyg X-1, related to
the 2006-September flaring activity. Magenta points: VHE gamma-ray spectrum
from Albert et al. (2007), MAGIC (150 GeV – 1.9 TeV), accounting for 78.9
minutes of observation. Magenta dashed line: MAGIC best fit. Cyan solid curve:
CTA input model for the simulation. Black points: CTA spectrum for a simulated
observation of 30 minutes.

##### CygX-1: persistent emission.

Cyg X-1 exhibits persistent HE emission during the hard state, as observed by
Fermi-LAT (Zanin et al., 2016; Zdziarski et al., 2017). Thus, we investigated
the possibility of a CTA detection of VHE persistent emission above 100 GeV.
Again, we assumed the same setup as reported in Section 4.1.2. We analyzed
three different scenarios. In the first one, we assumed as input spectral
model for CTA, a simple extension of the power-law spectral shape reported in
the Fermi-LAT 4FGL Catalog, without any cut off around 100 GeV (Abdollahi et
al., 2020). In the second scenario, we assumed a spectral shape based on a
purely leptonic theoretical model, in which gamma-ray emission is produced due
to IC scatterings in the persistent jet during the hard state (Zdziarski et
al., 2017). According to this model, a sharp cut off – due to the Klein-
Nishina effects – is predicted at $\sim$100 GeV. In the third scenario, we
assumed a spectral shape based on the lepto-hadronic theoretical model
presented in Kantzas et al. (2021). In that paper, the authors modeled the GeV
persistent spectrum as detected by Fermi-LAT during the hard state, by
assuming that both electrons and protons are accelerated in the jet. A
comprehensive model, based on a superposition of leptonic (IC scatterings) and
hadronic processes (gamma rays from the decay of neutral mesons, produced in
$p$$\gamma$ interactions) can properly fit the multi-wavelength spectrum up to
the high-energy emission from Cyg X-1.

For the first hypothesis (4FGL-like spectrum), we assumed a simple power-law
(assuming: prefactor $P_{f}=3.2\times 10^{-14}$ ph $\mathrm{cm}^{-2}$
$\mathrm{s}^{-1}$ $\mathrm{MeV}^{-1}$, index $\gamma=2.15$ and pivot energy
$E_{0}=4.15$ GeV). A multi-source simulation with photon energies between 100
GeV and 1 TeV has been carried out. With this spectrum, we obtained a
detection with a significance of $\sim$17$\sigma$ for a 50h simulated
observation. The resulting simulated spectrum is shown in Fig. 10, together
with the Fermi-LAT 4FGL spectrum (Abdollahi et al., 2020), and the MAGIC flux
ULs during the hard state (Ahnen et al., 2017b).

For the second hypothesis (spectrum inferred from Zdziarski et al., 2017), we
assumed a simple power-law (with prefactor $P_{f}=9.5\times 10^{-21}$ ph
$\mathrm{cm}^{-2}$ $\mathrm{s}^{-1}$ $\mathrm{MeV}^{-1}$, index $\gamma=3.2$
and pivot energy $E_{0}=1$ TeV). A multi-source simulation with photon
energies between 100 GeV and 1 TeV has been carried out. In this case, we did
not detect any significant emission with CTA with a simulated observation of
50 h (significance $\sim$2$\sigma$). The resulting differential spectral ULs
are shown in Fig. 11, together with the theoretical model from Zdziarski et
al. (2017), the HE gamma-ray spectra as detected by Fermi-LAT (Zanin et al.,
2016; Zdziarski et al., 2017), and the MAGIC ULs related to the hard state
(Ahnen et al., 2017b).

For the third hypothesis (spectrum inferred from Kantzas et al., 2021), we
used as input the theoretical model itself, by simulating photon energies
between 100 GeV and 100 TeV. We carried out the usual multi-source binned
analysis, and we found a clear detection with a significance of
$\sim$36$\sigma$ for a 50h simulated observation. The resulting simulated
spectrum is shown in Fig. 12, together with the theoretical model from Kantzas
et al. (2021), the HE gamma-ray spectra as detected by Fermi-LAT (Zanin et
al., 2016; Zdziarski et al., 2017), and the MAGIC flux ULs during the hard
state (Ahnen et al., 2017b).

Figure 10: Gamma-ray SED of Cyg X-1, for a possible steady emission up to VHE.
Red shaded region: The Fermi-LAT 4FGL Catalog HE steady spectrum, (Abdollahi
et al., 2020), Fermi-LAT (1-100 GeV). Cyan solid curve: CTA input model for
the simulation. Magenta points: MAGIC (160 GeV – 3.5 TeV) VHE ULs (95% C.L.)
from Ahnen et al. (2017b). Black points: CTA spectrum for a simulated
observation of 50 h. Figure 11: Gamma-ray SED of Cyg X-1, for a possible
steady emission up to VHE. Black solid curve: theoretical model from Zdziarski
et al. (2017), based on IC processes in the jet during the hard state. Blue
points: HE steady spectrum during the hard state (Zdziarski et al., 2017),
Fermi-LAT (60 MeV – 200 GeV). Red points: HE steady spectrum during the hard
state (Zanin et al., 2016), Fermi-LAT (60 MeV – 200 GeV). Magenta points:
MAGIC (160 GeV – 3.5 TeV) VHE flux ULs (95% C.L.) from Ahnen et al. (2017b).
Cyan solid curve: input model used for the simulation. Black points: simulated
spectrum for a CTA observation of 50 h.  Figure 12: Gamma-ray SED of Cyg X-1,
for a possible steady emission up to VHE. Blue, red and magenta points as
reported in Fig. 11. Black solid curve: theoretical model from Kantzas et al.
(2021), based on lepto-hadronic processes in the jet during the hard state.
Cyan solid curve: input model used for the simulation. Black points: simulated
spectrum for a CTA observation of 50 h.

Thus, according to our simulations, CTA will be able to detect a possible
persistent VHE gamma-ray emission from the jet of Cyg X-1, if the spectrum is
not characterized by a sharp cut off around 100 GeV. According to purely
leptonic models, a sharp cut off is expected below 1 TeV. On the contrary,
hadronic processes could be responsible for a bright emission above 1 TeV,
which could be detected by the CTA Observatory.

###  4.2 Low-mass X-ray binaries

LMXBs harbor a low-mass companion star and a black hole (or an accreting
neutron star), object tightly connected to jet launching that are responsible
for the non-thermal multi-wavelength emission (see review in Chaty, 2022). Up
to now, no LMXB has been detected at HE (apart from tMSPs) and only strong
hints of emission at HE have been reported in V404 Cyg. No LMXB has neither
been detected at VHE by any IACT. (see e.g. Aleksić et al. 2011; Ahnen et al.
2017a; H. E. S. S. Collaboration et al. 2018). The most recent X-ray outburst
of a black hole LMXB (BH-LMXB) which was followed up by the IACTs MAGIC,
H.E.S.S. and VERITAS was that of MAXI J1820$+$070, without detecting any VHE
emission (Abe et al., 2022). We examine here if CTA will be able to detect
such a similar exceptionally bright outburst but for a hypothetical source
located within a maximal distance of 4 kpc from Earth. Based on the
theoretical lepto-hadronic model of Kantzas et al. (2022), used since the
modeled LMXB can be considered a canonical source, we perform a number of
simulations where we rescale the predicted VHE emission for a number of
different jet inclination angles between 5 and $65^{\circ}$. We perform each
simulation for a number of different hypothetical sources at different
distances within 2 and 4 kpc.

In Fig. 13, we show the predicted VHE flux for a BH-LMXB with inclination
angle of $30^{\circ}$ assuming that the emission persists in three different
energy bins between 0.1 and 10 TeV, for at least 2 weeks, and compare it to
the CTA sensitivity curves (see Fig. 1).

Figure 13: Predicted VHE emission of a hypothetical BH-LMXB for three
different energy bins, as shown in the legends. The BH-LMXB follows the recent
outburst of MAXI J1820$+$070, but with an inclination angle of $30^{\circ}$
instead, and its distance is given by the colormap (lighter colors correspond
to more distant sources). We assume an emission lasting at least two weeks.
The CTA sensitivity for each energy bin is represented as a dashed orange
line.

Figure 14: Same as Fig. 13 but for an inclination angle of 40∘.

We overall see that CTA will be able to detect an outburst similar to MAXI
J1820$+$070 in the sub-TeV regime within a few tens of minutes if the LMXB is
located closer than $\sim 4\,$kpc at energies $<1.6$ TeV. The inclination
angle of the LMXB we assume here is relatively small compared to the average
value between $40$ and $70^{\circ}$ (see, e.g., Tetarenko et al., 2016), but
LMXBs with an inclination angle greater than $\sim 30^{\circ}$ fail to be
detected within the first hour of observations (Fig. 14). Sources with an
inclination angle less than $\sim 20^{\circ}$ could be observed within a few
minutes, such as the case of MAXI J1836$-$194 or V4641 Sgr, both microblazar
candidates (Russell et al., 2014; Gallo et al., 2014).

####  4.2.1 The case of V404 Cyg.

The system V404 Cyg is a LMXB located at a distance of $2.39\pm 0.14$ kpc,
inferred through parallax measurements (Miller-Jones et al., 2009). The system
is composed of a $9^{+0.2}_{-0.6}$ $M_{\odot}$ black hole and a
$0.7^{+0.3}_{-0.2}$ $M_{\odot}$ K3 III companion star with an orbital period
of $6.4714\pm 0.0001$ days (Casares et al., 1992). LMXBs are known to undergo
long periods of quiescence (years) and rapid outburst states (weeks). After a
$\sim$26 year-long quiescent phase, V404 Cyg entered in a bright active phase
in the second half of June 2015. The outburst, lasting $\sim$2 weeks, was
observed in all the bands of the electromagnetic spectrum, from radio to GeV
energies. AGILE-GRID and Fermi-LAT observed a strong hint of emission in gamma
rays ($\approx$4$\sigma$), coincident with the brightest peak of luminosity
observed in radio, hard X-ray and soft gamma-ray bands (Loh et al., 2016;
Piano et al., 2017). The gamma-ray event was observed between June 24 and 26
and it is simultaneous with rapid transitions between the optically thin and
the optically thick phases of the radio emission in the jet, and coincident
with a bright peak of the 511 keV emission line detected by INTEGRAL (Siegert
et al., 2016). As for other microquasars, the HE emission could be related to
either leptonic (IC scattering on soft photons) or hadronic processes (decay
of $\pi^{0}$ mesons produced in proton-proton collisions) in the jet.
Nevertheless, in this case the companion is an old spectral type, cold and
small star, and it does not provide a sufficiently high density of seed
photons and hadronic material in the stellar wind. Thus, the HE emission is
possibly related to interactions between the particles accelerated in the jet
and the radiation (and the magnetic field) of the jet itself. MAGIC
repetitively pointed at V404 Cyg between June 18 and 27, for more than 10
hours, but the observations did not show any significant emission at TeV
energies (Ahnen et al., 2017a).

###### V404 Cyg: transient emission

We carried out a 50-h CTA simulated observation for V404 Cyg with the same
setup described in Section 4.1.2: 100 GeV – 1 TeV simulated photons with a
multi-source approach. The CTA input spectral model for V404 Cyg is a simple
extension of the power-law spectrum observed by Fermi-LAT during the 2015-June
flaring activity and reported by Loh et al. (2016) (assuming: prefactor
$=8\times 10^{-22}$ ph $\mathrm{cm}^{-2}$ $\mathrm{s}^{-1}$
$\mathrm{MeV}^{-1}$, index = 3.5 and pivor energy = 1 TeV). The resulting
spectrum from our simulation is shown in Fig. 15, together with the non-
thermal HE spectra observed during the 2015-June flare. Thus, if we assume the
same spectral trend as observed by the HE gamma-ray detectors, we expect no
detection with CTA in a 50-h observation. This is in agreement with the
simulations on LMXBs described in Subsection 4.2.

Figure 15: Multi-frequency SED of V404 Cyg, related to the 2015-June flaring
activity. Green points: hard X-ray spectrum (Siegert et al., 2016), INTEGRAL
data (30 keV – 2 MeV). Blue points: HE flaring spectrum (Piano et al., 2017),
AGILE (50 MeV – 1 GeV). Red points: HE flaring spectrum (Piano et al., 2017),
Fermi-LAT (60 MeV – 10 GeV). Red shaded region: HE flaring spectrum, (Loh et
al., 2016), Fermi-LAT (100 MeV – 100 GeV). Magenta points: MAGIC (50 GeV – 10
TeV) VHE flux ULs (95% C.L.) from Ahnen et al. (2017a). Cyan solid curve:
input model used for the simulation. Black points: simulated spectrum for a
CTA observation of 50 h.

###  4.3 Transitional millisecond pulsars

Out of the three confirmed tMSPs, only PSR J1023+0038 is currently in the LMXB
state, whereas XSS J1227$-$4853 and IGR J18245$-$2452 are currently in the
RMSP state. As previously mentioned, other candidates were found through X-ray
peculiar variability and association with Fermi-LAT sources (see review by
Papitto & de Martino, 2022). Particularly interesting are the two confirmed
tMSPs PSR J1023+0038 and XSS J1227-485 that when in LMXB state they were found
by Fermi-LAT with a luminosity of about 1034 erg s-1 in the energy range
0.1–10 GeV, which is up to ten times brighter than the levels observed during
the RMSP state (Papitto & Torres, 2015; Torres et al., 2017). This fact makes
them particularly interesting for a possible detection with CTA. In this
Section, we estimate the chances of detecting these two tMSPs with CTA given
also their relatively close distance of about 1.5 kpc.

####  4.3.1 PSR J1023+0038

This tMSP was initially detected as a variable source in the radio band (Bond
et al., 2002) and showing clear characteristics of an accretion disc around
the compact object in the optical band. Later, Thorstensen & Armstrong (2005)
suggested PSR J1023+0038 as an NS-LMXB. The observations did not reveal an
accretion disc but the existence of a strong irradiation on the optical star
from an unseen companion. The compact object was identified as a 1.69
millisecond radio pulsar in a 4.75 hr orbit around a 0.2 M⊙ companion star
(Archibald et al., 2009b). In June 2013 the source came back to a LMXB state,
where it has remained until now, and the radio pulsar signal switched off
(Stappers et al., 2013). During the LMXB state, PSR J1023+0038 shows a
peculiar behaviour in X-rays: it exhibits frequent modes switching between
three different X-ray levels, dubbed high, low and flaring (Bogdanov et al.,
2015). The HE gamma-ray emission detected by Fermi-LAT has been reported to
brighten by a factor of 5 after the transition (Stappers et al., 2013). The
average Fermi-LAT spectrum is described by a power-law with index 1.8 and a
cutoff at an energy of 2.3 GeV according to Takata et al. (2014) and by a
power-law with index 2 and an energy cutoff at 3.7 GeV, being the significance
of the cutoff is 4.3$\sigma$ level according to Torres et al. (2017). Neither
pulsations nor steady emission were found in the VHE regime (Aliu et al.,
2016). To test the capability of CTA to detect emission from this source we
first studied the HE gamma-ray emission from Fermi-LAT during the LMXB state
(2013-2021), in order to obtain the spectral parameters of the source. The two
spectral models that have been considered for the CTA simulations are a
logparabola and a broken power-law. The power-law with the exponential cutoff
is not further considered because the cutoff at a few GeV would prevent a
detection at VHE; whereas, a simple power-law extending in the energy range
from GeV up to 1 TeV appears physically difficult to achieve. This is
compatible by the low significance of the results by Takata et al. (2014) and
Torres et al. (2017).

For the broken power-law: prefactor = (0.06$\pm$0.01) $\times$ 10-10 photons
cm-2 s-1 MeV-1, Index1 = -2.12$\pm$0.03, Index2 = -2.91$\pm$0.06, Energy break
= (1.15$\pm$0.09) GeV. For the logparabola: prefactor = (0.34$\pm$0.007)
$\times$ 10-10 photons cm-2 s-1 MeV-1, $\alpha$ = 2.23$\pm$0.02, $\beta$ =
0.16$\pm$0.02, Energy break = 0.524 GeV. Batches of 100 simulations were run
using both CTA-N and CTA-S IRFs for 50, 100 and 200 hours of observations; we
binned the simulated data into initial 20 logarithmic energy bins considering
an energy range of 0.03-100 TeV. The resulting spectrum of PSR J1023+0038 is
shown in Fig. 16 and, for simplicity, only the results with the highest
statistic are reported (200 h observations). The full analysis results for the
broken power-law model are reported in Table 6. We find that long integration
times are needed to detect this tMSP, with at least 100 h for CTA-N and 50 h
for CTA-S.

Figure 16: CTA-S simulations for the tMSP PSR J1023+0038 considering the
broken power-law model. We consider 200 hours of observations. The CTA
performance curve (green) is rescaled for 200 h.

The fit with a logparabola model did not converge.

Table 6: Broken power-law model significance’s results for North and South IRFs, considering 50, 100 and 200 h of observations of the tMSP PSR J1023+0038.  | Hours | TS | $\sigma$
---|---|---|---
North | 50 | 18.50 | 4.30
| 100 | 39.86 | 6.31
| 200 | 77.15 | 8.78
South | 50 | 29.36 | 5.42
| 100 | 55.47 | 7.45
| 200 | 114.77 | 10.71

####  4.3.2 XSS J1227-48538

XSS J1227-48538 was initially detected as a hard X-ray source and was
tentatively identified as a cataclysmic variable, similarly to PSR J1023+0038,
based on the double-peaked emission lines (typical of an accretion disc) in
the optical spectrum (Masetti et al., 2006). While the low X-ray luminosity
was not in contrast with a cataclysmic variable interpretation, the peculiar
X-ray variability with mode switching and the unexpected association with a
Fermi-LAT source proned to identify XSS J1227-48538 as an unusual LMXB (de
Martino et al., 2010). The system transitioned to a radio pulsar state between
November 14 and December 21, 2012, characterized by the disappearance of the
emission lines in the optical spectrum and the softening observed in the
radio, optical, X-ray and gamma-ray bands (Bassa et al., 2014; Torres et al.,
2017). Just after the transition, observations with the Giant Metrewave Radio
Telescope allowed to detect a radio pulsar with a 1.69 ms spin period in a
binary system with an orbital period of 6.9 hr (Roy et al., 2015). Before the
transition to the radio state, the gamma-ray emission was a factor of 2 larger
(Torres et al., 2017). The Fermi-LAT analysis performed for the period in
which the source was in the sub-luminous disk state (2008-2012) provides
results consistent with those reported by Xing & Wang (2015) and
t2017ApJ...836...68T: XSS J1227-48538 is best described by a power-law with a
cutoff at Ecut=5.3 GeV (at 3.4$\sigma$) and a spectral index of 2.
Similarly to PSR J1023+0038, the two spectral models considered for the CTA
simulations are the logparabola and the broken power-law. As input models for
the CTA simulations we considered the output from the Fermi-LAT study. For the
broken power-law: prefactor = (2.71$\pm$0.71) $\times$ 10-12 photons cm-2 s-1
MeV-1, Index1 = -2.23$\pm$0.04, Index2 = -2.77$\pm$0.10, Energy break =
(1.32$\pm$1.44) GeV. For the logparabola: prefactor = (3.26$\pm$0.91) $\times$
10-11 photons cm-2 s-1 MeV-1, $\alpha$ = 2.28$\pm$0.05, $\beta$ =
0.09$\pm$0.02, Energy break = (4.45$\pm$5.42) GeV. We performed batches of 100
simulations using only the CTA-S site IRFs and 50, 100 and 200 h of
observations. The simulated data were binned into 20 logarithmic energy bins
in an energy range of 0.03-100 TeV.

The resulting spectrum of XSS J1227-48538 is shown in Figure 17 and, for
simplicity, we reported only the results with the highest statistics. The full
analysis results are reported in Table 7 . The source could be detected with
CTA-S at 8.14$\sigma$ with 50 h of observation. As for PSR J1023+0038,
simulations considering the logparabola model failed to calculate the ULs.

Our simulations prove that the detection of the spectral component seen by
Fermi-LAT from of close-by tMSPs when in a disc state could be possible with
long exposures, provided that the emission has no cutoff at few GeVs. While
this will likely not allow to catch fully a transition if lasting less than
several days, here we demonstrate that once a transition has occurred CTA
could be able to detect such type of sources, identifying tMSPs as VHE
emitters for the first time. Also, if there are additional components (not
considered here, such as magnetic reconnection of pulsar wind) it could be
possible to detect changes in the HE flux along transitions.

Figure 17: CTA-S simulations for the tMSP XSS J1227-48538 considering the broken power-law model. We consider 200 h of observations. The CTA performance curve (green) is rescaled for 200 h. Table 7: Broken power-law model significance’s results for South IRFs, considering 50, 100 and 200 h of observations of the tMSP XSS J1227-48538.  | Hours | TS | $\sigma$
---|---|---|---
South | 50 | 66.26 | 8.14
| 100 | 128.04 | 11.31
| 200 | 253.99 | 15.94

###  4.4 Flares in PWNe: the Crab Nebula

The Crab Nebula is the best-studied PWN in the VHE regime. It is located at a
distance of $\approx 2.2$ kpc with $\approx 3.8$ pc of size (Trimble, 1973;
Davidson & Fesen, 1985). Since 2009, several rapid and bright flares have been
detected from the nebula at HE with space-borne gamma-ray instruments (Tavani
et al., 2011; Abdo et al., 2011; Buehler et al., 2012; Mayer et al., 2013;
Striani et al., 2013; Arakawa et al., 2020). The observed flares presented
variability timescales of hours. During these flaring periods, the nebula
showed rapid variations of flux and large releases of energy (Tavani et al.,
2011; Abdo et al., 2011). Several multi-wavelength campaigns involving Chandra
X-Ray Observatory, Keck Observatory and Very Large Array (VLA) (Weisskopf et
al., 2013) and TeV searches by IACTs (Mariotti, 2010; Ong, 2010; H. E. S. S.
Collaboration et al., 2014; Aliu et al., 2014a; van Scherpenberg et al., 2019)
were carried out to follow these flares. However, none of them reported a
correlation of the flares with morphological and/or spectral variations in the
nebula.

CTA will cover a fundamental energy range to understand the origin of these
flares: on the one hand, the low energy threshold will allow the sampling of
the Fermi-LAT spectral shape at few tens of GeV of synchrotron nature,
providing important clues on the acceleration and emission processes; on the
other hand, the excellent sensitivity in the TeV regime will serve to explore
the IC component that might arise at a detectable level from the electron
population behind the MeV flares, off-scattering soft photon fields.

To evaluate the capability of CTA to detect Crab flares, we performed
simulations of the SEDs both in flaring and steady (non-flaring) states of the
nebula. We simulated flares of different spectral characteristics starting
from a parent particle population, varying the physical properties of the
environment. In particular, we simulated three types of flares: a very bright
flare with similar flux (at hundreds of MeV) to the one observed by _Fermi_
-LAT in April 2011 (Buehler et al., 2012; Striani et al., 2013) which is the
flare with largest flux to date, and two dimmer flares corresponding to the
first one re-scaled by a factor 0.5 and 0.1. Since no spectral variability has
been reported at HE, we assume the same spectral model for these dimmer
flares. The simulations of the nebula in flaring and steady states are
performed for the CTA-N with the methods and tools presented in previous works
(Mestre et al., 2020, 2021). The electron population was simulated with a
fixed index ($\Gamma_{\rm e}$) of 2.5, to guarantee the detection in the TeV
regime (e.g., from 1.25 TeV to 50 TeV) of the brightest model of flare (see
Fig. 6 of Mestre et al. 2021) in less than 10 h (see Table 8). The different
flare models are computed for a magnetic field (B) in the acceleration region
ranging from 100 $\mu$G to 1 mG and compared (see section 2 of Mestre et al.
2021) to the steady nebula SED in both tens of GeV (e.g., from 20 GeV to 200
GeV) and TeV regimes. We obtained the simulations of the Crab nebula SED in
steady state from Mestre et al. 2020. To compare the flaring and steady nebula
simulations, we computed the mean total expected excess (e.g., counts from the
source after background subtraction), both in flaring and steady state, in 21
bins of energy from 12 GeV to 200 TeV with observation times ranging from a
few minutes to 500 h. We compared the excess distributions using the Pearson’s
chi-squared test, corresponding the null hypothesis ($\rm{H}_{0}$) to the
steady state. Then, we consider the flare implies a detectable flux level if
$\rm{H}_{0}$ is rejected at 95 % confidence level (CL).

The simulations performed show that the different models of flare are best
detected in the GeV regime and in particular in less than an hour at energies
below 200 GeV, see Fig. 18. In the TeV regime, flares dimmer than April 2011
flare by a factor 0.5 (at hundreds of MeV) would be detected in less than 10 h
for B $<500$ $\mu$G (see Table 8). Some of the models considered imply an
energy in TeV electrons larger than $\tau_{\rm syn}\times L_{\gamma}\approx
5\times 10^{43}$ erg, being $\tau_{\rm syn}$ the synchrotron cooling time, and
$L_{\gamma}\sim 2\times 10^{35}$ erg s-1, the luminosity of the nebula in
gamma rays (Rudak & Dyks, 1998). However, note that the energy in electrons
available in the nebula is not limited to the one computed above if particle
re-acceleration takes place, which would introduce additional boosts in the
electron population energy reservoir. The simulations performed, together with
previous results reported (see Mestre et al., 2021), provide excellent
prospects for detecting flares from the Crab Nebula with CTA, especially for
the LST subarray, featuring the best sensitivity at energies of a few tens of
GeV.

Figure 18: The synchrotron (green lines), IC (purple lines), and total (black lines) emission from the Crab Nebula for different flare models. The solid lines correspond to the model fitted to the Fermi-LAT April 2011 flare data at energies above 80 MeV for a particle index of $2.5$. The dashed and dotted lines correspond to the same model re-scaled by a factor of 0.5 and 0.1, respectively. All the models are computed for a magnetic field of 500 $\mu$G. The red solid and dashed lines correspond to the sensitivities of the CTA-N and, if considering only its four LSTs for 5 h of integration time, respectively. The Crab Nebula steady spectrum simulations for 50 h of observation time with CTA-N are noted with the gray shaded area ($3\sigma$ region). Table 8: In the second, third, and fourth columns, the observation time (in hours) necessary to detect different models of flares from 1.25 TeV to 50 TeV with CTA-N. The first column indicates the magnetic field chosen for the acceleration region. The observation times in the second column are computed for flare models fitted to the Fermi-LAT SED (at the moment of maximum flux level) of the April 2011 flare. For the third and fourth columns, the LAT SED (dubbed $F_{2011}$) was re-scaled prior to the fit by a factor of 0.5 and 0.1, respectively. The models with an asterisk imply an energy in electrons above 1 TeV larger than $5\times 10^{43}$ erg. We assume Crab is in flaring state during the entire observation time. Model B[$\mu$G] |  | Model SED |
---|---|---|---
| $F_{2011}$ | $0.5\times F_{2011}$ | $0.1\times F_{2011}$
$1000$ | $8.0$ | $166^{*}$ | $>500^{*}$
$500$ | $0.8$ | $6.0^{*}$ | $>500^{*}$
$100$ | $0.02$ | $0.07$ | $32^{*}$

###  4.5 Novae

The only nova that has been detected at TeV energies so far is the symbiotic
system RS Oph (Acciari et al., 2022; H. E. S. S. Collaboration et al., 2022;
Abe et al., 2023) which shows recurrent outburst every 15-20 years and
harbours a white dwarf accreting from a late-type giant companion star.
However, it could be argued that the detection is due to selection-effects
based on the fact that RS Oph is relatively nearby (see below). By number,
novae that involve a small, low-mass donor such as a main sequence star (these
are usually the classical novae, see Chomiuk et al., 2021) are by far the most
common type of system. The majority of novae have been observed in outburst
only once in a human life timescale, and so far only a handful of novae are
known to erupt with a recurrence time of ${\sim}$tens of years. It has been
predicted from binary population synthesis studies (Kemp et al., 2021, 2022)
that most commonly, novae with evolved donors are more likely to contribute to
the total current Galactic nova rate, even though by number these systems make
up a smaller fraction of nova binaries.

As pointed out recently by De et al. (2021), a large number of novae in
optical bands might be being missed due to a number of sources residing behind
and in the Galactic bulge. Taking obscuration by dust into account, De et al.
(2021) estimated a current Galactic nova rate of $43.7\pm^{19.5}_{8.7}$ per
year. This is notably much larger than the actual Galactic nova detection rate
of $\lesssim 10$ per year.

Kemp et al. (2022) estimated the Galactic nova rate to be $33$ per year. That
study showed that the most common type of nova in our Galaxy today is expected
to originate from a binary system involving a giant-like donor (see Fig. 11 in
the aforementioned paper as a guide). As mentioned previously, currently the
only system to have clearly been detected at VHE (and detected also at HE) is
the symbiotic recurrent nova RS Oph. Though some groups have investigated
detailed modelling of shock generation in nova systems (Hachisu & Kato, 2022;
Metzger et al., 2016), which is believed to be mainly hadronic in nature, it
is still not clear how many Galactic novae would be detectable by CTA at and
beyond the ${\sim}$TeV energy range. The majority of novae thus far detected
at GeV energies with no clear evidence for a TeV component have been classical
novae (not symbiotic systems like RS Oph, see e.g. Zheng et al., 2022).
Nonetheless, we anticipate several more novae could be observed with CTA (see
Chomiuk et al., 2021), particularly if these novae are detected at other
wavelengths early on enabling rapid triggering and follow-up. However,
assuming we can expect of the order of $\thicksim$30 Galactic novae per year,
even with adequate triggering, it is unlikely that all of these outbursts will
be detectable by CTA. If CTA-N would have been operational since August 2008
to April 2023, it would have been able to perform observations of 7 novae
detected in HE gamma-ray by Fermi-LAT, in the 5 nights after their detection
in optical. Assuming a similar rate of novae detected at HE gamma-ray in the
future, it means that CTA-N would observe $\sim 0.5$ novae per year triggered
by their HE gamma-ray emission.

CTA observations will be important to put constraints on the maximum energies
attainable in nova explosions and the physical mechanisms involved in the
production of VHE gamma rays. We estimated the capability of CTA to detect
nova outbursts based on both theoretical modelling and empirical results.
First, simple theoretical considerations based on the RS Oph detection are
adopted to assess the gamma-ray emission at different outburst stages,
following the approach in Acciari et al. (2022); H. E. S. S. Collaboration et
al. (2022). Second, a parametric study based on phenomenological parameters
involved in the emission of gamma rays in nova outbursts is performed to
estimate the parameter space we could constrain with CTA observations.
Finally, we considered dedicated numerical simulations of RS Oph to assess the
expected detectability with CTA.

####  4.5.1 Modelling approach

We explored the capability of CTA to constrain the physical parameters of nova
phenomena of different types, building up from basic arguments. The expected
gamma-ray emission is obtained for different properties of a shock expanding
with velocity ${\rm v_{sh}(t)}$, generated by ejected material of total mass
$M_{\rm{ej}}(t)$ slamming into the companion star’s wind and producing gamma
rays through hadronic interactions. To accelerate protons to high energies via
diffuse shock acceleration (DSA), the magnetic field has to be amplified in
the shock. The maximum energy particles attain at a shock is limited
ultimately by the Hillas condition (Hillas, 1984). However a more constraining
limit is determined by either the time taken before radiative cooling
dominates over acceleration, or by the necessary escape of the particles up-
stream of the shock, in order to excite magnetic field fluctuations to a
sufficient level ahead of the shock (Bell, 2004). The maximum energy
$E_{\rm{max}}$ in the particle spectrum, defined as as power-law function with
an exponential cutoff, can be then described as:

$E_{\rm max}=10\left(\frac{v_{\rm
sh}}{5000~{}\mathrm{km/s}}\right)\left(\frac{R_{\rm
sh}}{1~{}\mathrm{AU}}\right)^{-1}\left(\frac{B_{*}}{1~{}{\rm
G}}\right)~{}~{}~{}{\rm TeV,}$ (2)

with $R_{\rm sh}$ the position of the shock with respect to the white dwarf,
and $B_{*}$ the companion surface magnetic field (typically $\sim$1 G for a
red giant). $R_{\rm sh}$ can be expressed in terms of shock velocity, for
which we assumed free expansion during the first few days, followed by
radiative expansion when entering the Sedov-Taylor phase (Bode & Kahn, 1985).
The particle flux per unit of time and energy is computed using the condition
that a fixed fraction (50%) of the kinetic energy of the protons (${\rm
E_{kin}=\frac{1}{2}M_{ej}v_{sh}^{2}}$) is transferred to non-thermal particles
(Acciari et al., 2022; H. E. S. S. Collaboration et al., 2022). Once the
particle spectrum is defined as function of these three parameters ($v_{\rm
sh}$, $B_{*}$, $M_{\rm ej}$) at different evolutionary stages of the shock
expansion, we derive the gamma-ray emission originated by proton-proton
interaction assuming a density of the ejecta which can be approximated
following equation 4 in Acciari et al. (2022). The particle spectrum and
density was used to compute the non-thermal emission, using the `Naima`
spectral model class (Zabalza, 2015) included in `Gammapy`.

In Fig. 19 we show the expected gamma-ray flux at different times from the
nova explosion, considering several physical parameters in the shock. The
upper panels show the expected emission for a explosion similar to RS Oph,
with $B_{*}$, $M_{\rm ej}$ equal to 1 G and $10^{-6}M_{\odot}$, respectively,
located at a distance of 2 kpc (left) and of 4 kpc (right). The effect of
increasing the star surface magnetic field (10 G) and decreasing the ejecta
mass ($10^{-7}M_{\odot}$) is shown in the bottom panels, for a fixed distance
of 2 kpc. For reference, the isoflux line at $10^{-13}$ TeV cm-2 s-1 is marked
when possible with a white line. The region below such line should be easily
accessible to CTA.

Figure 19: Expected energy flux in gamma rays with time after nova explosion
as a function of shock velocity, integrated above 10 GeV. Top left: for an RS
Oph-like system at 2 kpc. Top right: for the same physical properties yet at a
larger distance of 4 kpc. Bottom left: with increased magnetic field strength.
Bottom right: with decreased mass-loss rate. In all plots the white dashed
line indicates the CTA isoflux line at $10^{-13}$ TeV cm-2 s-1. Below this
line the region should be easily accessible to CTA.

####  4.5.2 Parametric space study

We utilised a phenomenological approach to study the parameter space of gamma-
ray emission from novae. The emission was assumed to be produced by hadronic
processes from $\pi^{0}$ decay (Kafexhiu et al., 2014), as indicated by the
gamma-ray emission of RS Oph (see Section 4.5.3). The $\pi^{0}$ decay
radiative model was parameterised using the target proton density
($n_{\rm{h}}$) and the relativistic proton energy distribution. For the
latter, we considered a particle distribution function parameterised as a
power-law model with an exponential cutoff. We described the parameter space
under study as a 3D space, where we set the parameter space domain in the
range of plausible values based on observed novae at gamma rays. A 2D grid was
defined with different values for the prefactor ($A$) and the cutoff energy
($E_{\rm{cp}}$) of the proton energy distribution. The former in the range
between $A=[10^{28},10^{32}]\,\mathrm{protons\,eV^{-1}}$ at a pivot energy of
$100\,\rm{GeV}$ and the latter between $E_{\rm{cp}}=[10,1000]\,\rm{GeV}$. Two
slices for the target proton density were used for the third axis,
$n_{\rm{h}}=10^{8}\,\rm{cm^{-3}}$ and $n_{\rm{h}}=10^{11}\,\rm{cm^{-3}}$,
which correspond to typical shock density values in novae (Metzger et al.,
2016). The distance to the gamma-ray emitter was fixed to $d=2\,\rm{kpc}$. The
spectral energy distribution for each model was obtained using the software
package `Naima` (Zabalza, 2015).

The emission detectability was assessed for both arrays of CTA using the
official IRFs from `prod5-v0.1` in the Alpha configuration (`20deg-AverageAz`
for $5\,\rm{h}$ observation time) The results of the simulations for CTA-N and
CTA-S are shown in panels a and b of Fig. 20, respectively. The total proton
energy above 100 GeV ($W_{\rm p}$) multiplied by $\frac{n_{\rm h}}{d^{2}}$,
hereafter “effective proton energy reservoir”, was used as a function of
$E_{\rm{cp}}$ to display the ratio between the integral source flux and the
CTA sensitivity. This ratio was computed to obtain a qualitative estimation of
the detectability of CTA for each model in the parameter space. The higher the
integral flux-to-CTA-sensitivity ratio, the more feasible the detection.
Moreover, the region where we would detect each model with CTA in at least one
energy bin is lower-delimited in Fig. 20 by a dashed orange line to have a
more precise boundary of the detection region. Therefore, the region between
the dashed orange line and the white region (integral flux-to-CTA-sensitivity
close to 0) delimits the border of the parameter space where CTA will likely
begin to detect the gamma-ray emission of the models. Qualitatively, RS Oph
would be located approximately in the top right corner of Fig. 20, while V959
Mon (the first classical nova discovered by Fermi-LAT; Ackermann et al., 2014)
would be in the lower left region of the plots.

The integral gamma-ray emission and the integral flux-to-CTA-sensitivity ratio
in Fig. 20 increases as the effective proton energy reservoir and
$E_{\rm{cp}}$ increase. Both top regions of plots a and b in Fig. 20 have
positive values of integral flux-to-CTA-sensitivity ratio (about 30% of the
total combinations), while the bottom region do not (about 70% of the total
combinations). When comparing the results between CTA-N and CTA-S, the former