11institutetext:  Dublin Institute for Advanced Studies, 31 Fitzwilliam Place,
Dublin 2, Ireland 22institutetext: Max-Planck-Institut für Kernphysik, P.O.
Box 103980, D 69029 Heidelberg, Germany 33institutetext: Yerevan Physics
Institute, 2 Alikhanian Brothers St., Yerevan 0036, Armenia 44institutetext:
Yerevan State University, 1 Alek Manukyan St, Yerevan 0025, Armenia
55institutetext: Landessternwarte, Universität Heidelberg, Königstuhl, D 69117
Heidelberg, Germany 66institutetext: Kapteyn Astronomical Institute,
University of Groningen, Landleven 12, 9747 AD Groningen, The Netherlands
77institutetext: Laboratoire Leprince-Ringuet, École Polytechnique, CNRS,
Institut Polytechnique de Paris, F-91128 Palaiseau, France 88institutetext:
University of Namibia, Department of Physics, Private Bag 13301, Windhoek
10005, Namibia 99institutetext: Centre for Space Research, North-West
University, Potchefstroom 2520, South Africa 1010institutetext: Universität
Hamburg, Institut für Experimentalphysik, Luruper Chaussee 149, D 22761
Hamburg, Germany 1111institutetext: Deutsches Elektronen-Synchrotron DESY,
Platanenallee 6, 15738 Zeuthen, Germany 1212institutetext: Department of
Physics, University of the Free State, PO Box 339, Bloemfontein 9300, South
Africa 1313institutetext: Institut für Physik und Astronomie, Universität
Potsdam, Karl-Liebknecht-Strasse 24/25, D 14476 Potsdam, Germany
1414institutetext: Université Paris Cité, CNRS, Astroparticule et Cosmologie,
F-75013 Paris, France 1515institutetext: Department of Physics and Electrical
Engineering, Linnaeus University, 351 95 Växjö, Sweden 1616institutetext:
Institut für Physik, Humboldt-Universität zu Berlin, Newtonstr. 15, D 12489
Berlin, Germany 1717institutetext: Institut für Astronomie und Astrophysik,
Universität Tübingen, Sand 1, D 72076 Tübingen, Germany 1818institutetext:
Laboratoire Univers et Théories, Observatoire de Paris, Université PSL, CNRS,
Université Paris Cité, 5 Pl. Jules Janssen, 92190 Meudon, France
1919institutetext: Sorbonne Université, Université Paris Diderot, Sorbonne
Paris Cité, CNRS/IN2P3, Laboratoire de Physique Nucléaire et de Hautes
Energies, LPNHE, 4 Place Jussieu, F-75252 Paris, France 2020institutetext:
IRFU, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
2121institutetext: Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen
Centre for Astroparticle Physics, Nikolaus-Fiebiger-Str. 2, 91058 Erlangen,
Germany 2222institutetext: Astronomical Observatory, The University of Warsaw,
Al. Ujazdowskie 4, 00-478 Warsaw, Poland 2323institutetext: Université Savoie
Mont Blanc, CNRS, Laboratoire d’Annecy de Physique des Particules - IN2P3,
74000 Annecy, France 2424institutetext: Instytut Fizyki Ja̧drowej PAN, ul.
Radzikowskiego 152, 31-342 Kraków, Poland 2525institutetext: Université
Bordeaux, CNRS, LP2I Bordeaux, UMR 5797, F-33170 Gradignan, France
2626institutetext: School of Physics, University of the Witwatersrand, 1 Jan
Smuts Avenue, Braamfontein, Johannesburg, 2050 South Africa 2727institutetext:
University of Oxford, Department of Physics, Denys Wilkinson Building, Keble
Road, Oxford OX1 3RH, UK 2828institutetext: School of Physical Sciences,
University of Adelaide, Adelaide 5005, Australia 2929institutetext: Aix
Marseille Université, CNRS/IN2P3, CPPM, Marseille, France 3030institutetext:
Laboratoire Univers et Particules de Montpellier, Université Montpellier,
CNRS/IN2P3, CC 72, Place Eugène Bataillon, F-34095 Montpellier Cedex 5, France
3131institutetext: Universität Innsbruck, Institut für Astro- und
Teilchenphysik, Technikerstraße 25, 6020 Innsbruck, Austria 3232institutetext:
Obserwatorium Astronomiczne, Uniwersytet Jagielloński, ul. Orla 171, 30-244
Kraków, Poland 3333institutetext: Institute of Astronomy, Faculty of Physics,
Astronomy and Informatics, Nicolaus Copernicus University, Grudziadzka 5,
87-100 Torun, Poland

3434institutetext: Nicolaus Copernicus Astronomical Center, Polish Academy of
Sciences, ul. Bartycka 18, 00-716 Warsaw, Poland 3535institutetext: Department
of Physics and Astronomy, The University of Leicester, University Road,
Leicester, LE1 7RH, United Kingdom 3636institutetext: GRAPPA, Anton Pannekoek
Institute for Astronomy, University of Amsterdam, Science Park 904, 1098 XH
Amsterdam, The Netherlands 3737institutetext: Department of Physics, Konan
University, 8-9-1 Okamoto, Higashinada, Kobe, Hyogo 658-8501, Japan
3838institutetext: Kavli Institute for the Physics and Mathematics of the
Universe (WPI), The University of Tokyo Institutes for Advanced Study (UTIAS),
The University of Tokyo, 5-1-5 Kashiwa-no-Ha, Kashiwa, Chiba, 277-8583, Japan
3939institutetext: RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
4040institutetext: School of Science, Western Sydney University, Locked Bag
1797, Penrith South DC, NSW 2751, Australia

# Unveiling extended gamma-ray emission around HESS J1813$-$178

H.E.S.S. Collaboration  F. Aharonian Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 F.
Ait Benkhali Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.
Aschersleben Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 H.
Ashkar Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 M. Backes Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 A. Baktash Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 V.
Barbosa Martins Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.
Barnard Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 R. Batzofin Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 Y. Becherini Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 D.
Berge Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178Unveiling extended gamma-ray emission
around HESS J1813$-$178 K. Bernlöhr Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 B. Bi Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Böttcher Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 C.
Boisson Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 J. Bolmont Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 M. de Bony de Lavergne Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 J. Borowska Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 M. Bouyahiaoui Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
M. Breuhaus Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 R.
Brose Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 F. Brun Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 B. Bruno Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 T. Bulik Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 C.
Burger-Scheidlin Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S.
Caroff Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 S. Casanova Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 R. Cecil Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 J. Celic Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Cerruti Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 P. Chambery
11footnotemark: 1 Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 T.
Chand Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 A. Chen Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 J. Chibueze Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 O. Chibueze Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 G.
Cotter Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 J. Damascene Mbarubucyeye
Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 A. Djannati-Ataï Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 A. Dmytriiev Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 V. Doroshenko Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
S. Einecke Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.-P.
Ernenwein Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 K.
Feijen Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 M. Filipovic Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 G. Fontaine Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 M. Füßling Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S.
Funk Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 S. Gabici Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 Y.A. Gallant Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 S. Ghafourizadeh Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
G. Giavitto Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 D.
Glawion Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 J.F. Glicenstein Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 P. Goswami Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 G. Grolleron Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
M.-H. Grondin Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.A.
Hinton Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 W. Hofmann Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 T. L. Holch Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 M. Holler Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Jamrozy Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 F. Jankowsky Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 V. Joshi 11footnotemark: 1 Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 I. Jung-Richardt Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 K. Katarzyński Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 R. Khatoon Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 B.
Khélifi Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 S. Klepser Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 W. Kluźniak Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 Nu. Komin Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 K.
Kosack Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 D. Kostunin Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 A. Kundu Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 R.G. Lang Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S. Le
Stum Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 F. Leitl Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 A. Lemière Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 M. Lemoine-Goumard Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 J.-P. Lenain Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 F.
Leuschner Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.
Mackey Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 D. Malyshev Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 D. Malyshev Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 V. Marandon Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 P.
Marinos Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 G. Martí-Devesa Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 R. Marx Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 A. Mehta Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 A.
Mitchell 11footnotemark: 1 Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 R.
Moderski Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 L.
Mohrmann Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 A.
Montanari Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 E.
Moulin Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 T. Murach Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 M. de Naurois Unveiling extended gamma-
ray emission around HESS J1813$-$178Unveiling extended gamma-ray emission
around HESS J1813$-$178 J. Niemiec Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 A. Priyana Noel Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 P.
O’Brien Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 S. Ohm Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 L. Olivera-Nieto Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 E. de Ona Wilhelmi Unveiling extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 M. Ostrowski Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S.
Panny Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 M. Panter Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 R.D. Parsons Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 D.A. Prokhorov Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
G. Pühlhofer Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Punch Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 A. Quirrenbach Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 M. Regeard Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 P. Reichherzer Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
A. Reimer Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 O.
Reimer Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 H. Ren Unveiling extended
gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-ray
emission around HESS J1813$-$178 M. Renaud Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 B. Reville Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 F.
Rieger Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 G. Roellinghoff Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 B. Rudak Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 V. Sahakian Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 H.
Salzmann Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Sasaki Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 F. Schüssler Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 H.M. Schutte Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 J.N.S. Shapopi Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
A. Specovius Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S.
Spencer Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 R. Steenkamp Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 S. Steinmassl Unveiling extended gamma-
ray emission around HESS J1813$-$178Unveiling extended gamma-ray emission
around HESS J1813$-$178 C. Steppa Unveiling extended gamma-ray emission around
HESS J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178
I. Sushch Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 H.
Suzuki Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 T. Takahashi Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 T. Tanaka Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 R. Terrier Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Tluczykont Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 N.
Tsuji Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 T. Unbehaun Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 C. van Eldik Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 M. Vecchi Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 J.
Veh Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 C. Venter Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178 J. Vink Unveiling extended gamma-ray
emission around HESS J1813$-$178Unveiling extended gamma-ray emission around
HESS J1813$-$178 T. Wach Corresponding authors;
e-mail<EMAIL_ADDRESS>extended gamma-ray emission
around HESS J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178 S.J. Wagner Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 A.
Wierzcholska Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 M.
Zacharias Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 D.
Zargaryan Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 A.A.
Zdziarski Unveiling extended gamma-ray emission around HESS
J1813$-$178Unveiling extended gamma-ray emission around HESS J1813$-$178 S.
Zouari Unveiling extended gamma-ray emission around HESS J1813$-$178Unveiling
extended gamma-ray emission around HESS J1813$-$178 N. Żywucka Unveiling
extended gamma-ray emission around HESS J1813$-$178Unveiling extended gamma-
ray emission around HESS J1813$-$178

(March 25, 2024)

###### Abstract

Context. HESS J1813$-$178 is a very-high-energy $\gamma$-ray source spatially
coincident with the young and energetic pulsar PSR J1813$-$1749 and thought to
be associated with its pulsar wind nebula (PWN). Recently, evidence for
extended high-energy emission in the vicinity of the pulsar has been revealed
in the _Fermi_ Large Area Telescope (LAT) data. This motivates revisiting the
HESS J1813$-$178 region, taking advantage of improved analysis methods and an
extended data set.

Aims. Using data taken by the High Energy Stereoscopic System (H.E.S.S.)
experiment and the _Fermi_ -LAT, we aim to describe the $\gamma$-ray emission
in the region with a consistent model, to provide insights into its origin.

Methods. We performed a likelihood-based analysis on 32 hours of H.E.S.S. data
and 12 years of _Fermi_ -LAT data and fit a spectro-morphological model to the
combined datasets. These results allowed us to develop a physical model for
the origin of the observed $\gamma$-ray emission in the region.

Results. In addition to the compact very-high-energy $\gamma$-ray emission
centered on the pulsar, we find a significant yet previously undetected
component along the Galactic plane. With _Fermi_ -LAT data, we confirm
extended high-energy emission consistent with the position and elongation of
the extended emission observed with H.E.S.S. These results establish a
consistent description of the emission in the region from GeV energies to
several tens of TeV.

Conclusions. This study suggests that HESS J1813$-$178 is associated with a
$\gamma$-ray PWN powered by PSR J1813$-$1749\. A possible origin of the
extended emission component is inverse Compton emission from electrons and
positrons that have escaped the confines of the pulsar and form a halo around
the PWN.

###### Key Words.:

gamma rays: general - pulsars: individual PSR J1813-1749 - Pulsar Wind Nebulae

##  1 Introduction and multiwavelength context

Results of the Galactic plane survey, conducted by the Imaging Atmospheric
Cherenkov Telescope (IACT) Array H.E.S.S. (Aharonian et al., 2005, 2006b;
H.E.S.S. Collaboration, 2018), have significantly improved our knowledge of
the Galactic very-high-energy (VHE) $\gamma$-ray sky. This survey detected
many previously unknown sources, many of which have multi-wavelength
counterparts, shedding light on the acceleration mechanism of charged
particles. However, due to a large number of possible acceleration sites, firm
identification of VHE sources often remains elusive, with high-energy
$\gamma$-rays being mainly produced by either the interaction of leptons with
interstellar radiation fields or inelastic collisions of hadronic cosmic rays
with nuclei of the interstellar medium such as molecular clouds. Therefore,
$\gamma$-rays are a valuable probe for understanding the acceleration of
particles to extreme energies.

HESS J1813$-$178 is a bright source discovered in 2006, located directly on
the Galactic plane (GLON: $12.82\pm 0.03^{\circ}$, GLAT: $-0.03\pm 0.02\degr$)
with a $1\,\sigma$ radius of $\sigma=(0.050\pm 0.004)\degr$, (H.E.S.S.
Collaboration, 2018). This discovery was confirmed by the IACT system MAGIC
(Albert et al., 2006), and the detection of an X-ray counterpart was reported
(Ubertini et al., 2005; Funk et al., 2007; Helfand et al., 2007). HESS
J1813$-$178 is positionally coincident with the young shell-type radio
supernova remnant G012.8–00.0, with an estimated age of $300-2500\,$years
(Brogan et al., 2005a; Camilo et al., 2021) and the SNR G012.7–00.0, as well
as the young, energetic pulsar PSR J1813$-$1749 with a characteristic age of
$5600\,$years and a spin-down luminosity of $\dot{E}=5.6\times
10^{37}\,\text{erg}\text{s}^{-1}$ (Gotthelf & Halpern, 2009; Camilo et al.,
2021).

Additionally to the compact emission, extended emission, labeled as HGPSC 063,
was observed, but it was believed to be a potential background artefact and
therefore discarded (H.E.S.S. Collaboration, 2018).

In contrast to the $0.036\degr$ extended source detected at TeV, analysis of
GeV _Fermi_ -LAT data revealed emission that is positionally coincident with
HESS J1813$-$178, but with an extension of $0.6\degr\pm 0.06\degr$ (Araya,
2018). A recent study of the region with _Fermi_ -LAT supports the detection
of extended emission and estimates a spatial extent of the emission of
$0.56^{\circ}$ in an energy range of $1\,\text{GeV}-20\,\text{GeV}$ (Xin &
Guo, 2021). While previous studies of the TeV emission favour a leptonic
origin connected to the pulsar (Funk et al., 2007), Araya (2018) concluded
that the origin of the GeV $\gamma$-ray emission is more likely to be cosmic
rays accelerated at the shock fronts of the Supernova Remnant (SNR) or the HII
star-forming region W33, located at a distance of $10\arcmin$ from HESS
J1813$-$178\. In this case, cosmic rays collide with ambient gas, producing
$\pi_{0}$ which then decay into two $\gamma$-ray photons.

Studies of the region have also been conducted by HAWC, revealing the extended
emission 3HWC J1813$-$174, with an extension of less than $0.5^{\circ}$
(Albert et al., 2020). LHAASO observations of this region also reveal extended
emission. The source LHAASO J1814$-$1719u∗ observed with an extension of
$(0.71\pm 0.07)^{\circ}$ by the Water Cherenkov Detector Array (WCDA) and an
extension of $<\,0.27^{\circ}$ in the one square kilometer array (KM2A) data,
as well as the source LHAASO J1814$-$1636u only observed by the KM2A array
with an extension of $(0.68\pm 0.08)^{\circ}$ (Cao et al., 2023). Note,
however, that there are intrinsic uncertainties in the association of sources
detected by the WCDA and KM2A LHAASO facilities, with LHAASO J1814$-$1719u∗
indicated as an uncertain merger, such that the extended LHAASO J1814$-$1719u∗
observed by WCDA may actually correspond to the extended LHAASO J1814$-$1636u
observed by KM2A.

The confirmation of the detection of large, extended emission in the region
around HESS J1813$-$178 by the Water Cherenkov Detectors, and improvements in
background rejection and event reconstruction, have recently led to the
discovery of previously undetected, large extended emission in IACT data
(Abdalla et al., 2021; H. E. S. S. Collaboration et al., 2023). This is a
particularly interesting development for the region around HESS J1813$-$178
and warrants a reanalysis of the region to resolve the disagreement between
the different observed morphologies.

While pulsar halos have been detected in evolved systems, regions powered by
the emission from young pulsars usually present a confined PWN (Giacinti et
al., 2020). Therefore, a significant detection of extended $\gamma$-ray
emission in the TeV energy range around PSR J1813$-$1749 will help to resolve
the discrepancy in extension between GeV and TeV energies. Observing the
escape of electrons from the PWN into the interstellar medium at such a young
age is highly unlikely, therefore the detection of extended emission resulting
from highly relativistic electrons could hint at an untypical behaviour of the
pulsar or an early interaction of the reverse shock of the SNR with the pulsar
wind, disrupting the system and facilitating an early release of particles
into the surrounding Interstellar medium (ISM).

We present an updated analysis of the H.E.S.S. data in the region around PSR
J1813$-$1749\. To obtain a consistent description of the region, we carry out
an analysis of the _Fermi_ -LAT data, with increased exposure compared to the
study conducted in Araya (2018), and a joint likelihood minimisation of these
datasets, allowing us to analyse the data from both experiments simultaneously
and obtain a consistent description. We additionally present a leptonic and
hadronic model in order to explain the emission observed around PSR
J1813$-$1749.

##  2 Data analysis

###  2.1 H.E.S.S.

####  2.1.1 Data selection

The H.E.S.S. array consists of four imaging atmospheric Cherenkov telescopes
with a mirror diameter of $12\,$m, constructed in 2003, located in the Khomas
Highland in Namibia (Aharonian et al., 2006a). A fifth $28\,$m diameter
telescope was added to the array in 2012. The telescopes are capable of
detecting photons in an energy range from a few tens of GeV up to $100$ TeV.
The data used in this analysis was obtained between 2004 and 2010 as part of
different observation campaigns in the sky region, therefore the fifth
telescope has not been used in the following analysis.

H.E.S.S. observations consist of data collection intervals of $\sim 28\,$min,
called observation runs. The selection of suitable data is based on the
observation characteristics for each run. For this data analysis,
participation of at least three telescopes per run was required. An additonal
requirement was the pointing position of the telescopes, which was required to
not be offset by more than $2.0\degr$ from $\text{RA}=273.40^{\circ}$,
$\text{Dec}=-17.84\degr$, the position of HESS J1813$-$178 as derived in
Aharonian et al. (2006b).

After applying standard selection cuts used in spectral analysis (Aharonian et
al., 2006a), this selection resulted in a dataset with a total exposure of 32
hours. The average angular distance of the position of HESS J1813$-$178 to the
centre of the field of view (FoV) in all observations of the dataset is
$1.28\degr$, as most observations were taken around a neighboring source, HESS
J1809-193 (Fig. 16, H.E.S.S. Collaboration 2023).

The data reduction was performed using the H.E.S.S. analysis package (see
Aharonian et al. 2006a). The data was reconstructed using the ImPACT (Image
pixel-wise fit for atmospheric Cherenkov Telescope) algorithm, which
determines the best-fit parameters of the $\gamma$-ray-like events by using a
template-based maximum-likelihood approach (Parsons & Hinton, 2014).

An important source of background in the analysis of IACT data are atmospheric
air showers initiated by charged cosmic-ray particles. Cosmic-ray showers
outnumber the showers initiated by $\gamma$-rays by several orders of
magnitude. To describe this background across the whole field of view, a
template model was used. This model was constructed from a large set of runs
taken in regions without known $\gamma$-ray sources, following the scheme
described in Mohrmann et al. (2019). The flux normalisation and spectral index
of this field of view background template were used used to account for the
different observation conditions in each run (for more information see
Appendix A).

For each individual run, a safe energy threshold was defined to exclude the
threshold region where effective detection areas vary steeply with energy, and
where the energy reconstruction is biased. The threshold was chosen as the
energy at which the energy bias (the deviation between true and reconstructed
event energy (Aharonian et al., 2006a)) is below 10%. A second energy
threshold was defined as the peak in the field of view background template
spectrum (Mohrmann et al., 2019); the higher of the two thresholds was applied
for the run.

The events passing the cut criteria were then stacked into a single dataset
and the field of view background template, as discussed in Mohrmann et al.
(2019), was applied. In addition to the run-wise threshold, a global energy
threshold for the dataset of $0.4$ TeV was set. All events below this energy
were excluded from the binned-likelihood estimation.

####  2.1.2 Data processing

The open-source Python package gammapy, version 0.18.2 (Deil et al., 2020;
Donath et al., 2023) was used for the data analysis, to characterise the
spectral and morphological properties of the $\gamma$-ray emission. Gammapy
enables a three-dimensional likelihood analysis that stores the data and
models in data cubes, allowing a simultaneous parameter optimisation of the
model in the two spatial dimensions and energy. All results were cross-checked
using an independent calibration and reconstruction scheme (Khelifi et al.,
2015).

The background model flux normalisation and spectral index were fitted to each
run used in the analysis to account for differences in atmospheric conditions
and changes in the optical efficiency of the telescopes over time. The list of
events passing the selection criteria was then combined into a data cube of
$4\,^{\circ}\times 4\,^{\circ}$, centred on the previously derived position of
HESS J1813$-$178 in the equatorial coordinate system. This size ensures a
sufficiently large off-source region for estimating the rate of remaining
hadronic background events, without adding a large number of unrelated
$\gamma$-ray sources. Spatial bins of $0.02\,^{\circ}$ size, and a logarithmic
energy binning of 25 bins between $0.1\,$TeV, and $100\,$TeV, were chosen for
this study.

A likelihood fit to determine the best description of the emission in the FoV
was then conducted. For this purpose symmetric and elongated 2-dimensional
Gaussian source models where used to describe the morphology. The symmetric
Gaussian is defined as:

$\Phi\,(\Theta)=\frac{1}{2\pi\sigma_{M}^{2}}\exp{\left(-\frac{1}{2}\frac{\Theta^{2}}{\sigma_{M}^{2}}\right)}\,\,,$
(1)

with $\sigma_{M}$ the major axis of the Gaussian and $\Theta$ the angular
distance to the model centre. In the case of an elongated Gaussian, the major
axis $\sigma_{M}$ is defined by $\sigma_{\text{eff}}$, the effective
containment radius:

$\sigma_{\text{eff}}\,(\Delta\phi)=\sqrt{\left(\sigma_{M}\sin{(\Delta\phi)}\right)^{2}+\left(\sigma_{M}\cdot\sqrt{(1-e^{2})}\cos{(\Delta\phi)}\right)^{2}}\,\,,$
(2)

with $e$ the eccentricity and $\Delta\phi$ the difference between the position
angle of the Gaussian $\phi$, and the position angle of the evaluation point.
As a spectral model, a power law was used. This model is described by:

$\frac{\text{dN}}{\text{dE}}=\text{N}_{0}\cdot\left(\frac{\text{E}}{\text{E}_{0}}\right)^{-\Gamma}\,\,,$
(3)

where $\text{N}_{0}$ is the flux normalisation factor, $\Gamma$ the spectral
index and $\text{E}_{0}$ the reference energy, which is set to $1\,$TeV for
the whole study. Alternatively, a logarithmic parabola spectral model was
used:

$\frac{\text{dN}}{\text{dE}}=\text{N}_{0}\cdot\left(\frac{\text{E}}{\text{E}_{0}}\right)^{-\Gamma-\beta\log\left(\frac{\text{E}}{\text{E}_{0}}\right)}\,\,,$
(4)

where $\beta$ is the curvature, as well as a power law with a generalised
exponential cut-off

$\frac{\text{dN}}{\text{dE}}=\text{N}_{0}\cdot\left(\frac{\text{E}}{\text{E}_{0}}\right)^{-\Gamma}\cdot\exp{(-\lambda\text{E})}\,\,,$
(5)

with $\lambda$, the inverse of the cut-off energy.

Significance maps of the region were computed using the method described in Li
& Ma (1983). For all sky maps, a correlation radius of $0.4^{\circ}$ was
applied, since this has proven beneficial for detecting extended emission in
previous studies (Abdalla et al., 2021). The choice of correlation radius has
no influence on the analysis, it only improves the visibility of large
extended emission.

####  2.1.3 Estimation of systematic uncertainties

The Instrument Response Functions (IRFs) describe the response of the system
under various observation conditions. The IRFs for each run were obtained by
interpolating between IRFs generated from Monte Carlo simulations covering a
grid of observational conditions (Bernlöhr, 2008). This method cannot describe
all variations of observational conditions in detail, which leads to
systematic uncertainties affecting the likelihood minimisation. In this
analysis, three possible sources of uncertainties were considered in our
results.

Firstly, a discrepancy between the true and reconstructed pointing positions
will lead to uncertainties in source position estimation. As indicated in
Acero et al. (2010), the uncertainty of the pointing is $20\,\arcsec$,
estimated using the position of known $\gamma$-ray sources and stars.

Secondly, the reconstruction of the energy of a $\gamma$-ray strongly depends
on the optical efficiency of the telescopes, influenced by effects such as
degradation of the photomultiplier tubes or mirrors over time. Additionally,
the transparency of the atmosphere, affected by effects such as the presence
of aerosols, strongly influences the accuracy of the energy reconstruction. A
discrepancy in energy reconstruction particularly influences the estimated
spectral parameters of the source.

Thirdly, an important aspect of the data analysis is the correct statistical
description of the inferred background event rate as a function of energy. The
background model used in this analysis was constructed using observation runs
taken under not fully identical observation conditions from those runs used in
this analysis. The statistical and systematic uncertainties in the inferred
background model will lead to uncertainty in the prediction of background
counts and affect all fit parameters.

To assess the systematic errors, a large number of pseudo-datasets with a
shift of the energy scale, as well as a shift of the amplitude and index of
the background model were created, and a linear gradient to the hadronic
background model was applied. Then, a likelihood minimisation for these
pseudo-datasets was performed. Using this method, the spread of the resulting
fit values can be interpreted as the systematic error of the respective
parameter. In addition, the systematic error in the pointing position is
added. A more detailed description of the method can be found in Appendix B,
and the systematic errors estimated for the source parameters are presented in
Table 1.

###  2.2 _Fermi_ -LAT Data

The LAT onboard the _Fermi_ satellite detects $\gamma$-rays between $20\,$MeV
and more than $300\,$GeV from the entire sky by pair-conversion within the
detector (Atwood et al., 2009).

In this study, the data from the beginning of the mission in August 2008 until
October 2021 was analysed. The most recent IRFs from Pass 8 version 3 —
P8R3_SOURCE_V2 (Ajello et al., 2021) were used and the catalogue models were
taken from the 12-year 4FGL source catalogue (Abdollahi et al., 2020). A
$6\degr$ region of interest (ROI) around the source position of 4FGL
J1813$-$1737e, as derived in Araya (2018), a bin size of $0.025\degr$ and 8
energy bins per decade with logarithmic spacing were used. Only events
arriving with a maximum zenith angle of $90\degr$ were considered, in order to
avoid including secondary $\gamma$-rays from the Earth’s horizon.

The background was modeled using a isotropic background model
(iso_P8R3_SOURCE_V3_v1.txt), and a Galactic diffuse background model
(gll_iem_v07.fits). In order to describe the region well, all known catalogue
sources in a region of $10\degr$ around the source position were included.

For the analysis, the Python package fermipy, version 1.0.1 (Wood et al.,
2017), optimised for performing a binned likelihood analysis of _Fermi_ -LAT
data using the _Fermi_ Science Tools, was used. With fermipy a counts cube and
IRF cubes in an energy range between $1\,$GeV and $1\,$TeV was created. For
the analysis of the source, the data, IRFs, and background models were
exported to gammapy. In contrast to the standard analysis chain of the _Fermi_
-LAT data, this allows us to fit both morphological and spectral parameters
simultaneously.

##  3 Results

###  3.1 H.E.S.S. Results

A significance map of the region, computed with a correlation radius of
$0.4^{\circ}$, is shown in Fig. 1. A significance map computed with a
correlation radius of $0.06^{\circ}$, which is equivalent to the point-spread-
function (PSF) of the analysis, has also been computed and can be seen in
figure 15.

Figure 1: Significance maps of the data taken by H.E.S.S. in the energy range
between $0.4\,$TeV to $100\,$TeV. For both maps, a correlation radius of
$0.4^{\circ}$ was used. Left: Significance map of the region around PSR
J1813$-$1749\. The contours correspond to the $3\,\sigma$ and $5\,\sigma$
regions. The dashed line indicates the position of the Galactic plane. Right:
Significance map of the region after subtracting the emission using four
components. The blue dots indicate the positions of both pulsars. The
$1\,\sigma$ Gaussian extend of the models used to describe the emission are
indicated by the grey and black lines.

Bright $\gamma$-ray emission around the pulsar PSR J1813$-$1749 is visible.
Additionally, one can observe diffuse, extended emission around the pulsar, as
well as $\gamma$-ray emission from the source HESS J1809$-$193 an extended
source potentially powered by the pulsar PSR J1809$-$1917\. The $\gamma$-ray
emission from this source was accounted for by using the best-fit description
derived in H.E.S.S. Collaboration (2023). The $1\,\sigma$ extends of the two
Gaussian models used in the analysis are indicated by the grey dashed lines in
the right panel of Fig. 1.

The compact emission can be accounted for using a Gaussian model, centred at a
position of $\text{R.A.}=(273.396\pm 0.004)\degr,\text{Dec.}=(-17.831\pm
0.004)\degr$ and $\sigma=(0.056\pm 0.003)\degr$, hereafter referred to as HESS
J1813$-$178A. The emission is well described with a power-law spectral model
and detected with a significance of $38\,\sigma$. The best-fit position and
extension derived in this analysis are compatible with the results reported in
Aharonian et al. (2006b).

In addition to the compact emission centred at the location of PSR
J1813$-$1749, a second extended emission component was detected during the
Galactic plane survey (H.E.S.S. Collaboration, 2018), but discarded because of
large uncertainties in the background estimation. The emission was reported to
be located at $\text{R.A.}=(273.46\pm 0.05)\degr,\text{Dec.}=(-17.77\pm
0.06)\degr$ with a Gaussian width of $\sigma=(0.31\pm 0.06)\degr$ (H.E.S.S.
Collaboration, 2018). In addition to the improved image reconstruction
technique ImPACT (Parsons & Hinton, 2014), this study used a background
template created from a large number of archival observations in order to
estimate the background events, as opposed to the former approach, which only
used a ring-shaped area around the source from the observation run itself and
is therefore heavily biased by the initial assumption of an extension of the
emission (Aharonian et al., 2006b). With these improvements, a firm detection
of significant extended emission in the source region is possible. The
morphological model which best describes the emission is evaluated, testing
both a disk-like model and a Gaussian model, each with and without the
possibility of an elongation. This study finds that an elongated Gaussian
model centred at $\text{R.A.}=(273.61\pm 0.06)\degr,\text{Dec.}=(-17.39\pm
0.07)\degr$ with a semi-major axis of $\sigma=(0.72\pm 0.08)\degr$ describes
the emission best. The gaussian model is preferred over the disk-like model
with $\Delta TS=59.91$, while the elongated Gaussian model is preferred by
$3.4\,\sigma$ compared to the symmetric Gaussian model. The increased size
compared to the first report of possible extended emission can be attributed
to the difference in background estimation. A power-law model was used to
describe the emission. This additional extended emission, hereafter referred
to as HESS J1813$-$178B, was detected with a significance of $13\,\sigma$. The
best-fit spectral and spatial parameters of both models are shown in Table 1.

Table 1: Best-fit parameters obtained for the likelihood minimisation of H.E.S.S. data, following the spatial and spectral description introduced in section 2.1.2. | HESS J1813$-$178A | HESS J1813$-$178B
---|---|---
$\Gamma$ | $2.17\pm 0.05_{\text{stat}}\pm 0.03_{\text{sys}}$ | $2.36\pm 0.09_{\text{stat}}\pm 0.05_{\text{sys}}$
$\text{N}_{0}\text{ at }1\,\text{TeV}\,\,[10^{-12}\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}]$ | $3.16\pm 0.18_{\text{stat}}\pm 0.24_{\text{sys}}$ | $9.89\pm 1.40_{\text{stat}}\pm 1.23_{\text{sys}}$
R.A. $[^{\circ}]$ | $273.400\pm 0.004_{\text{stat}}\pm 0.001_{\text{sys}}$ | $273.61\pm 0.06_{\text{stat}}\pm 0.07_{\text{sys}}$
Dec. $[^{\circ}]$ | $-17.831\pm 0.004_{\text{stat}}\pm 0.001_{\text{sys}}$ | $-17.39\pm 0.07_{\text{stat}}\pm 0.08_{\text{sys}}$
$\sigma_{M}$ $[^{\circ}]$ | $0.056\pm 0.003_{\text{stat}}\pm 0.001_{\text{sys}}$ | $0.72\pm 0.08_{\text{stat}}\pm 0.09_{\text{sys}}$
$e$ | - | $0.80\pm 0.06_{\text{stat}}\pm 0.04_{\text{sys}}$
$\Delta\varphi$ $[^{\circ}]$ | - | $40\pm 7_{\text{stat}}\pm 6_{\text{sys}}$

The best-fit position and extension along the major axis of components A and B
are shown in Fig. 1 by the black lines. The morphology of HESS J1813$-$178B is
in good spatial agreement with the extended emission 3HWC J1813$-$174 observed
by HAWC, as well as 1LHAASO J1814$-$1719u*, extended emission observed by the
WCDA of LHAASO (see figure 20).

Figure 2: Spectra and Spectral energy distribution (SED) of the H.E.S.S.
$\gamma$-ray emission from HESS J1813$-$178A and the extended emission from
HESS J1813$-$178B. The SED derived in Aharonian et al. (2006b) are shown as
filled triangles, and follow the emission from HESS J1813$-$178A closely.

The spectra of both components are depicted in Fig. 2. Additionally, the
morphological structure is tested for energy-depencence, the results of this
study are presented in section 3.3.

###  3.2 Fermi-_LAT_ results

Figure 3: Significance maps of the _Fermi_ -LAT data around the position of
$4\text{FGL}\,\text{J}1813$-$1737$e in the energy range from $1\,$GeV to
$1\,$TeV, with a correlation radius of $0.1^{\circ}$. Left: The position of
the Galactic plane is indicated by the dashed line, the pulsar position is
indicated in blue, and $3\,\sigma$ and $5\,\sigma$ contours are depicted.
Right: Significance map of the region after subtracting the emission using an
elongated Gaussian model and a symmetric Gaussian model. The $1\,\sigma$
Gaussian extent of the models is depicted by the black dashed lines.  Figure
4: SED and best-fit spectral models of the two-component description derived
from the analysis of the data obtained by the _Fermi_ -LAT satellite, and SED
derived in Araya (2018).

A study using nine years of data revealed extended emission, later referred to
as 4FGL J1813$-$1737e, in the region around PSR J1813$-$1749 (Araya, 2018).
They reported significant, symmetric, $\gamma$-ray emission with an extension
of $(0.60\pm 0.06)^{\circ}$ and a power-law spectral index of $2.14\pm 0.04$.
This study reanalyses the region using an increased exposure of 12 years.

In Fig. 3, a significance map of the emission in the region around 4FGL
J1813$-$1737e is shown. After the verification of the data export from fermipy
to gammapy (Appendix D), the morphological and spectral properties of the
emission are estimated. The emission in the ROI is best described by an
elongated Gaussian model centred at $\text{R.A.}=(273.33\pm 0.05)\,^{\circ}$
and $\text{Dec.}=(-17.57\pm 0.05)\,^{\circ}$, with $\sigma=(0.56\pm
0.07)\,^{\circ}$. This position and size are similar to the source position of
HESS J1813$-$178B observed with H.E.S.S. (see Appendix, Fig. 18), indicating
that the emission from 4FGL J1813$-$1737e and HESS J1813$-$178B could be
connected. The best-fit parameters are shown in Table 2. The significance of
the fitted model is $35\,\sigma$. After accounting for the emission from this
component, residual emission spatially overlapping with the pulsar is
observed. Therefore a second component with a symmetric Gaussian model was
added to the data, to account for this residual emission. Because of the
spectral shape below $10\,$GeV, a simple power-law spectral model cannot
reflect the observed emission well. Therefore a power-law with exponential
cut-off was chosen as a spectral model. Minimisation yields a compact
component, positionally coincident with PSR J1813$-$1749\. The residual
significance map after the application of both models is shown on the right-
hand side of Fig. 3. Because the shape of the SED does not suggest a possible
connection to HESS J1813$-$178A, this compact component will be referred to as
component C. The best-fit parameters for 4FGL J1813$-$1737e and component C
are given in Table 2.

Table 2: The best-fit source parameters obtained for the _Fermi_ -LAT data for a model consisting of an elongated Gaussian model with a power-law and a symmetric Gaussian model with an exponential cut-off power-law as a spectral model. These components are described by the equations in section 2.1.2 | component C | 4FGL J1813$-$1737e
---|---|---
$\Gamma$ | $0.95\pm 0.22_{\text{stat}}$ | $2.17\pm 0.09_{\text{stat}}$
$\lambda$ [$\text{TeV}^{-1}$] | $551.5\pm 84.4_{\text{stat}}$ | -
$\text{N}_{0}\text{ at }2\,\text{GeV}$ $[10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}]$ | $8.4\pm 2.5_{\text{stat}}\pm 1.83_{\text{sys}}$ | $2.7\pm 0.6_{\text{stat}}\pm 0.40_{\text{sys}}$
R.A. $[^{\circ}]$ | $273.452\pm 0.004_{\text{stat}}$ | $273.33\pm 0.05_{\text{stat}}$
Dec. $[^{\circ}]$ | $-17.73\pm 0.03_{\text{stat}}$ | $-17.57\pm 0.05_{\text{stat}}$
$\sigma_{M}$ $[^{\circ}]$ | $0.21\pm 0.03_{\text{stat}}$ | $0.56\pm 0.07_{\text{stat}}$
$e$ | - | $0.78\pm 0.07_{\text{stat}}$
$\Delta\varphi$ $[^{\circ}]$ | - | $33\pm 8_{\text{stat}}$

The cut-off of this model was estimated to be $1.81\,$GeV. Component C
improved the likelihood of the model with a significance of $3.8\,\sigma$. To
detect this second component with certainty and probe the nature of this
emission, events with energies below $1\,$GeV would need to be included. The
SED are given in Fig. 4. Differences between the SED derived in this analysis
and the analysis performed in Araya (2018) can be attributed to the changes
from the 3FGL to the 4FGL catalogue, the usage of newly computed IRFs from
Pass 8 version 3, and four years of additional data used in this analysis.

In order to estimate the systematic uncertainties on the best-fit flux
normalisation factor, two separate factors are considered. In order to
estimate the error introduced by the instrument itself, the effective area has
been scaled up and down by 3%, and the analysis has been repeated. This
procedure is explained in detail in _Fermi_ LAT Collaboration (2019). The
errors estimated from this method are $0.36\cdot
10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}$ for 4FGL
J1813$-$1737e and $1.79\cdot
10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}$ for component C.

In order to estimate the error introduced by the background estimation, the
residual flux inside a region corresponding to the source region, at a empty
position in the ROI, has been calculated. The systematic uncertainty on the
number of measured counts can then be derived by dividing the total amount of
residual counts by the total amount of background in the shifted region and
then multiplying by the total amount of background counts in the original
source region. The number of counts per bin is then scaled up and down for the
whole ROI and the likelihood minimization is repeated. This process has been
repeated for ten different regions. This estimation yields an systematic
uncertainty of $0.18\cdot
10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}$ for 4FGL
J1813$-$1737e and $0.36\cdot
10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}$ for component C.
Both errors where then added in quadrature.

###  3.3 Energy-dependent morphology

The spatial association of the $\gamma$-ray emission with PSR J1813$-$1749,
and an X-ray PWN detected by the INTEGRAL satellite, XMM-Newton and Chandra
(Ubertini et al., 2005; Funk et al., 2007; Helfand et al., 2007) (Fig. 19),
suggest that a leptonic origin of the emission is plausible. Previous analyses
of evolved PWNe suggest an energy-dependent morphology caused by electron
diffusion and cooling (H.E.S.S. Collaboration, 2019; MAGIC Collaboration,
2020; Principe et al., 2020). To test for energy dependence of the extended
emission, the data observed with H.E.S.S. was divided into three energy ranges
(H1 - H3, specified in table 3.3) and the source models for HESS J1813$-$178A
and HESS J1813$-$178B were fitted in each range. The _Fermi_ -LAT data was
divided into six energy ranges (F1 - F6, also specified in table 3.3) and the
source model for 4FGL J1813$-$1737e was refitted in each range. The spacing of
these energy ranges was chosen to account for the small amount of statistics
in the H.E.S.S. data and the high-energy range in the _Fermi_ -LAT data. While
F1 - F6 span 3 energy bins each, F6 spans 11 energy bins. The H.E.S.S. data
was divided such that H1 and H2 contain five energy bins of the dataset, while
H3 spans 10 energy bins.

Table 3.3 shows the extension along the semi-major axis, as well as the
eccentricity of the ellipse describing the emission in each energy bin and the
distance of the centre of the spatial model to the pulsar. In Fig. 5, the
dependence of the $1\,\sigma$ containment area of the ellipse and the offset
to the centre of the fitted model from the pulsar position as a function of
the energy is depicted. The area of the ellipse is defined as
$A=\pi\sigma_{M}^{2}\sqrt{(1-e^{2})}$. The binning was chosen based on the
available statistics for each dataset.

The enclosed area is compatible within errors in the overlapping energy ranges
of the _Fermi_ -LAT and H.E.S.S. data. There is no significant indication for
energy-dependence of the best-fit containment area of HESS J1813$-$178A and
HESS J1813$-$178B. This study does however reveal a dependence of the distance
between the pulsar and the centre of the emission, which increases with
increasing energy. As the morphology of HESS J1813$-$178A remains fixed
throughout all energy bands, the increased offset of the best-fit position
towards higher energies may indicate that the particle transport occurs
preferentially towards a single direction before spreading out more
isotropically as the particles lose energy and cool. Alternatively, this could
indicate that a second faint source is present in the region.

Table 3: The best-fit parameters for the morphology of HESS J1813$-$178B in
different energy bands, for both _Fermi_ -LAT (F1 - F6) and H.E.S.S. datasets
(H1 large - H3 large) An elongated Gaussian model is assumed in all cases and
the $1\,\sigma$ statistical uncertainties are given. Additionally, the best-
fit values for the symmetrical Gaussian used to account for the emission from
HESS J1813$-$178A.

| Energy [GeV] | RA $[^{\circ}]$ | Dec $[^{\circ}]$ |  $\sigma_{M}$ [∘] | $e$
---|---|---|---|---|---
F1 | $1.0\,-\,2.0$ | $273.46\pm 0.02$ | $-17.67\pm 0.02$ | $0.39\pm 0.04$ | $0.81\pm 0.05$
F2 | $2.0\,-\,4.0$ | $273.48\pm 0.03$ | $-17.69\pm 0.03$ | $0.42\pm 0.04$ | $0.85\pm 0.04$
F3 | $4.0\,-\,7.5$ | $273.38\pm 0.04$ | $-17.66\pm 0.06$ | $0.39\pm 0.08$ | $0.87\pm 0.07$
F4 | $7.5\,-\,18$ | $273.26\pm 0.09$ | $-17.52\pm 0.12$ | $0.53\pm 0.11$ | $0.75\pm 0.19$
F5 | $18\,-\,58$ | $273.17\pm 0.10$ | $-17.77\pm 0.08$ | $0.57\pm 0.16$ | $0.77\pm 0.21$
F6 | $58\,-\,1.0\times 10^{3}$ | $273.22\pm 0.20$ | $-17.75\pm 0.13$ | $0.71\pm 0.19$ | $0.92\pm 0.08$
1-6 H1 small | $(0.4\,-\,1.3)\times 10^{3}$ | $273.393\pm 0.005$ | $-17.832\pm 0.005$ | $0.054\pm 0.004$ | $--$
H2 small | $(1.3\,-\,5.7)\times 10^{3}$ | $273.397\pm 0.006$ | $-17.834\pm 0.007$ | $0.064\pm 0.005$ | $--$
H3 small | $(5.7\,-\,100)\times 10^{3}$ | $273.408\pm 0.009$ | $-17.817\pm 0.009$ | $0.035\pm 0.006$ | $--$
1-6 H1 large | $(0.4\,-\,1.3)\times 10^{3}$ | $273.61\pm 0.08$ | $-17.48\pm 0.09$ | $0.87\pm 0.12$ | $0.88\pm 0.04$
H2 large | $(1.3\,-\,5.7)\times 10^{3}$ | $273.41\pm 0.09$ | $-17.42\pm 0.11$ | $0.48\pm 0.09$ | $0.48\pm 0.38$
H3 large | $(5.7\,-\,100)\times 10^{3}$ | $273.65\pm 0.11$ | $-17.18\pm 0.10$ | $0.41\pm 0.09$ | $0.00\pm 0.02$

Figure 5: The best-fit angular offset and area of the ellipse of HESS
J1813$-$178A and HESS J1813$-$178B with $1\,\sigma$ uncertainties, as well as
4FGL J1813$-$1737e data in independent energy bins (see Table 3.3) H1 - H3 and
F1 - F6.

###  3.4 Joint Model Fit

A consistent description of the ROI through the GeV-TeV range can be reached
by fitting the _Fermi_ -LAT and H.E.S.S. data jointly. Following the results
derived in the analysis of the respective datasets, three source models were
used to describe the data across five decades of energy. First a symmetric
Gaussian model, as well as an elongated Gaussian model was added to both
datasets. These models will be referred to as component A and B respectively.
Additionally, a symmetric Gaussian model with an exponential cut-off power-law
spectral model was added only to the _Fermi_ -LAT data. This model component,
referred to as component C in the analysis of the _Fermi_ -LAT data. The
likelihood minimisation was then performed on both datasets at the same time.
The best-fit parameters are shown in Table 3.4.

Table 4: The best-fit parameters derived in the joint analysis of the H.E.S.S.
and _Fermi_ -LAT data.

| comp. A | comp. B | comp. C
---|---|---|---
$\Gamma$ | $2.05\pm 0.03$ | $2.17\pm 0.03$ | $-0.12\pm 0.02$
$\beta$ | $0.0620\pm 0.003$ | $0.0437\pm 0.008$ | -
$\alpha$ | - | - | $0.66\pm 0.01$
$\lambda$ [$10^{3}\cdot\text{TeV}^{-1}$] | - | - | $3.93\pm 0.20$
$\text{N}_{0}\text{ at }1\,\text{TeV}$ $[10^{-12}\,\text{cm}^{-2}\,\text{s}^{-1}\,\text{TeV}^{-1}]$ | $3.16\pm 0.14$ | $6.47\pm 0.43$ | $9.89\pm 1.64$
1-4 RA $[^{\circ}]$ | $273.400\pm 0.003$ | $273.39\pm 0.03$ | $273.48\pm 0.02$
Dec $[^{\circ}]$ | $-17.832\pm 0.003$ | $-17.50\pm 0.04$ | $-17.67\pm 0.02$
$\sigma_{M}$ $[^{\circ}]$ | $0.056\pm 0.003$ | $0.54\pm 0.03$ | $0.29\pm 0.02$
$e$ | - | $0.73\pm 0.04$ | -
$\Delta\varphi$ $[^{\circ}]$ | - | $33\pm 7$ | -

Figure 6 depicts the spectra and SED of the best-fit models, together with the
sensitivity of the LAT for 12 years of exposure in blue. The curve shows the
broadband sensitivity for sources located in the Galactic plane (Ajello et
al., 2021). While the best-fit parameters of the models where estimated using
the data from both datasets at the same time, the flux points were computed in
the respective datasets. This results in a energy range where both the
H.E.S.S. and _Fermi_ -LAT data show significant flux or upper limits.

Figure 6: SED from a joint-analysis of the combined H.E.S.S. and _Fermi_ -LAT
data. The 12 year sensitivity of the LAT is indicated by the blue line.

If the spectrum of component A does not change drastically at the lower
energies, measuring it in the LAT data would not be possible as components A
and C are positionally coincident and the detector sensitivity is
insufficient. Together these three different source models describe the
emission of the ROI well. The advantage of this joint model becomes evident in
the GeV energy regime. The spatial separation between 4FGL J1813$-$1737e and
the compact emission component detected in the _Fermi_ -LAT data is
complicated, but using the assumption that 4FGL J1813$-$1737e and HESS
J1813$-$178B have the same origin, the influence of the second component on
the model parameters can be reduced. This becomes evident when comparing the
flux around $1\,$GeV, which has been reduced by a factor two in the joint
model.

##  4 Spectral Modeling using GAMERA

Two scenarios were investigated for the origin of the extended $\gamma$-ray
emission in the region of PSR J1813$-$1749\. In the first scenario, a
magnetised wind of charged particles, primarily electrons and positrons,
originating from PSR J1813$-$1749, forms a PWN. This leptonic emission
scenario has been favoured in previous analyses of the X-ray and TeV emission
(Ubertini et al., 2005; Funk et al., 2007). In systems older than $10\,$kyr,
the electrons can escape the confines of the PWNe and diffuse through the ISM,
although the age at which this occurs may vary for individual systems. The
diffuse $\gamma$-ray emission produced by these electrons is typically
observed around middle-aged pulsars and one can distinguish between a majority
of the particles still confined in the PWN and one where most particles have
escaped into the ISM (Giacinti et al., 2020). This evolutionary stage of a
leptonic system could potentially correspond to the extended emission observed
as HESS J1813$-$178B.

Another possible origin of the extended emission are cosmic-ray nuclei,
accelerated at shock fronts and which have since escaped from their
accelerator. A possible candidate for such an acceleration site is the SNR
$\text{G}12.82-0.02$, which is positionally coincident with the pulsar PSR
J1813$-$1749 and believed to be the pulsars host SNR (see Fig. 19). After
acceleration and propagation, the nuclei may interact within dense molecular
clouds in the region, producing high-energy $\gamma$-rays.

This emission scenario has been favoured in an analysis of nine years of
_Fermi_ -LAT data, performed by Araya (2018). He suggested the stellar cluster
$\text{Cl}\,\text{J}1813$-$178$ as a possible origin, but also states that the
extension of the $\gamma$-ray emission exceeds the extension of the star-
forming region, and therefore an unknown component of star formation would be
necessary.

###  4.1 Leptonic scenario

To describe the $\gamma$-ray emission in the region using a time-dependent
model of electrons originating from PSR J1813$-$1749, the GAMERA package
(Hahn, 2015) was used.

Table 5: The assumed properties of PSR J1813$-$1749 following newest estimates from Camilo et al. (2021). For the braking index and break energy canonical values are assumed. Parameter | Assumed Value
---|---
Distance, d |  $6.2\,$kpc
spin-down power, $\dot{E}$ |  $5.6\times 10^{37}\,$erg/s
spin period, $P$ |  $44.7\cdot 10^{-3}\,$s
change in spin period, $\dot{P}$ |  $1.27\times 10^{-13}\,$s/s
characteristic age $\tau_{c}$ |  $5.585\,$kyr
Braking index, $n$ | $3.0\,$
Break energy, $E_{\text{b}}$ |  $100\,$GeV

Additionally to the SED derived in the joint analysis, measurements of the
region in the $20-100\,$keV band, showing an unresolved hard X-ray source
observed by the INTEGRAL satellite (Ubertini et al., 2005), XMM-Newton (Funk
et al., 2007) (with an extraction region of $75\arcsec$), and Chandra (Helfand
et al., 2007, with an elliptical extraction region of $6\arcsec\times
8\arcsec$) were used, as well as observation data from the Very Large Array in
the $20\,$cm and $90\,$cm band, revealing a shell-like non-thermal radio
source identified as SNR G12.82–0.02 (Brogan et al., 2005b). The radio data is
only shown for comparison and was not included in the modeling.

The SED used for this model were not derived using the same spatial extent.
While one possible solution for this discrepancy would be to scale the
observed flux for the different observation regions, this would require the
assumption that a linear scaling can be applied. Additionally, X-ray emission
generally traces higher energy electrons, and hence younger electrons, than
the TeV emission. To account for these differences, three electron
‘generations’ were defined, following the procedure in H.E.S.S. Collaboration
(2023). The first electron generation, the relic electrons, were injected
since the birth of the pulsar and are now detected as extended high-energy
$\gamma$-ray emission. The second electron generation, the middle-aged
electrons, were injected since $t_{e}=t_{\text{true}}\cdot t_{\text{PWN}}$,
with $t_{\text{true}}$ the age of the system, and are now detected as PWN
around PSR J1813$-$1749\. The third electron generation, the young electrons
injected since $t_{e}=t_{\text{true}}\cdot t_{\text{X-ray}}$ are responsible
for the X-ray synchrotron emission.

Figure 7: SED derived in this analysis, as well as X-ray SED by XMM-Newton
(Funk et al., 2007) Chandra (Helfand et al., 2007) and INTEGRAL (Ubertini et
al., 2005) and SED derived in the analysis of VLA data (Brogan et al., 2005b),
compared to the SED curves expected from the leptonic model obtained with
GAMERA. Left: Full energy range. Right: Comparison between the $\gamma$-ray
flux estimated from the leptonic model from $0-1.6\,$kyrs and the last
$2.5\,$kyrs and the emission observed from HESS J1813$-$178B and HESS
J1813$-$178A respectively. The shaded grey error bands indicate the possible
parameter space, given in Table 6.

For this model, an electron injection spectrum following a power-law with a
spectral index of $\alpha$, a break energy of $E_{b}$ and a cutoff $E_{\rm
cut}$:

$N(E_{\rm
e})=\left(1+\frac{E_{e}}{E_{b}}\right)^{\alpha}\cdot\exp\left(\frac{-E_{\rm
e}}{E_{\rm cut}}\right)\,,$ (6)

where $E_{e}$ the electron energy, was used.

The distance to the pulsar, as well as pulsar-specific parameters, such as
spin-down period P, change in spin period $\dot{\text{P}}$, and spin-down
power $\dot{\text{E}}$ were taken from Camilo et al. (2021). All assumed
properties of the pulsar used for this model are given in Table 5.

The injection index $\alpha$, the birth period $\text{P}_{0}$, and the
conversion fraction of the spin-down luminosity to electrons $\vartheta$, as
well as the magnetic field present at the time of the observation of the
$\gamma$-ray emission $\text{B}_{\text{now}}$, and the age of the electron
populations were free parameters of the model. The spin-down power of the
pulsar was assumed to evolve in time with:

$\dot{\text{E}}=\dot{\text{E}}_{0}\left(1+\frac{t}{\tau_{0}}\right)^{-2}\,,$
(7)

with $\tau_{0}=\text{P}_{0}/(2\,\dot{\text{P}_{0}})$, the spin-down time at
the birth of the pulsar and $\dot{\text{E}}_{0}$ the initial spin-down energy
loss rate at birth of the pulsar. Similarly the pulsar period was assumed to
evolve as $\text{P(t)}=\text{P}_{0}\left(1+\frac{t}{\tau_{0}}\right)^{0.5}$,
with $\text{P}_{0}$ the birth period of the pulsar and the magnetic field as
$\text{B(t)}=\text{B}_{0}\left(1+\left(\frac{t}{\tau_{0}}\right)^{0.5}\right)^{-1}$
(Gaensler & Slane, 2006; Venter & de Jager, 2007) with $\text{B}_{0}$ the
magnetic field at birth of the pulsar. The spin down luminosity is defined as:

$\text{L}=\text{L}_{0}\cdot\vartheta\cdot\left(1+\frac{t}{t_{0}}\right)^{-2}$
(8)

with the inital spin down luminosity
$L_{0}=\dot{\text{E}}\cdot(1+(t_{\text{true}}/t_{0}))^{2}$ and
$t_{0}=\frac{P_{0}^{2}}{2P\dot{P}}$.

Since the time at which the escape of the particles into the ISM first occurs
is unknown, this modeling approach assumes that the particles have been able
to escape instantly and therefore the relic electrons have been injected since
the birth of the pulsar. An additional caveat of this model is, that while
this model is time-dependent and cooling losses of electrons were taken into
account, no spatial dependence or spatial evolution was added. The fit of the
different electron generations was performed only on the SED.

The free parameters of the model were fitted to the observation data from the
X-ray satellites, as well as the SEDs derived in the joint-analysis from
components A and B. For optimisation, the package _EMCEE_ (Foreman-Mackey et
al., 2013), which applies a Markov chain Monte Carlo (MCMC) method, was used.

The optimised model is shown in Fig. 7, while the parameter space that yields
the highest numerical probability ($16-84$% range of the probability
distribution) for the MCMC method is listed in Table 6. This morphology
independent model can account well for the observed emission.

The observed X-ray data in the vicinity of PSR J1813$-$1749 can be well
explained by young electrons that were produced only in the last $0.4\,$kyr,
the electrons of the third generation. The electrons produced in the last
$2.7\,$kyr, the second generation, were observed by H.E.S.S. as compact
emission around the pulsar.

Table 6: Validity range of the parameters used in the evolution of the leptonic model. The parameter combination presented here should be interpreted as a range of possible combinations, not best-fit values.  Parameter | Validity range
---|---
$B_{\text{now}}$ | [$11.36$ $-$ $13.18$]$\,\mu$G
$P_{0}$ | [$20.19$ $-$ $22.97$ ] ms
$\vartheta$ | [$0.15$ $-$ $0.17$]
$\alpha$ | [$2.35$ $-$ $2.40$]
$\Delta t_{\text{X-ray}}$ | [$0.88$ $-$ $0.91$]
$\Delta t_{\text{PWN}}$ | [$0.35$ $-$ $0.39$]

Taking into account the low statistics at high energies, the population of
relic electrons from the first generation, released from the birth of the
pulsar up to an age of $1.6\,$kyrs, can describe the extended emission from
HESS J1813$-$178B reasonably well but fails to describe the emission from
component C. To describe this emission in a leptonic scenario, a second
electron population and an unreasonably high particle density, only
experienced by the second electron generation, would need to be introduced.

Using the parameters of the model, the true age of the system was estimated,
following Gaensler & Slane (2006):

$t_{\text{true}}=\frac{\text{P}}{(n-1)\dot{\text{P}}}\left(1-\left(\frac{\text{P}_{0}}{\text{P}}\right)^{n-1}\right)\,\,.$
(9)

with $n$ the braking index of the pulsar. For the validity range of parameters
in this analysis, the true age of the system was estimated to be $\sim
4.7\,$kyrs.

Figure 8: The measured extension of HESS J1813$-$178B in continuous energy
bands, specified in table 3.3, is shown in red. The figure also shows the
expected $1\,\sigma$ containment radius for different diffusion coefficients.

With this information, together with the measurement of the extension of 4FGL
J1813$-$1737e and HESS J1813$-$178B in the energy bands specified in table
3.3, an estimation of the diffusion coefficient and diffusion index can be
made by comparing the observed angular size to that expected for the relic
electron population at different $\gamma$-ray energies. In order to estimate a
diffusion coefficient radial symmetric diffusion was assumed. To get a
estimation of the radial symmetric extend of the the emission from HESS
J1813$-$178B, a symmetric Gaussian model was fitted to the emission in the
energy bands defined in Section 3.3. This derived extension, as well as the
age of the system, derived using equation 9, were then used to estimate the
distance which the relic electrons have diffused since they were injected,
with the expected angular size calculated as
$r_{\text{diff}}=\sqrt{2t_{\text{age}}\cdot D}$, with $D$ the diffusion
coefficient. The diffusion coefficient was derived using the electron energy
$\text{E}_{e}$, the diffusion index $\delta$ and the diffusion coefficient
$\text{D}_{0}$ at the reference energy of $1\,$TeV:

$\text{D}=\text{D}_{0}\left(\frac{\text{E}_{e}}{1\,\text{GeV}}\right)^{\delta}\,\,.$
(10)

The diffusion coefficient is estimated to $\text{D}_{0}=(6.98\pm 0.69)\times
10^{28}\,\text{cm}^{2}/\text{s}$ with a diffusion index $\delta=(0.30\pm
0.06)$. The estimated radius as a function of $\gamma$-ray energy, as well as
the measurement, can be seen in Fig. 8. The estimated diffusion index lies in
the range between Kraichnan turbulence ($\delta=0.5$, (Kraichnan, 1965)) and
Kolmogorov turbulence ($\delta=0.33$, (Kolmogorov, 1991)), which is the
canonical diffusion index typically assumed for PWNe. The best-fit diffusion
coefficient is comparable with the diffusion coefficient estimated for the ISM
(Strong & Moskalenko, 1998).

To compare the results to the population of known pulsars, the energy density
of both HESS J1813$-$178A and HESS J1813$-$178B in the TeV energy range was
estimated, following the scheme in Giacinti et al. (2020). The energy density
of the electrons was estimated using
$\epsilon_{e}=\frac{\text{E}_{\text{inj}}}{\text{V}}$, or using the properties
of the pulsar

$\displaystyle\epsilon_{e}$ $\displaystyle=$
$\displaystyle\frac{\dot{\text{E}}\tau_{c}}{4\pi(\text{R}_{1}^{2}\cdot\text{R}_{2})/3}\,\,,$
(11)

with $\dot{E}$ the present-day spin-down power, $\tau_{c}$ the present-day
characteristic age, $\text{R}_{1}$ the extension of the semi-major axis of the
ellipse and $\text{R}_{2}$ the size the semi-minor axis. The energy density
using the total TeV $\gamma$-ray luminosity was estimated by integrating over
the electron population inferred by our best-fit model. This study finds
$E_{\text{inj}}=$3.62$\cdot 10^{48}\,$erg. The derived electron densities are
given in Table 7. The energy density calculated from the $\gamma$-ray
luminosity is lower than that estimated from the properties of the pulsar.
This effect was already observed by Giacinti et al. (2020), a possible reason
could be that only the estimation using the $\gamma$-ray luminosity takes the
evolution into account, while the estimation using the current pulsar
properties cannot sufficiently describe this evolution. The energy density
calculated for HESS J1813$-$178A is compatible with the energy densities
estimated for other PWNe, while the energy density of HESS J1813$-$178B is
close to $0.1\,\text{eV}/\text{cm}^{3}$ and therefore comparable to the values
estimated for pulsar halos (Giacinti et al., 2020).

Table 7: Estimated electron density following equation (11). $\epsilon_{e}\,\,[\text{eV}/\text{cm}^{3}]$ | HESS J1813$-$178A | HESS J1813$-$178B
---|---|---
estimated from $\dot{\text{E}}$ |  $65.29$ $\pm$ $4.49$ |  $0.11$ $\pm$ $0.02$
estimated from $\text{L}_{\gamma}$ |  $23.95$ $\pm$ $1.64$ |  $0.04$ $\pm$ $0.01$

###  4.2 Hadronic origin

Due to the positional coincidence of the emission and the SNRs G012.8–00.0 and
G012.7–00.0 or the star-forming region W33, there is also the possibility that
the observed emission is a superposition of $\gamma$-ray emission produced by
different sources that overlap along the line of sight. While there is no
information available for SNR G012.7-00.0, the distance to PSR J1813$-$1749
and the SNR G012.8–00.0 is estimated to be $6.2-12\,$kpc (Camilo et al.,
2021), while the stellar cluster is expected to be located at a much smaller
distance of $4.8\,$kpc (Messineo et al., 2011). It is therefore possible that
the emission observed as HESS J1813$-$178A is a pulsar wind nebula powered by
PSR J1813$-$1749, while the extended emission observed in the _Fermi_ -LAT and
H.E.S.S. data is caused by protons accelerated at the SNR shock front or the
stellar cluster.

In order to produce high energy $\gamma$-rays via hadronic interactions,
target material is necessary. Using the molecular cloud catalogues provided in
Rice et al. (2016) and Miville-Deschênes et al. (2017), three molecular
clouds, positionally coincident with the best-fit position of the emission
from HESS J1813$-$178B were identified. Their location compared to the
emission observed in the analysis of the _Fermi_ -LAT data can be seen in Fig.
9.

Figure 9: Significance map computed from the H.E.S.S data with an correlation
radius of $0.06^{\circ}$. The estimated position and density of molecular
clouds in the region are indicated by the dashed lines. Additionally, the
morphology of the best-fit model derived in the analysis of the _Fermi_ -LAT
and H.E.S.S. data is indicated. Only clouds with a distance between $4\,$kpc
and $12\,$kpc and a large positional overlap with the extended emission
observed in _Fermi_ -LAT and H.E.S.S. are depicted in the counts map.

In order to investigate the feasibility of this scenario as the origin of the
emission observed from 4FGL J1813$-$1737e and HESS J1813$-$178, a proton and
electron population, accelerated at the shock front of the SNR were evolved
over time. Following Diesing & Caprioli (2019), the protons were injected
with:

$\displaystyle f(p)$ $\displaystyle=$ $\displaystyle N_{p}\cdot
E^{-\alpha_{p}}\cdot\exp{\left(\frac{-E}{E_{\text{max}}}\right)}\cdot\exp{\left(-\frac{E_{\text{min}}}{E}\right)}$
(12)

where $N_{p}$ is the normalisation factor, $E$ is the energy of the injected
particles, $E_{\text{min}}=m_{p}$, the rest mass of the proton,
$E_{\text{max}}$ is assumed to be $1\,$PeV, and $\alpha_{p}$ is the spectral
index of the injected protons. The injection spectrum of the electrons was
defined as:

$\displaystyle f_{e}(p)$ $\displaystyle=$ $\displaystyle N_{p}\cdot
k_{ep}\cdot
E^{-(\alpha_{p}+\Delta\alpha)}\cdot\exp{\left(\frac{E}{E_{\text{max}}}\right)}\cdot\exp{\left(-\frac{E_{\text{min}}}{E}\right)}$
(13)

with $\Delta\alpha$ the difference between the injection index of the
electrons and protons, $k_{ep}$ the electron-to-proton ratio, and
$E_{\text{min}}=100m_{e}$, with the electron rest mass, as well as
$E_{\text{max}}=1\,$TeV. This particle population is evolved in an environment
with the ambient magnetic field $B_{\text{now}}$ and the particle density $d$.
We assume a particle density of $d=60\,\text{cm}^{-3}$, which corresponds to
the density of one of the molecular clouds in the region (see figure 9).

We evolve this particle population with time following the approach in Section
4.1, using a MCMC-Chain. The fit parameters of the model, as well as the
adjusted parameter range can be seen in table 8. A comparison of the leptonic
model derived in Section 4.1 and the hadronic model can be seen in Figure 10,
while Figure 21 shows the comparison of both models with the SED derived in
this analysis, as well as the spectra derived from the emission observed in
HAWC (Albert et al., 2020) and LHAASO (Cao et al., 2023).

Both models exhibit good agreement with the SED from component B as derived in
section 3.4, while only the leptonic model shows good agreement with the
spectrum of 1LHAASO J1814$-$1719u* measured by KM2A. The spectrum of 3HWC
J1813$-$174 does not show good agreement with either model.

Additionally to the discrepancy with the spectra derived by HAWC and LHAASO,
the hadronic model has further caveats. The estimated distance between the
molecular cloud at $4.6\,$kpc and the SNR at $6.2-12\,$kpc are not compatible,
and the location of the molecular cloud can account for the emission observed
in the GeV energy range, but not the extension of the TeV emssion. Assuming a
particle density of $d=1\,\text{cm}^{-3}$, corresponding to ISM level, however
results in the need for a very powerful SNR with the energy of the protons
required to be $\log_{10}(E_{p}/\text{erg})=[51.2-51.7]\,$, to describe the
emission well. Since there is no evidence supporting this scenario, a origin
of the observed emission only from acceleration of protons on the SNR seems
unlikely.

While such a high energy output seems unlikely in the case of only one object,
collective effects of a population of young stars in the stellar cluster CL
J1813-178 (located at a distance of $4.8\,$kpc Messineo et al. (2011)) could
account for the required energy. For example, for a kinetic luminosity of
$3\times 10^{38}$ erg/s and an age of 3-10 Myr, as may be typical for a young,
massive stellar cluster, the available total energy budget is
$\log_{10}(E_{p}/\text{erg})=[52.5-53]\,$ (Morlino et al., 2021).

Acceleration of protons in the stellar cluster remains therefore a valid
possible origin for the observed extended $\gamma$-ray emission, a detailed
examination is, however, beyond the scope of this paper.

Figure 10: The estimated $\gamma$-ray flux for the hadronic model compared to the $\gamma$-ray flux expected for the leptonic model computed in Section 4.1. The deviation of the SED to the respective model curves are shown in the bottom panel.  Table 8: The validity range of the free parameters of the hadronic model. $\alpha_{\text{p}}$ | $[2.01-2.08]$
---|---
$\log_{10}(E_{p})$ | $[48.49-49.65]\,\log{(\text{erg})}$
$\Delta\alpha$ | $-[0.15-0.27]\,$
$k_{ep}$ | $-[1.72-6.05]\,$
$B_{\text{now}}$ | $[73-271]\,\mu G$

##  5 Discussion

In previous analyses of the region around PSR J1813$-$1749 the analysis of
H.E.S.S. data revealed compact emission with an extension of $0.06^{\circ}$
around the pulsar (Aharonian et al., 2006b), while the analysis of _Fermi_
-LAT data, as well as data aquired by HAWC and LHAASO showed largely extended
emission. With these results, no connection between the _Fermi_ -LAT source
4FGL J1813$-$1737e and the H.E.S.S. source HESS J1813$-$178 could be
established. We reanalysed the region using an improved reconstruction for the
TeV data and increased exposure in the GeV energy range.

In the TeV energy range, we confirm the detection of HESS J1813$-$178, a
bright, TeV $\gamma$-ray source, centred at the position of the PSR
J1813$-$1749, with an extension of $0.06^{\circ}$, observed as HESS
J1813$-$178A in this analysis. The results derived for this emission component
are consistent with the results derived in H.E.S.S. Collaboration (2018). We
also detect a fainter $\gamma$-ray structure, with an extension of
$0.7^{\circ}$ enclosing the pulsar and HESS J1813$-$178A, which we refer to as
HESS J1813$-$178B.

In the GeV energy range observed with _Fermi_ -LAT, we find $\gamma$-ray
emission with an extension of $0.4^{\circ}$, positionally coincident with the
extended emission observed in the H.E.S.S. dataset. Additionally, we observe
compact emission positionally coincident with the pulsar. This emission has
already been reported by Araya (2018), but was not significant. While we also
cannot claim a significant detection, adding component C improves the region’s
description.

By combining the datasets in a joint analysis we find that the extended
emission detected in the H.E.S.S. and _Fermi_ -LAT data can be connected and
described by a single source model, while the emission from HESS J1813$-$178A
can only be observed in the H.E.S.S. data, since the emission drops below the
sensitivity of the detector in the _Fermi_ -LAT energy range. We can therefore
establish a consistent description of the region over five decades of energy
and conclude that the emission observed by _Fermi_ -LAT and H.E.S.S. have the
same origin.

Araya (2018) concluded that the emission was most likely of hadronic origin
due to the spectral shape. While Araya (2018) only took $\gamma$-rays in the
GeV energy range into account, in this work, a combined model of GeV and TeV
photons was used, as well as X-ray data included. We computed a physical model
that can describe the observed $\gamma$-ray emission by evolving an electron
population, or alternatively an proton population, over time. We find that the
leptonic emission scenario describes the combined data well, while a
acceleration at the SNR shock front seems less justified since the present
target material cannot explain the observed extension of the TeV emission. The
energetics necessary to produce the observed $\gamma$-ray emission could also
be explained by acceleration of protons inside the stellar cluster, but has
not been further investigated in this study.

We find, that the data from HESS J1813$-$178A, as well as HESS J1813$-$178B
can be described well by $\gamma$-ray emission from synchrotron and IC
emission of electrons originating from the pulsar. This indicates that HESS
J1813$-$178A, is likely a PWN, while the extended emission is possibly caused
by electrons and positrons escaping the confines of the PWN and diffusing into
the ISM. The effect of constructing a model that considers only time
dependence, but not spatial dependence, leads to an overprediction in the keV
energy range. Since the measurement of the flux observed by INTEGRAL and XMM-
Newton only includes a small area (with an extension of less than $80"$),
while the measurement of the flux from HESS J1813$-$178B was conducted in an
area of $\sim 0.5\degr$, we can assume that a low surface brightness, as well
as the limitations of the detectors cause the difference between predicted
flux and measured flux in the X-ray energy range.

Diffuse leptonic emission around a pulsar is usually only observed in systems
older than $\sim 10\,$kyr (Giacinti et al., 2020). The true age estimated in
this study, as well as previous observations of PSR J1813$-$1749 (Dzib &
Rodríguez, 2021), indicate that the system is younger than $5\,$kyrs, but it
is not implausible that environmental factors, such as the local ISM density
distribution or the pulsar proper motion, might lead to particles diffusing
outwards faster than in previously observed systems.

The estimated diffusion coefficient for HESS J1813$-$178B is within the
expected range of diffusion in the ISM (Strong & Moskalenko, 1998) and
comparable to the diffusion coefficient estimated for the $\gamma$-ray
emission observed around PSR B1823$-$13, the pulsar powering the highly
extended PWN HESS J1825$-$137 (H.E.S.S. Collaboration, 2019). Assuming the
same diffusion coefficient for HESS J1813$-$178A, would lead to a extension
far bigger than the observed emission, implying that the diffusion coefficient
is non uniform, which is expected for a pulsar environment. Additionally, we
find that the energy density estimated for the extended emission is comparable
to the densities estimated for the halos observed around the evolved systems
around PSR J0633$+$1746 and PSR B0656$+$14 (Giacinti et al., 2020). While we
would expect the diffusion coefficient in a TeV halo to be below the diffusion
observed in the ISM, the low energy density and lack of other accelerators in
the area suggest that the system around PSR J1813$-$1749 shows characteristics
of an older, evolved system despite its young age. Although it would be
unusual to note electron escape from young PWNe, this may occur if the system
becomes disrupted at an early stage, such as due to an early return of the
supernova reverse shock preferentially from one direction.

This study also investigates the possibility of a hadronic origin of the
emission, by evolving a proton population originating from SNR G012.8–00.0.

In order to estimate the statistical description of both models, the absolute
chi-squared ($\chi^{2}$) goodness-of-fit was estimated using the SED of
component B derived in the joint-fit. This study finds
$\chi^{2}_{\text{had}}=18.56$ for the hadronic model and
$\chi^{2}_{\text{lep}}=30.62$ for the leptonic model. The hadronic model is
therefore preferred at a $3.47\sigma$ level.

Whilst the hadronic model yields a marginally better statistical description
for the emission, the target material identified in the region is not
sufficient to account for the extent of the detected $\gamma$-ray emission and
target material with a density of the level of the ISM would require an
unreasonably high proton energy to explain the detected $\gamma$-ray flux.

For the data below $10\,$GeV, observed as component C, we cannot find evidence
that convincingly points towards either a leptonic or hadronic origin. A
hadronic scenario cannot be supported since no association to a nearby
interstellar cloud or target material can be made. A leptonic scenario would
imply the existence of a second electron population, or an unreasonably high
particle density, which is only experienced by this second electron
population. Another possible leptonic scenario might be a pulsar origin, which
may alternatively account for the emission component, but this study cannot
find convincing evidence for such an explanation. For a firm identification of
the soft $\gamma$-ray emission as originating from the pulsar, a dedicated
study of the emission at lower energies needs to be performed.

While we are not able to fully resolve the origin of the $\gamma$-ray emission
in the region around PSR J1813$-$1749, we present a detailed morphological and
spectral analysis of the region, as well as possible emission scenarios. To
further add to the understanding about this source, more observations at high-
energy $\gamma$-rays are necessary, especially the addition of further data
taken by the Water Cherenkov detector arrays HAWC or LHAASO into the joint-fit
and the addition of further data taken by _Fermi_ -LAT will be of great value
in constraining the possible origin of the different components.

###### Acknowledgements.

The support of the Namibian authorities and of the University of Namibia in
facilitating the construction and operation of H.E.S.S. is gratefully
acknowledged, as is the support by the German Ministry for Education and
Research (BMBF), the Max Planck Society, the German Research Foundation (DFG),
the Helmholtz Association, the Alexander von Humboldt Foundation, the French
Ministry of Higher Education, Research and Innovation, the Centre National de
la Recherche Scientifique (CNRS/IN2P3 and CNRS/INSU), the Commissariat à
l’Énergie atomique et aux Énergies alternatives (CEA), the U.K. Science and
Technology Facilities Council (STFC), the Irish Research Council (IRC) and the
Science Foundation Ireland (SFI), the Knut and Alice Wallenberg Foundation,
the Polish Ministry of Education and Science, agreement no. 2021/WK/06, the
South African Department of Science and Technology and National Research
Foundation, the University of Namibia, the National Commission on Research,
Science & Technology of Namibia (NCRST), the Austrian Federal Ministry of
Education, Science and Research and the Austrian Science Fund (FWF), the
Australian Research Council (ARC), the Japan Society for the Promotion of
Science, the University of Amsterdam and the Science Committee of Armenia
grant 21AG-1C085. We appreciate the excellent work of the technical support
staff in Berlin, Zeuthen, Heidelberg, Palaiseau, Paris, Saclay, Tübingen and
in Namibia in the construction and operation of the equipment. This work
benefited from services provided by the H.E.S.S. Virtual Organisation,
supported by the national resource providers of the EGI Federation.

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##  Appendix A Estimation of the hadronic background

The hadronic background was estimated using a template model constructed from
archival H.E.S.S. data (see Mohrmann et al. (2019)). To account for the
variation in cosmic-ray flux for the respective observation conditions, a 3D
likelihood fit of this template background model for every observation was
performed, using the background amplitude $\Phi$ and spectral index $\delta$
as fit parameters. Using the spectral index small inacurracies in the spectral
shape of the background model can be corrected by modifying the predicted
background rate
$R^{*}_{\text{BG}}=R_{\text{BG}}\cdot(E/E_{0})^{-\delta_{\text{BG}}}$ at
Energy $E$, with a reference energy $E_{0}=1\,$TeV.

To get an accurate estimation of the background counts the regions in which
significant emission is detected needs to be excluded from the background fit.
These excluded regions are shown in Fig. 11.

Figure 11: Significance map of the region around HESS J1813$-$178, as seen
after the fit of the background model, the exclusion regions used for the
fitting are indicated by the dashed lines. A correlation radius of
$0.4^{\circ}$ is used for the computation of this map.

Figure 12 shows the distribution of the background amplitude and spectral
index, as well as a Gaussian fit indicated in red, while Fig. 13 shows the
significance distribution outside of the exclusion regions.

Figure 12: The distribution of the fit parameters of the template background
model and a Gaussian fit to the respective distribution. The mean and standard
deviation of the background spectral index $\delta$ and amplitude $\Phi$ are
indicated.

This distribution follows a Gaussian distribution with a mean close two zero
and a width that is close to one, indicating that only statistical
fluctuations are present outside of the exclusion regions.

Figure 13: Significance distribution of the data outside of the defined
exclusion regions. The orange curve shows the expected behaviour for a normal
distribution, indicating that only statistical fluctuations are present, while
the red curve shows a fit of a Gaussian distribution to the data.

##  Appendix B Calculation of systematic uncertainties

In order to derive the systematic uncertainties introduced by a mismodeling of
the energy axis of the IRFs, a randomly generated value is drawn from a
Gaussian distribution with a mean of 1 and a standard deviation of 10%. We
apply this factor $\varrho_{E}$ to the energy axes of the IRFs. To estimate
the uncertainties introduced through mis-modeling of the hadronic background,
a linear gradient with a direction angle $\alpha_{bkg}$ and a gradient
amplitude $\Phi_{bkg}$ is applied to the background model. In addition to the
gradient parameters, the amplitude $\Phi$ and index $\delta$ of the model is
varied by randomly drawing a value from Gaussian distributions. The mean and
deviation of these distributions are indicated in table 9.

Table 9: Parameter distribution used for the computation of the systematic errors. parameter | distribution | variation
---|---|---
$\varrho_{E}$ | Gaussian | $\mu=1,\sigma=0.1$
$\Phi$ | Gaussian | $\mu=1,\sigma=0.05$
$\delta$ | Gaussian | $\mu=0,\sigma=0.05$
$\alpha_{bkg}$ | uniform | $0^{\circ}-360^{\circ}$
$\Phi_{bkg}$ | Gaussian | $\mu=1,\sigma=0.01$

The standard deviation of these distributions was chosen such that they
represent the deviation between the mean value estimated in the pre-fit of the
background model (described in Appendix A) and the values estimated in the
likelihood minimisation on the whole dataset. Then, the shift, corresponding
to the randomly drawn factor, was applied to the IRFs of the dataset and the
background gradient introduced. The best-fit model, described in section 3.1,
was applied, and the likelihood fit executed. This process was repeated 500
times. An example of the resulting distribution of fit parameters can be seen
in Fig. 14, where the statistical error is indicated by the orange band and
the orange dashed line represents the best-fit value derived in the analysis
of the original dataset. The standard deviation of this Gaussian distribution
represents the systematic error derived by this method. The small systematic
uncertainties estimated for the spectral index and morphological parameters
indicate that this method does not take into account all possible sources of
systematic uncertainties. A more general estimation of uncertainties on the
spectral index can be found in Aharonian et al. (2006a).

Figure 14: Distribution of the best-fit values of the spectral index for HESS
J1813$-$178B. A Gaussian fit is performed on the data, which is indicated in
red. The orange dashed line corresponds to the fit value derived in the
analysis of the original dataset, the orange band indicates the statistical
error.

##  Appendix C Coverage of the region using H.E.S.S.

To visualize the coverage of the region using H.E.S.S., an exposure map
(figure 16)was computed. Additionally, a significance map computed with a
small correlation radius of $0.06^{\circ}$, which is comparable to the PSF of
the analysis, is depicted in figure 15

Figure 15: Signficiance map of the ROI, computed with a correlation radius of
$0.06^{\circ}$. Figure 16: Exposure map of the dataset used for the analysis
of the H.E.S.S. data. Most of the exposure comes from observations centred on
the neighbouring source $\text{HESS}\,\text{J}1809$-$193$.

##  Appendix D _Fermi_ -LAT data: Fermipy-Gammapy cross check

Figure 17:  Best-fit spectrum of a power-law model applied to the _Fermi_ -LAT
data in fermipy and gammapy.

Whilst gammapy cannot be used to directly analyse _Fermi_ -LAT data, the
fermipy analysis package is not able to perform a three-dimensional fit to the
data. To combine both methods, the count’s cube, the IRFs and the background
model cubes were computed using the fermipy package. Then, the cubes and
background source models were extracted and convert into a format that is
supported by gammapy. The robustness of exporting the data and models to
gammapy needs to be validated before the analysis results are used for further
investigation. For this purpose, a simple analysis of the source region in
fermipy and gammapy is carried out. The morphology of the source given in the
$4\text{FGL}$-catalog, a disc model with a source position of
$\text{R.A.}=273.405\degr$, $\text{Dec.}=-17.653\degr$ and an extension of
$0.6\degr$, was used for this validation. Then, the ROI was optimised with
fermipy by only taking into account sources with a test statistics (TS)
greater than four and predicted counts of more than 50. These cuts yielded a
total of 24 source models present in the analysis region. The spectral
parameters of these sources in a $5\degr$ radius around the catalogue position
of 4FGL J1813$-$1737e were refitted.

For the analysis in gammapy, the morphology of the source was fixed to the
position derived in fermipy and the best-fit spectral parameters were
evaluated. The spectral parameters and SED derived in gammapy and fermipy
agree within errors. In addition to the spectral fit parameters, a comparison
of the counts spectra of the background models and other source models in the
ROI, can be seen in Appendix, Fig. 17. We find that the results from both
likelihood minimisations are in agreement with each other.

##  Appendix E Multiwavelength-context

To better understand the nature of the emission in the region around PSR
J1813$-$1749, a comparison of the observed emission in different energy ranges
was made. Comparing the best-fit model derived in the analysis of the _Fermi_
-LAT data and the H.E.S.S. data yields good spatial agreement (Fig. 18). The
elongation is in both cases observed along the galactic plane and the pulsar
is contained.

Figure 18: Excess map of the H.E.S.S. data after the addition of the Gaussian
and elongated Gaussian model. The position of PSR J1813$-$1749 is indicated by
the blue dot. The best-fit model describing the emission observed by H.E.S.S.
is indicated by the black dashed lines. The _Fermi_ -LAT best-fit model is
depicted by the green ellipse. The models show good spatial agreement

Taking into account data taken by the VLA (red contours in Fig. 19), a
positional coincidence between HESS J1813$-$178A, the pulsar and supernova
remnant can be observed. Additionally shown in the figure is a part of the
stellar cluster Cl J1813$-$178 located in close vincinity to the pulsar.

Figure 19: Zoom-in on a significance map with a correlation radius of
$0.06^{\circ}$ of the region around PSR J1813$-$1749 as seen with H.E.S.S..
The best-fit morphology of HESS J1813$-$178A and HESS J1813$-$178B are
indicated by the white lines, the black countours depict SNR G012.8–00.0 and
CL J1813$-$178 as observed by VLA. The positon of PSR J1813$-$1749 is
indicated in blue.

The region has also been observed by HAWC (Albert et al. 2020) and LHAASO (Cao
et al. 2023), both detecting extended emission around the position of HESS
J1813$-$178A. In order to obtain a better understanding of the region, the
position and extension of these sources, as well as the best-fit model
obtained in this work, are visualized in a significance map computed from the
H.E.S.S. data (see figure 20).

Figure 20: The best-fit morphology derived from the analysis of the H.E.S.S.
data is indicated in black. The best-fit morphology of the source 3HWC
J1813$-$174 is indicated in blue. The description of the region obtained with
LHAASO is indicate by the pink and orange dashed circles.

The morphology of the different components show a good spatial agreement.
Additionally to the morphology, the spectra, derived in Albert et al. (2020)
and Cao et al. (2023) are visualized in figure 21, together with the leptonic
and hadronic model derived in this work. The spectra of 1LHAASO
J1814$-$1719u*, observed by KM2A and 3HWC J1813$-$174 show a good agreement
with the results derived in this study, while the spectrum of 1LHAASO
J1814$-$1719u*, observed by WCDA as well as the spectrum of 1LHAASO
J1814$-$1636u do not agree. A possible reason for this could be the
differences in the separation between source emission and diffuse emission
along the galactic plane.

Figure 21: The estimated $\gamma$-ray flux for the hadronic and leptonic model
together with the spectra derived in the analysis of the Fermi-LAT, H.E.S.S.,
HAWC and LHAASO data.