# The Low-Redshift Lyman Continuum Survey I:
New, Diverse Local Lyman-Continuum Emitters

Sophia R. Flury Department of Astronomy, University of Massachusetts Amherst,
Amherst, MA 01002, United States  Anne E. Jaskot  Department of Astronomy,
Williams College, Williamstown, MA 01267, United States  Harry C. Ferguson
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD,
21218, USA  Gabor Worseck  Institut für Physik und Astronomie, Universität
Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam, Germany  Kirill Makan
Institut für Physik und Astronomie, Universität Potsdam, Karl-Liebknecht-Str.
24/25, D-14476 Potsdam, Germany  John Chisholm  Department of Astronomy,
University of Texas at Austin, Austin, TX 78712, United States  Alberto
Saldana-Lopez Department of Astronomy, University of Geneva, Chemin Pegasi 51,
1290 Versoix, Switzerland  Daniel Schaerer  Department of Astronomy,
University of Geneva, Chemin Pegasi 51, 1290 Versoix, Switzerland  Stephan
McCandliss  Department of Physics and Astronomy, Johns Hopkins University,
Baltimore, MD 21218, United States  Bingjie Wang  Department of Physics and
Astronomy, Johns Hopkins University, Baltimore, MD 21218, United States  N. M.
Ford  Department of Astronomy, Williams College, Williamstown, MA 01267,
United States  Timothy Heckman  Department of Physics and Astronomy, Johns
Hopkins University, Baltimore, MD 21218, United States  Zhiyuan Ji  Department
of Astronomy, University of Massachusetts Amherst, Amherst, MA 01002, United
States  Mauro Giavalisco  Department of Astronomy, University of Massachusetts
Amherst, Amherst, MA 01002, United States  Ricardo Amorín Instituto de
Investigación Multidisciplinar en Ciencia y Tecnología, Universidad de La
Serena, Raúl Bitrán 1305, La Serena, Chile  Departamento de Astronomía,
Universidad de La Serena, Av. Juan Cisternas 1200 Norte, La Serena, Chile
Hakim Atek  Institut d’astrophysique de Paris, CNRS UMR7095, Sorbonne
Université, 98bis Boulevard Arago, F-75014 Paris, France  Jeremy Blaizot  Univ
Lyon, Univ Lyon1, Ens de Lyon, CNRS, Centre de Recherche Astrophysique de Lyon
UMR5574, F-69230, Saint-Genis-Laval, France  Sanchayeeta Borthakur  School of
Earth & Space Exploration, Arizona State University, Tempe, AZ 85287, USA
Cody Carr  Minnesota Institute for Astrophysics, School of Physics and
Astronomy, University of Minnesota, 316 Church str SE, Minneapolis, MN
55455,USA  Marco Castellano  INAF, Osservatorio Astronomico di Roma, via
Frascati 33, I-00078 Monteporzio Catone, Italy  Stefano Cristiani  INAF –
Osservatorio Astronomico di Trieste, via G. B. Tiepolo 11, I-34143, Trieste,
Italy  Stephane De Barros  Department of Astronomy, University of Geneva,
Chemin Pegasi 51, 1290 Versoix, Switzerland  Mark Dickinson  National Optical-
Infrared Astronomy Research Laboratory, Tucson, AZ, USA  Steven L. Finkelstein
Department of Astronomy, The University of Texas at Austin, Austin, TX, USA
Brian Fleming  Laboratory for Atmospheric and Space Physics, Boulder,
Colorado, United States  Fabio Fontanot  INAF–Osservatorio Astronomico di
Trieste, via G.B. Tiepolo, 11, I-34143 Trieste, Italy  Thibault Garel
Department of Astronomy, University of Geneva, Chemin Pegasi 51, 1290 Versoix,
Switzerland  Andrea Grazian  INAF-Osservatorio Astronomico di Padova, Vicolo
dell’Osservatorio 5, I-35122, Padova, Italy  Matthew Hayes  The Oskar Klein
Centre, Department of Astronomy, Stockholm University, AlbaNova, SE-10691
Stockholm, Sweden  Alaina Henry  Space Telescope Science Institute, 3700 San
Martin Drive, Baltimore, MD, 21218, USA  Valentin Mauerhofer  Department of
Astronomy, University of Geneva, Chemin Pegasi 51, 1290 Versoix, Switzerland
Genoveva Micheva  Leibniz-Institute for Astrophysics Potsdam, An der
Sternwarte 16, 14482 Potsdam, Germany  M. S. Oey  Department of Astronomy,
University of Michigan, Ann Arbor, MI 48109, USA  Goran Ostlin  The Oskar
Klein Centre, Department of Astronomy, Stockholm University, AlbaNova,
SE-10691 Stockholm, Sweden  Casey Papovich  George P. and Cynthia Woods
Mitchell Institute for Fundamental Physics and Astronomy, Department of
Physics and Astronomy, Texas A&M University, College Station, TX, USA  Laura
Pentericci  INAF, Osservatorio Astronomico di Roma, via Frascati 33, I-00078
Monteporzio Catone, Italy  Swara Ravindranath  Space Telescope Science
Institute, 3700 San Martin Drive, Baltimore, MD, 21218, USA  Joakim Rosdahl
Univ Lyon, Univ Lyon1, Ens de Lyon, CNRS, Centre de Recherche Astrophysique de
Lyon UMR5574, F-69230, Saint-Genis-Laval, France  Michael Rutkowski
Department of Physics and Astronomy, Minnesota State University, Mankato, MN,
56001, USA  Paola Santini  INAF, Osservatorio Astronomico di Roma, via
Frascati 33, I-00078 Monteporzio Catone, Italy  Claudia Scarlata  Minnesota
Institute for Astrophysics, School of Physics and Astronomy, University of
Minnesota, 316 Church str SE, Minneapolis, MN 55455,USA  Harry Teplitz
Infrared Processing and Analysis Center, California Institute of Technology,
Pasadena, CA 91125, USA  Trinh Thuan  Astronomy Department, University of
Virginia, Charlottesville, VA 22904, USA  Maxime Trebitsch  Astronomy, Kapteyn
Astronomical Institute, Landleven 12, 9747 AD Groningen, The Netherlands  Eros
Vanzella  INAF, Osservatorio Astronomico di Bologna, via Gobetti 93/3 I-40129
Bologna, Italy  Anne Verhamme  Department of Astronomy, University of Geneva,
Chemin Pegasi 51, 1290 Versoix, Switzerland  Univ. Lyon, Univ. Lyon 1, ENS de
Lyon, CNRS, Centre de Recherche Astrophysique de Lyon UMR5574, 69230 Saint-
Genis-Laval, France  Xinfeng Xu  Department of Physics and Astronomy, Johns
Hopkins University, Baltimore, MD 21218, United States

###### Abstract

The origins of Lyman continuum (LyC) photons responsible for the reionization
of the universe are as of yet unknown and highly contested. Detecting LyC
photons from the epoch of reionization is not possible due to absorption by
the intergalactic medium, which has prompted the development of several
indirect diagnostics to infer the rate at which galaxies contribute LyC
photons to reionize the universe by studying lower-redshift analogs. We
present the Low-redshift Lyman Continuum Survey (LzLCS) comprising
measurements made with HST/COS for a $z=0.2-0.4$ sample of 66 galaxies. After
careful processing of the FUV spectra, we obtain a total of 35 Lyman continuum
emitters (LCEs) detected with 97.725% confidence, nearly tripling the number
of known local LCEs. We estimate escape fractions from the detected LyC flux
and upper limits on the undetected LyC flux, finding a range of LyC escape
fractions up to 50%. Of the 35 LzLCS LCEs, 12 have LyC escape fractions
greater than 5%, more than doubling the number of known local LCEs with
cosmologically relevant LyC escape.

cosmology: reionization – ISM: interstellar absorption – galaxies: emission
line galaxies, intergalactic medium, star formation

††journal: ApJS††software:  astropy  (Astropy Collaboration et al., 2013,
2018),  bpass  (Stanway & Eldridge, 2018),  calcos,  Cloudy  (Ferland et al.,
2013),  emcee  (Foreman-Mackey et al., 2013),  FaintCOS  (Worseck et al.,
2016; Makan et al., 2020),  matplotlib  (Hunter, 2007),  numpy  (van der Walt
et al., 2011),  Prospector  (Leja et al., 2017; Johnson et al., 2019),  pyneb
(Luridiana et al., 2015),  scipy  (P. Virtanen, 2020), Starburst99  (Leitherer
et al., 1999, 2010, 2014)

##  1 Introduction

Numerous observations in the last decade indicate that the universe was
reionized by a redshift of $z\approx 6$. The Gunn-Peterson effect observed as
an absorption trough in the continua of distant quasars (e.g., Gunn &
Peterson, 1965; Becker et al., 2001) and as the absorption of Ly$\alpha$
photons (e.g., Fan et al., 2006; Yang et al., 2020), the optical depth of the
cosmic microwave background in the form of Thomson scattering (e.g., Paoletti
et al., 2020; Planck Collaboration et al., 2020), and the reduced transmission
of Ly$\alpha$ observed at higher redshifts (e.g., Mason et al., 2018; Pahl et
al., 2020) all demonstrate that the intergalactic medium (IGM) transitions
from neutral to ionized near this redshift.

While the state of reionization is clear, the nature of the objects that
regulated and dominated this process is not. Dwarf galaxies (
${M_{\star}\lesssim 10^{9}}$ M⊙), which have weaker gravitational potentials,
are more susceptible to clearing of attenuating material by stellar winds and
supernovae (SNe), thereby increasing the fraction of Lyman continuum (LyC)
photons which escape their host galaxy (e.g., Razoumov & Sommer-Larsen, 2010;
Wise et al., 2014; Paardekooper et al., 2015). However, more massive galaxies
have the gas reservoirs necessary for high star formation rate densities and
experience less suppressive feedback from stellar winds and supernovae,
allowing more stars to form and, ergo, more LyC photon production (Wyithe &
Loeb, 2013).

Which galaxy mass regime dominates reionization is a matter of some
contention. Current empirically-motivated models suggest relatively more
luminous (albeit still faint) galaxies are the primary, if not sole, source of
escaping LyC photons responsible for reionization (Naidu et al., 2020). Other
models predict less luminous galaxies dominate reionization (e.g., Finkelstein
et al., 2019), owing largely to steeper luminosity functions than those
adopted by Naidu et al. (2020). Local observations of LyC (e.g., Izotov et
al., 2018b) seem to favor the dwarf-galaxy scenario suggested by radiation
hydrodynamical simulations (e.g., Trebitsch et al., 2017) as do some holistic
models incorporating massive galaxies, active galactic nuclei (AGN), and dwarf
galaxies (e.g., Finkelstein et al., 2019; Dayal et al., 2020).

Although star-forming galaxies remain the most likely candidates for
reionization, their exact contribution is still unknown. One of the least
constrained parameters in our understanding of reionization is the so-called
escape fraction $f_{esc}^{LyC}$, the fraction of LyC photons which escape from
the host galaxy into the IGM (Steidel et al., 2001). As it pertains to
reionization, $f_{esc}^{LyC}$ relates to the cosmic ionization rate by

$\dot{n}_{gal}=f_{esc}^{LyC}\xi_{ion}\rho_{\rm SFR}$ (1)

where $\dot{n}_{gal}$ is the emission rate of LyC photons by high-redshift
($z\geq 6$) galaxies per unit comoving volume, $\xi_{ion}$ is the total rate
of LyC photons produced within their progenitor galaxies per star formation
rate (SFR), and $\rho_{\mathrm{SFR}}$ is the volume density of galaxies per
unit SFR. All properties on the right-hand side of Equation 1 may vary with
other galaxy properties such as galaxy mass. Further complicating constraints
on $\dot{n}_{gal}$ is the fact that, whereas $\rho_{\mathrm{SFR}}$ can be
inferred from observations, $f_{esc}^{LyC}$ is degenerate with $\xi_{ion}$ if
measured from Balmer emission lines, which complicates estimating
$f_{esc}^{LyC}$ from LyC measurements. Some constraint on $\xi_{ion}$, such as
H$\alpha$ or [O III]$\lambda 5007$ (e.g., Bouwens et al., 2016; Schaerer et
al., 2016), is necessary to break this degeneracy (e.g., Steidel et al.,
2018). Values of $f_{esc}^{LyC}$ required by reionization models typically
span 0.1 (Finkelstein et al., 2015, 2019) to 0.2 (Robertson et al., 2015;
Naidu et al., 2020).

Unfortunately, observational constraints on $f_{esc}^{LyC}$ have proven
difficult to obtain. Early space-based LyC observations of local galaxies
yielded upper limits (Leitherer et al., 1995; Deharveng et al., 2001),
suggesting $f_{esc}^{LyC}$$\lesssim 3$%. Many putative detections at higher
redshifts ($z\sim 3$) over the next ten years turned out to be non-LyC
contamination from lower-redshift interlopers at small angular separation
(e.g., Vanzella et al., 2012; Mostardi et al., 2015; Siana et al., 2015).
Another difficulty stems from IGM attenuation at higher redshifts, which (i)
makes LyC measurements at or beyond reionization ($z\gtrsim 6$) impossible
because all the LyC photons are absorbed (e.g., Becker et al., 2021); and (ii)
makes imaging detections of the LyC at moderately high redshifts ($z=2-3$)
complicated because the Lyman series and LyC attenuation are uncertain along
any particular line of sight (e.g., Inoue et al., 2014; Steidel et al., 2018).
Moreover, the LyC is too faint at $z\gtrsim 4$ to be detected with even the
largest contemporary ground-based telescopes.

Despite these complications, the past several years have enjoyed an explosion
of LyC detections from a few upper limits to a few tens of significant
measurements. Observations of local ($z<0.4$) galaxies with the Hubble Space
Telescope (HST) Cosmic Origins Spectrograph (COS; Green et al., 2012) have
yielded $\gtrsim 16$ LyC detections (Leitet et al., 2013; Borthakur et al.,
2014; Leitherer et al., 2016; Izotov et al., 2016a, b, 2018a, 2018b; Wang et
al., 2019; Izotov et al., 2021). These measurements are not without
difficulty: scattered telluric light can contaminate the LyC (cf. Chisholm et
al., 2017 regarding Leitherer et al., 2016) and even masquerade as LyC (cf.
Izotov et al., 2016b regarding _FUSE_ observations by Leitet et al., 2013).

Of the best measurements of the LyC from local galaxies, the Green Peas (GPs),
which in many ways resemble galaxies in early cosmological epochs (e.g.,
Cardamone et al., 2009; Amorín et al., 2010, 2012; Jaskot & Oey, 2013;
Schaerer et al., 2016), exhibit $f_{esc}^{LyC}$ which can exceed 20% (e.g.,
Izotov et al., 2018b). Ground-based observations have made significant headway
at higher redshifts ($z\sim 3$) with careful measurements of $f_{esc}^{LyC}$
for 16 galaxies (Steidel et al., 2018; Vanzella et al., 2018). Further HST
observations have contributed to the $z\sim 3$ measurements of $f_{esc}^{LyC}$
by adding $\gtrsim 10$ LyC detections (Mostardi et al., 2015; de Barros et
al., 2016; Vanzella et al., 2016; Bian et al., 2017; Micheva et al., 2017;
Fletcher et al., 2019; Rivera-Thorsen et al., 2019; Ji et al., 2020).

The search for Lyman continuum emitters (LCEs, sometimes referred to as Lyman
continuum “leakers”, e.g., Bergvall et al., 2013) at high redshift relies on
indirect indicators of the physical mechanisms involved in LyC escape. The [O
III]$\lambda$5007/[O II]$\lambda\lambda$3726,29 ($O_{32}$) emission line flux
ratio, thought to be a proxy for optical depth in extreme GP galaxies (e.g.,
Jaskot & Oey, 2013; Nakajima & Ouchi, 2014), has successfully been used to
select LCE candidates for two HST/COS observing programs (Izotov et al.,
2016a, b, 2018a, 2018b). However, a third observing program using O32 as a
selection criterion, Izotov et al. (2021), did not reproduce this success.
Star formation rate surface density ($\Sigma_{SFR}$) can gauge the role of
stellar feedback in facilitating LyC escape (e.g., Heckman et al., 2001;
Clarke & Oey, 2002). Indeed, cosmological simulations predict that
$\Sigma_{SFR}$ correlates with $f_{esc}^{LyC}$ where $\Sigma_{SFR}>0.1$ M⊙
yr-1 kpc-2 corresponds to cosmologically relevant values of
$f_{esc}^{LyC}$$\gtrsim 5$% (e.g., Sharma et al., 2017; Naidu et al., 2020).
Extinction and starburst age determine the slope (measured by the spectral
index assuming $f_{\lambda}\propto\lambda^{\beta}$) of the non-ionizing UV
continuum. Values of $\beta\lesssim-2$ indicate young ($<$30 Myr),
unextinguished stellar populations from which LyC photons could escape (e.g.,
Zackrisson et al., 2013, 2017). Together, O32, $\Sigma_{SFR}$, and $\beta$ can
serve as holistic selection criteria for LCE candidates, although these
properties may select galaxies with intrinsically strong LyC flux rather than
galaxies with high $f_{esc}^{LyC}$.

This paper presents the Low-Redshift Lyman Continuum Survey (LzLCS). We have
assembled a sample of 66 star-forming galaxies from the Sloan Digital Sky
Survey (SDSS, York et al., 2000) and the Galaxy Evolution Explorer (GALEX,
Martin et al., 2003) that reside nearby ($z\sim 0.3$) and are considered
likely candidates for LyC escape according to the above criteria (§2). We have
observed each of these 66 galaxies with HST/COS to measure the LyC (§3-4).
From the HST/COS and SDSS photometry and spectra, we derive physical and
observational properties to characterize these 66 galaxies and compare them to
a set of LCEs from the literature which have been previously observed with
HST/COS (§5). From our measurements of the LyC flux, we provide estimates of
$f_{esc}^{LyC}$ for our sample (§6). Companion papers present our initial
tests of indirect LyC diagnostics (Flury et al. submitted, Saldaña-Lopez et
al. submitted, Wang et al., 2021). Throughout this paper, we assume $H_{0}=70$
km s-1 Mpc-1, $\Omega_{m}=0.3$, and $\Omega_{\Lambda}=0.7$.

##  2 Sample Definition

We define a sample of 66 LCE candidates, the LzLCS, to investigate the
properties, physical mechanisms, and diagnostics associated with LyC escape.
To begin, we search for star-forming galaxies in the SDSS Data Release 15
(Blanton et al., 2017) using either the tabulated emission line fluxes or our
own measurements made following Jaskot et al. (2019). We limit our sample to
star-forming galaxies by using the BPT diagram (Baldwin et al., 1981) to
exclude AGN and composite systems. Then, we match these objects with
photometry from the GALEX data archive. We select galaxies which are
relatively nearby ($z\sim 0.3$) so that the rest-frame LyC can be readily
observed by HST/COS with the G140L grating while reaching the sensitivity
required to detect $f_{esc}^{LyC}$$\sim 5$% at S/N$>5$ for each object. The
COS throughput imposes a redshift limit of $z\gtrsim 0.22$ to this detection
goal because its sensitivity declines by roughly two orders of magnitude for
wavelengths below 1100 Å (Green et al., 2012).

From the SDSS-GALEX star-forming galaxies, we select objects to evenly sample
the O32, $\beta$, and $\Sigma_{SFR}$ methods of inferring $f_{esc}^{LyC}$ with
$\sim 50$ objects each across a range of the relevant parameter space.The
LzLCS is thus designed to span a far wider range of relevant parameter spaces
than previous investigations, allowing us to determine whether LCEs are a
heterogeneous or homogeneous population of galaxies.

Figure 1: Venn diagram showing the overlap of the three selection criteria for
the LzLCS: O32=[O III]/[O II] flux ratio (top left), UV slope parameterized by
spectral index $\beta$ (top right), and star formation rate surface density
$\Sigma_{SFR}$ (bottom center).

We include 37 objects from the low-redshift SDSS/GALEX with O32$>3$, bringing
the number of objects with high O32 to 50 when combined with previous studies.
We include an additional 29 galaxies with high star formation rate surface
densities (lower limit of $\Sigma_{SFR}>0.1$ M☉ yr-1 kpc-2 estimated from the
dust-corrected GALEX FUV magnitude assuming $A_{FUV}\sim 12\times E(B-V)$ and
SDSS $u$-band half-light radius) and/or blue UV continua (power law index
$\beta<-2$ estimated from the GALEX photometry). We chose galaxies with
various combinations of these criteria to improve the chances of targeting
true LCEs. As a result, at least 37 galaxies in the total sample satisfy each
criterion with 11 galaxies satisfying all three (Fig 1).

##  3 Observations with HST/COS

For the sample of 66 candidate LyC-leaking galaxies, we obtained 134 orbits of
HST/COS spectroscopy under observing program GO 15626 (Cycle 26, P.I. Jaskot).
COS acquires each object via NUV imaging and centered its 2.5″ diameter
spectroscopic aperture on the peak NUV flux. We used the G140L grating at 800
Å in COS Lifetime Position 4, covering a wavelength range of $800-1950$ Å with
a resolution of $R\sim 1050$ at 1100 Å (cf. Izotov et al., 2021). We show a
log of the observations in Table 1 and example acquisition images in Figure 2.

Table 1: HST/COS observation log for the LzLCS. Also indicated are the average number of dark current observations used to model the background dark current in each visit. A full version of this table is available online.  Object | RA (deg) | Dec (deg) | $z$ | Visit | Date | Exp Time (s) | N Darks
---|---|---|---|---|---|---|---
J003601+003307 |  9.002641 |  0.552006 | 0.3479 | ldxe08 | 2019-09-25 |  3980.384 | 13
J003601+003307 |  9.002641 |  0.552006 | 0.3479 | ldxew9 | 2019-12-08 |  3980.672 |  9
J004743+015440 |  11.928487 |  1.911086 | 0.3535 | ldxe42 | 2019-07-29 |  1495.904 |  9
J011309+000223 |  18.286905 |  0.039839 | 0.3062 | ldxez5 | 2019-08-03 |  1363.904 | 13
J012217+052044 |  20.569425 |  5.345561 | 0.3656 | ldxe05 | 2019-09-20 |  3780.320 | 15

Figure 2: Example log-scaled acquisition images of a non-emitter (left),
marginally detected LCE (center) and well detected LCE (right) from the LzLCS.
Circle indicates the 2.5″ COS spectroscopic aperture. Bar in the lower left
indicates a physical scale of 5 kpc at the target’s redshift with 1 kpc ticks.
Acquisition image thumbnails for the full sample are available online.

Following previous works (Worseck et al., 2016; Izotov et al., 2018b; Wang et
al., 2019; Izotov et al., 2021), we process the raw HST/COS spectra using a
combination of standard and custom software to best model the background and
optimize measurement of the LyC. The COS detector measures the pulse height
amplitude (PHA) of charge produced by an amplifying microchannel plate. Dark
current and location-dependent geomagnetic activity like the South Atlantic
Anomaly can trigger the COS detector, resulting in spurious background events
with a PHA distribution extending beyond PHAs of science events (Worseck et
al., 2016; Izotov et al., 2016b). Before processing the spectra, we screen
PHAs to include only values within the $1$–$12$ range for Lifetime Position 4
to mitigate dark current and other without excluding science events. We reduce
the spectra using the calcos pipeline (v3.3.9) to perform flat-fielding, dead
time and stim pulse corrections, and wavelength and flux calibrations. For the
extraction, we draw a rectangular aperture 25 pixels wide along the cross-
dispersion axis (hatched region in Figure 4), a range comparable to the 95th
percentiles of the total starlight continuum profile after excluding
geocoronal Ly$\alpha$ emission.

With the custom software FaintCOS (Worseck et al., 2016; Makan et al.,
2020)111https://github.com/kimakan/FaintCOS, we estimate the dark current and
scattered geocoronal Ly$\alpha$ background and co-add individual exposures to
improve signal-to-noise ratios while preserving Poisson counts. For each
observation, we compare the PHA cumulative distribution function of each dark
obtained from a $\pm$1 month window, selecting those which match the PHA
cumulative distribution function of the background in the science image by
means of a Kolmogorov-Smirnoff test ($D<0.03$) to ensure the solar and
geomagnetic conditions during the recording of the darks are comparable to
those of the science image (Worseck et al., 2016; Izotov et al., 2018b). We
show the number of dark observations selected in this manner for each visit in
Table 1. To evaluate the success of the dark model, we compare the spatial
variations of the dark model to the background of the science image and find
the two consistently agree (see grey line in Figure 4). We scale the Worseck
et al. (2016) model for scattered light background by the peak telluric
Ly$\alpha$ counts in each extraction. We co-add the spectra and background
models for each object and bin from the over-sampled detector dispersion of
0.0803 Å to 0.5621 Å in order to Nyquist-sample the G140L resolution of $\sim
1.1$ Å. In cases where the gross counts are less than 100 counts above the
background, we determine the Neyman-Pearson 1$\sigma$ confidence intervals in
the flux measurements following Feldman & Cousins (1998). Otherwise, we sample
variates from the Poisson distributions of the background and science spectra
to compute the $1$-$\sigma$ confidence in the flux in each pixel. Finally, we
correct each spectrum for Milky Way extinction using Galactic $E(B-V)$
estimates from the dust maps by Green et al. (2018) and the Fitzpatrick (1999)
extinction law. To determine the final uncertainty in the corrected flux in
each pixel, we sample flux measurements and the Green et al. (2018) reddening
$10^{4}$ times.

##  4 Measuring Lyman Continuum

We measure the LyC flux in a rest-frame 20 Å window as close as possible to
$\lambda_{rest}=900$ Å while avoiding wavelengths above $\lambda_{obs}=1180$ Å
to minimize telluric contamination, rounding down to the nearest 10 Å in the
rest frame. This constraint ensures as uniform a measurement of the LyC as
possible across the entire sample while simultaneously preventing any
contamination by the Ly$\alpha$ and N I $\lambda 1200$ geocoronal emission
lines or by non-LyC starlight introduced into the 900-912 Å range by
dispersion through the HST/COS optics. To evaluate any unresolved geocoronal
contamination, we compare the count rate during orbital night to that of the
total visit and find good agreement between the two, indicating no significant
contributions of telluric radiation to the LyC. Moreover, the scattered light
model by Worseck et al. (2016) rectifies minor discrepancies between the two
count rates, indicating that our treatment of the background light is
appropriate.

Figure 3: Top: Example spectra (black) of a non-emitter (left), marginally
detected Lyman continuum emitter (LCE, center) and well detected LCE (right)
from the LzLCS, downsampled to 4 Å resolution for visualization. Grey shaded
region indicates the 1-$\sigma$ uncertainty in flux density. Red circle is the
measured LyC flux with black lines showing the 68% confidence intervals
(capped) and rest-frame 20 Å spectral bin (uncapped). Grey broken lines
indicate the clipped geocoronal emission from telluric Ly$\alpha$ and O I.
Dashed vertical line indicates the Lyman limit. Bottom: Same as top but with
LyC region magnified. Spectrum thumbnails for the full sample are available
online.

Figure 4: Example spatial cross-section of the 2d spectrum for a non-emitter
(left), marginally detected Lyman continuum emitter (LCE, center) and well
detected LCE (right) from the LzLCS. The black line represents the non-
ionizing starlight continuum, the grey line the model dark current, red line
the LyC scaled to the same median background counts as the starlight profile,
and the grey hatched stripe the spectral extraction aperture.

We consider the mean background-subtracted flux density in the spectral window
to be the LyC flux, $F_{\lambda\rm LyC}^{obs}$, and the 84th percentile in the
background distribution (i.e., the $1\sigma$ sensitivity limit) to be the
upper limit on $F_{\lambda\rm LyC}^{obs}$ in cases of non-detections. As a
robust assessment of detection, we determine the probability, $P(>N|B)$, that
the total observed, or gross, counts $N$ within the spectral window are
realized from the distribution of background counts $B$. Worseck et al. (2016)
define $P(>N|B)$ as the survival function for the Poisson distribution of the
background counts evaluated at the gross observed counts. Proceeding with this
convention, the probability that the gross measured LyC counts $N$ is a chance
realization of the background $B$ is

$P(>N|B)=1-\mathrm{Q}(N+1,B)$ (2)

where $\mathrm{Q}$ is the regularized incomplete gamma function. We consider
$P(>N|B)=0.02275$, the 2$\sigma$ value given by the normal distribution
survival function, an acceptable maximum probability that the observed counts
are sampled from the background. We list the number of galaxies in the LzLCS
which satisfy traditional 2, 3, and 5$\sigma$ detection criteria in Table 2
and provide examples of the rest-frame LyC for non-, weak ($\sim 2\sigma$),
and strong ($\gtrsim 5\sigma$) detections in Figure 3. In total, 35 galaxies
satisfy our detection requirements.

To confirm these detections, we examine the cross-dispersion profile of the
two-dimensional spectrum in the LyC window to qualitatively verify the
presence of a LyC profile which appears roughly consistent with the non-LyC
starlight profile. We show such a comparison of LyC with the non-LyC starlight
profile in Figure 4. In summary, we detect 35 LCEs out of 66 targets. We show
the LzLCS LyC fluxes in Figure 5 as a function of redshift to highlight the
effect of changes in COS sensitivity across the detector222 We estimate that
pending changes to the COS flux calibration, which are not yet public for our
Lifetime Position 4 settings, will result in a 6-6.5% increase in our measured
LyC flux and a smaller increase in flux at longer wavelengths. However, this
increase is comparable to the relative uncertainty in the measured flux and
will only increase the corresponding $f_{esc}^{LyC}$ by a factor of $\sim
1.02$..

Table 2: LzLCS and published detections of local LCEs with HST/COS. Significance is the number of Poisson standard deviations between the measured LyC counts and the model background counts. $P(>N|B)$ is the probability of measuring LyC counts greater than those measured in the COS spectrum given the background counts. LzLCS indicates the number of galaxies from the LzLCS corresponding to each detection criterion. Pub. indicates the number of galaxies from HST/COS observations published in the literature and reprocessed by the LzLCS collaboration.  Quality | Signif. | max $P(>N|B)$ | LzLCS | Pub.
---|---|---|---|---
Good | $>5$ | $2.867\times 10^{-7}$ | 12 |  14
Fair |  $3$-$5$ | $1.350\times 10^{-3}$ | 13 |  0
Marginal |  $2$-$3$ | $2.275\times 10^{-2}$ | 10 |  1
Detected | $>2$ | $2.275\times 10^{-2}$ | 35 | 15
Upper limit | $\leq 2$ | $1$ | 31 | 8

To ensure consistency in our method, we reprocess the raw HST/COS spectra for
the 23 galaxies in the Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et
al. (2019) investigations of local ($z\lesssim 0.4$) LCE candidates following
the same procedure and find that we reproduce their LyC fluxes. The median
relative difference between the published fluxes and our measurements is
$0.094_{-0.022}^{+0.043}$, indicating that we recover their results to within
10% but with a statistically significant difference. While the scatter and
differences are small, this slight disagreement suggests our reprocessing and
re-measurement of the Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et
al. (2019) LyC fluxes are necessary to mitigate any systematic discrepancies.
Because we used the same custom reduction software, we attribute the
difference to a combination of the spectral window over which we measure the
LyC. We find 15 of the 23 Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang
et al. (2019) LCE candidates satisfy our detection requirements. For the 23
LCE candidates, our significance assessment is consistent with the literature;
however, we consider two objects, J124810+425954 (Izotov et al., 2018b) and
J112721+461042 (Izotov et al., 2021), to be non-detections because our
detection requirement is more stringent. Both we and the authors report
$1\sigma$ LyC detection significance in these instances. We present the LyC
fluxes for these published LCE candidates with the LzLCS results in Figure 5.

Thus, the 35 detections in the LzLCS sample nearly triples the total number of
confirmed LCEs in the local universe.

Figure 5: LyC measurements (circles) and upper limits (triangles) for the
combined LzLCS and published samples show the HST/COS LyC flux sensitivity
limits as a function of redshift. The increase in sensitivity with redshift is
due primarily to the location of the LyC on the COS detector.

##  5 LzLCS Galaxy Properties

Below, we detail the measurement and calculation of various properties of the
LzLCS galaxies and compare them to the same properties for the 23 local
($z\lesssim 0.4$) galaxies discussed in §4 with _HST_ /COS observations of the
LyC published in Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al.
(2019). Furthermore, we demonstrate the much broader range of the LzLCS
properties relative to previous LCE surveys. We list these properties in
Tables 4-8 for several LzLCS targets and provide the full tables of these
properties online.

###  5.1 Optical Extinction

We have measured fluxes and equivalent widths (EWs) of emission lines in the
SDSS DR15 spectra by fitting them with one to two Gaussian profiles following
Jaskot et al. (2019). In some cases, the [O III]$\lambda$5007 profile appears
“sheared off” or affected by sky lines, and the [O III] $F_{5007}/F_{4959}$
flux ratio deviates significantly from the expected ratio of 2.98 (Storey &
Zeippen, 2000). In these cases, we adopt $F_{5007}=2.98F_{4959}$. We convert
the observed EWs to the rest frame using redshifts obtained from the SDSS.
Using the dust maps by Green et al. (2018) and the Fitzpatrick (1999)
extinction law, we correct the observed-frame emission line fluxes for
Galactic extinction. Then, we iteratively compute the uncertainty-weighted
rest-frame internal $E(B-V)$ and stellar absorption from the H$\alpha$,
H$\beta$, H$\gamma$, H$\delta$, and H$\varepsilon$ emission line fluxes and
EWs if the emission line flux is detected at S/N$>5$. Correction for stellar
absorption is adapted from Equation 1 from Izotov et al. (1994). In the seven
cases where the H$\alpha$/H$\beta$ is more than one standard deviation below
the Case B value of 2.747 (Storey & Hummer, 1995, assuming the extreme case of
$T_{e}=2\times 10^{4}$ K and $n_{e}=10^{2}$ cm-3) and the four cases where the
H$\alpha$ profile appears sheared off (likely due to spurious cosmic ray
clipping or saturation), we exclude H$\alpha$ from the procedure.

We iterate the following procedure until converging on a solution for
$E(B-V)$: (i) derive the electron temperature and density from nebular lines,
(ii) calculate the intrinsic flux ratios from the results of step (i) by
interpolating over the grid of recombination coefficients from Storey & Hummer
(1995), and (iii) compute the variance-weighted average $E(B-V)$ from the
ratio of observed to intrinsic Balmer decrements. Electron temperature and
density derivation follows the temperature-scaling approach described by Flury
& Moran (2020) with collisional populations and emissivities computed by pyneb
(Luridiana et al., 2015). For the electron temperature, we use the [O III]
$\lambda\lambda 4363;4959,5007$ auroral line and nebular doublet, substituting
the [O III] $\lambda 4363~{}$ flux inferred from the “ff–relation” by Pilyugin
et al. (2006) for the 12 galaxies in the total LzLCS sample where the auroral
line is not detected (see discussion in Curti et al., 2017). For the electron
density, we use the [S II] $\lambda\lambda 6716,31$ doublet, available for 56
galaxies, as the [O II] $\lambda\lambda 3726,29$ doublet is not resolved in
the SDSS spectra. Otherwise, we assume $n_{e}=100$ cm-3. We assume the
Cardelli et al. (1989) extinction law as this choice gives $E(B-V)$ values
comparable to other extinction laws (e.g., Gordon et al., 2003) and
appropriately describes the extinction of nebular emission lines in LCEs such
as the GPs (Izotov et al., 2017).

Figure 6: Distribution of rest-frame H$\beta$ equivalent width (EW) values for
galaxies in the LzLCS (solid) with detected LyC (dark grey) and undetected LyC
(light grey). For comparison, we include the EWs for LCE candidates with
published _HST_ /COS spectra (hatched) with detected LyC (black) and
undetected LyC (grey). Error bars represent the $1\sigma$ Poisson binomial
uncertainty in each histogram bin. Figure 7: Same as Figure 6 but for [O
III]$\lambda 5007$/[O II]$\lambda 3727,29$=O32.

These corrected flux measurements from the optical spectra provide the
H$\beta$ EW (accounting for stellar absorption) and O32 flux ratios
(accounting for extinction). We show the H$\beta$ EW for the LzLCS galaxies
and published LCEs in Figure 6. Values range from 11 to 426 Å with a median of
91 Å. For the LzLCS galaxies and published LCEs, $\log_{10}$O32 spans -0.32 to
1.56 with a median of 0.65, as we show in Figure 7. From both figures, the
previously published LCE H$\beta$ EWs and O32 ratios are located towards the
high end of the LzLCS sample distribution. In other words, the LzLCS extends
to much lower H$\beta$ EWs and O32 than these previous studies. The LzLCS
nearly doubles the number of detected low-redshift LCEs with H$\beta$ EWs
$>100$ Å and O32 $>3$. Moreover, the LzLCS dramatically improves the number of
detected low-redshift LCEs with H$\beta$ EWs $<100$ Å and O32 $<3$, a space
previously sampled by just 3 LCEs. The presence of LCEs across such a wide
range of EW H$\beta$ suggests galaxies with a variety of burst ages and/or
star formation histories can leak LyC photons. Similarly, the presence of LCEs
across nearly 2 dex in O32 indicates that LCEs span a wide range of ionization
parameters and/or nebula boundary conditions.

###  5.2 Nebular Abundances

Figure 8: Same as Figure 6 but for $12+\log_{10}({\rm O/H})$.

With the electron temperatures and densities derived above, we determine
direct-method relative oxygen abundances from emissivities computed by pyneb
and extinction-corrected optical emission lines. Monte Carlo sampling the
emissivities using the uncertainties in the fluxes, temperatures, and
densities yields the total statistical uncertainty in our direct-method
abundances. As evident in Figure 8, the LzLCS spans a range of about 6 to 60%
solar oxygen abundance (as defined by Steffen et al., 2015) while the
published LCEs are more narrowly concentrated to a range of 10 to 30% solar.
The LzLCS samples higher metallicities than previous studies, with $\sim$50%
of the galaxies having $12+\log_{10}({\rm O/H})$ above the highest published
local LCEs. Furthermore, the LzLCS increases the number of detected low-
redshift LCEs across all abundances, particularly above $12+\log_{10}({\rm
O/H})\sim 8.2$, demonstrating that, as with H$\beta$ EWs, LCEs span a wide
range of of star formation histories because $12+\log_{10}({\rm O/H})$ traces
the net number of type II SNe.

###  5.3 Half-light Radius

Using the reduced MIRROR-A NUV COS acquisition images, we compute the source
radius $r_{50}$ containing 50% of the background-subtracted counts. We
estimate the median background counts in an annulus centered on the source
with an inner radius of 53 pixels to avoid contamination by the source and
subtract the median counts from the image. After background subtraction, we
correct for vignetting effects. While the galaxies in the LzLCS are typically
compact (typical uncorrected galaxy profile FWHM$\lesssim 0.4$″ in the NUV),
we correct the acquisition images for the radial decline in throughput because
the total source counts can still be affected by vignetting. Then, we compute
the total source counts by measuring the counts enclosed by a range of radii
until the total counts vary by less than the rms of the background noise. We
then interpolate over the counts distribution to obtain the radius at half the
total source counts. Uncertainty in the half-light radius is determined by
summing the Poisson error of the gross counts, the COS acquisition image plate
scale of 0.0235″ px-1, and a maximum NUV imaging PSF FWHM of 2.4 px.

In Figure 9, we show that the UV-emitting stellar populations inhabit small
regions with $0.3<r_{50}<0.6$ kpc in both the published LCEs and half of the
LzLCS galaxies. While the number of galaxies in each bin decreases quickly
with increasing halflight radius, the LzLCS galaxies have $r_{50}$ as high as
$2.25$ kpc, indicating the survey includes galaxies with spatially-extended
star formation. However, as in previous studies, the LzLCS finds that LCEs
predominantly have compact star-forming regions. To confirm this result, we
also fit the surface brightness distributions with two-dimensional Sérsic and
exponential profiles and find close agreement between the best-fit effective
radii and the model-independent halflight radii.

Figure 9: Same as Figure 6 but for $r_{50}$.

###  5.4 Ly$\alpha$ and Continuum Properties

The HST/COS spectra are extracted and reduced a second time following the
procedure discussed in §3, this time using a 30-pixel aperture (0.637″) in
place of the 25-pixel aperture to include more signal because Ly$\alpha$ is
more spatially extended than the UV continuum (e.g., Guaita et al., 2015;
Wisotzki et al., 2016; Leclercq et al., 2017; Rasekh et al., 2021) and
requires less background exclusion than the LyC. For the LzLCS, the Ly$\alpha$
extraction aperture radius corresponds to a factor of about 2.6 more than the
UV continuum halflight radius and thus should contain most of the Ly$\alpha$
flux (e.g., Hayes et al., 2013), although vignetting of the COS aperture may
exclude some of the Ly$\alpha$ even in the more compact sources. We process
the data using the same assumptions as in the previous section, most notably
the same Galactic extinction. From these wider extractions, we measure the
integrated galactic Ly$\alpha$ flux. We fit the continuum within 100 Å of
Ly$\alpha$ with a linear fit using iterative sigma clipping to exclude noise
spikes and absorption features, conservatively assuming a 25% uncertainty in
the continuum fit. We then integrate the continuum-subtracted flux density
where the Ly$\alpha$ feature deviates from the continuum to obtain the
Ly$\alpha$ flux, masking the 1206 and 1240 Å features to avoid contamination.
To obtain the rest-frame Ly$\alpha$ EW, we divide by the continuum flux and
correct for redshift. We do not correct for stellar Ly$\alpha$ absorption as
its effect on the measured emission line flux and EW is, at most, relatively
small (Peña-Guerrero & Leitherer, 2013).

In Figure 10, we show the Ly$\alpha$ EWs for the LzLCS and Izotov et al.
(2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) LCE candidates. The LzLCS
Ly$\alpha$ EWs $\gtrsim 60$ Å are consistent with the majority of published
LCEs; however, 45 of the 66 galaxies in the LzLCS sample have EWs smaller than
this value. As with H$\beta$, we find that LCEs span a wider range in
Ly$\alpha$ EWs than previous studies. Because Ly$\alpha$ is more sensitive to
the H I column density and the corresponding continuum is more sensitive to
recent star formation, the LzLCS results demonstrate that LCEs span a wider
range of burst ages and/or H I opacities than previously published surveys may
have indicated.

Figure 10: Same as Figure 6 but for rest-frame Ly$\alpha$ EW.

To determine the spectral index $\beta_{1200}$ of the rest-frame UV continuum,
we fit the wide-extraction spectra using the affine-invariant Markov chain
Monte Carlo sampling software emcee (Foreman-Mackey et al., 2013) to sample
the posterior of $\beta_{1200}$. We set a lower limit of 1050 Å in the rest
frame to avoid the combined O VI $\lambda\lambda 1032,1038$ Å and C II
$\lambda 1036$ Å absorption features and mask the galactic Ly$\alpha$. We show
the distribution of $\beta_{1200}$ values in Figure 11. The LzLCS samples
roughly the same range of $-2.5<\beta_{1200}<-0.35$ as previous studies of
local LCEs but with most galaxies concentrated at $\beta_{1200}=-1.6$. One
exception, J131904+510309, exhibits substantial extinction in the
UV—$E(B-V)_{UV}$=0.5, $E(B-V)_{neb}$=0.42—which results in
$\beta_{1200}=0.79$. While the LzLCS LCEs span a range in UV $\beta$
comparable to that of previously published LCE candidates, our LCEs are, on
average, redder, suggesting that LCEs can have a larger range of burst ages
and/or dust content than previously found.

Figure 11: Same as Figure 6 but for $\beta_{1200}$.

Because the flux at 1500 Å often falls outside the COS window for these
redshifts, we also measure the continuum flux at 1100 Å as other studies have
done (e.g., Wang et al., 2019). This spectral window is a reliably bright part
of the starlight continuum which avoids the aforementioned absorption features
spanning 1030-1040 Å. We take $F(1100)$ to be the average flux from 1090 to
1110 Å, the same width as the LyC flux for consistency. At our sample’s
redshifts, this choice also serves to eliminate potential contamination of
$F(1100)$ by telluric O I $\lambda 1304$ emission.

###  5.5 UV Spectral Modeling

Following Chisholm et al. (2019), we estimate stellar $E(B-V)$ values and
$f_{esc}^{LyC}$ by comparing our data with a library of synthetic spectra
compiled from Starburst99 models (Leitherer et al., 2010) for non-rotating
stars and nebular continuum modeled by Cloudy (Ferland et al., 2013). These
models are fit to the continua with scaling factors multiplied by the Reddy et
al. (2016) extinction law with reddening as an additional free parameter. Our
reference library contains forty synthetic spectra for simple stellar
populations spanning ten burst ages (1, 2, 3, 4, 5, 8, 10, 15, 20 and 40 Myr)
and four metallicities (0.05, 0.2, 0.4 and 1 $Z_{\odot}$). These are combined
allowing for multiple generations of star formation with metallicity as a free
parameter (Saldaña-Lopez et al. submitted). Fits are performed in the rest-
frame after convolving model spectra by a Gaussian kernel to the COS spectral
resolution. We discuss the derivation of $f_{esc}^{LyC}$ further in §6.

###  5.6 Star Formation Rate Surface Density and Stellar Mass

We convert the observed properties into a star formation rate surface density,
$\Sigma_{SFR}$, assuming the H$\beta$ and FUV star formation rate calibrations
from Kennicutt & Evans (2012) and dividing by $2\pi r_{50,NUV}^{2}$ following
Naidu et al. (2020). We note that these star formation rate indicators using
H$\beta$ and UV luminosities are based on standard calibrations rather than
tailored to the detailed properties (e.g., metallicity) of our sample. Thus,
these star formation rates are more representative of the H$\beta$ and FUV
luminosities than the true star formation rate. Figure 12 shows that the LzLCS
spans a much wider range in $\Sigma_{SFR}$ than previous studies. While many
LzLCS LCEs exhibit $\Sigma_{SFR}$$>10$ M⊙ yr-1 like their published LCE
counterparts, many LzLCS LCEs have much lower $\Sigma_{SFR}$. Since the LzLCS
LCEs’ half-light radii are similar to those of published LCEs, the difference
in LCE $\Sigma_{SFR}$ is a distinction in SFR, suggesting concentration is
more important than SFR for LyC escape.

Stellar masses, $M_{\star}$, are determined by using the stellar population
inference code Prospector (Leja et al., 2017; Johnson et al., 2019) to fit
aperture-matched photometry from SDSS and GALEX assuming a non-parametric star
formation history, a Kroupa (2001) initial mass function, Cloudy
photoionization models, and a Calzetti (2001) dust attenuation curve (Ji et
al. in prep, see also Rutkowski et al. in prep), noting that the inferred
stellar mass changes negligibly if adopting the Reddy et al. (2016) extinction
law instead. As shown in Figure 13, $M_{\star}$ ranges from $10^{8.25}$ to
$10^{10.75}$ $M_{\odot}$ with half of the sample having $M_{\star}<10^{9}$
$M_{\odot}$. The LzLCS LCEs are primarily dwarf galaxies but do persist up to
much higher mass ($M_{\star}>10^{10}$ $M_{\odot}$) galaxies. While the
distribution of LCEs suggests that dwarf galaxies dominate the LCE population,
higher mass galaxies can still be LCEs.

We use these stellar masses to compute the specific star formation rate,
sSFR$=$SFR${}_{{\rm H}\beta}/M_{\star}$.

Figure 12: Same as Figure 6 but for $\Sigma_{SFR}$ derived from H$\beta$.
Figure 13: Same as Figure 6 but for $M_{\star}$.

###  5.7 Ly$\alpha$ Escape Fraction

Using the temperatures and densities derived from the optical emission lines,
we compute the Case B emissivities for Ly$\alpha$ and H$\beta$ from the pyneb
grid of recombination coefficients from Storey & Hummer (1995). We correct
H$\beta$ for both Galactic and internal extinction and use the ratio of
Ly$\alpha$ to H$\beta$ emissivities to infer the intrinsic Ly$\alpha$ flux. We
then use the observed Ly$\alpha$ flux, corrected for Galactic extinction, to
calculate the fraction of Ly$\alpha$ photons, $f_{esc}^{Ly\alpha}$, which
escape the host galaxy. Uncertainties in the $f_{esc}^{Ly\alpha}$ are
determined using Monte Carlo sampling of the grid of Case B emissivities from
the uncertainties in temperature and density. We show the distribution of
$f_{esc}^{Ly\alpha}$ values in Figure 14. While the LzLCS samples roughly the
same range of $f_{esc}^{Ly\alpha}$$\in[0,0.6]$ as previous studies, half of
the sample exhibits low ($<16$%) Ly$\alpha$ escape. This concentration at low
$f_{esc}^{Ly\alpha}$ suggests a high H I column along the line of sight in
many of the LzLCS galaxies (e.g., Verhamme et al., 2015).

Figure 14: Same as Figure 6 but for $f_{esc}^{Ly\alpha}$.

As demonstrated in Figure 14, two objects exhibit atypically high
$f_{esc}^{Ly\alpha}$: J081112+414146 and J164849+495751. These galaxies also
have H$\alpha$/H$\beta$ and H$\gamma$/H$\beta$ decrements which are not
permitted by traditional Case B limits of $\geq 2.747$ and $\leq 0.475$,
respectively. This inconsistency most likely indicates that the Balmer lines
in SDSS spectra are problematic. Alternatively, such high $f_{esc}^{Ly\alpha}$
values may indicate collisional excitation of the H I $n=2$ state in galactic
winds or a hot diffuse halo (e.g., Carr et al., 2021) or excess Ly$\alpha$
scattered into the line of sight (e.g., Giavalisco et al., 1996). Excepting
these two extreme cases, the LzLCS LCEs tend to have
$f_{esc}^{Ly\alpha}$$<0.5$ like their published counterparts. However, the
LzLCS non-LCEs tend to have much lower $f_{esc}^{Ly\alpha}$ ($<0.15$). Such
$f_{esc}^{Ly\alpha}$ values demonstrate that the LzLCS more robustly samples
the LCE population at high H I column densities than previous studies and even
suggests LyC photons can escape even when a substantial amount of neutral gas
is present.

###  5.8 Ly$\alpha$ Peak Velocity Separation

The G140L resolution is insufficient to resolve the red and blue peaks of the
Ly$\alpha$ profile. However, seven targets from the LzLCS have existing
archival G160M COS spectra in which the two peaks are resolved. We obtain
measurements of the velocity separation $v_{sep}$ of these peaks from Henry et
al. (2015), Yang et al. (2017), and Orlitová et al. (2018) and compare them to
peak separations for published LCEs from Verhamme et al. (2017) and Izotov et
al. (2018b) in Figure 15. While the number of LzLCS galaxies with measured
$v_{sep}$ is small, the LCEs in our sample have Ly$\alpha$ peak separations
larger than the characteristic value for published LCEs. This difference
indicates a larger H I column density in the LzLCS LCEs than in published
LCEs, which may suggest LyC escape can occur in a variety of ISM geometries.
However, the lack of $v_{sep}$ measurements prevents further insight.

Figure 15: Same as Figure 6 but for the velocity separation of the blue and
red peaks of the Ly$\alpha$ profile. No error bars are shown as insufficient
uncertainties are reported in the literature.

###  5.9 UV Magnitudes

We compute the absolute UV magnitude at 1500 Å (M1500) from the Starburst99
templates best-fit to the COS spectra after correcting for Galactic (but _not_
internal) extinction. These magnitudes are computed by summing the template
flux density over a 20 Å boxcar window and converting to absolute AB magnitude
using the luminosity distance derived from the spectroscopic redshift.

Figure 16: Same as Figure 6 but for M1500. Dashed line indicates the
characteristic $M_{1600}^{*}=-20.87$ at $z=7$ (Bouwens et al., 2015).

We show the COS UV magnitudes in Figure 16, finding M${}_{1500}\in[-22,-17]$.
Figure 16 indicates that the younger stellar populations in many LzLCS
galaxies are, like their published counter parts, fainter than the
characteristic $M^{\star}$. However, the LCEs in LzLCS span a wider range in
$M_{1500}$ than the published LCEs, indicating that more luminous galaxies can
also be LCEs.

##  6 LyC Escape Fraction

We use three estimates of the LyC escape fraction, $f_{esc}^{LyC}$: the
$F_{\lambda\rm LyC}/F_{\lambda 1100}$ flux ratio, $f_{esc}^{LyC}$ derived from
H$\beta$, and $f_{esc}^{LyC}$ determined from fits to the UV continuum. Each
independent metric allows us to assess possible systematics in
$f_{esc}^{LyC}$, providing an additional constraint on how much the escape
fraction depends on our assumptions about, e.g., star formation history, dust
extinction, etc. The $F_{\lambda\rm LyC}/F_{\lambda 1100}$ flux ratio is an
empirical proxy for $f_{esc}^{LyC}$ (cf. Wang et al., 2019). While less direct
than $f_{esc}^{LyC}$, $F_{\lambda\rm LyC}/F_{\lambda 1100}$ is free of any
assumptions about stellar populations or dust. However, this flux ratio
depends implicitly on extinction, burst age, and metallicity, making a direct
interpretation less meaningful. Values for this flux ratio span 0.0 to 0.328
with a median of 0.023.

Figure 17:  $F_{\rm{H}\beta}^{mod}/F_{\lambda 900}^{mod}$ ratio predicted by
instantaneous (left) and continuous (right) star formation histories from
Starburst99 (top) and bpass (bottom) models for $f_{esc}^{LyC}$$=0$ as a
function of H$\beta$ EW for a range of metallicities. Metallicity increases
with increasing dash length over the interval $Z=[0.001,0.04]$, as shown by
the arrow in the top right panel. The change in $F_{{\rm
H}\beta}/F_{\lambda\rm LyC}$ with metallicity is due to the softening of
stellar SEDs with increasing metallicity. Solid black line (top left)
indicates the Izotov et al. (2016b) relation. Symbols represent the inferred
$F_{\rm{H}\beta}/F_{\lambda\rm LyC}$ for $f_{esc}^{LyC}$$=0$ for LCEs
(circles) and non-detections (open triangles) implied by the measured
$F_{\lambda\rm LyC}$, H$\beta$, $12+\log_{10}\left(\frac{\rm O}{\rm
H}\right)$, and $f_{esc}^{LyC}$ for each set of models. Median uncertainties
are shown in the lower left panel, increased by a factor of three for
visualization. Figure 18:  Difference between $f_{esc}^{LyC}$ calculated from
bpass instantaneous (open diamonds) and continuous (light grey squares) star
formation or from Starburst99 continuous star formation (dark grey circles)
models and $f_{esc}^{LyC}$ calculated using Starburst99 instantaneous star
formation models as compared to H$\beta$ EW for $f_{esc}^{LyC}$ derived from
H$\beta$ for the combined LzLCS and published samples. Symbol size corresponds
to the LyC detection significance. Characteristic uncertainties are shown on
the right. Increasing scatter with decreasing H$\beta$ EW indicates the
increasing effect of assumptions about star formation history on the inferred
$f_{esc}^{LyC}$.

###  6.1 H$\beta$ $f_{esc}^{LyC}$

To estimate the absolute $f_{esc}^{LyC}$, we use the extinction-corrected flux
and rest-frame EW of H$\beta$ to infer the LyC absorbed by the ISM in the
galaxy as described by Izotov et al. (2016b, 2018a). This approach assumes
that the extinction-corrected H$\beta$ flux is a proxy for the total number of
ionizing photons absorbed by the nebula (e.g., Osterbrock & Ferland, 2006).
The conversion between the total ionizing photon flux and the LyC flux at a
particular wavelength depends on the stellar population age. The H$\beta$ EW
yields the burst age for an assumed star formation history. Use of the
H$\beta$ EW is necessary to select the appropriate model
$F_{\rm{H}\beta}^{mod}/F_{\lambda\rm LyC}^{mod}$ independent of the UV SED
fits. Here, the $F_{\rm{H}\beta}^{mod}/F_{\lambda\rm LyC}^{mod}$ ratio
accounts for the shape of the LyC by tracing the amount of ionizing flux that
falls within the 20 Å bin over which the LyC flux is measured. Because the
ionization cross-section of H I is proportional to $\lambda^{3}$, the emergent
flux increases with decreasing LyC wavelength for a fixed escape fraction. We
calculate the synthetic LyC flux in the 20 Å bins used to measure the LyC in
the COS spectra, matching the model and observed wavelength bins.

To obtain model LyC and H$\beta$ values for deriving $f_{esc}^{LyC}$, we
consider two sets of population models, each with two different star formation
histories. To predict LyC fluxes and H$\beta$ properties, we use Starburst99
models (Leitherer et al., 1999, 2014) and bpass models (Stanway & Eldridge,
2018) assuming either an instantaneous burst or continuous star formation.
Model ages span from 0.1 to 500 Myr while metallicities range from $Z=0.001$
to $0.04$. For the Starburst99 and bpass models, we assume a Kroupa (2001) and
Chabrier (2003) initial mass functions, respectively, with mass ranges from
0.1 to 100 M⊙ for both sets of models. In all cases, the shape of the relation
changes as a function of stellar metallicity (see Figure 17), meaning there is
no single function from which to infer the absorbed LyC flux. To select the
appropriate sequence, we take advantage of our $12+\log_{10}({\rm O/H})$
abundance estimate derived in §5.2, assuming that the gas and stellar
metallicities are comparable since the stars have recently formed and have not
yet further enriched the ISM. While at high redshift, $\alpha$ enhancement may
affect the scaling of oxygen to total metalicity; however, Izotov et al.
(2011) find that GPs have Fe/O ratios comparable to those of other low-
redshift dwarf galaxies and that dust depletion sufficiently explains any
apparent gas-phase $\alpha$ excess relative to iron. Thus, scaling the total
metallicity by the relative oxygen abundance is appropriate for the combined
sample.

We then interpolate over the grid of $F_{{\rm H}\beta}/F_{\lambda\rm LyC}$
from the stellar population models to obtain the predicted intrinsic flux
ratio vs H$\beta$ EW for the given galaxy’s metallicity. As in Izotov et al.
(2016b), we take the LyC flux $F_{\lambda\rm LyC}^{abs}$ implied by the
H$\beta$ flux to be the absorbed LyC flux such that the $f_{esc}^{LyC}$ is

$f_{esc}^{LyC}({\rm H}\beta)=\frac{F_{\lambda\rm LyC}^{obs}}{F_{\lambda\rm
LyC}^{obs}+F_{\lambda\rm LyC}^{abs}}=\frac{F_{\lambda\rm
LyC}^{obs}}{F_{\lambda\rm LyC}^{mod}}.$ (3)

This relation is only an initial estimate as the H$\beta$ EW, the burst age
indicator used to infer $F_{\rm{H}\beta}^{mod}/F_{\lambda\rm LyC}^{mod}$, is
in fact affected by LyC escape, meaning that H$\beta$ EW must be corrected for
$f_{esc}$ in order to yield the appropriate flux ratio (e.g., Izotov et al.,
2018b). Using the $f_{esc}^{LyC}$ calculated from the uncorrected value as the
initial condition, we iteratively correct H$\beta$ EW and recompute $f_{esc}$
until converging on a value of $f_{esc}^{LyC}$, typically within 10 or fewer
iterations. Uncertainties in $f_{esc}^{LyC}$ are estimated by Monte Carlo
simulation, sampling the uncertainties in H$\beta$ flux and EW, LyC flux, and
$12+\log_{10}({\rm O/H})$ and recalculating $f_{esc}^{LyC}$ $10^{4}$ times.

As evident in Figure 17, the Starburst99 models reproduce the Izotov et al.
(2016b) relation between H$\beta$ EW and the $F_{\rm{H}\beta}/F_{\lambda\rm
LyC}$ flux ratio for an instantaneous starburst of 10% solar metallicity
(Figure 17, upper left). However, our results indicate that using the Izotov
et al. (2016b) prescription will consistently yield higher
$F_{\rm{H}\beta}/F_{\lambda\rm LyC}$ and thus over-estimate $f_{esc}^{LyC}$
for an instantaneous burst. We also take into account the effects of binary
star evolution by considering the bpass model (Stanway & Eldridge, 2018). This
model increases the ionizing photon budget by an amount comparable to that of
the continuous starburst (Figure 17, lower left). Continuous Starburst99 and
BPASS models predict $F_{\rm{H}\beta}/F_{\lambda\rm LyC}$ values higher than
those of the Starburst99 instantaneous burst models (Figure 17, upper and
lower right), with the difference increasing as H$\beta$ EW decreases due to
subsequent generations of young stars.

Using the H$\beta$ line with the Starburst99 and BPASS continuous star
formation models yields $f_{esc}^{LyC}$ values ranging from 0 to 20% for the
LzLCS sample and from 0 to 45% for the published LCEs. 15 of the LzLCS LCEs
and 9 of the published LCEs have cosmologically relevant values of
$f_{esc}^{LyC}$$>0.05$. The BPASS instantaneous burst models yield similar
results, with a median difference in $f_{esc}^{LyC}$ of $\approx 0.001$%. The
$f_{esc}^{LyC}$ values derived from Starburst99 instantaneous star formation
models diverge from the bpass and Starburst99 $f_{esc}^{LyC}$ with increasing
burst age. We illustrate this effect in Figure 18 by comparing the difference
in $f_{esc}^{LyC}$ to the H$\beta$ EW. For the youngest bursts, the difference
is negligible because the early O stars dominate the LyC and optical continuum
in every scenario; however, the effects of continuously forming new O and B
stars or accretion onto stripped stars in binary star systems can amplify
$f_{esc}^{LyC}$ by as much as a factor of two or three, respectively, at later
burst ages.

Figure 19: Top: $f_{esc}^{LyC}$ derived from fitting the COS UV spectrum
compared to $f_{esc}^{LyC}$ derived from H$\beta$ using the Starburst99
continuous star formation models. Shaded region indicates the rms log
difference of the two $f_{esc}^{LyC}$ values. Bottom: Comparison of
$f_{esc}^{LyC}$ with $F_{\lambda\rm LyC}/F_{\lambda 1100}$ for the combined
sample of LzLCS and published LCEs. Open symbols represent $f_{esc}^{LyC}$
derived from H$\beta$ using the Starburst99 continuous star formation models
while filled symbols represent $f_{esc}^{LyC}$ derived from fits to the UV
continuum. In both figures, symbol size corresponds to the LyC detection
significance, and grey arrows indicate upper limits on $f_{esc}^{LyC}$. Error
bars in the lower right indicate the median uncertainty for objects with
detected LyC ($P(>N|B)<0.02275$). Dashed line is 1:1 agreement.

###  6.2 UV SED $f_{esc}^{LyC}$

To determine $f_{esc}^{LyC}$ from the UV continuum fits, we compute the ratio
of the measured LyC flux to the intrinsic (unreddened) LyC flux implied by the
best-fit Starburst99 templates. We obtain the intrinsic LyC flux by using the
low-resolution Starburst99 bases, summing the model flux in the same spectral
window used to measure the LyC in the COS spectrum. The UV escape fraction is
then obtained by

$f_{esc}^{LyC}({\rm UV})=\frac{F_{\lambda\rm LyC}^{obs}}{F_{\lambda\rm
LyC}^{fit}}.$ (4)

This yields a range of $f_{esc}^{LyC}$ from 0 to 50% with 9 of the LzLCS LCEs
having $f_{esc}^{LyC}$$>0.05$. While the uncertainties for the UV
$f_{esc}^{LyC}$ are higher due to the SNR of the COS spectrum, this approach
is less sensitive to the presence of older stellar populations than H$\beta$
because the FUV continuum is only sensitive to the youngest stars.

###  6.3 Comparison of $f_{esc}^{LyC}$ Results

In Figure 19, we show that the UV and H$\beta$ methods typically agree to
within $\sim$0.5 dex, which we confirm by calculating the rms ratio of the two
$f_{esc}^{LyC}$ values. Even the strongest LCEs exhibit this scatter,
indicating the persistence of systematic uncertainty across a dynamic range of
escape fractions. The UV $f_{esc}^{LyC}$ values are consistently higher at
high values of $F_{\lambda\rm LyC}/F_{\lambda 1100}$. While both approaches to
deriving $f_{esc}^{LyC}$ depend on assumptions, the consistency between all
three measures of LyC escape gives us confidence in assessing the relevance of
different galaxies to reionization. Despite the effects of extinction and
stellar populations implicit to the measured $F_{\lambda\rm LyC}/F_{\lambda
1100}$, we show in Figure 19 that $f_{esc}^{LyC}$ correlates well with it,
indicating this flux ratio is a rough proxy for $f_{esc}^{LyC}$. Of all the
H$\beta$ $f_{esc}^{LyC}$ estimates, the Starburst99 continuous star formation
models yield $f_{esc}^{LyC}$ values most consistent with the UV
$f_{esc}^{LyC}$. This agreement suggests the the UV and continuous H$\beta$ EW
star formation histories are most comparable, although discrepancies still
persist between the two. We find that the observed $F_{\lambda\rm
LyC}/F_{\lambda 1100}$ are best predicted by the continuous star formation
models. Thus, we proceed with $f_{esc}^{LyC}$ derived using the continuous
star formation models in subsequent analysis.

While the UV-fit $f_{esc}^{LyC}$ tends to be higher at high $F_{\lambda\rm
LyC}/F_{\lambda 1100}$, only 9 LzLCS targets have significantly high
$f_{esc}^{LyC}$ ($>0.05$). Despite lower maximum $f_{esc}^{LyC}$ values,
H$\beta$ yields 15 objects with high $f_{esc}^{LyC}$. In our re-measurement of
$f_{esc}^{LyC}$ for published HST/COS LyC observations, we find 13 have high
$f_{esc}^{LyC}$ from fits to the UV continuum and 14 have high $f_{esc}^{LyC}$
from H$\beta$. Thus, through the LzLCS, we have roughly doubled the number of
known LCEs with cosmologically significant $f_{esc}^{LyC}$ ($\gtrsim 5$ %),
demonstrating the immense scientific value of the LzLCS program.

##  7 Conclusion

We present the Low-redshift Lyman Continuum Survey, the largest search for
LCEs in the low-redshift ($z\sim 0.3$) universe. With careful processing of
HST/COS spectra, we measure the LyC in 66 candidate LCEs, detecting flux with
$>$97.725% significance from 35 galaxies in the sample. The LzLCS nearly
triples the number of known local LCEs.

From UV and optical spectra and UV photometry, we characterize the global
properties of the LzLCS galaxies. The sample contains low metallicity galaxies
with direct-method oxygen abundances ranging from $12+\log_{10}({\rm
O/H})$=7.5 to 8.5, a much broader range than previously published LCEs.
Stellar masses span $M_{\star}=10^{8}$ to $10^{10}$ $M_{\odot}$ with the UV
halflight radii ranging from 0.3 to 2.25 kpc. The halflight radii,
$\Sigma_{SFR}$, and $sSFR$ imply highly concentrated star formation. H$\beta$
EWs and O32 imply a range of starburst ages, ionization parameter, and/or
optical depth effects. The LzLCS covers a wider range of properties than
previously published low-redshift LCEs, demonstrating the ability of our
survey to explore and test the heterogeneity of LCEs and $f_{esc}^{LyC}$.

From empirical methods and synthetic stellar population models, we derive
escape fractions ranging from 0 to 50%. Although previous studies suggest
$f_{esc}^{LyC}$ derived by different methods agree (e.g., Izotov et al.,
2016b, 2018b), the broader scope of the LzLCS demonstrates that
$f_{esc}^{LyC}$ estimates can be sensitive to assumptions about stellar
populations and star formation history as well as the data used. Based on our
assessment of different methods and related systematic uncertainties, the
$f_{esc}^{LyC}$ based on the UV starlight continuum is the most reliable
because it is less sensitive to assumptions than the $f_{esc}^{LyC}$ based on
H$\beta$.

With the LzLCS, we have roughly doubled the number of local LCEs with
cosmologically relevant LyC escape ($f_{esc}^{LyC}$$>0.05$, e.g., Robertson et
al., 2015) from 13 to 22 (or 14 to 29) using the UV (or H$\beta$) method. The
LzLCS thus offers an unprecedented opportunity to investigate the conditions
related to LyC escape in galaxies, the results of which may be extended to the
epoch of reionization.

We evaluate LCE and $f_{esc}^{LyC}$ diagnostics in companion papers (Flury et
al. submitted, Wang et al., 2021). We also analyze the UV absorption lines
(Saldaña-Lopez et al. submitted) and SED parameters (Ji et al. in prep) of
LCEs and non-emitters. Additional planned work includes investigation of the
shape of the LyC and the Lyman break, feedback and gas dynamics, neutral and
low-ionization gas covering fractions, and photoionization modeling to further
understand the ISM conditions and physical mechanisms of escaping LyC.

We thank the anonymous referee for feedback which improved the clarity of this
paper. Support for this work was provided by NASA through grant number _HST_
-GO-15626 from the Space Telescope Science Institute. Additional work was
based on observations made with the NASA/ESA Hubble Space Telescope, obtained
from the data archive at the Space Telescope Science Institute from _HST_
proposals 13744, 14635, 15341, and 15639. STScI is operated by the Association
of Universities for Research in Astronomy, Inc. under NASA contract NAS
5-26555. Funding for the Sloan Digital Sky Survey IV has been provided by the
Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science,
and the Participating Institutions. SDSS-IV acknowledges support and resources
from the Center for High Performance Computing at the University of Utah. The
SDSS website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research
Consortium for the Participating Institutions of the SDSS Collaboration. RA
acknowledges support from ANID Fondecyt Regular 1202007.

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Table 3: Flux ratios measured from the SDSS optical spectra for the combined LzLCS and Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) samples. A full version of this table is available online.  Object | EW(H$\beta$) | $\log_{10}R_{23}$ | $\log_{10}O_{32}$ | $\log_{10}O_{31}$ |  $\log_{10}$[O I]/H$\beta$
---|---|---|---|---|---
| Å |  |  |  |
J003601+003307 | 160.469$\pm$ 6.509 |  0.938$\pm$ 0.024 |  1.113$\pm$ 0.039 |  $>$ 2.621 |  $<$-1.836
J004743+015440 | 61.511$\pm$ 1.137 |  0.956$\pm$ 0.024 |  0.655$\pm$ 0.026 |  $>$ 2.870 |  $<$-2.124
J011309+000223 | 40.896$\pm$ 1.775 |  0.964$\pm$ 0.076 |  0.357$\pm$ 0.086 |  $>$ 2.349 |  $<$-1.668
J012217+052044 | 87.255$\pm$ 3.110 |  0.942$\pm$ 0.041 |  0.881$\pm$ 0.047 |  $>$ 2.553 |  $<$-1.790
J012910+145935 | 73.370$\pm$ 1.180 |  0.855$\pm$ 0.026 |  0.340$\pm$ 0.031 |  1.717$\pm$ 0.088 | -1.150$\pm$ 0.088

Table 4: Properties derived from the SDSS optical spectra for the combined LzLCS and Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) samples. A full version of this table is available online. Object |  $\log_{10}$SFRHβ |  $n_{e}$ (cm-3) |  $T_{e}$ (K) | $12+\log_{10}\left(\frac{\rm O}{\rm H}\right)$
---|---|---|---|---
J003601+003307 |  1.184$\pm$ 0.024 | 100 | 15770$\pm$970 |  7.781$\pm$ 0.037
J004743+015440 |  1.336$\pm$ 0.024 | 1610$\pm$150 | 13820$\pm$850 |  8.290$\pm$ 0.037
J011309+000223 |  0.699$\pm$ 0.076 | 6590$\pm$180 | 11640$\pm$1060 |  8.329$\pm$ 0.115
J012217+052044 |  0.971$\pm$ 0.041 | 100 | 16220$\pm$1760 |  7.799$\pm$ 0.064
J012910+145935 |  1.125$\pm$ 0.026 | 2600$\pm$120 | 10000$\pm$250 |  8.411$\pm$ 0.044

Table 5: Properties derived from the HST/COS G140L spectra for the combined
LzLCS and
Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) samples. A full version of this table is available online. Object | $M_{1500}$ | $r_{50}$ | $\beta_{1200}$ | $f_{1100}\times 10^{17}$ | EW(Ly$\alpha$) |  $\log_{10}$SFR${}_{f_{1100}}$
---|---|---|---|---|---|---
|  | kpc |  | erg s-1 cm-2 Å-1 | Å |  $M_{\odot}$ yr-1
J003601+003307 | -17.905$\pm$ 0.100 |  0.445$\pm$ 0.148 | -2.900$\pm$ 0.328 |  6.445${}_{-0.381}^{+0.418}$ | 93.900$\pm$ 9.330 |  0.345$\pm$ 0.028
J004743+015440 | -20.300$\pm$ 0.094 |  0.618$\pm$ 0.145 | -2.380$\pm$ 0.298 | 38.611${}_{-2.507}^{+2.787}$ | 41.526$\pm$ 4.427 |  1.325$\pm$ 0.031
J011309+000223 | -19.657$\pm$ 0.118 |  0.627$\pm$ 0.133 | -1.990$\pm$ 0.253 | 36.421${}_{-3.649}^{+2.623}$ | 31.291$\pm$ 3.560 |  1.252$\pm$ 0.031
J012217+052044 | -19.410$\pm$ 0.098 |  0.713$\pm$ 0.151 | -1.609$\pm$ 0.274 | 23.193${}_{-1.595}^{+1.427}$ | 70.616$\pm$ 6.793 |  0.922$\pm$ 0.027
J012910+145935 | -19.862$\pm$ 0.058 |  0.636$\pm$ 0.127 | -1.672$\pm$ 0.205 | 50.705${}_{-3.600}^{+2.979}$ | 39.593$\pm$ 4.840 |  1.370$\pm$ 0.026

Table 6: Properties derived jointly from HST/COS, and SDSS data for the combined LzLCS and Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) samples. A full version of this table is available online. Object | $f_{esc}^{\mathrm{Ly}\alpha}$ | $\log_{10}\Sigma_{SFR,\mathrm{H}\beta}$ | $\log_{10}\Sigma_{SFR,f_{1100}}$ | $\log_{10}M_{\star}$
---|---|---|---|---
J003601+003307 |  0.116$\pm$ 0.011 |  1.880$\pm$ 0.146 |  0.249$\pm$ 0.147 |  8.754${}_{-0.425}^{+0.444}$
J004743+015440 |  0.194$\pm$ 0.019 |  0.956$\pm$ 0.105 |  0.945$\pm$ 0.107 |  9.203${}_{-0.430}^{+0.439}$
J011309+000223 |  0.398$\pm$ 0.075 |  0.307$\pm$ 0.119 |  0.860$\pm$ 0.098 |  9.111${}_{-0.430}^{+0.438}$
J012217+052044 |  0.594$\pm$ 0.069 |  0.467$\pm$ 0.100 |  0.417$\pm$ 0.096 |  8.762${}_{-0.423}^{+0.448}$
J012910+145935 |  0.193$\pm$ 0.017 |  0.719$\pm$ 0.091 |  0.965$\pm$ 0.091 |  9.154${}_{-0.305}^{+0.583}$

Table 7: Measurements of the LyC. A full version of this table is available online. Object |  $\lambda_{LyC}$ aaRest-frame central wavelength of 20 Å LyC spectral window | Dark | Sky | Source | $P(>N|B)$ |  $f_{LyC}\times 10^{17}$ bbLyC flux density corrected for MW extinction
---|---|---|---|---|---|---
| Å | counts | counts | counts |  | erg s-1 cm-2 Å-1
J003601+003307 | 860 | 62.388 | 19.298 | 13.314 | 0.066 |  $<$ 0.114
J004743+015440 | 860 | 12.438 |  6.664 | 25.898 | $1.305\times 10^{-7}$ |  1.557${}_{-0.407}^{+0.457}$
J011309+000223 | 890 |  8.970 |  6.471 | 20.559 | $2.282\times 10^{-6}$ |  1.445${}_{-0.428}^{+0.490}$
J012217+052044 | 850 | 34.209 |  5.945 | 34.845 | $3.045\times 10^{-7}$ |  1.118${}_{-0.266}^{+0.292}$
J012910+145935 | 890 | 11.290 |  9.734 | 2.237 | 0.266 |  $<$ 0.556

Table 8: Empirical $F_{\lambda\rm LyC}/F_{\lambda 1100}$ and absolute $f_{esc}^{LyC}$ derived from Starburst99 using continuous star formation predictions and H$\beta$ or the burst predictions fit to the HST/COS spectrum for the combined LzLCS and Izotov et al. (2016a, b, 2018a, 2018b, 2021); Wang et al. (2019) samples. A full version of this table is available online. Object | $f_{LyC}/f_{1100}$ |  $f_{esc}^{LyC}$(H$\beta$) |  $f_{esc}^{LyC}$(UV)
---|---|---|---
J003601+003307 |  $<$ 0.017 |  $<$ 0.005 |  $<$ 0.010
J004743+015440 |  0.040${}_{-0.010}^{+0.012}$ |  0.049${}_{-0.012}^{+0.014}$ |  0.015${}_{-0.004}^{+0.019}$
J011309+000223 |  0.040${}_{-0.012}^{+0.013}$ |  0.123${}_{-0.035}^{+0.042}$ |  0.020${}_{-0.012}^{+0.019}$
J012217+052044 |  0.048${}_{-0.012}^{+0.013}$ |  0.084${}_{-0.019}^{+0.022}$ |  0.038${}_{-0.014}^{+0.057}$
J012910+145935 |  $<$ 0.011 |  $<$ 0.014 |  $<$ 0.007