# Measuring White Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-Epoch
Photometry

Maya Steen Department of Astronomy, Boston University, 725 Commonwealth Ave.,
Boston, MA 02215, USA  Department of Astronomy, New Mexico State University,
Las Cruces, NM 88003, USA  J. J. Hermes Department of Astronomy, Boston
University, 725 Commonwealth Ave., Boston, MA 02215, USA  Joseph A. Guidry NSF
Graduate Research Fellow  Department of Astronomy, Boston University, 725
Commonwealth Ave., Boston, MA 02215, USA  Annabelle Paiva  Department of
Astronomy, Boston University, 725 Commonwealth Ave., Boston, MA 02215, USA
Jay Farihi Department of Physics & Astronomy, University College London, Gower
Street, London WC1E 6BT, UK  Tyler M. Heintz Department of Astronomy, Boston
University, 725 Commonwealth Ave., Boston, MA 02215, USA  Brison B. Ewing
Department of Astronomy, Boston University, 725 Commonwealth Ave., Boston, MA
02215, USA  Nathaniel Berry Department of Physics and Astronomy, University of
North Carolina, Chapel Hill, NC 27599, USA

###### Abstract

White dwarf stars are ubiquitous in the Galaxy, and are essential to
understanding stellar evolution. While most white dwarfs are photometrically
stable and reliable flux standards, some can be highly variable, which can
reveal unique details about the endpoints of low-mass stellar evolution. In
this study we characterize a sample of high-confidence white dwarfs with
multi-epoch photometry from Gaia Data Release 3. We compare these Gaia light
curves with light curves from the Zwicky Transiting Facility and the
Transiting Exoplanet Survey Satellite to see when Gaia data independently can
accurately measure periods of variability. From this sample, 105 objects have
variability periods measured from the Gaia light curves independently, with
periods as long as roughly 9.5 d and as short as 256.2 s (roughly 4 min),
including seven systems with periods shorter than 1000 s. We discover 86 new
objects from the 105 target sample, including pulsating, spotted, and binary
white dwarfs, and even a new 68.4 min eclipsing cataclysmic variable. The
median amplitude of the absolute photometric variability we confirm from Gaia
independently is 1.4%, demonstrating that Gaia epoch photometry is capable of
measuring short-term periods even when observations are sparse.

††facilities: The Gaia Collaboration, The Zwicky Transient Facility, The
Transiting Exoplanet Survey Satellite, NTT, SOAR††software: astropy (Astropy
Collaboration et al., 2013, 2018), numpy (Harris et al., 2020), lightkurve
(Lightkurve Collaboration et al., 2018), pandas (Reback et al., 2022),
astroquery (Ginsburg et al., 2019), matplotlib (Hunter, 2007), lmfit (Newville
et al., 2016), TOPCAT (Taylor, 2005)

##  1 Introduction

As the endpoints of all stars below roughly 8 $M_{\odot}$, white dwarfs are
extremely common. Their ubiquity and relative simplicity mean that white dwarf
stars play an important role as flux standards, which are needed for precise
absolute photometry and spectroscopy (e.g., Calamida et al., 2022).

Roughly 97% of all apparently isolated white dwarfs are empirically stable to
less than 1% variability on weeks-long timescales (Hermes et al., 2017a). When
white dwarfs are photometrically variable they can reveal unique physical
properties such as the presence of magnetism or surface rotation periods
(e.g., Maoz et al., 2015), binary properties (e.g., Holberg & Howell, 2011),
remnant planetary systems (e.g, Hallakoun et al., 2018; Guidry et al., 2021),
or even their interiors through asteroseismology (e.g., Romero et al., 2012).

Binary systems with at least one white dwarf star can tell us about stellar
ages and close binary evolution (e.g., Rebassa-Mansergas et al. 2007; Heintz
et al. 2022). These objects can also be progenitors of Type Ia supernovae,
which are important distance indicators (Maoz et al., 2015). Binaries with
short periods (less than roughly 1 hour) are also potential candidates for
gravitational waves detectable with the Laser Interferometer Space Antenna
(LISA, Burdge et al. 2020).

There are a number of ways binaries with a white dwarf can be photometrically
variable. Eclipsing systems are the most dramatic, where one star passes in
front of the other (e.g., Hallakoun et al. 2016). Eclipsing white dwarfs,
which can be used to measure the masses and radii of the system components
(Parsons et al., 2017, 2018), are still relatively rare so any increase in the
sample is valuable. Eclipses are not necessary to detect close binaries, as
hot stars in the system can create a reflection effect from reprocessed
heating off a cool companion (e.g., Schaffenroth et al. 2022). In addition,
cataclysmic variables (CVs) are highly variable white dwarfs with stochastic
mass-transfer from a Roche-lobe-filling main-sequence companion (Warner,
1995).

Magnetic white dwarfs can also exhibit strong photometric changes, such as
cold (e.g., Brinkworth et al. 2013; Kilic et al. 2015) or hot (e.g., Hoard et
al. 2018) spots corresponding to the surface rotation period. Measuring these
rotation periods can help to investigate the angular momentum loss during
white dwarf formation (Fuller et al., 2019).

Pulsating white dwarfs are variable due to non-radial pulsations as they cool
through different instability strips that depend on their surface composition
(Winget & Kepler, 2008a; Fontaine & Brassard, 2008; Hermes et al., 2017c).
With enough identified pulsation modes, asteroseismology affords the
opportunity to significantly constrain the interiors of white dwarfs,
including global rotation rates (e.g., Hermes et al. 2015, 2017b) and core
composition (e.g., Giammichele et al. 2018; Chidester et al. 2022).

Motivated by the need to find and constrain new variable white dwarfs, we
analyze here a new data product from Gaia Data Release 3 (DR3), which features
multi-epoch light curves for sources classified as variable via a machine
learning algorithm trained on constant objects (Eyer et al., 2023). This new
Gaia DR3 dataset includes photometric time series in the Gaia $G$,
$G_{\mathrm{BP}}$, and $G_{\mathrm{RP}}$ bands. Previous efforts have focused
on literature cross-matches of DR3 variables (Gavras et al., 2023; Rimoldini
et al., 2023), as well as specific object types (Gaia Collaboration et al.,
2023a; Marton et al., 2023).

In Section 2 we discuss our target selection for variable white dwarfs in Gaia
DR3, and in Section 3 describe our period-finding analysis. In Section 4 we
explain our classification of new white dwarf variables, including new
(eclipsing) binaries, spotted (magnetic) white dwarfs, and pulsating white
dwarfs, all with coherent periodicities detected from Gaia DR3 photometry
independently and confirmed in multiple datasets. We discuss the strengths and
limitations of Gaia for period analysis in Section 5 and conclude in Section
6.

##  2 Target Selection and Observations

We set out to select and analyze all apparently isolated white dwarf stars
flagged as photometrically variable in Gaia DR3 (Gaia Collaboration et al.,
2023b). A new, expanded data product in DR3 is the release of multi-epoch,
multi-color ($G$, $G_{\mathrm{BP}}$, $G_{\mathrm{RP}}$) light curves for
roughly 10.5 million objects with anomalously large scatter in their many Gaia
visits (a.k.a. transits) that make them high-probability candidate variables
(Eyer et al., 2023). These objects are cataloged in Gaia DR3 with the entry
phot_variable_flag set to VARIABLE; full light curves are available through
the Gaia Datalink Service (Cánovas & de Bruijne, 2022), which we accessed
using astroquery.gaia (Ginsburg et al., 2019).

In order to focus on isolated white dwarfs, we first restrict the 10.5 million
variables in DR3 to be near the white dwarf region of the Gaia color-magnitude
diagram by requiring $M_{G}>(4.5\times G_{\mathrm{BP}}-G_{\mathrm{RP}})+9.0$,
similar to the absolute magnitude selection of Hollands et al. (2018). This
excludes many white dwarfs in close binaries, such as CVs (Pala et al., 2020)
and post-common-envelope (WD+dM) binaries.

We then cross-match this down-selected sample with the Gaia DR3 catalog of
candidate white dwarfs of Gentile Fusillo et al. (2021). This cross-match
results in a final sample of 1333 objects, 1217 of which are high-confidence
single white dwarfs (with $P_{{\mathrm{W}D}}>0.75$, see Table 1); only 42
objects have $P_{{\mathrm{W}D}}<0.3$. We expect minor contamination from our
color cuts from non-isolated white dwarfs, especially CVs with low-luminosity
donors.

We further cross-match this sample with the Montreal White Dwarf Database
(Dufour et al., 2017) and SIMBAD (Wenger et al., 2000) by matching coordinates
for each source (precessing the Gaia DR3 epoch to J2000). This cross-match was
done in order to collect as much supporting information as possible including
literature references and spectroscopic classifications. Relevant information
found in this cross match is listed in Table Measuring White Dwarf Variability
from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry.

We compare the Gaia multi-color light curves of our 1333 objects with two
other long-baseline photometric surveys. First, we use the Python package
Lightkurve (Lightkurve Collaboration et al., 2018; Saunders, 2020) to download
any 20-second- and 2-min-cadence PDCSAP light curves of our objects as seen by
the Transiting Exoplanet Survey Satellite (TESS, Ricker et al. 2015). This
provides at least one month of nearly continuous TESS data for 698 objects in
our sample, most brighter than roughly $G=17.0$ mag.

Where available, we also download light curves within a 1.4-arcsecond search
radius of our targets from Data Release 12 of the Zwicky Transient Facility
(ZTF, Bellm et al. 2019). This provides long-baseline ZTF observations for 992
objects across all magnitudes in our sample, all with declinations north of
$-20$ degrees. We also search for light curves in the south from the All-Sky
Automated Survey for SuperNovae (ASAS-SN, Shappee et al. 2014; Kochanek et al.
2017) and the Asteroid Terrestrial-impact Last Alert System (ATLAS, Tonry et
al. 2018) projects. However, any objects without TESS photometry in the south
mostly had upper limits on photometry due to their faintness, so we did not
use their light curves in our analysis here.

##  3 Period-Finding Analysis

Figure 1: Color-magnitude diagram showing our sample of 1333 high-confidence
white dwarf candidates flagged as photometrically variable in Gaia DR3 as
black stars. The larger colored symbols show the 105 objects discussed in this
manuscript which have variability periods measured from their Gaia light
curves independently; the color for each point corresponds to the
corresponding variability period. The background of this plot is a two-
dimensional histogram of white dwarfs within 200 pc matching the magnitude
distribution of the 1333 photometrically variable white dwarfs. Dashed red
lines show the expected cooling tracks of a 0.6 $M_{\odot}$ white dwarf at top
and 1.2 $M_{\odot}$ white dwarf at bottom; white dwarfs cool from the upper
left to the lower right in this diagram.

We analyze the Gaia light curves and ZTF and TESS light curves, when
available, simultaneously. All available light curves are visually inspected
for signatures of variability in both the time and frequency domain, informed
by the spectroscopic classification of the white dwarf if known.

We analyze every light curve in the frequency domain by computing Lomb-Scargle
periodograms (Astropy Collaboration et al., 2013) using astropy (Astropy
Collaboration et al., 2013, 2018, 2022). We also separate the light curves by
band-pass filters ($G$, $G_{\mathrm{BP}}$, $G_{\mathrm{RP}}$, $g$, $r$, $T$
from Gaia, ZTF, and TESS, respectively) to search for color-dependant
variability. We initially classify frequencies as significant if their
amplitude exceeds five times the mean amplitude of all frequencies in the
periodogram, a relatively conservative limit given prior sporadically sampled
datasets (Breger et al., 1993; Guidry et al., 2021). For simplicity, we use a
constant frequency step size for Gaia and ZTF data: $10^{-8}$ Hz, which
corresponds to a critical sampling of 1157 days, consistent with the length of
the typical Gaia and ZTF datasets. The step size for the TESS periodogram
frequencies is set by the inverse of the TESS light curve baseline,
oversampled by a factor of 10. All periodograms are computed to the TESS 2-min
Nyquist frequency of 4160 $\mu$Hz.

We use all available survey information in addition to our coherent period
analysis to attempt to classify as many variable candidate white dwarfs in our
sample as possible (see Figure 1 and top-line summary in Table 1). The amount
of information differs significantly from source to source. For example, only
586 of 1333 objects have a spectral type in the literature listed from either
MWDD (Dufour et al., 2017) or SIMBAD (Wenger et al., 2000). Therefore, our
classification for 86 of 105 objects in Table Measuring White Dwarf
Variability from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry listed as
“likely” is based on the limited information available and requires
spectroscopic follow-up to truly confirm the variability classification.

Most variables are categorized by their periods of variability (from
$100-1500$ s for pulsating white dwarfs, to minutes to days for spotted white
dwarfs), as well as their position in the color-magnitude diagram (e.g., CVs
are composed of a composite spectra mixing some fraction of a white dwarf,
main-sequence star, and accretion disk, and are considerably over-luminous to
an isolated white dwarf). Using the color-magnitude position along with any
periods constrained from the survey light curves allows us to suggest likely
classifications for the subset of objects in this manuscript; we will present
full classification of all 1333 objects in a future publication.

We devote our attention here to objects where at least one Gaia light curve
successfully identifies the period of variability of a candidate white dwarf.
We consider Gaia to successfully recover a period if the Gaia-$G$ periodogram
has its highest peak matching (to within 0.05 $\mu$Hz) the highest peak of an
independent ZTF and/or TESS periodogram, or an independent Gaia bandpass light
curve.

Regardless of its significance (we discuss further in Section 5), we use the
highest-amplitude of the periodogram of the available Gaia, ZTF, and TESS
datasets as an initial guess for a linear-least-squares (LLS) fit of a
sinusoid to the data using the Python package lmfit (Newville et al., 2016).
This process returns the best-fit period, amplitude, and phase of a single
sinusoid to the light curve, as well as associated uncertainties. All reported
periods in the main text of this manuscript are the LLS fits of the Gaia DR3
$G$-band photometry.

Table 1: Summary table of the full sample and a subset of Gaia-detected variable candidate white dwarfs.  | Full Sample | Gaia Period Match
---|---|---
Variable objects near white dwarfs in CMD (”Variable candWDs”) | 1333 | 105
Candidate WDs with $P_{\rm WD}>0.75$ | 1217 | 104
Variable candWDs with spectroscopic confirmation | 568 | 36
Variable candWDs that are known binaries | 91 | 8
Variable candWDs that are known pulsating WDs | 49 | 2
Variable candWDs known to have magnetic spots | 12 | 8
Variable candWDs with TESS data | 698 | 65
Variable candWDs with ZTF data | 992 | 72

In total we find 105 candidate white dwarfs which have photometric variability
periods that can be correctly measured from their Gaia DR3 light curve
independently. Of these 105 objects, 72 have data from ZTF and 65 have data
from TESS (including 32 with both ZTF and TESS data). Based on our
classification (see Section 4), we show where these 105 objects sit in the
Gaia color-magnitude diagram in Figure 1. Because binary systems and objects
with cool spots both show sinusiodal variability, we use mass and temperature
estimate fits to Gaia photometry by Gentile Fusillo et al. (2021) (listed in
Table Measuring White Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-
Epoch Photometry) to distinguish between these objects. We classify candidate
white dwarfs with an effective temperature of $>$ $31{,}000$ K or a
photometrically determined mass $<$ $0.525$ $M_{\odot}$ (which cannot have
formed as single-stars within a Hubble time) as binaries; all other
sinusoidally variable white dwarfs are classified as rotationally modulated
spots. Since not all spotted white dwarfs are strongly magnetic (e.g., Hermes
et al. 2017b), the only way to absolutely distinguish between a spot or binary
is to use follow-up spectroscopy to search for radial-velocity variability.

Previous spectroscopy exists for just 36 of our 105 targets. Our photometric
classifications lacking spectroscopic constraints will suffer some ambiguity.
For example, WD J202932.51$+$070107.70 is hotter than $31{,}000$ K and
exhibits absorption from ultra-highly excited metals, but is likely variable
due to a magnetic spot (Reindl et al., 2021). Similarly, the $>$ $100{,}000$ K
white dwarf WD J095125.94$+$530930.72 is likely spotted, based on a lack of
radial-velocity variation (Werner et al., 2019). Still, classifying as
binaries the sinusoidal variables with ${T}_{\mathrm{eff}}$ $>$ $31{,}000$ K
or ${M}_{\mathrm{WD}}<$ $0.525$ $M_{\odot}$ will be appropriate for the vast
majority of our objects.

##  4 Classified white dwarf variables

We attempt to classify the origin of the variability for the 105 candidate
variable white dwarfs where we can measure a coherent, sinusoidal variability
period from the Gaia light curves that matches a period detected in an
independent dataset. Initially we inspect the Gaia DR3 machine learning output
classifier (GaiaDR3Class), which is available for 62/105 objects. In most
cases, however, this classifier simply says WD, revealing little about the
specific nature of these objects.

We instead classify all objects based on variability period and position in
the Gaia color-magnitude diagram, informed by past white dwarf variability
studies (Hermes et al., 2017a; Reding et al., 2018). All discovery literature
on our sources is collected in Table Measuring White Dwarf Variability from
Sparsely Sampled Gaia DR3 Multi-Epoch Photometry, and our full classification
and variability information is collected in Table Measuring White Dwarf
Variability from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry. Table 1
provides a summary of the overall sample and our analyzed sub-sample
referenced in this manuscript.

###  4.1 Non-Eclipsing White Dwarf Binaries

Binary systems are often distinguishable from isolated white dwarfs because
they are an unresolved pair of stars, making them over-luminous to single star
cooling tracks, such as those shown in Figure 1. For this reason, over-
luminous objects with sinusiodal variability that have an effective
temperature exceeding $31{,}000$ K as determined by the hydrogen-rich-
atmosphere fits from Gentile Fusillo et al. (2021) or a photometrically
determined mass $<0.525$ $M_{\odot}$ are categorized as binary systems.
Objects without mass determinations from Gentile Fusillo et al. (2021) are
likely over-luminous and also classified as binaries. Typical values for
orbital periods of binary systems with a white dwarf paired with an M dwarf
have been studied by Nebot Gómez-Morán et al. (2011), where SDSS data showed
that post common envelope binaries containing a white dwarf and main sequence
star have orbital periods ranging from 1.9 hr to 103.2 hr, with an average of
approximately 10.3 hr.

We find 72 likely variable binaries in our sample, including seven eclipsing
binaries (Section 4.3), with orbital periods ranging from 0.957 hr to 29.366
hr, with a mean of approximately 8.411 hr and a standard deviation of
approximately 7.417 hr, consistent with the Nebot Gómez-Morán et al. (2011)
distribution.

Figure 2: Phase-folded light curves of three representative variable white
dwarfs from binarity, revealing orbital periods of 5.725 hr, 2.873 hr, and
2.500 hr, respectively. All folded light curves (ZTF $g$ in blue, Gaia $G$ in
green, and TESS photometry in red) are phased to the same ephemeris. ZTF $g$
and TESS data are grouped into 151 bins for each light curve. The larger
amplitudes at redder wavelengths in these systems indicates they are all
likely reflection-effect binaries of a cool main-sequence star reprocessing
flux from a nearby hot white dwarf.

Three representative examples of variable binaries are shown in Figure 2. The
first object (WD J153938.12$+$270605.84, $G$ = 16.6 mag) is a known DA+dM
system with an orbital period of $5.72120\pm 0.00087$ hr measured from the
Palomar Transient Factory (PTF, Kao et al., 2016). We measure from Gaia DR3
photometry only $P_{\mathrm{orb}}=5.7213\pm 0.0053$ hr, agreeing with the PTF
measurement to within our estimated uncertainty. The second object (WD
J041033.37$-$585203.63, $G$ = 17.6 mag) is a newly discovered binary system
with a sinusiodal pattern in both the Gaia $G$ and TESS bands with a Gaia $G$
band period of $2.87254\pm 0.00054$ hr. The higher amplitude from the redder
TESS data is indicative of flux reprocessing from a reflection-effect binary,
though no spectroscopy exists for this target. Finally, WD
J200937.02$+$165219.12 ($G$ = 16.8 mag) is also likely a new reflection-effect
binary with an orbital period of $2.49878\pm 0.00086$ hr.

The shortest-period, likely detached new binary in our sample is WD
J123955.40$+$834707.51 ($G$ = 20.0 mag), which shows significant variability
in ZTF at $0.95661\pm 0.00015$ hr that is also seen in the Gaia $G$-band light
curve at an amplitude exceeding 40%. No spectroscopy exists of this target,
which has a position in the Gaia CMD consistent with a 7020 K, 0.27
$M_{\odot}$ white dwarf, suggesting it might be a new WD+WD binary containing
at least one ELM white dwarf (e.g., Brown et al. 2022).

###  4.2 Periodicities in Known Cataclysmic Variables

There are also likely some binaries that are not detached in our sample. CVs
are a class of accreting white dwarf binaries, and are often eruptive
variables that show large brightening events from dwarf novae and other
outbursts (Szkody et al., 2020, 2021). We have not intended to search for new
CVs among the 1333 high-confidence white dwarfs, which has been the focus of
previous work on Gaia light curves using eruptions and outbursts (e.g., Gaia
Collaboration et al. 2019). However, we have identified coherent periods in
three objects classified as CVs in the literature.

WD J083843.35$-$282701.14 ($G$ = 17.6 mag) is a known CV (Halpern et al.,
2017; Rea et al., 2017) for which we find a new potential period of
variability of $16.109\pm 0.029$ hr. This period differs slightly from the
approximately 15-hr period of flux variability interpreted as the beat period
between the orbital and spin periods (Rea et al., 2017), as well as the
$14.7\pm 1.2$ hr period of X-ray modulations observed by Halpern et al.
(2017). WD J031413.25$-$223542.92 ($G$ = 18.2 mag) was studied by Warner
(1980) and Bond et al. (1979). The Gaia DR3 data show a significant
periodicity at $1.34947\pm 0.00017$ hr, which is in close agreement with both
studies.

Finally, WD J130017.86$-$325805.23 ($G$ = 20.3 mag), is a CV candidate that
has undergone at least two measured outbursts detected in CRTS (Drake et al.,
2014). We lack TESS or ZTF coverage for this faint southern object, but all
three Gaia band-passes have their highest periodogram peak at 2171.36 s (36.2
min). The amplitude of the signal exceeds 80% in all Gaia band-passes. Such
large-amplitude periodic variations are not commonly observed as spurious
signals in Gaia DR3 at such short periods (Holl et al., 2023), though we
cannot independently rule out an instrumental origin for this 36.2-min
variability. We strongly encourage follow-up of this faint southern target.

###  4.3 Eclipsing White Dwarf Binaries

Figure 3: Following the same convention as Figure 2, we show phase-folded
light curves of seven eclipsing binaries detected from their Gaia DR3 light
curves. In this figure, ZTF and Gaia data are not binned, but TESS data are
grouped into 251 bins. The first three systems are previously published
eclipsing binaries containing a white dwarf (Drake et al., 2010; Parsons et
al., 2015; Kosakowski et al., 2022). Four systems are newly discovered
eclipsing binaries containing a white dwarf, including a new 1.3-hr eclipsing
CV (WD J154008.28$-$392917.61, further detailed in Section 4.3.1 and Figure
4). With only sparse Gaia DR3 data, we do not claim to confirm binarity in WD
J154008.28$-$392917.61, but include it as an interesting candidate.

Eclipsing binaries often display near-total flux dropouts in randomly sampled
light curves (Parsons et al., 2013), as the fainter companion passes in front
of the brighter member. These eclipses should occur at exactly the same phase
in a folded light curve, manifesting as stable, repeated photometric
variability. The seven known and likely eclipsing systems are shown in Figure
3.

The top panels in Figure 3 detail three previously known eclipsing white dwarf
binaries, in order of orbital period. WD J085746.18$+$034255.35 ($G$ = 18.3
mag) is a known eclipsing WD+dM with a measured orbital period of 1.562317 hr
by the Catalina Sky Survey (CSS, Parsons et al. 2015), which is consistent
with our measurement from Gaia DR3 photometry of $1.562316(17)$ hr. This
object shows both ZTF and Gaia dropouts, notable since the Gaia DR3 light
curves have a reasonably aggressive outlier rejection (Eyer et al., 2023). WD
J132518.18$+$233808.02 ($G$ = 18.2 mag) is also a known eclipsing DA+dM binary
with an orbital period of 4.679 hr measured by CSS (Drake et al., 2010;
Parsons et al., 2015) consistent with our measurement from Gaia DR3 photometry
of $4.67901(39)$ hr. The lack of in-eclipse data from Gaia is likely related
to outlier rejection of the Gaia photometry111Gaia DR3 Documentation Section
5.1.4: Photometric Calibration. WD J003352.64$+$385529.70 ($G$ = 18.3 mag) was
identified by Kosakowski et al. (2022) to have a strong 4.86-hr signal in ZTF,
and has all the hallmarks of a WD+dM eclipsing binary, especially featuring
ZTF dropouts in both the $g$\- and $r$-bands when folded on a period of
$4.86465(31)$ hr. These dropouts align in phase space and show a decrease in
amplitude of nearly 100%.

Our analysis identifies four new candidate eclipsing binaries. Most compact is
WD J154008.28$-$392917.61, showing multiple low Gaia points when folded on the
TESS-determined period of $1.319(13)$ hr. We detail follow-up observations of
this source in Section 4.3.1 and Figure 4.

WD J130905.43$-$470852.39 ($G$ = 18.3 mag) may be an eclipsing binary, having
only Gaia light curves to analyze. When folded on a period of $3.32265(44)$
hr, the source shows dropouts in both the $G$ and $G_{\mathrm{RP}}$ bands with
small uncertainties leading us to believe that these are genuine eclipses.
Photometric fits to the Gaia CMD suggest this system has an extremely low-mass
($<$0.16 $M_{\odot}$), 11040 K white dwarf with a high probability of being a
white dwarf ($P_{\rm WD}=0.91$, Gentile Fusillo et al. 2021). With only sparse
Gaia DR3 data and possibly long transit durations, we cannot confirm this
system as eclipsing yet, but encourage further follow-up.

We are far more confident in the fidelity of the final two systems shown in
Figure 3. WD J004502.35$+$503408.46 ($G$ = 17.6 mag) is over-luminous to the
isolated white dwarf position in the Gaia CMD (suggesting binarity) and
features ZTF and Gaia dropouts suggesting an orbital period of $6.87794(72)$
hr. WD J202811.64$+$350525.08 ($G$ = 17.9 mag), is also over-luminous and
features ZTF dropouts when folded on a period of $10.3937(17)$ hr. There is
also a strong Gaia-$G$ sinusiodal pattern that aligns with the ZTF data with a
minimum in the time of transit.

####  4.3.1 Follow-Up of a New Eclipsing CV

We obtained follow-up time-series photometry and spectroscopy for our most
compact new eclipsing system (WD J154008.28$-$392917.61), located in the
southern hemisphere ($G$ = 17.3 mag).

We obtained high-speed time-series photometry using the ULTRACAM instrument
(Dhillon et al., 2007) mounted on the 3.6-meter New Technology Telescope (NTT)
telescope at the La Silla Observatory in Chile. This camera obtains
simultaneous three-channel photometry with frame-transfer detectors; we used
high-throughput Super-SDSS $u_{s}g_{s}r_{s}$ filters (Dhillon et al., 2021).
We observed WD J154008.28$-$392917.61 over two consecutive nights, analysing
here only the SDSS-$g_{s}$ data. We collected 9.0-s exposures on UT date 2023
March 16 with an average seeing of 0.8 arcsec. We collected 4.5-s exposures on
UT date 2023 Mar 17 with an average seeing of 0.7 arcsec. All ULTRACAM data
were bias-subtracted and flat-field corrected using the HiPERCAM
pipeline222https://github.com/HiPERCAM/hipercam.

We also obtained follow-up spectroscopy of this system using the Goodman
spectrograph (Clemens et al., 2004) mounted on the 4.1-meter SOAR Telescope in
Chile. We collected eleven $10$ min spectra using the 400-line grating with a
1-arcsec slit and the M1 grating setup on UT date 2023 May 24, yielding a
resolution of roughly 4.4 Å. We extracted the data using the pypeit data
reduction pipeline (Prochaska et al., 2020), and flux calibrated using the
standard star EG 274.

Figure 4: Follow up data for WD J154008.28$-$392917.61 reveals deep primary
eclipses in the two top panels. Follow-up spectroscopy (note the broken
x-axis) confirms this is a 68.365-min CV, likely descending from a previously
detached white dwarf + brown dwarf post-common-envelope binary (e.g.,
Littlefair et al. 2007).

We captured two primary eclipses with ULTRACAM, shown in the top two panels of
Figure 4. Fitting the mid-time of the eclipses with a Gaussian bounded by when
the flux decreases below $-$20%, we find that the primary eclipses occur at
BJDTDB = 2460019.8887179(17) and 2460020.8778468(11), separated by 18 cycles
of our TESS-determined main periodicity of $1.319(13)$ hr. There is
considerable out-of-transit variability, including an extended feature from a
bright spot on the white dwarf, seen in many eclipsing CVs (e.g., Savoury et
al. 2011; McAllister et al. 2019).

Our coadded spectrum in the bottom panel of Figure 4 confirms this is an
accreting white dwarf binary. Broad Balmer-line absorption from the white
dwarf is visible, along with strong emission features from accretion,
especially dominant at H$\alpha$. Our spectrum is not high-enough resolution
to attempt a radial-velocity fit. We do not observe Zeeman splitting at the
Balmer lines, though our limits are weak given the strong emission in the line
cores.

A purported orbital period of 68.365 min is well below the CV period minimum
of roughly 80 min, after which convective donor stars expand on further mass
loss (Patterson, 1984; Knigge et al., 2011; Kalomeni et al., 2016; McAllister
et al., 2019). However, the full photometric phase coverage from TESS shown in
Figure 3 reveals this is the correct period of recurrent variability. This
makes WD J154008.28$-$392917.61 among the shortest-period CVs known, similar
to the 66.61-min CV SDSS J150722.30$+$523039.8 (Littlefair et al., 2007).
These ultracompact CVs are likely descended from a previously detached white
dwarf + brown dwarf binary. It is also possible the system descended from a
low-metallicity, significantly evolved donor (Uthas et al., 2011).

###  4.4 Magnetic Spotted White Dwarfs

Spotted white dwarfs are difficult to distinguish from reflection-effect
binaries like those discussed in Section 4.1. When spectroscopy is not
available, we classify all objects with apparently mono-periodic variability
and photometrically determined (Gentile Fusillo et al., 2021) masses $>$0.525
$M_{\odot}$ and temperatures $<$$31{,}000$ K as isolated white dwarfs with
rotational modulation from magnetic spots.

Figure 5: Following the same convention as Figure 2, we show phase-folded
light curves of three magnetic spotted white dwarfs. ZTF-$g$ and TESS data are
grouped into 151 phase bins, whereas the Gaia data are not binned.

The period of the spot-induced modulations corresponds to the rotational
period at the star’s surface (e.g., Brinkworth et al. 2013; Kilic et al. 2015;
Hoard et al. 2018). We recover the periods of eight previously known spotted
white dwarfs from the Gaia DR3 light curves independently, and identify 17 new
likely spotted white dwarfs. The majority of the newly identified spotted
white dwarfs (12/17) have effective temperatures between $6500-10{,}000$ K,
placing them inside the range of known DAHe strongly magnetic white dwarfs
with Balmer-line emission (Greenstein & McCarthy, 1985; Reding et al., 2020;
Gänsicke et al., 2020; Walters et al., 2021; Reding et al., 2023; Manser et
al., 2023), motivating future time-resolved spectroscopic follow-up. Our
sample contains several known DAHe (see Table Measuring White Dwarf
Variability from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry). WD
J083531.17$+$533230.91 ($G$ = 18.2 mag) is the only other spectroscopically
confirmed strongly magnetic white dwarf in our sample, and appears to have a
2.16-hr period.

Examples of three spotted white dwarfs are shown in Figure 5. The top object
WD J052026.35$+$381240.87 ($G$ = 15.4) is a spectroscopically confirmed white
dwarf from LAMOST claimed to be a DBA (Kong et al., 2019) but is likely a DAH;
Gaia DR3 photometry shows it is likely rotating at $6.7856\pm 0.0046$ hr. The
second object (WD J195629.23$-$010232.67, $G$ = 13.6 mag) has been known to be
spotted (the white dwarf is highly magnetic with a complex field structure,
shown in Maxted et al. 2000). We observe clear sinusoidal variability in the
$G$ data with a period of $34.898\pm 0.074$ hr, in close agreement with the
literature value from Brinkworth et al. (2005). The final object is WD
J202932.51$+$070107.70 ($G$ = 16.6 mag), a known DO white dwarf (Dreizler et
al., 1995). This white dwarf was observed to have a ZTF $g$ photometric
variability period of $6.97882\pm 0.00012$ hr from Reindl et al. (2021), which
is close to our LLS fit to the Gaia-$G$ data of $6.9572\pm 0.0022$ hr. It is
likely that the ZTF or Gaia data has selected an incorrect alias due to gaps
in the data.

Figure 6: Lomb-Scargle periodograms showing two rapidly rotating spotted white
dwarfs recovered in sparsely sampled Gaia DR3 light curves. At top is WD
J031715.85$-$853225.56 (Ferrario et al., 1997); the 725 s variability period
has a $<$0.1% false-alarm probability in the Gaia $G$ light curve. At bottom
is WD J125230.93$-$023417.72, which has a 0.1% false-alarm probability, with
the highest peak in the periodogram at exactly the same period, within the
uncertainties, as the known variability discovered by Reding et al. (2020).

Figure 6 demonstrates Gaia DR3 light curves are able to recover the
variability in two of the shortest-period spotted white dwarfs known. The top
panel details WD J031715.85$-$853225.56 ($G$ = 14.8 mag), a well-studied,
rapidly rotating, high-field magnetic white dwarf (Ferrario et al., 1997). The
Gaia $G$ peak occurs at the same period as the TESS data, to within the
uncertainties of the LLS fits. The light curve from Gaia is sparsely sampled,
with visits separated by $32.5\pm 8.8$ d, where 8.8 d is the standard
deviation of the time between visits. False-alarm probability lines for
periodograms are estimated by holding the time sampling the same but randomly
shuffling the fluxes with replacement 10,000 times, in an attempt to quantify
the probability that the amplitude of a peak can be generated by pure noise
(e.g., Greiss et al. 2014; VanderPlas 2018). For WD J031715.85$-$853225.56 at
the top of Figure 6, none of our bootstrapped periodograms have a peak as high
as the observed Gaia $G$ periodogram, yielding a false-alarm probability of
$<$0.1%.

In the bottom panel of Figure 6 we show Gaia and TESS peaks measured for the
strongly magnetic, emission-line (DAHe) white dwarf WD J125230.93$-$023417.72
($G$ = 17.5 mag, Reding et al. 2020). While not statistically significant, the
highest peak in the Gaia periodogram occurs at the known dominant period of
317.278 s (which is the first harmonic the 634.56-s rotation period, see
Farihi et al. 2023). We bootstrap a false-alarm probability of 0.1% for this
peak.

Aside from these two previously known spotted white dwarfs, we recover the
literature periods for six other known spots. Two are known emission-line DAs:
the 36.3-min DAHe system WD J003512.88$-$122508.84 (Reding et al., 2023) and
the 2.29-hr, non-magnetic DAe white dwarf WD J041246.84$+$754942.26 (Tremblay
et al., 2020; Elms et al., 2023). We recover two cooler white dwarfs with
spots: the 0.72-hr WD J053432.93$+$770757.40 (Guidry et al., 2021) and the
1.44-d WD J195629.23$-$010232.67 shown in Figure 5. We also recover two much
hotter spotted stars discussed at the end of Section 3, the 6.98-hr WD
J202932.51$+$070107.70 (Reindl et al., 2021) and the 3.45-d WD
J095125.94$+$530930.72 (Werner et al., 2019).

The shortest-period new spotted white dwarf in our sample is WD
J115033.35$-$063618.07 ($G$ = 16.4 mag). This spotted white dwarf features a
highest peak in the $G$ light curve matching the TESS-significant peak at
$884.0679\pm 0.0094$ s. Spectropolarimetry puts a 3$\sigma$ upper limit on the
magnetic field of LP 673-41 of $<$6 kG (Kawka & Vennes, 2012), raising
questions about the origin of the spot on this 8600 K white dwarf. The longest
period spot appears on WD J124740.10$+$303007.41 ($G$ = 17.9 mag), with a
highest peak in the periodogram at 9.487 d in both its Gaia and ZTF light
curves.

###  4.5 Pulsating White Dwarfs

Figure 7: Panels of periodograms for the four objects we classify as Gaia-
detected pulsating white dwarfs, all with periods $<$400 s. The photometric
bands in these figures are $G$, $G_{\mathrm{BP}}$, $G_{\mathrm{RP}}$, $g$,
$r$, $T$ (Gaia G, BP, and RP bands, ZTF g and r bands, and the TESS photometry
band, respectively). A bootstrapped 99.9% confidence lines is shown as a
horizontal dashed line in gray (see description in Section 4.4). The false-
alarm probabilities of all four Gaia peaks are all between 2.5% and 28.9% (see
Table Measuring White Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-
Epoch Photometry).

Pulsating white dwarfs are variable due to non-radial pulsations, with periods
typically ranging from $100-1500$ s, amplitudes up to several percent, and
usually multiple, non-harmonically related periods present at the same time
(Fontaine & Brassard, 2008; Winget & Kepler, 2008b). DA white dwarfs are
unstable to pulsations in a narrow temperature range between roughly
$13{,}500-10{,}500$ K (Hermes et al., 2017c). These hydrogen-atmosphere
pulsators are commonly known as ZZ Cetis and DAVs.

From Gaia DR3 photometry alone we are able to independently identify the
periods for two new candidate pulsating white dwarfs and confirm the periods
of two known DAVs. All objects lie within the empirical DAV instability strip
in the Gaia color-magnitude diagram (Figure 1), and their Lomb-Scargle
periodograms are shown in Figure 7. As with our spotted white dwarfs in Figure
5, we bootstrap false-alarm probabilities to assess the significance of a peak
in the periodogram and quantify the likelihood a peak cannot arise from noise
alone. The significance lines in Figure 7 are the 99.9% confidence line
($<$0.1% false alarm); false-alarm probabilities for all objects in this
manuscript are listed in Table Measuring White Dwarf Variability from Sparsely
Sampled Gaia DR3 Multi-Epoch Photometry. While none of our pulsating white
dwarfs have formally significant peaks, the chance that the highest peak in
the periodogram exactly matches significant peaks in an independent ZTF or
TESS dataset is exceptionally low; our periodograms all have step sizes of
0.01 $\mu$Hz and run beyond 4000 $\mu$Hz, giving hundreds of thousands of
trial frequencies. In three of the four cases in Figure 7, the false-alarm
probability is $<$10%.

We find WD J120650.89 $-$380549.23 ($G$ = 15.7 mag) is a new pulsating WD with
a pulsation period at $259.9127\pm 0.0013$ s in $G$ with a 8.1% false-alarm
probability that is also significantly detected in TESS. WD
J215823.88-585353.81 ($G$ = 15.8 mag) is a known DAV with multiple detected
modes from rotational splittings revealed by TESS at 310.27 s, 309.79 s, and
309.31 s (Romero et al., 2022). The highest peak in the $G_{\mathrm{RP}}$
periodogram is consistent with this pulsational variability, at a period of
$310.0049\pm 0.0021$ s, though this peak has a marginal 28.9% false-alarm
probability. WD J082924.77$-$163337.25 ($G$ = 17.6 mag) was identified as a
variable white dwarf in Guidry et al. (2021). We detect variability consistent
with pulsations in both the Gaia-$G$ and ZTF-$g$ light curves at $359.0045\pm
0.0025$ s, with just a 2.5% false-alarm probability. Finally, WD
J195227.88$+$250929.18 ($G$ = 15.1 mag), is a known DAV with a dominant
pulsation period of 256.2 s (Kepler, 1984; Fontaine et al., 1980). Our
analysis agrees closely with a peak in $G_{\mathrm{BP}}$ at $255.999\pm 0.001$
s and a 3.7% false-alarm probability of matching peaks in ZTF and TESS.

The four white dwarfs with likely pulsations detected in their Gaia light
curves all have periods $<$400 s; longer-period modes are likely unstable over
long baselines (Hermes et al., 2017c), suggesting longer-period modes will be
hard to detect from Gaia data independently. However, pulsating white dwarfs
appear to be the most numerous white dwarfs flagged as variable in Gaia DR3.
There is an overdensity of points in Figure 1 near the DAV instability strip
relative to the 200-pc sample of white dwarfs in the background. In fact, of
the 883 candidate white dwarfs that are flagged as photometrically variable in
Gaia DR3 with $P_{\mathrm{W}D}>0.98$ and masses $>$0.45 $M_{\odot}$ from
Gentile Fusillo et al. (2021), nearly half (422) have effective temperatures
near the DAV instability strip boundaries
($13{,}500>$${T}_{\mathrm{eff}}$$>10{,}500$ K). Literature searches of this
sample reveal at least 50 are already-known DAVs, and at least 120 that can be
photometrically confirmed with TESS, ZTF or ASAS-SN data; this analysis will
be presented in a future publication.

##  5 Gaia-Detected Periods

We use Gaia DR3 epoch photometry, which includes photometric time series data
in the $G$-, $G_{\mathrm{BP}}$-, and $G_{\mathrm{RP}}$\- bands (Eyer et al.,
2023). Each time-series data point is a so-called field-of-view transit, after
an object has passed through nine consecutive CCD observations, each separated
by 4.85 s (Roelens et al., 2018). As the Gaia spacecraft spins, objects will
then be re-observed at a cadence separated by 1 hr 46 min (Roelens et al.,
2017). The time sampling after this revisit is considerably longer, and
different for each source, set by the Gaia scanning law (e.g., Boubert et al.
2021).

Figure 8: Top left histogram shows the average time between Gaia DR3
observations (ignoring the 1 hr 46 min revisit) for the full sample of 1333
candidate white dwarfs flagged as variable in gray, inset in red by the 105
candidate white dwarfs in this manuscript where their variability period can
be determined by Gaia independently. The top right panel shows the number of
points in each $G$ light curve, and the bottom left panel shows the $G$
magnitude distribution of both samples. The bottom right panel shows the
distribution of the 105 periods for objects detected by Gaia independently
(note that the x-axis is log scale). Although we are slightly more sensitive
to objects with more frequent visits, our sample of 105 sources covers most of
this parameter space.

We analyze the revisit cadence of these observations by creating a histogram
of the average time between each observation, shown in Figure 8. We ignore the
revisit timescale of 1 hr 46 min (set by the 6-hr spin period of Gaia, as
discussed in de Bruijne 2012) by excluding time between observations of less
than 0.3 days, and find an average time of $49.7\pm 12.5$ d between
observations for the full sample of 1333 objects (the uncertainty is set by
the standard deviation of these revisit times). Of the 105 objects where we
can measure variability from the Gaia light curves independently, the average
revisit time is $44.2\pm 10.3$ d. Our subset of 105 objects has slightly less
time between observations, only a few more Gaia-G data points (with an average
number of points of $49\pm 17$ compared to $41\pm 14$ for the full sample),
and is slightly brighter (with an average magnitude of $G=17.0\pm 1.2$ mag
compared to $G=17.2\pm 1.6$ mag for the full sample). The distributions in
Figure 8 show we are not heavily biased towards objects with frequent revisits
set by the Gaia scanning law. The average and standard deviation in the
revisit times between FoV transits for each object is included in Table
Measuring White Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-Epoch
Photometry. Among the 72 of 105 objects with ZTF data, the average object has
393 ZTF visits, which is completely consistent with the typical sky coverage
of the average fields in ZTF DR12.

We also analyze short-period variability in the Gaia DR3 light curves, which
is measured as the object moves from one CCD to the next every 4.85 s (e.g.,
Roelens et al. 2018). Included in DR3 are per-CCD least-squares fits listed as
“Frequency” for objects flagged as vari_short_timescale, for select objects
with candidate variability periods shorter than 0.5 d. The inverse of the
vari_short_timescale frequency is listed in Table Measuring White Dwarf
Variability from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry as $P_{\rm
G,S}$, and we check each period generated by our LLS fit ($P_{\rm G,DR3}$ in
Table Measuring White Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-
Epoch Photometry) against $P_{\rm G,S}$. In our final 105 object sample, 65
objects are flagged in Gaia DR3 as short-timescale sources, and 55 of these 65
(85%) have $P_{\rm G,S}$ that matches $P_{\rm G,DR3}$ to within 3% (after
which the agreement is never better than 22%).

We compare the Gaia DR3 short-timescale analysis against our LLS fits by
object type. We find that of our 72 binary objects, 48 of 53 (91%) with
vari_short_timescale data have $P_{\rm G,S}$ that matches our determinations
of $P_{\rm G,DR3}$, and of the spotted white dwarfs, 5 of 7 with short-
timescale analysis match. For all variable types, the Gaia DR3 short-timescale
analysis returns 55/60 (92%) matches for objects with vari_short_timescale
between 0.278 and 2.78 hours, and routinely does poorly for periods longer
than 3 hr.

We also attempt to assess the reliability of the Gaia variability identifier
(Eyer et al., 2023). Gaia uses a machine learning algorithm trained on non-
variable objects and then tested against training sets (built from various
published catalogues of variable stars) to confirm how effectively this
algorithm can identify variable objects. Objects are categorized as variable
when there is a large value for the ratio of the difference in magnitude from
the average for that object to the interquartile range of the magnitude. These
objects are then passed through one of two paths in the machine learning
process to be sorted into a specific Gaia “class,” discussed in depth in
Rimoldini et al. (2023). This Gaia class is listed in Table Measuring White
Dwarf Variability from Sparsely Sampled Gaia DR3 Multi-Epoch Photometry.

We find that this “class” is not generally useful, as most are simply “WD.”
There is one case where this class correctly identifies a known CV (WD
J130017.86$-$325805.23). The Gaia “class” also marks two objects as “S” or
stars with short-timescale variability: WD J083843.35$-$282701.14 (a known CV
with $P_{\rm G,S}$ that matches $P_{\rm G,DR3}$ at $16.109\pm 0.029$ hr) and
WD J233923.79$-$485350.19 (a likely new binary system with $P_{\rm G,S}$ that
matches $P_{\rm G,DR3}$ at $2.52962\pm 0.00075$ hr). The new eclipsing CV WD
J154008.28$-$392917.61 also has a Gaia “class” of CV.

Finally, we note that Gaia epoch photometry may contain spurious periodicities
due to scan-angle-dependent signals, especially in marginally resolved, fixed-
orientation pairs of stars separated by $<$0.5 arcsec (Holl et al., 2023).
Although previous work has only explored signals up to 10 days, and most
signals determined here are below that, we investigate the likelihood that any
of our detections are spurious.

All 1333 white dwarf candidates in our sample have information in the
vari_spurious_signals table from Holl et al. (2023), including important
metrics that can reveal close binarity, the Spearman rank correlation
coefficient with corrected flux excess factor ($r_{\rm exf,G}$) and the Image
Parameter Determination model ($r_{\rm ipd,G}$). Only three white dwarfs have
both $r_{\rm exf,G}$ and $r_{\rm ipd,G}$ values $>$0.8 (WD
J020426.03$+$571026.62, WD J031047.57$-$100153.85, and WD
J100643.74$-$221757.86), none of which are included in our subset of 105 white
dwarfs with variability measured independently from Gaia. In our subset of 105
objects, only one has $r_{\rm ipd,G}>0.6$ and that is WD
J003512.88$-$122508.84, which has confirmed variability from TESS (Reding et
al., 2023). We conclude that contamination from spurious Gaia scanning-law-
dependent periods is unlikely in our sample of white dwarfs.

##  6 Discussion & Conclusions

We analyze 105 white dwarf candidates for which Gaia is capable of detecting
accurate periods from DR3 photometry. These periods of variability range from
9.5 d to as short as 256.2 s (roughly 4 min), including seven objects with
periods shorter than 1000 s. We obtained this result by comparing Gaia multi-
band photometry to data from ZTF and TESS to identify significant periods
within the Gaia data. Analysis of the Gaia photometry resulted in the
discovery of new pulsating, spotted and binary white dwarfs. This includes a
new 68.4-min eclipsing cataclysmic variable, which has a period well below the
CV period minimum of roughly 80 min (Knigge et al., 2011) and is one of the
shortest-period CVs known.

Our overall analysis demonstrates that Gaia epoch photometry is precise enough
to detect short-term, low-amplitude periods even when observations are
sparsely sampled. The absolute median amplitude of the photometric variability
we confirm from Gaia independently is $1.4\%$, with an average period of
roughly 12 hr. This is notable compared to the distribution of time between
observations, which is on average roughly 44 d. We find that overall, the 105
variables that are significant in Gaia are slightly brighter and sampled more
often than the full sample of 1333 objects, but the distributions of
magnitudes or number of points are not significantly biased in either
parameter space, as shown in Figure 8.

The likelihood that the highest peak in two independent periodograms match is
small, given that there are more than $10^{5}$ frequency elements in each
periodogram. This is the basis for which we claim Gaia has detected a
periodicity. Still, we have bootstrapped estimates that a peak in the
periodogram can be caused by noise alone and find that 33/105 objects have
significant peaks in their Gaia light curves, with a $<$0.1% false-alarm
probability. Nearly half the sample, 50/105, have peaks with a false alarm
$<$1%. Only three have $>$35%, but all 105 have Gaia peaks with a $<$41%
false-alarm probability (Table Measuring White Dwarf Variability from Sparsely
Sampled Gaia DR3 Multi-Epoch Photometry details this value for all objects in
our sample). Our work provides an empirically determined set of cutoffs for
which variability in a Gaia DR3 light curve is likely to be genuine, and it
also represents a useful value for future analysis of sparsely sampled, high-
precision photometry from large surveys like the Vera C. Rubin Observatory and
its Legacy Survey of Space and Time (LSST; Ivezić et al. 2019), as well as the
Nancy Grace Roman Space Telescope (Akeson et al., 2019).

Previous spectroscopy exists for only 36 of the 105 objects discussed in this
paper, so follow up is encouraged for most of these sources. There are many
objects of interest that would expand sample sizes of rare object types. Some
notable examples include WD J123955.40$+$834707.51 ($G$ = 20.0 mag), which may
be a new WD+WD binary containing an ELM white dwarf, and WD
J130017.86$-$325805.23 ($G$ = 20.3 mag) which is a candidate CV with recorded
outbursts (Drake et al., 2014) but shows a dominant photometric period of 36.2
min closer to the orbital period of AM CVn binaries (see Section 4.1). There
are also multiple candidate eclipsing binaries discussed in Section 4.3.
Finally, one of the shortest-period new spotted white dwarfs we discovered
here (WD J115033.35$-$063618.07) appears to have an 884.73-s spin period but a
$<$6 kG magnetic field, raising questions about the origin of its fast
rotation (see Section 4.4).

As Gaia continues to scan the sky, the methods discussed in this paper provide
a foundation for analyzing short-period variables within even longer-baseline
data. Verifying that Gaia data independently can be used to detect short
periods will allow future work on sources with no additional spectroscopic or
photometric information. Increasing the numbers of rare variable stellar
remnants, especially those in short-period binaries or with magnetic spots,
will help constrain their space density and formation channels.

##  7 acknowledgements

The authors thank the anonymous referee for a very useful report, as well as
fruitful discussions with Stu Littlefair. Support for this work was in part
provided by NASA TESS Cycle 2 Grant 80NSSC20K0592 and Cycle 4 grant
80NSSC22K0737, as well as the National Science Foundation under grant No. NSF
PHY-1748958, as portions of this project were completed at the KITP Program
“White Dwarfs as Probes of the Evolution of Planets, Stars, the Milky Way and
the Expanding Universe.”

The authors acknowledge the European Southern Observatory program
110.23UU.001, as well as the Transiting Exoplanet Survey Satellite (TESS), the
Zwicky Transiting Facility (ZTF), the All-Sky Automated Survey for Supernovae
(ASAS-SN), and the Asteroid Terrestrial-impact Last Alert System (ATLAS) for
the public release of all-sky photometry data for many of these objects. This
work has also made use of data from the European Space Agency (ESA) mission
Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing
and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement.

This research is also based on observations obtained at the Southern
Astrophysical Research (SOAR) telescope, which is a joint project of the
Ministério da Ciência, Tecnologia e Inovações (MCTI/LNA) do Brasil, the US
National Science Foundation’s NOIRLab, the University of North Carolina at
Chapel Hill (UNC), and Michigan State University (MSU).

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=16mm

Table 2: Literature information for the 105 white dwarfs in this study with
significant variability measured from their Gaia DR3 light curve.

Class | Gaia Source ID | WD J Name† | RA | DEC | $G$ |  $P_{\rm WD}$† |  ${T}_{\mathrm{eff}}$† | Mass† | Sp. Type | Dist. | Class‡ | Score‡ |  $N_{\rm G}$‡ |  $N_{\rm g}$∗∗ | Skew‡ | IQR‡ |  $N_{\rm G,S}$∗ | Abbe∗ |  $P_{\rm G,S}$∗ | $P_{\rm lit}$ | Ref.
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
(This Work) | (DR3) |  | (J2016) | (J2016) | [mag] |  | [K] | [$M_{\odot}$] |  | [pc] |  |  |  |  | ($G$) | ($G$) |  |  | [hr] | [hr] |
Likely Binary | 2780903539324180736 | WD J003213.13+160434.78 | 8.054739 | 16.076395 | 15.7 | 0.982 |  |  | DO | 415.3 | WD | 0.6 | 50 | 68.0 | 0.755 | 0.036 | 50.0 | 0.836 | 21.7869583 |  | 1
Likely Binary | 2317319612801004416 | WD J003449.86-312952.69 | 8.707866 | -31.497956 | 16.1 | 0.882 | 25410.0 | 0.24 | DA | 431.1 |  |  | 39 |  | -0.416 | 0.133 | 39.0 | 0.822 | 2.3167499 |  | 2
Likely Binary | 522432163970498048 | WD J011053.06+604831.03 | 17.721109 | 60.808565 | 17.0 | 0.949 | 14770.0 | 0.2 |  | 301.7 |  |  | 58 | 491.0 | -0.088 | 0.068 | 58.0 | 0.872 | 8.3619614 |  |
Likely Binary | 323342459647016448 | WD J012828.99+385436.63 | 22.12078 | 38.910093 | 15.9 | 0.998 | 38310.0 | 0.54 | DA | 236.1 | WD | 0.651 | 30 | 375.0 | -0.396 | 0.025 |  |  |  |  | 3
Likely Binary | 2478893842934875136 | WD J013148.02-055900.14 | 22.950116 | -5.983399 | 17.3 | 0.939 | 96630.0 | 0.63 |  | 930.9 | WD | 0.465 | 44 | 329.0 | -0.49 | 0.041 |  |  |  |  |
Likely Binary | 459237630076876672 | WD J022704.24+591502.04 | 36.768226 | 59.25064 | 15.9 | 0.988 | 7360.0 | 0.51 | DA | 37.7 | WD | 0.52 | 48 | 420.0 | 0.282 | 0.029 |  |  |  |  | 4
Likely Binary | 4846154678323893248 | WD J032205.10-472106.46 | 50.521313 | -47.351787 | 17.3 | 0.978 |  |  |  | 970.5 | WD | 0.501 | 48 |  | 0.465 | 0.121 |  |  |  |  |
Likely Binary | 117770030481927936 | WD J032803.02+265151.65 | 52.012578 | 26.864324 | 18.2 | 0.98 |  |  |  | 656.2 | WD | 1.0 | 27 | 426.0 | -0.095 | 0.16 |  |  |  |  |
Likely Binary | 235184643828418688 | WD J032902.63+390340.87 | 52.260969 | 39.061346 | 18.6 | 0.973 |  |  |  | 876.2 | WD | 0.5 | 41 | 251.0 | -0.841 | 0.082 | 42.0 | 0.984 | 4.0387314 |  |
Likely Binary | 5090605830056251776 | WD J035814.52-213813.74 | 59.560498 | -21.637194 | 17.8 | 0.938 | 24810.0 | 0.24 |  | 802.3 |  |  | 76 | 242.0 | -0.302 | 0.147 | 77.0 | 0.924 | 1.7951253 |  |
Likely Binary | 4681729620697295360 | WD J041033.37-585203.63 | 62.639044 | -58.867634 | 17.6 | 0.94 | 15430.0 | 0.13 |  | 659.0 |  |  | 39 |  | -0.386 | 0.175 | 39.0 | 0.902 | 2.8736527 |  |
Likely Binary | 3204352783173513728 | WD J043103.75-041702.63 | 67.765647 | -4.284043 | 17.9 | 0.854 | 28220.0 | 0.24 |  | 1021.7 |  |  | 34 | 68.0 | 3.032 | 0.171 | 34.0 | 0.911 | 2.432582 |  |
Likely Binary | 3230486971974872192 | WD J043832.74+003117.01 | 69.636517 | 0.521344 | 17.5 | 0.981 | 94280.0 | 0.75 |  | 635.9 | WD | 0.437 | 53 | 570.0 | -0.394 | 0.037 |  |  |  |  |
Likely Binary | 2974680502235811712 | WD J050433.01-213007.93 | 76.137575 | -21.502202 | 18.1 | 0.959 |  |  |  | 1208.7 | WD | 0.252 | 51 | 171.0 | -0.096 | 0.107 | 53.0 | 0.941 | 15.0267735 |  |
Likely Binary | 3341182435406679424 | WD J053632.07+123128.65 | 84.133666 | 12.524682 | 16.4 | 0.979 | 19510.0 | 0.25 |  | 291.4 |  |  | 48 | 317.0 | -0.347 | 0.141 | 50.0 | 0.906 | 3.8008657 |  |
Likely Binary | 2941800362921100928 | WD J061234.26-191111.75 | 93.142763 | -19.18675 | 18.0 | 0.984 | 23960.0 | 0.33 |  | 640.1 | WD | 0.5 | 48 | 188.0 | -0.096 | 0.115 |  |  |  | 2.2251 | 5
Likely Binary | 5549322119820590208 | WD J061815.27-512305.52 | 94.563662 | -51.384787 | 15.9 | 0.998 | 30420.0 | 0.5 |  | 194.3 | WD | 0.639 | 36 |  | 1.031 | 0.024 |  |  |  |  |
Likely Binary | 3125897813875563904 | WD J064316.01+013012.78 | 100.816765 | 1.503518 | 15.8 | 0.996 | 93720.0 | 0.83 | DO | 251.9 | WD | 0.318 | 24 | 300.0 | -0.773 | 0.06 | 24.0 | 0.817 | 6.0384346 |  | 6
Likely Binary | 5575611644702244992 | WD J064753.57-403756.16 | 101.973208 | -40.632249 | 17.7 | 0.987 |  |  |  | 862.7 |  |  | 43 |  | -0.232 | 0.15 | 44.0 | 0.831 | 7.0115164 |  |
Likely Binary | 5286227228018008576 | WD J064802.27-634629.90 | 102.009505 | -63.774891 | 17.5 | 0.917 | 22690.0 | 0.23 |  | 691.9 |  |  | 45 |  | -0.084 | 0.136 | 45.0 | 0.917 | 3.7701112 |  |
Likely Binary | 1099005032089977984 | WD J070647.52+613350.31 | 106.698306 | 61.563912 | 13.5 | 0.984 |  |  |  | 158.0 |  |  | 64 | 915.0 | -0.414 | 0.02 | 64.0 | 0.837 | 8.9701518 |  |
Likely Binary | 989059981050056320 | WD J072146.74+564408.41 | 110.444764 | 56.735656 | 18.8 | 0.983 | 13400.0 | 0.23 |  | 651.7 |  |  | 32 | 41.0 | 0.164 | 0.093 | 32.0 | 0.947 | 2.7708059 |  |
Likely Binary | 1085903148454238208 | WD J073121.39+595737.01 | 112.839236 | 59.960251 | 16.1 | 0.988 |  |  | DO | 424.5 | WD | 0.273 | 43 | 550.0 | -0.417 | 0.088 | 44.0 | 0.937 | 5.3138963 |  | 7
Likely Binary | 5615892360564187008 | WD J074316.04-224656.86 | 115.816834 | -22.782453 | 19.0 | 0.831 | 38940.0 | 0.39 |  | 1534.0 |  |  | 69 | 139.0 | -0.59 | 0.196 | 71.0 | 0.919 | 8.289411 |  |
Likely Binary | 5216924803961432192 | WD J090240.78-742331.37 | 135.669175 | -74.391845 | 17.2 | 0.881 | 10270.0 | 0.15 |  | 278.8 | WD | 0.559 | 38 |  | -0.111 | 0.036 |  |  |  |  |
Likely Binary | 3842377248804727168 | WD J091748.20+001041.72 | 139.450873 | 0.178195 | 17.4 | 0.998 | 34570.0 | 0.56 |  | 406.2 | WD | 0.606 | 36 | 237.0 | 0.155 | 0.069 |  |  |  |  |
Likely Binary | 5437786045395659520 | WD J093611.12-340059.16 | 144.046282 | -34.016386 | 17.1 | 0.929 | 49990.0 | 0.41 |  | 649.3 |  |  | 96 |  | -0.357 | 0.042 | 97.0 | 0.92 | 20.8380364 |  |
Likely Binary | 3834895969825628800 | WD J100645.76+003204.48 | 151.690524 | 0.534619 | 16.7 | 0.98 | 15890.0 | 0.21 | DA | 336.9 | CV | 0.382 | 26 | 238.0 | -0.622 | 0.083 |  |  |  |  | 8
Likely Binary | 5456112705203412352 | WD J105228.94-295308.20 | 163.120558 | -29.885628 | 17.3 | 0.996 | 92120.0 | 0.83 |  | 510.5 |  |  | 49 |  | -0.548 | 0.049 | 49.0 | 0.923 | 8.2170957 |  |
Likely Binary | 5390573840730111872 | WD J110318.00-401544.50 | 165.825071 | -40.262433 | 15.1 | 0.982 |  |  |  | 310.3 |  |  | 42 |  | -0.099 | 0.182 | 42.0 | 0.932 | 0.8834878 |  |
Likely Binary | 5383832838018956032 | WD J112355.21-400614.63 | 170.979607 | -40.103915 | 14.9 | 0.979 |  |  |  | 319.2 |  |  | 50 |  | -0.584 | 0.045 | 50.0 | 0.847 | 16.9484344 |  |
Likely Binary | 5378958286359002624 | WD J113832.79-435817.73 | 174.636565 | -43.971582 | 16.5 | 0.981 |  |  |  | 611.8 | WD | 0.552 | 61 |  | -0.176 | 0.076 | 61.0 | 0.893 | 13.2968409 |  |
Likely Binary | 6076202559948311040 | WD J121622.61-545907.30 | 184.094154 | -54.98536 | 18.7 | 0.956 | 17070.0 | 0.24 |  | 748.2 |  |  | 66 |  | -0.378 | 0.406 | 67.0 | 0.888 | 2.5750134 |  |
Likely Binary | 1726297924930902400 | WD J123955.40+834707.51 | 189.979829 | 83.785334 | 19.8 | 0.708 | 7020.0 | 0.27 |  | 333.9 | CV | 0.716 | 27 | 32.0 | 0.544 | 0.796 |  |  |  | 1.91383 | 9
Likely Binary | 3509435507186636288 | WD J125005.11-203632.29 | 192.521286 | -20.609046 | 17.4 | 0.992 |  |  |  | 699.1 | WD | 0.577 | 29 | 222.0 | -0.571 | 0.129 |  |  |  |  |
Likely Binary | 3721943209023827456 | WD J135523.92+085645.42 | 208.849658 | 8.945966 | 17.5 | 0.979 | 26600.0 | 0.32 | DA | 594.8 |  |  | 42 | 402.0 | -0.37 | 0.054 | 42.0 | 0.905 | 2.7448209 | 2.74511 | 10
Likely Binary | 1671880139535534208 | WD J140330.89+671255.16 | 210.878613 | 67.215384 | 18.7 | 0.953 | 16210.0 | 0.17 |  | 1042.8 |  |  | 43 | 615.0 | -0.334 | 0.1 | 43.0 | 0.906 | 3.447414 |  |
Likely Binary | 1286055427676135808 | WD J144007.60+315413.02 | 220.031656 | 31.903652 | 17.3 | 0.992 |  |  |  | 670.6 |  |  | 96 | 692.0 | -0.477 | 0.055 | 97.0 | 0.978 | 23.2727485 |  |
Likely Binary | 5773385817714683776 | WD J145623.30-793654.99 | 224.096814 | -79.615325 | 17.5 | 0.926 |  |  |  | 934.8 |  |  | 58 |  | -0.314 | 0.155 | 58.0 | 0.92 | 4.8197997 |  |
Likely Binary | 5873013322220969984 | WD J145817.91-651024.94 | 224.574476 | -65.173657 | 17.7 | 0.957 | 38640.0 | 0.42 |  | 635.7 |  |  | 88 |  | -0.317 | 0.074 | 89.0 | 0.898 | 3.679142 |  |
Likely Binary | 1728880879608190592 | WD J153028.82+874848.48 | 232.613053 | 87.813576 | 15.6 | 0.99 |  |  | DA | 324.5 | WD | 0.605 | 48 |  | -0.306 | 0.056 |  |  |  |  | 11
Likely Binary | 1272870835853944704 | WD J154012.07+290828.96 | 235.050333 | 29.141305 | 18.9 | 0.945 | 22570.0 | 0.25 | DAH | 1132.5 |  |  | 74 | 446.0 | -0.019 | 0.226 | 74.0 | 0.848 | 2.3768165 |  | 12
Likely Binary | 2121629147470776704 | WD J181824.35+465721.46 | 274.601506 | 46.95593 | 17.5 | 0.937 | 18100.0 | 0.18 |  | 640.1 |  |  | 37 | 1008.0 | -0.253 | 0.175 | 37.0 | 0.903 | 3.7342113 | 7.46843 | 13
Likely Binary | 2095490942878080256 | WD J183243.45+354518.42 | 278.181011 | 35.755123 | 18.1 | 0.994 | 24510.0 | 0.42 |  | 503.6 | WD | 0.264 | 45 | 1602.0 | -0.302 | 0.069 |  |  |  |  |
Likely Binary | 2144580907240525568 | WD J184506.31+505412.15 | 281.276271 | 50.903336 | 17.8 | 0.911 | 18230.0 | 0.16 |  | 830.7 |  |  | 45 | 1033.0 | -0.512 | 0.105 | 45.0 | 0.955 | 5.7531055 |  |
Likely Binary | 2126940892444693760 | WD J191931.09+443243.88 | 289.879471 | 44.54546 | 16.6 | 0.926 | 33990.0 | 0.3 | CV | 535.7 | WD | 0.5 | 41 | 956.0 | 0.19 | 0.071 | 41.0 | 0.794 | 6.2207431 |  | 14
Likely Binary | 1807309147099442432 | WD J195952.94+143534.17 | 299.970566 | 14.592818 | 17.5 | 0.994 |  |  |  | 643.8 |  |  | 51 | 329.0 | -0.138 | 0.05 | 52.0 | 0.905 | 7.1919594 |  |
Likely Binary | 1809460380271929344 | WD J200937.02+165219.12 | 302.404376 | 16.872102 | 16.8 | 0.949 | 13230.0 | 0.14 |  | 341.6 |  |  | 61 | 87.0 | -0.119 | 0.166 | 62.0 | 0.938 | 2.49783 |  |
Likely Binary | 2061416695278519808 | WD J202034.57+392212.12 | 305.143844 | 39.369926 | 17.4 | 0.999 | 36520.0 | 0.72 |  | 326.4 |  |  | 46 |  | -0.63 | 0.079 | 47.0 | 0.886 | 5.3152144 |  |
Likely Binary | 6679158828046846336 | WD J202354.90-433513.67 | 305.978719 | -43.58712 | 17.0 | 0.976 |  |  |  | 902.0 | WD | 0.515 | 49 |  | -0.07 | 0.107 |  |  |  |  |
Likely Binary | 1863757043284422784 | WD J202841.38+325837.35 | 307.172333 | 32.976997 | 17.5 | 0.92 |  |  |  | 758.4 |  |  | 56 | 453.0 | -0.135 | 0.378 | 56.0 | 0.883 | 19.4392732 |  |
Likely Binary | 6910676050839449728 | WD J210110.17-052751.14 | 315.29212 | -5.464319 | 14.8 | 0.998 | 36900.0 | 0.52 | DBA | 140.5 | WD | 0.662 | 58 | 37.0 | 0.21 | 0.025 | 58.0 | 0.868 | 12.8962353 |  | 15
Likely Binary | 2177297391130977792 | WD J210840.53+554502.63 | 317.168856 | 55.750555 | 18.9 | 0.939 | 8530.0 | 0.52 |  | 180.9 |  |  | 53 | 613.0 | -0.135 | 0.133 | 53.0 | 0.873 | 2.7846556 |  |
Likely Binary | 1867851869401000960 | WD J211557.58+364255.40 | 318.989974 | 36.715394 | 18.0 | 0.978 |  |  |  | 773.2 |  |  | 60 | 477.0 | -0.114 | 0.094 | 61.0 | 0.889 | 6.7479039 |  |
Likely Binary | 1950573244454108160 | WD J213119.93+345246.84 | 322.833067 | 34.879639 | 17.5 | 0.984 | 48120.0 | 0.54 |  | 547.8 |  |  | 68 | 373.0 | -0.601 | 0.073 | 69.0 | 0.985 | 10.3988838 |  |
Likely Binary | 2667317799127474944 | WD J213958.29-074126.17 | 324.992963 | -7.690733 | 16.7 | 0.99 |  |  |  | 517.2 | WD | 0.5 | 46 | 224.0 | -0.197 | 0.093 |  |  |  | 9.91934 | 16
Likely Binary | 2000785539622175104 | WD J221545.15+503759.46 | 333.938098 | 50.633181 | 18.1 | 0.967 |  |  |  | 847.4 |  |  | 54 | 55.0 | 0.126 | 0.129 | 54.0 | 0.913 | 5.4185123 |  |
Likely Binary | 2833849800205759360 | WD J224539.30+201633.35 | 341.414024 | 20.275965 | 15.7 | 0.994 | 14490.0 | 0.26 |  | 157.0 | WD | 0.296 | 36 | 771.0 | 0.024 | 0.03 |  |  |  |  |
Likely Binary | 2608280729159380992 | WD J224653.73-094834.48 | 341.724052 | -9.809701 | 16.4 | 0.982 |  |  | DA | 525.7 | WD | 0.62 | 23 | 82.0 | -0.134 | 0.038 |  |  |  |  | 17
Likely Binary | 6609580078678720512 | WD J225206.39-274012.56 | 343.026633 | -27.670175 | 16.7 | 0.993 | 72550.0 | 0.65 |  | 447.8 |  |  | 32 | 268.0 | -0.316 | 0.137 | 32.0 | 0.835 | 5.1362607 |  |
Likely Binary | 2411529617359368960 | WD J230047.06-125054.98 | 345.196258 | -12.848608 | 16.7 | 0.995 | 34300.0 | 0.51 | DB | 310.9 | WD | 0.686 | 26 | 244.0 | -0.148 | 0.053 |  |  |  |  | 18
Likely Binary | 2210180554096762624 | WD J232411.16+653053.05 | 351.04663 | 65.514762 | 16.1 | 0.932 | 32760.0 | 0.27 |  | 356.7 | WD | 1.0 | 54 | 558.0 | 0.109 | 0.108 | 54.0 | 0.858 | 7.2978052 |  |
Likely Binary | 6523373973310305664 | WD J233923.79-485350.19 | 354.849218 | -48.897269 | 17.0 | 0.978 | 24160.0 | 0.27 |  | 454.1 | S | 0.157 | 78 |  | -0.36 | 0.095 | 78.0 | 0.914 | 2.530295 |  |
Likely Eclipsing Binary | 414813439007636352 | WD J004502.35+503408.46 | 11.25983 | 50.568959 | 17.6 | 0.955 | 19200.0 | 0.23 |  | 557.1 |  |  | 53 | 585.0 | 4.153 | 0.098 | 55.0 | 0.912 | 1.8351065 | 6.87792 | 19
Likely Eclipsing Binary | 6086116512688802176 | WD J130905.43-470852.39 | 197.272675 | -47.147918 | 18.3 | 0.908 | 11040.0 | 0.13 |  | 542.4 |  |  | 49 |  | 3.648 | 0.18 | 50.0 | 0.817 | 0.5338794 |  |
Likely Eclipsing Binary | 6008982469163902464 | WD J154008.28-392917.61 | 235.034874 | -39.488217 | 17.3 | 0.973 | 9590.0 | 0.41 |  | 131.9 | CV | 0.067 | 48 |  | 4.052 | 0.095 | 49.0 | 0.738 | 0.6007567 |  |
Likely Eclipsing Binary | 2056368017063855360 | WD J202811.64+350525.08 | 307.048487 | 35.090314 | 17.9 | 0.955 | 20320.0 | 0.23 |  | 670.1 |  |  | 52 | 610.0 | -0.316 | 0.079 | 52.0 | 0.901 | 10.3938399 |  |
Known Eclipsing Binary | 380560941677424768 | WD J003352.64+385529.70 | 8.469299 | 38.924891 | 18.3 | 0.956 | 20640.0 | 0.24 |  | 841.3 |  |  | 40 | 828.0 | -0.285 | 0.113 | 40.0 | 1.002 | 4.8646611 | 4.86 | 20
Known Eclipsing Binary | 578539413395848704 | WD J085746.18+034255.35 | 134.442416 | 3.715389 | 18.3 | 0.872 | 21040.0 | 0.19 | DA | 1088.4 |  |  | 72 | 209.0 | 1.739 | 0.235 | 73.0 | 0.874 | 1.5623108 | 1.562316667 | 21,22
Known Eclipsing Binary | 1446230735421615872 | WD J132518.18+233808.02 | 201.325817 | 23.635475 | 18.2 | 0.983 | 17000.0 | 0.24 | DA+dM | 621.7 |  |  | 52 | 439.0 | -0.328 | 0.077 | 52.0 | 0.944 | 4.6790375 | 4.679015783 | 23,24
Known Binary | 1112171030998592256 | WD J071709.79+740040.53 | 109.292486 | 74.01089 | 15.0 | 0.996 | 14340.0 | 0.29 | DA | 101.3 | WD | 0.469 | 58 | 567.0 | -0.331 | 0.025 | 58.0 | 0.796 | 2.4735485 | 2.473008 | 25
Known Binary | 5660008787157868928 | WD J095017.97-251124.79 | 147.574789 | -25.190355 | 15.5 | 0.888 | 19340.0 | 0.16 | DA+dM | 309.8 | WD | 1.0 | 42 |  | 0.346 | 0.068 | 42.0 | 0.96 | 7.6478424 | 7.647696 | 26,27
Known Binary | 1223988576107848832 | WD J153938.12+270605.84 | 234.908707 | 27.10159 | 16.6 | 0.955 | 24650.0 | 0.24 | DA | 447.5 | WD | 0.5 | 113 | 204.0 | -0.027 | 0.044 | 116.0 | 0.865 | 5.7252728 | 5.725033333 | 28,29
Likely CV | 6180386608127234432 | WD J130017.86-325805.23 | 195.074344 | -32.968155 | 20.3 | 0.851 |  |  |  | 590.8 | CV | 0.906 | 31 |  | -2.053 | 0.176 |  |  |  |  | 30
Known CV | 5099482805904892288 | WD J031413.25-223542.92 | 48.555884 | -22.595499 | 18.2 | 0.996 | 10710.0 | 0.66 | CV | 160.4 | WD | 0.578 | 31 | 79.0 | -0.763 | 0.107 | 31.0 | 0.877 | 1.3503827 | 1.35 | 31,32
Known CV | 5645504991845223936 | WD J083843.35-282701.14 | 129.680548 | -28.450262 | 17.6 | 0.978 | 9500.0 | 0.41 | CV | 156.6 | S | 0.6 | 77 |  | 0.232 | 0.847 | 77.0 | 0.513 | 16.1135388 | 1.640216667 | 33,34
Likely DAV | 5709854047291834496 | WD J082924.77-163337.25 | 127.353247 | -16.560327 | 17.6 | 0.996 | 10930.0 | 0.58 |  | 141.4 |  |  | 40 | 140.0 | -0.599 | 0.069 | 41.0 | 0.724 | 1.0316165 |  | 35
Likely DAV | 3459790225027896448 | WD J120650.89-380549.23 | 181.711597 | -38.097216 | 15.7 | 0.998 | 11870.0 | 0.65 |  | 58.8 | WD | 0.524 | 62 |  | -1.156 | 0.034 | 62.0 | 0.845 | 7.0349461 |  |
Known DAV | 2026653131220381824 | WD J195227.88+250929.18 | 298.116179 | 25.158763 | 15.1 | 0.998 | 11710.0 | 0.6 | DA | 47.4 |  |  | 79 | 393.0 | -1.407 | 0.026 | 79.0 | 0.725 | 0.566988 | 0.071166667 | 36,37
Known DAV | 6410501923531836928 | WD J215823.88-585353.81 | 329.599553 | -58.898156 | 15.8 | 0.998 | 11640.0 | 0.61 | DA | 63.7 | WD | 0.761 | 62 |  | 0.009 | 0.026 |  |  |  | 0.086186111 | 38,39
Likely Spot | 313206676129937408 | WD J011157.12+313632.67 | 17.987841 | 31.608892 | 16.9 | 0.999 | 18120.0 | 0.8 |  | 125.3 | WD | 0.355 | 32 | 281.0 | 0.158 | 0.033 |  |  |  |  |
Likely Spot | 5139880551029408768 | WD J013832.02-195446.58 | 24.634396 | -19.912219 | 15.5 | 0.994 | 8430.0 | 0.93 | DA | 24.4 |  |  | 62 | 179.0 | 0.201 | 0.032 | 62.0 | 0.933 | 3.9428678 |  | 40
Likely Spot | 105601048101988992 | WD J020322.94+255851.90 | 30.845585 | 25.981003 | 18.1 | 0.992 | 9210.0 | 0.64 |  | 124.9 | WD | 0.569 | 26 |  | 0.695 | 0.129 |  |  |  |  |
Likely Spot | 4618860233015905408 | WD J024235.52-820636.32 | 40.651134 | -82.110184 | 16.4 | 0.995 | 9450.0 | 0.79 | DA | 53.1 | WD | 0.549 | 42 |  | 0.711 | 0.035 | 42.0 | 0.91 | 3.3447333 |  | 41
Likely Spot | 187576000803144704 | WD J052026.35+381240.87 | 80.109816 | 38.211059 | 15.4 | 1.0 | 19830.0 | 0.69 | DAB | 74.6 | WD | 0.562 | 28 | 407.0 | -0.391 | 0.017 |  |  |  |  | 42
Likely Spot | 2951380789991336192 | WD J062555.04-141442.31 | 96.479499 | -14.245324 | 16.5 | 0.994 | 8020.0 | 0.74 |  | 43.9 | WD | 0.509 | 42 | 219.0 | 0.293 | 0.069 | 42.0 | 0.897 | 4.4630736 |  |
Likely Spot | 3161618477052648192 | WD J072758.87+101157.08 | 111.995427 | 10.198911 | 17.4 | 0.995 | 7600.0 | 0.77 |  | 58.8 | WD | 0.331 | 24 | 286.0 | 0.242 | 0.027 |  |  |  |  |
Likely Spot | 1030289712881895296 | WD J083531.17+533230.91 | 128.879468 | 53.541364 | 18.2 | 0.992 | 8490.0 | 0.8 | DAH | 96.7 | WD | 0.536 | 35 | 75.0 | -0.382 | 0.065 |  |  |  |  | 43
Likely Spot | 5620763437599189376 | WD J090212.89-394553.32 | 135.554166 | -39.764881 | 16.0 | 0.993 | 8770.0 | 0.83 |  | 36.4 | WD | 0.586 | 57 |  | -0.027 | 0.024 |  |  |  |  |
Likely Spot | 3598424931753893888 | WD J115033.35-063618.07 | 177.637567 | -6.605365 | 16.4 | 0.993 | 8770.0 | 0.89 | DA | 41.5 | WD | 0.509 | 48 | 130.0 | 0.259 | 0.026 |  |  |  |  | 44
Likely Spot | 1465214177336901376 | WD J124740.10+303007.41 | 191.91707 | 30.501779 | 17.9 | 0.992 | 7460.0 | 0.65 | DA | 82.3 | WD | 0.632 | 41 | 548.0 | -0.381 | 0.042 |  |  |  |  | 45
Likely Spot | 6279014454702485632 | WD J144410.08-214338.33 | 221.041685 | -21.727292 | 16.9 | 0.999 | 25120.0 | 1.12 |  | 106.0 | WD | 0.777 | 22 | 102.0 | 0.454 | 0.045 |  |  |  |  |
Likely Spot | 1639907647071426176 | WD J154801.37+623611.57 | 237.005479 | 62.603291 | 18.6 | 0.999 | 30150.0 | 0.75 |  | 449.5 | ECL | 0.005 | 57 | 984.0 | 0.369 | 0.155 |  |  |  | 9.474283333 | 46
Likely Spot | 4334641562477923712 | WD J165335.21-100116.33 | 253.397409 | -10.022141 | 15.7 | 0.991 | 7350.0 | 0.54 |  | 32.6 | WD | 0.508 | 67 | 161.0 | 0.496 | 0.039 |  |  |  |  |
Likely Spot | 2043899619620928000 | WD J185924.85+330157.53 | 284.853197 | 33.03259 | 17.7 | 0.993 | 9320.0 | 0.78 |  | 91.8 | WD | 0.531 | 41 | 380.0 | -0.083 | 0.089 |  |  |  |  |
Likely Spot | 2216598403463898112 | WD J215432.26+634154.11 | 328.634861 | 63.698414 | 18.9 | 0.997 | 16590.0 | 1.03 |  | 201.3 | WD | 0.4 | 38 | 542.0 | -0.205 | 0.131 |  |  |  |  |
Likely Spot | 6613841171565998848 | WD J221452.56-314333.98 | 333.719762 | -31.726229 | 17.1 | 0.994 | 7670.0 | 0.75 |  | 53.9 | WD | 0.515 | 42 |  | 0.22 | 0.068 | 42.0 | 1.01 | 7.383116 |  |
Known Spot | 2375576682347401216 | WD J003512.88-122508.84 | 8.804346 | -12.419793 | 16.9 | 0.993 | 8440.0 | 0.81 | DAHe | 52.7 | WD | 0.627 | 26 | 623.0 | -0.107 | 0.041 |  |  |  | 1.210483333 | 47
Known Spot | 4613612951211823104 | WD J031715.85-853225.56 | 49.311809 | -85.540486 | 14.8 | 1.0 | 26460.0 | 1.27 | DAH | 29.4 | WD | 0.614 | 46 |  | -0.146 | 0.136 | 46.0 | 0.607 | 0.6268161 | 0.201388889 | 48
Known Spot | 551153263105246208 | WD J041246.85+754942.26 | 63.192633 | 75.828522 | 15.8 | 0.991 | 8600.0 | 0.76 | DAHe | 35.0 | WD | 0.525 | 51 | 418.0 | 0.249 | 0.037 | 52.0 | 0.933 | 2.2891284 | 2.2891 | 49,50
Known Spot | 504240778439455872 | WD J053432.93+770757.40 | 83.637543 | 77.131959 | 16.5 | 0.995 | 10670.0 | 0.84 |  | 60.7 |  |  | 48 | 410.0 | 0.176 | 0.074 | 48.0 | 0.909 | 0.7234655 | 0.72347 | 51
Known Spot | 1020641700210987520 | WD J095125.94+530930.72 | 147.858294 | 53.158533 | 15.3 | 0.983 | 126070.0 | 0.78 | DA | 314.7 | WD | 0.596 | 54 | 397.0 | -0.461 | 0.099 |  |  |  | 82.8 | 52
Known Spot | 3682469122383597056 | WD J125230.93-023417.72 | 193.129111 | -2.571767 | 17.5 | 0.992 | 7740.0 | 0.56 | DAHe | 77.7 | WD | 0.555 | 58 |  | -0.362 | 0.054 |  |  |  | 0.088132778 | 53
Known Spot | 4235280071072332672 | WD J195629.23-010232.67 | 299.11983 | -1.045547 | 13.6 | 0.994 | 7790.0 | 0.7 | DA | 11.6 | WD | 1.0 | 36 |  | 0.206 | 0.059 |  |  |  | 34.60319444 | 54,55
Known Spot | 1748833236082347136 | WD J202932.51+070107.70 | 307.385483 | 7.018813 | 16.6 | 0.943 | 63100.0 | 0.52 | DO | 522.1 | WD | 0.294 | 45 | 183.0 | -0.08 | 0.038 |  |  |  | 6.96 | 56,57

(51) Guidry et al. (2021); (52) Werner et al. (2019); (53) Reding et al.
(2020); (54) Brinkworth et al. (2005); (55) Maxted et al. (2000); (56) Reindl
et al. (2021); (57) Dreizler et al. (1995);

References. — †WD J Name, $P_{\rm WD}$ and atmospheric parameters determined
from H-atmosphere fits of Gentile Fusillo et al. (2021). Spectral type
information collected from the Montreal White Dwarf Database and SIMBAD. All
Gaia information arises from DR3 (Gaia Collaboration et al., 2023c). ‡The best
classification (Class) and classification score (Score) arise from the
variability classification results of all classifiers table in DR3 (vclassre).
Summary statistics from the Gaia $G$ light curve such as the number of FoV
transits used in analysis ($N_{\rm G}$), the skew, and the interquartile range
(IQR) arise from the variability summary table in DR3 (varisum). ∗∗
Information from Zwickey Transient Facility, including the number of FoV
transitys used in analysis from the $g$ band ($N_{\rm g}$) . ∗Information for
any objects flagged as short-timescale sources, such as the number of FoV
transits used in the short-period analysis ($N_{\rm G,S}$), the mean of per-
FoV Abbe values (Abbe), and the hypothesized timescale of variability ($P_{\rm
G,S}$) arise from the short-timescale sources table in DR3 (vst). Literature
periods have been collected from (1) Kepler et al. (2016); (2) Koester et al.
(2001); (3) Kleinman et al. (2013); (4) Tremblay et al. (2020); (5) Ren et al.
(2023); (6) Liebert et al. (1981); (7) Dreizler et al. (1995); (8) Kepler et
al. (2015); (9) Ren et al. (2023); (10) Badenes et al. (2013); (11) Mickaelian
(2008); (12) Kepler et al. (2015); (13) Ren et al. (2023); (14) Howell et al.
(2013); (15) Raddi et al. (2017); (16) Drake et al. (2014); (17) Eisenstein et
al. (2006); (18) Kilkenny et al. (2016); (19) Ren et al. (2023); (20)
Kosakowski et al. (2022); (21) Bours et al. (2016); (22) Parsons et al.
(2015); (23) Drake et al. (2010); (24) Bours et al. (2016); (25) Marsh & Duck
(1996); (26) Drake et al. (2017); (27) Kosakowski et al. (2020); (28) Kao et
al. (2016); (29) Rebassa-Mansergas et al. (2010); (30) Drake et al. (2014);
(31) Bond et al. (1979); (32) Warner (1980); (33) Halpern et al. (2017); (34)
Rea et al. (2017); (35) Guidry et al. (2021); (36) Kepler (1984); (37)
Fontaine et al. (1980); (38) Romero et al. (2022); (39) Kilkenny et al.
(2015); (40) Koester et al. (2001); (41) Raddi et al. (2017); (42) Kong et al.
(2019); (43) Eisenstein et al. (2006); (44) Kawka & Vennes (2012); (45)
Kleinman et al. (2013); (46) Ren et al. (2023); (47) Reding et al. (2023);
(48) Ferrario et al. (1997); (49) Walters et al. (2021); (50) Tremblay et al.
(2020).

=16mm

Table 3: New variability information determined for the 105 white dwarfs in
this study with significant variability measured from their Gaia DR3 light
curve.

Class |  | WD J Name† | $P_{\rm G,DR3}$ | $\sigma P_{\rm G,DR3}$ | $A_{\rm G}$ | $\sigma A_{\rm G}$ | $t_{\rm min,G}$ | $\sigma t_{\rm min}$ | Match | $P_{\rm ZTF}$ | $\sigma P_{\rm ZTF}$ | $A_{\rm ZTF}$ | $\sigma A_{\rm ZTF}$ | $P_{\rm TESS}$ | $\sigma P_{\rm TESS}$ | $A_{\rm TESS}$ | $\sigma A_{\rm TESS}$ | Rev. | Std. Rev. | False Alarm
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
(This Work) |  |  | [hr] | [hr] | [%] | [%] | MJDTDB | [d] |  | [hr] | [hr] | [%] | [%] | [hr] | [hr] | [%] | [%] | [d] | [d] | [%]
Likely Binary |  | WD J003213.13+160434.78 | 21.771792 | 0.06451811 | 0.0053 | 0.004 | 56890.44 | 1.73 | ZTF, TESS | 21.886956 | 0.05957178 | 0.6484 | 0.3454 | 19.402039 | 0.38635639 | 0.0036 | 0.0014 | 52.9 | 43.2 | 0.7
Likely Binary |  | WD J003449.86-312952.69 | 2.314931 | 0.00036725 | 0.0357 | 0.0157 | 56870.52 | 0.08 | TESS |  |  |  |  | 2.316131 | 13.20032778 | 0.0 | 0.0015 | 50.5 | 40.0 |  $<$0.1
Likely Binary |  | WD J011053.06+604831.03 | 8.357258 | 0.00766065 | 0.007 | 0.006 | 56897.32 | 0.57 | TESS | 8.373517 | 0.00404841 | 0.2803 | 0.1418 | 8.362356 | 0.00191441 | 0.0643 | 0.0035 | 35.3 | 22.1 |  $<$0.1
Likely Binary |  | WD J012828.99+385436.63 | 118.136167 | 0.46444972 | 0.0155 | 0.0041 | 56909.06 | 2.68 | ZTF | 119.6655 | 0.41811806 | 0.7473 | 0.1757 | 122.246833 | 47.54794444 | 0.0042 | 0.0032 | 61.7 | 46.9 | 24.9
Likely Binary |  | WD J013148.02-055900.14 | 2.055886 | 0.00033342 | 0.01 | 0.0055 | 56897.97 | 0.11 | TESS | 2.056135 | 0.00019699 | 0.6549 | 0.2721 | 2.025781 | 0.00804038 | 0.0096 | 0.0036 | 56.7 | 47.6 | 19.3
Likely Binary |  | WD J022704.24+591502.04 | 12.736229 | 0.0122765 | 0.0073 | 0.0034 | 56898.86 |  | ZTF | 12.770364 | 0.0103218 | 0.3655 | 0.177 |  |  |  |  | 38.8 | 27.5 |  $<$0.1
Likely Binary |  | WD J032205.10-472106.46 | 24.768553 | 0.02279821 | 0.0393 | 0.0129 | 56912.94 | 0.43 | TESS |  |  |  |  | 23.463694 | 0.75380139 | 0.0048 | 0.0026 | 30.6 | 8.3 | 4.6
Likely Binary |  | WD J032803.02+265151.65 | 8.611367 | 0.00638363 | 0.0314 | 0.0211 | 56904.43 | 0.42 | ZTF | 8.618753 | 4500.0 | 0.0 | 0.5263 |  |  |  |  | 65.6 | 57.7 | 28.8
Likely Binary |  | WD J032902.63+390340.87 | 4.036247 | 0.00198967 | 0.0242 | 0.0159 | 56903.7 | 0.23 | ZTF | 4.0431 | 0.00155644 | 1.2607 | 0.6927 |  |  |  |  | 51.2 | 43.8 | 5.2
Likely Binary |  | WD J035814.52-213813.74 | 1.794933 | 0.00023552 | 0.0227 | 0.0118 | 56914.03 | 0.09 | ZTF | 1.794894 | 0.00033893 | 0.7248 | 0.6254 |  |  |  |  | 39.3 | 29.8 |  $<$0.1
Likely Binary |  | WD J041033.37-585203.63 | 2.872539 | 0.0005393 | 0.0394 | 0.0189 | 56935.79 | 0.11 | TESS |  |  |  |  | 2.871769 | 0.00595186 | 0.002 | 0.0019 | 35.9 | 13.1 | 15.9
Likely Binary |  | WD J043103.75-041702.63 | 2.434396 | 0.00052726 | 0.0686 | 0.0404 | 56912.57 | 0.11 | ZTF | 2.434496 | 0.00043268 | 2.0772 | 0.7928 |  |  |  |  | 50.4 | 46.0 | 21.9
Likely Binary |  | WD J043832.74+003117.01 | 26.014614 | 0.06736786 | 0.0099 | 0.0049 | 56914.98 | 1.14 | ZTF | 26.073231 | 0.11561044 | 0.1405 | 0.1963 |  |  |  |  | 43.2 | 37.5 | 1.1
Likely Binary |  | WD J050433.01-213007.93 | 15.028869 | 0.02485904 | 0.0143 | 0.0107 | 56918.23 | 0.87 | ZTF | 14.956056 | 0.01491123 | 1.5712 | 0.9047 |  |  |  |  | 36.6 | 23.7 | 4.4
Likely Binary |  | WD J053632.07+123128.65 | 3.801928 | 0.00249101 | 0.0102 | 0.0126 | 56912.42 | 0.46 | ZTF, TESS | 3.799225 | 0.00054618 | 0.8572 | 0.2873 | 3.840864 | 0.03100203 | 0.002 | 0.0023 | 47.9 | 47.7 |  $<$0.1
Likely Binary |  | WD J061234.26-191111.75 | 2.224975 | 0.00058326 | 0.0143 | 0.0134 | 56919.44 | 0.16 | ZTF | 2.225262 | 0.00038728 | 1.3633 | 0.9595 |  |  |  |  | 36.7 | 27.1 | 1
Likely Binary |  | WD J061815.27-512305.52 | 9.674728 | 0.00529894 | 0.0112 | 0.004 | 56932.46 | 0.31 | TESS |  |  |  |  | 9.645339 | 0.00446996 | 0.0097 | 0.001 | 35.0 | 11.1 | 28.6
Likely Binary |  | WD J064316.01+013012.78 | 6.036606 | 0.00212576 | 0.0224 | 0.0097 | 56918.12 | 0.24 | ZTF, TESS | 6.041864 | 0.00277571 | 0.5138 | 0.3596 | 6.038822 | 0.00072595 | 0.0091 | 0.0015 | 60.1 | 49.8 | 22.3
Likely Binary |  | WD J064753.57-403756.16 | 7.011806 | 0.0106999 | 0.0142 | 0.0172 | 56996.71 | 0.67 | Gaia BP |  |  |  |  |  |  |  |  | 32.5 | 10.0 |  $<$0.1
Likely Binary |  | WD J064802.27-634629.90 | 3.775269 | 0.00143243 | 0.0166 | 0.0146 | 56931.78 | 0.2 | TESS |  |  |  |  | 3.765814 | 0.00170344 | 0.005 | 0.0015 | 34.9 | 10.6 |  $<$0.1
Likely Binary |  | WD J070647.52+613350.31 | 8.965739 | 0.00733039 | 0.0044 | 0.0021 | 56904.96 | 0.45 | ZTF, TESS | 8.956211 | 0.00547992 | 0.1324 | 0.0848 | 8.963867 | 0.00529426 | 0.0002 | 0.0001 | 44.7 | 33.5 | 7
Likely Binary |  | WD J072146.74+564408.41 | 2.715027 | 0.00056963 | 0.0218 | 0.012 | 56907.27 | 0.14 | ZTF | 2.714582 | 0.0013891 | 1.2807 | 1.4401 |  |  |  |  | 51.8 | 44.8 | 3.6
Likely Binary |  | WD J073121.39+595737.01 | 5.315978 | 0.00316432 | 0.0104 | 0.0106 | 56906.67 | 0.33 | ZTF, TESS | 5.309414 | 0.00956094 | 0.1098 | 0.3165 | 5.313603 | 19.30418611 | 0.0 | 0.0013 | 46.9 | 37.6 | 33.7
Likely Binary |  | WD J074316.04-224656.86 | 8.310972 | 0.00983921 | 0.019 | 0.0187 | 56959.09 | 0.64 | ZTF | 8.279997 | 0.00263236 | 4.3029 | 1.709 |  |  |  |  | 38.1 | 19.1 |  $<$0.1
Likely Binary |  | WD J090240.78-742331.37 | 5.449119 | 0.0018044 | 0.0101 | 0.0045 | 56893.28 | 0.21 | TESS |  |  |  |  | 5.416497 | 0.02826039 | 0.0045 | 0.0026 | 33.9 | 11.8 | 9
Likely Binary |  | WD J091748.20+001041.72 | 29.146361 | 0.08106744 | 0.0119 | 0.0097 | 56962.01 | 1.71 | ZTF, TESS | 29.178917 | 0.03566194 | 1.0295 | 0.4407 | 42.345667 | 4.53270833 | 0.009 | 0.0049 | 49.6 | 44.6 | 0.5
Likely Binary |  | WD J093611.12-340059.16 | 20.793195 | 0.0359738 | 0.0067 | 0.0043 | 56965.09 |  | TESS |  |  |  |  | 16.100917 | 0.39214361 | 0.033 | 0.0097 | 36.4 | 20.0 |  $<$0.1
Likely Binary |  | WD J100645.76+003204.48 | 2.536604 | 0.00066172 | 0.0242 | 0.0185 | 56959.73 | 0.13 | ZTF, TESS | 2.535475 | 0.00043236 | 0.5741 | 0.3772 | 2.536101 | 0.00034043 | 0.0023 | 0.0013 | 57.0 | 50.2 | 17.6
Likely Binary |  | WD J105228.94-295308.20 | 8.229394 | 7527.777778 | 0.0 | 0.0001 | 56874.03 | 432563.6 | TESS |  |  |  |  | 8.361094 | 0.12081919 | 0.0189 | 0.0056 | 50.6 | 36.1 | 27.6
Likely Binary |  | WD J110318.00-401544.50 | 29.047667 | 0.0949295 | 0.0272 | 0.0174 | 56881.84 | 1.83 | TESS |  |  |  |  | 29.240944 | 2.59028361 | 0.0008 | 0.0004 | 47.7 | 31.5 | 5.9
Likely Binary |  | WD J112355.21-400614.63 | 16.972742 | 0.01447909 | 0.0288 | 0.0131 | 56887.85 | 0.45 | TESS |  |  |  |  | 16.983225 | 135.3446944 | 0.0 | 0.0 | 45.4 | 30.1 | 12.8*
Likely Binary |  | WD J113832.79-435817.73 | 13.311775 | 0.03923664 | 0.004 | 0.008 | 56891.91 | 1.75 | Gaia BP, Gaia RP |  |  |  |  |  |  |  |  | 39.7 | 25.8 |  $<$0.1
Likely Binary |  | WD J121622.61-545907.30 | 2.576151 | 0.00050299 | 0.0664 | 0.035 | 56894.91 | 0.11 | Gaia BP, Gaia RP |  |  |  |  |  |  |  |  | 34.1 | 17.6 | 0.1
Likely Binary |  | WD J123955.40+834707.51 | 0.956676 | 0.00035594 | 0.0388 | 0.0896 | 56898.18 | 0.19 | ZTF | 0.956609 | 0.00014681 | 4.9308 | 5.1684 |  |  |  |  | 47.2 | 22.8 | 7.4
Likely Binary |  | WD J125005.11-203632.29 | 21.147906 | 0.02900806 | 0.0345 | 0.0262 | 56896.21 | 0.91 | TESS | 21.082511 | 0.03706747 | 0.9748 | 0.9013 | 21.486694 | 1.88802694 | 0.0084 | 0.0065 | 62.8 | 50.7 | 12
Likely Binary |  | WD J135523.92+085645.42 | 2.744749 | 0.0006954 | 0.0132 | 0.0078 | 56901.83 | 0.17 | ZTF, TESS | 2.744139 | 0.00024016 | 0.7035 | 0.2419 | 2.780175 | 0.02776044 | 0.0084 | 0.0055 | 53.3 | 48.4 | 0.1
Likely Binary |  | WD J140330.89+671255.16 | 3.443786 | 0.00139008 | 0.0168 | 0.0122 | 56897.06 | 0.24 | ZTF | 3.4503 | 0.00066051 | 0.6072 | 0.3348 |  |  |  |  | 36.0 | 11.9 | 3.1
Likely Binary |  | WD J144007.60+315413.02 | 23.245372 | 0.04633281 | 0.0135 | 0.0083 | 56913.96 | 1.1 | ZTF, TESS | 23.265067 | 0.01444292 | 0.7476 | 0.2314 | 23.246072 | 0.01754755 | 0.0206 | 0.0051 | 33.5 | 14.0 | 9.3
Likely Binary |  | WD J145623.30-793654.99 | 4.819789 | 0.0018614 | 0.0221 | 0.0159 | 56898.7 | 0.22 | Gaia BP |  |  |  |  |  |  |  |  | 32.5 | 10.2 |  $<$0.1
Likely Binary |  | WD J145817.91-651024.94 | 3.677164 | 0.00275866 | 0.004 | 0.0062 | 56900.11 | 0.5 | Gaia BP |  |  |  |  |  |  |  |  | 31.9 | 16.9 |  $<$0.1
Likely Binary |  | WD J153028.82+874848.48 | 21.206697 | 0.02246878 | 0.0186 | 0.007 | 56904.12 | 0.54 | TESS |  |  |  |  | 21.425442 | 0.01431244 | 0.0013 | 0.0003 | 32.5 | 8.7 |  $<$0.1
Likely Binary |  | WD J154012.07+290828.96 | 2.377268 | 0.00026954 | 0.0467 | 0.0179 | 56914.8 | 0.07 | ZTF | 2.377583 | 0.000173 | 1.8722 | 0.5728 |  |  |  |  | 30.5 | 16.8 |  $<$0.1
Likely Binary |  | WD J181824.35+465721.46 | 3.730808 | 0.00084071 | 0.0454 | 0.0209 | 56930.63 | 0.14 | ZTF | 3.735769 | 0.00101204 | 0.374 | 0.2643 |  |  |  |  | 37.8 | 13.4 | 0.9
Likely Binary |  | WD J183243.45+354518.42 | 1.416905 | 0.00019062 | 0.0107 | 0.0079 | 56927.91 | 0.08 | ZTF | 1.416682 | 5.93e-05 | 0.4607 | 0.1244 |  |  |  |  | 32.7 | 10.5 | 0.4
Likely Binary |  | WD J184506.31+505412.15 | 5.742764 | 0.00158156 | 0.0332 | 0.0131 | 56931.08 | 0.16 | ZTF, TESS | 5.75205 | 0.00177661 | 0.2939 | 0.1531 | 5.739953 | 0.00302524 | 0.0211 | 0.0079 | 32.6 | 7.3 |  $<$0.1
Likely Binary |  | WD J191931.09+443243.88 | 6.209089 | 0.00248988 | 0.0163 | 0.0074 | 56928.17 | 0.22 | ZTF, TESS | 6.21685 | 0.0016627 | 0.2733 | 0.1146 | 6.234617 | 0.00393408 | 0.0038 | 0.0016 | 33.9 | 9.6 | 0.3
Likely Binary |  | WD J195952.94+143534.17 | 7.188675 | 0.0166399 | 0.0029 | 0.0059 | 56992.27 | 1.04 | ZTF | 7.191394 | 0.00177492 | 0.8598 | 0.3362 |  |  |  |  | 42.2 | 30.9 | 0.4
Likely Binary |  | WD J200937.02+165219.12 | 2.498782 | 0.00086119 | 0.0176 | 0.0127 | 56958.77 | 0.15 | ZTF | 2.500491 | 0.00017069 | 2.4724 | 0.5959 | 2.547105 | 0.02237542 | 0.0085 | 0.0055 | 40.0 | 29.4 |  $<$0.1
Likely Binary |  | WD J202034.57+392212.12 | 5.324653 | 0.00283764 | 0.0192 | 0.0106 | 56990.84 | 0.28 | TESS |  |  |  |  | 5.320283 | 0.00187972 | 0.024 | 0.0072 | 31.7 | 9.4 | 2.4
Likely Binary |  | WD J202354.90-433513.67 | 15.2327 | 0.02066798 | 0.0214 | 0.0114 | 56914.23 | 0.69 | TESS |  |  |  |  | 16.172639 | 0.25935103 | 0.0278 | 0.0049 | 51.3 | 41.7 |  $<$0.1
Likely Binary |  | WD J202841.38+325837.35 | 19.422681 | 0.02613492 | 0.0656 | 0.0348 | 56963.42 | 0.66 | ZTF, TESS | 19.616389 | 0.02075202 | 2.0971 | 1.0358 | 21.614186 | 0.15849081 | 0.5815 | 0.0392 | 32.7 | 12.6 |  $<$0.1
Likely Binary |  | WD J210110.17-052751.14 | 12.874175 | 0.01180351 | 0.0077 | 0.0031 | 56957.41 | 0.45 | Gaia BP, Gaia RP | 12.673861 | 90555.55556 | 0.0 | 0.0066 |  |  |  |  | 51.5 | 43.6 | 0.5
Likely Binary |  | WD J210840.53+554502.63 | 2.781769 | 0.00053615 | 0.0281 | 0.0141 | 56873.09 | 0.09 | ZTF | 2.782606 | 0.0006235 | 0.7013 | 0.5455 |  |  |  |  | 37.2 | 16.3 | 0.3
Likely Binary |  | WD J211557.58+364255.40 | 6.753503 | 0.00451239 | 0.0125 | 0.0088 | 56963.93 | 0.36 | ZTF | 6.748281 | 0.00153208 | 1.049 | 0.3375 |  |  |  |  | 32.7 | 13.4 | 0.3
Likely Binary |  | WD J213119.93+345246.84 | 10.373233 | 0.01306096 | 0.0105 | 0.0079 | 56988.5 | 0.61 | ZTF | 10.412589 | 0.00437928 | 1.075 | 0.3873 |  |  |  |  | 37.1 | 22.2 |  $<$0.1
Likely Binary |  | WD J213958.29-074126.17 | 6.250269 | 0.00316512 | 0.0244 | 0.0108 | 56983.85 | 0.25 | ZTF | 6.261194 | 0.00157262 | 1.4742 | 0.6431 |  |  |  |  | 53.2 | 46.4 |  $<$0.1
Likely Binary |  | WD J221545.15+503759.46 | 5.414369 | 0.00237553 | 0.0224 | 0.0144 | 56882.25 | 0.25 | ZTF | 5.431119 | 0.00513291 | 1.6915 | 1.2771 |  |  |  |  | 35.7 | 13.0 | 12.2
Likely Binary |  | WD J224539.30+201633.35 | 3.905189 | 0.00094606 | 0.0096 | 0.0051 | 56867.64 | 0.11 | ZTF | 3.905517 | 0.00084593 | 0.1878 | 0.0921 |  |  |  |  | 60.1 | 45.2 | 6.6
Likely Binary |  | WD J224653.73-094834.48 | 19.826454 | 0.01028305 | 0.0452 | 0.0036 | 56958.88 |  | TESS | 19.837572 | 0.16538997 | 1.1215 | 0.5601 | 18.505856 | 0.11626889 | 0.036 | 0.0024 | 57.0 | 50.1 | 32.1
Likely Binary |  | WD J225206.39-274012.56 | 5.132572 | 0.0023864 | 0.0258 | 0.0159 | 56954.48 | 0.31 | ZTF | 5.133864 | 0.00253317 | 0.6989 | 0.6005 |  |  |  |  | 58.8 | 51.9 | 4.6
Likely Binary |  | WD J230047.06-125054.98 | 16.714308 | 0.02454316 | 0.0129 | 0.007 | 56959.68 | 0.93 | TESS | 16.589397 | 0.01605333 | 0.4336 | 0.2738 | 16.554344 | 0.01973398 | 0.0091 | 0.0027 | 62.4 | 52.3 | 27.1
Likely Binary |  | WD J232411.16+653053.05 | 7.271892 | 0.00379897 | 0.0196 | 0.009 | 56895.47 | 0.33 | ZTF, TESS | 7.303556 | 0.00417417 | 0.491 | 0.3447 | 7.314125 | 0.00476089 | 0.0057 | 0.0011 | 31.8 | 8.9 |  $<$0.1
Likely Binary |  | WD J233923.79-485350.19 | 2.529616 | 0.00074594 | 0.0091 | 0.0078 | 56912.48 | 0.14 | TESS |  |  |  |  | 2.521869 | 0.01775451 | 0.002 | 0.0021 | 36.4 | 27.2 |  $<$0.1
Likely Eclipsing Binary |  | WD J004502.35+503408.46 | 6.883219 | 0.00192382 | 0.0772 | 0.0294 | 56927.53 | 0.16 | ZTF | 6.869319 | 0.00253022 | 1.1385 | 0.4951 |  |  |  |  | 41.8 | 31.2 | 40.7
Likely Eclipsing Binary |  | WD J130905.43-470852.39 | 3.320381 | 0.00107816 | 0.0589 | 0.0493 | 56896.94 | 0.22 | Gaia RP |  |  |  |  |  |  |  |  | 52.6 | 38.5 | 27
Likely Eclipsing Binary |  | WD J154008.28-392917.61 | 1.31965 | 0.00016547 | 0.0486 | 0.0276 | 56903.93 | 0.06 | TESS |  |  |  |  | 1.323371 | 0.00525961 | 0.01 | 0.0055 | 46.0 | 39.4 | 28.5
Likely Eclipsing Binary |  | WD J202811.64+350525.08 | 10.405553 | 0.00659212 | 0.0212 | 0.0081 | 56963.46 | 0.34 | ZTF | 10.396467 | 27611.11111 | 0.0 | 0.3689 |  |  |  |  | 32.7 | 13.7 | 1.8
Known Eclipsing Binary |  | WD J003352.64+385529.70 | 4.861628 | 0.00576532 | 0.0082 | 0.0111 | 56895.07 | 0.84 | ZTF | 4.862839 | 0.0011144 | 0.9914 | 0.4022 |  |  |  |  | 52.6 | 39.9 |  $<$0.1
Known Eclipsing Binary |  | WD J085746.18+034255.35 | 1.561434 | 0.00047608 | 0.0307 | 0.0246 | 56956.65 | 0.14 | ZTF | 1.561681 | 0.0001148 | 2.6183 | 1.2482 |  |  |  |  | 49.5 | 44.8 |  $<$0.1
Known Eclipsing Binary |  | WD J132518.18+233808.02 | 4.678903 | 0.0018771 | 0.0127 | 0.0074 | 56886.94 | 0.25 | ZTF | 4.674961 | 0.0018441 | 0.6449 | 0.5285 |  |  |  |  | 48.2 | 37.5 | 0.2
Known Binary |  | WD J071709.79+740040.53 | 2.472226 | 0.00034023 | 0.0078 | 0.0032 | 56902.62 | 0.08 | ZTF, TESS | 2.474291 | 0.00035304 | 0.1626 | 0.0756 | 2.473012 | 0.00029588 | 0.0006 | 0.0003 | 33.1 | 14.5 | 21
Known Binary |  | WD J095017.97-251124.79 | 7.644542 | 0.00560631 | 0.0145 | 0.0063 | 56963.73 | 0.34 | TESS |  |  |  |  | 7.290883 | 0.11245208 | 0.0027 | 0.0011 | 51.1 | 38.6 |  $<$0.1
Known Binary |  | WD J153938.12+270605.84 | 5.72125 | 0.00534064 | 0.0032 | 0.0033 | 56914.25 | 0.55 | TESS | 5.721197 | 0.00086724 | 0.598 | 0.2038 | 5.727303 | 0.00233915 | 0.0028 | 0.0017 | 33.5 | 17.1 |  $<$0.1
Likely CV |  | WD J130017.86-325805.23 | 0.603127 | 9.41e-05 | 0.1924 | 0.2752 | 57021.15 | 0.08 | Gaia BP, Gaia RP |  |  |  |  |  |  |  |  | 54.9 | 44.6 | 20.2
Known CV |  | WD J031413.25-223542.92 | 1.349474 | 0.00016573 | 0.0242 | 0.0178 | 56912.08 | 0.07 | ZTF, TESS | 1.350296 | 0.00015006 | 2.167 | 1.0267 | 1.360255 | 0.00542343 | 0.0099 | 0.0053 | 50.1 | 37.3 | 29.8
Known CV |  | WD J083843.35-282701.14 | 16.109283 | 0.02880356 | 0.0893 | 0.0609 | 56960.29 | 0.99 | Gaia BP, Gaia RP |  |  |  |  |  |  |  |  | 31.6 | 16.7 |  $<$0.1
Likely DAV |  | WD J082924.77-163337.25 | 0.099723 | 1.77e-06 | 0.0079 | 0.0086 | 56959.48 | 0.01 | ZTF | 0.099723 | 6.9e-07 | 1.195 | 0.7069 |  |  |  |  | 48.6 | 34.4 | 2.5
Likely DAV |  | WD J120650.89-380549.23 | 0.072198 | 3.6e-07 | 0.0079 | 0.004 | 56893.04 | 0.0 | TESS |  |  |  |  | 0.072209 | 1.86e-05 | 0.0018 | 0.0011 | 47.4 | 37.3 | 8.1
Known DAV |  | WD J195227.88+250929.18 | 0.07111 | 7.6e-07 | 0.0036 | 0.0031 | 56960.12 | 0.01 | ZTF, TESS | 0.071112 | 3.3e-07 | 0.2168 | 0.1663 | 0.071111 | 3e-07 | 0.0009 | 0.0006 | 33.9 | 17.1 | 3.7*
Known DAV |  | WD J215823.88-585353.81 | 0.086112 | 5.8e-07 | 0.0079 | 0.0037 | 56907.42 | 0.0 | TESS |  |  |  |  | 0.086111 | 8.4e-07 | 0.0003 | 0.0003 | 37.9 | 22.1 | 28.9**
Likely Spot |  | WD J011157.12+313632.67 | 9.814925 | 0.01994233 | 0.0043 | 0.0043 | 56897.32 | 1.42 | ZTF | 9.821594 | 0.00612669 | 0.3733 | 0.2035 |  |  |  |  | 57.6 | 49.9 | 12.3
Likely Spot |  | WD J013832.02-195446.58 | 3.941892 | 0.00119064 | 0.0051 | 0.003 | 56891.56 | 0.16 | ZTF | 3.943017 | 0.00196275 | 0.3572 | 0.3089 | 3.942033 | 0.00057022 | 0.0099 | 0.003 | 43.4 | 35.1 |  $<$0.1
Likely Spot |  | WD J020322.94+255851.90 | 25.724439 | 0.04739078 | 0.0346 | 0.0185 | 56893.56 | 0.86 | TESS |  |  |  |  | 31.755639 | 5.15051111 | 0.0047 | 0.0044 | 65.7 | 55.8 | 10.2
Likely Spot |  | WD J024235.52-820636.32 | 3.342828 | 0.00118396 | 0.0068 | 0.0049 | 56897.31 | 0.21 | TESS |  |  |  |  | 3.339775 | 0.00235079 | 0.0008 | 0.0006 | 33.8 | 12.5 | 1.2
Likely Spot |  | WD J052026.35+381240.87 | 6.785561 | 0.00458165 | 0.0084 | 0.0051 | 56908.17 | 0.38 | ZTF, TESS | 6.795878 | 0.00127562 | 0.6634 | 0.1692 | 6.830475 | 0.04033464 | 0.0067 | 0.001 | 61.4 | 53.6 | 24.6
Likely Spot |  | WD J062555.04-141442.31 | 4.459511 | 0.00126425 | 0.0193 | 0.0075 | 56920.07 | 0.15 | ZTF, TESS | 4.463656 | 0.00153086 | 0.7396 | 0.4556 | 4.734681 | 0.06312842 | 0.0027 | 0.0014 | 47.8 | 37.3 |  $<$0.1
Likely Spot |  | WD J072758.87+101157.08 | 0.491355 | 2.25e-05 | 0.0063 | 0.0055 | 56918.41 | 0.03 | ZTF | 0.491394 | 1.51e-05 | 0.4658 | 0.2585 |  |  |  |  | 64.3 | 54.5 | 25.1
Likely Spot |  | WD J083531.17+533230.91 | 2.163019 | 0.00042838 | 0.0135 | 0.009 | 56909.2 | 0.12 | ZTF | 2.161886 | 0.00042694 | 1.6366 | 1.0268 |  |  |  |  | 49.1 | 40.6 | 33.7
Likely Spot |  | WD J090212.89-394553.32 | 3.560872 | 0.00073476 | 0.0081 | 0.0028 | 56964.15 | 0.1 | TESS |  |  |  |  | 3.642272 | 0.05924833 | 0.0018 | 0.0016 | 31.6 | 10.6 | 0.6
Likely Spot |  | WD J115033.35-063618.07 | 0.245574 | 2.62e-06 | 0.0118 | 0.0039 | 56876.94 | 0.0 | ZTF, TESS | 0.245557 | 6.9e-06 | 0.2916 | 0.3757 | 0.245566 | 1.33e-05 | 0.0011 | 0.0008 | 56.5 | 48.7 | 9.8
Likely Spot |  | WD J124740.10+303007.41 | 225.656194 | 1.46535889 | 0.0216 | 0.0057 | 56878.2 | 3.13 | ZTF | 228.333778 | 2.97987222 | 0.508 | 0.2783 | 1545.405833 | 377777.7778 | 0.0474 | 11.0918 | 51.9 | 39.8 | 2.2
Likely Spot |  | WD J144410.08-214338.33 | 2.120309 | 0.0011789 | 0.0037 | 0.0061 | 56902.83 | 0.33 | ZTF | 2.120568 | 0.00021151 | 0.6368 | 0.328 |  |  |  |  | 65.6 | 50.7 | 35.5
Likely Spot |  | WD J154801.37+623611.57 | 4.736575 | 0.00205755 | 0.0224 | 0.0148 | 56875.26 | 0.2 | ZTF | 4.736792 | 0.00128098 | 0.7656 | 0.4439 |  |  |  |  | 34.2 | 11.1 | 0.1
Likely Spot |  | WD J165335.21-100116.33 | 79.865139 | 0.29106056 | 0.0143 | 0.0038 | 56922.1 | 1.61 | ZTF | 79.478111 | 0.579565 | 0.5255 | 0.578 |  |  |  |  | 43.2 | 39.6 |  $<$0.1
Likely Spot |  | WD J185924.85+330157.53 | 1.634021 | 3.47e-05 | 0.354 | 0.006 | 56926.42 |  | ZTF | 1.634515 | 0.00050539 | 0.5311 | 0.4539 |  |  |  |  | 35.2 | 18.1 | 40.7*
Likely Spot |  | WD J215432.26+634154.11 | 0.934589 | 6.78e-05 | 0.0244 | 0.015 | 56892.59 | 0.04 | ZTF | 0.934499 | 5.65e-05 | 0.6797 | 0.4345 |  |  |  |  | 33.8 | 10.6 | 0.6
Likely Spot |  | WD J221452.56-314333.98 | 7.392242 | 0.00398858 | 0.0142 | 0.0071 | 56951.62 | 0.35 | TESS |  |  |  |  | 6.902656 | 0.13466103 | 0.0063 | 0.003 | 49.5 | 43.3 | 0.2
Known Spot |  | WD J003512.88-122508.84 | 0.605106 | 6.89e-06 | 0.078 | 0.0054 | 56879.66 |  | ZTF, TESS | 0.60499 | 1.93e-05 | 0.4396 | 0.2066 | 0.604392 | 26.48977778 | 0.0 | 0.0 | 65.5 | 51.2 | 25.3
Known Spot |  | WD J031715.85-853225.56 | 0.201399 | 1.92e-06 | 0.0362 | 0.013 | 56897.19 | 0.01 | TESS |  |  |  |  | 0.201389 | 0.00105979 | 0.0 | 0.0003 | 32.5 | 8.8 |  $<$0.1
Known Spot |  | WD J041246.85+754942.26 | 0.344425 | 9.77e-06 | 0.0066 | 0.0036 | 56937.29 | 0.12 | ZTF, TESS | 0.344443 | 1.04e-05 | 0.2687 | 0.1765 | 0.344439 | 5.52e-06 | 0.0013 | 0.0006 | 33.1 | 14.6 | 4.2
Known Spot |  | WD J053432.93+770757.40 | 0.723311 | 7.13e-05 | 0.0076 | 0.0085 | 56900.79 | 0.06 | ZTF, TESS | 0.723223 | 16.23804444 | 0.0 | 0.0064 | 0.72334 | 0.00451125 | 0.0 | 0.0004 | 35.6 | 13.5 | 5.5*
Known Spot |  | WD J095125.94+530930.72 | 82.886 | 1.00760111 | 0.0132 | 0.0119 | 56918.71 | 6.77 | ZTF, TESS | 82.097083 | 0.5039775 | 0.7059 | 0.509 | 83.268694 | 0.14100106 | 0.0038 | 0.0007 | 36.4 | 25.6 |  $<$0.1
Known Spot |  | WD J125230.93-023417.72 | 0.088057 | 0.00133891 | 0.0 | 0.0055 | 56890.23 | 7.57 | TESS |  |  |  |  | 0.088 | 5.57e-05 | 0.0023 | 0.003 | 54.4 | 45.2 | 0.1
Known Spot |  | WD J195629.23-010232.67 | 34.898417 | 0.07376844 | 0.016 | 0.0051 | 56917.58 | 1.05 | TESS |  |  |  |  | 34.644361 | 0.40300639 | 0.0047 | 0.0003 | 48.0 | 41.6 |  $<$0.1
Known Spot |  | WD J202932.51+070107.70 | 6.957214 | 0.00222029 | 0.0159 | 0.0045 | 56959.12 | 0.18 | ZTF | 6.971394 | 0.00149846 | 1.11 | 0.3097 | 7.140053 | 0.06677989 | 0.0173 | 0.0044 | 44.0 | 36.0 | 13.8

References. — ∗Gaia BP ($G_{\mathrm{BP}}$) band used in analysis instead of
Gaia G band. ∗∗Gaia RP ($G_{\mathrm{RP}}$) band used in analysis instead of
Gaia G band. Note that “Rev.” (revisit) is the average time between two Gaia
detections of a source, and “Std. Rev.” is the standard deviation of this
revisit time.