Microlensing Events in the Galactic Plane Using the Zwicky Transient Facility

In a gravitational microlensing event, the light from a background source is magnified by a foreground lensing object as the light rays emitted from the source are deflected by the gravitational field of the lensing object (Paczyński 1986, 1996). The lens, source, and observer are moving with respect to one another, and so a microlensing event can lead to a transient brightening and dimming of the source. Since microlensing is independent of the brightness of the lensing object, it serves as one of the very few ways to study "dark" objects such as exoplanets (rogue or otherwise), brown dwarfs, low-luminosity stars, neutron stars, and stellar-mass black holes. Microlensing is almost the only way to study isolated black holes. Probing the most massive of these stellar dark objects explores the most extreme densities and gravitational fields in the universe, placing these studies at the forefront of fundamental physics.

However, from a qualitative description alone, it is clear that microlensing events have low probability to be observed from the vantage point of an astronomer on Earth. Thus, early dedicated microlensing surveys were directed toward the parts of the sky with the highest density of sources, such as the Galactic bulge and the Large and Small Magellanic Clouds. These early surveys included Expérience pour la Recherche d'Objets Sombres (EROS; Aubourg et al. 1993), Optical Gravitational Lensing Experiment (OGLE; Udalski et al. 1992), the search for Massive Compact Halo Objects (Alcock et al. 1993), and Microlensing Observations in Astrophysics (Sako et al. 2008). Early surveys purposefully avoided the more sparsely populated Galactic plane, where finding microlensing events was deemed to be difficult due to the highly reduced numbers of both sources and lenses, and would thus lead to very low event rates per unit area on the sky.

The Zwicky Transient Facility (ZTF) is undertaking a survey of the entire Northern sky down to ∼21 mag, making use of a 47 deg² field-of-view camera, operating on a 1–3 days cadence. A several-day cadence is sufficient for detecting stellar-mass microlensing events in the Galactic bulge caused by brown dwarfs, white dwarfs, main-sequence stars, neutron stars, and stellar-mass black holes (Gaudi 2012). This observing cadence is even better suited for microlensing events in the Galactic plane, where they are expected to have longer timescales (Sajadian & Poleski 2019). Gould (2013) strongly advocated for a microlensing survey of the Galactic plane because these events are much more likely to be longer, which allows for the measurement of the "microlensing parallax" from the light curve. The microlensing parallax (not to be confused with the traditional distance parallax) causes deviations from the typical microlensing light curve due to the projection of the lens onto Earth's revolution around the Sun. The microlensing parallax provides another constraint on the lens mass by allowing an observer on Earth to view the microlensing event from two different vantage points.

Better yet, in the Galactic plane, microlensing events are also more likely to be located closer to Earth, which makes the measurement of the microlensing astrometric effect easier (e.g., Rybicki et al. 2018). Astrometry provides another constraint on the mass of the lens, leading to a possible total of three independent mass constraints that are more difficult to obtain for Galactic bulge events. Thus, a microlensing survey of the Galactic plane would reveal the distribution of exoplanets, isolated brown dwarfs, neutron stars, and black holes, as well as provide a novel exploration of the structure of the disk of the Milky Way. Theoretical predictions of the detection of Galactic plane microlensing events by the Rubin Observatory Legacy Survey of Space and Time were undertaken by Sajadian & Poleski (2019) and Street et al. (2018), and by ZTF including Medford et al. (2020).

EROS, as part of a three-year survey, looked at small regions in the sky toward the Galactic spiral arms (Derue et al. 2001). This study revealed the lower overall optical depth to microlensing for events located toward the plane compared to events located toward the bulge. The OGLE Galaxy Variability Survey (GVS; Udalski et al. 2015) looked toward the Galactic equator in the range 0° < ℓ < 50° and 190° < ℓ < 360°, and found that microlensing events in the plane are three times longer than events found toward the Galactic bulge (Mróz et al.2020b). Other studies have previously found a handful of microlensing events toward the Galactic plane (Griest et al. 2014; Moniez et al. 2017; Husseiniova et al. 2021). Both EROS and OGLE studies were concentrated in the Southern Hemisphere, while our study is located in the Northern Hemisphere. A pilot search through ZTF Data Release 2 (DR2) data already revealed a sizable population of microlensing candidate events (Mróz et al. 2020a), paving the way for a bigger study.

In this work, we search the three-year-long archive of ZTF Data Release 5 (DR5) to find microlensing events in the Galactic plane. In Section 2, we describe our data collection process. In Section 3, we outline our methodology including our accounting for false positives. In Section 4, we present the candidate microlensing events along with model parameters. We conclude with a discussion of the detection efficiency of our algorithm, and discuss implications on Galactic structure.

The ZTF is a photometric survey that uses a wide 47 deg² field-of-view camera on the Samuel Oschin 48 inch telescope at Palomar Observatory with g, r, and i filters (Graham et al. 2019; Masci et al. 2019; Bellm et al. 2019b; Dekany et al. 2020). In its first year of operations, ZTF carried out a public nightly Galactic plane survey in the g and r bands (Bellm et al. 2019a; Kupfer et al. 2021). This survey is in addition to the Northern Sky Survey, which operates on a 3 days cadence (Bellm et al. 2019b). The pixel size of the ZTF camera is 1'' and the median delivered image quality is 20 at FWHM.

We use ZTF DR5, and analyze all available Galactic plane fields (∣b∣ < 20°), which are a combination of public data taken from 2018 March–2021 January as well as the ZTF partnership and Caltech-exclusive data up to 2021 April. Light curves have a photometric precision of 0.01 mag at 13–14 mag down to a precision of 0.1–0.2 mag for the faintest objects at 20–21 mag. Due to Galactic reddening, we begin by only analyzing the brighter r-band light curves.

The entire data download process is done using Kowalski, a data archive tool developed for the ZTF collaboration ¹¹ (Duev et al. 2019). Potential events are followed up with baseline-corrected forced photometry provided for the ZTF collaboration through the Infrared Processing and Analysis Center ¹² (IPAC; Masci et al. 2019). While both raw photometry and forced photometry are PSF-fit photometry (PSF is the point-spread function), the forced photometry calculates photometry of the object on all available frames by forcing the location of the PSF to remain fixed according to the ZTF absolute astrometric reference. This has the effect of reducing the uncertainties compared to the raw photometry since ZTF absolute astrometry for frames is generally better than individual point-source astrometry. All final models are based on data taken from forced photometry. In total, we analyzed 194 fields, and the resulting trove has ∼2 × 10⁹ sources, which amounts to 535,218,421 light curves that contain at least 30 data points.

In essence, a microlensing event is an apparent amplification of an otherwise steady source. The simplest model of a microlensing light curve is the point-source, point-lens (PSPL) model. The model is described by the following equation:

$$\begin{eqnarray}F(t)=\left\{\begin{array}{ll}{F}_{s}A(t;{t}_{0},{u}_{0},{t}_{{\rm{E}}})+{F}_{b} & \mathrm{no}\ \mathrm{parallax}\\ {F}_{s}A(t;{t}_{0},{u}_{0},{t}_{{\rm{E}}},{\pi }_{\mathrm{EN}},{\pi }_{\mathrm{EE}})+{F}_{b} & \mathrm{with}\ \mathrm{parallax}\end{array}\right.\end{eqnarray} \tag{ 1 }$$

where F_s is the source flux and F_b the blended flux in the aperture that is not magnified during the lensing event. A(t) is the magnification as a function of time. t₀ is time of closest approach between the source and the lens, u₀ is the effective impact parameter at the time of closest approach, and t_E is the Einstein timescale of the event. The microlensing parallax vector, π _E, is split into its north and east components, π_EN and π_EE, which characterize the effect of the Earth's orbital rotation around the Sun (see Section 3.3). We refer the reader to reviews such as Paczyński (1996) and Gaudi (2012) for a detailed derivation of the shape of the light curve and discussion of model parameters. Modeling of PSPL events and events featuring microlensing parallax is implemented efficiently in MulensModel ¹³ (Poleski & Yee 2019), which we use for all modeling in this study.

3.1. Methodology

We perform the series of cuts shown in Table 1 to find microlensing events in ZTF data. We begin by inspecting raw photometry light curves in the r band. While even less affected by reddening, we did not use i-band data from ZTF due to their substantially lower number of epochs that are unsuitable for finding microlensing events. We inspect g-band data, if available, when obtaining forced photometry. All cuts were initially tested to rediscover the maximum number of previously found events in Mróz et al. (2020a), and were iteratively tested on simulated events injected into ZTF light curves and updated. Not all events reported in Mróz et al. (2020a) are rediscovered, because some are binary events with light curves strongly departing from the PSPL model. By limiting our events to those with t₀ ± 0.3t_E taking place within the ZTF DR5 observing baseline, we exclude some previously reported candidate events. This is done to ensure a more pure sample at the end of our selection process. Given our model assumptions and quality cuts, we recover ∼75% of the events reported in Mróz et al. (2020a).

Table 1. Cuts on ZTF Data to Find Microlensing Events

Criteria	Remarks	Number
Begin with all objects in ZTF Galactic plane fields	Must have at least 30 data points.	535,218,421
$\gamma \lt 0.9\,\mathrm{and}\,{\mathrm{log}}_{10}(0.9-\gamma )\gt -1.25{\mathrm{log}}_{10}(1/\eta )+0.75$	All statistically significant outbursts.	174,950
Model converges	PSPL model converges. Removes flat light curves.	108,116
Algorithm tested on previously found events and simulated data:
Npts,lens ≥ 6	Significant number of magnified points within lens window.
Amplitude ≥ 0.2	Small-amplitude false positives removed.
${\chi }_{\mathrm{red},\mathrm{tot}}^{2}\leqslant 3$	Full light curve modeled well.
${\chi }_{\mathrm{red},\mathrm{lens}}^{2}\leqslant 3$	Lens window modeled well.
t0 ± 0.3tE fully in data	Removes events before/after DR5 baseline.
u0 ≤ 1	Only sensible values of u0 kept.
0 ≤ tE ≤ 500 days	Long-timescale contaminants removed.
Amplitude ≥ 0.3 if tE ≥ 80 days	Low-amplitude, long-period variables removed.	606
Visual inspection	All candidates scanned with raw photometry	92
With forced photometry	Reliable photometry removes final contaminants	59
Rescan	Visual rescanning with different cuts	60

Note. All cuts applied to ZTF DR5 data to find microlensing events. The final algorithm finds 59 events, and another was serendipitously found after testing different cuts on the data, leading to a total of 60 events.

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3.1.1. Skewness–Von Neumann Space

We begin with r-band light curves that each contain at least 30 data points. The first cut we apply to our data set serves two purposes: (1) pick out statistically significant deviations during quiescence and (2) find brightening as opposed to dimming events in an otherwise static light curve. The Von Neumann statistic, η, is meant to do the former, and the skewness, γ, the latter:

$$\begin{eqnarray}&&\eta ({\rm{von}}\,{\rm{Neumann}})=\displaystyle \sum _{i=2}^{N}\displaystyle \frac{{\left({x}_{i}-{x}_{i-1}\right)}^{2}}{(N-1){\hat{\sigma }}^{2}}\end{eqnarray} \tag{ 2 }$$

$$\begin{eqnarray}&&\gamma (\mathrm{skewness})=\sum _{i=1}^{N}\displaystyle \frac{{\left({x}_{i}-\overline{x}\right)}^{3}}{N{\hat{\sigma }}^{3}}\end{eqnarray} \tag{ 3 }$$

where $\hat{\sigma }$ is the sample standard deviation. The von Neumann statistic is defined as the mean square successive difference divided by the sample variance. Therefore, statistically significant bursts will lead to an overall large variance, while keeping a small successive difference that makes η small in those events. So we are looking for small η. Furthermore, a positive skewness corresponds to a dimming event, while a negative skewness corresponds to a brightening event. Wyrzykowski et al. (2016) found an explicit condition similar to the one outlined in Table 1 in γ–η space, while we modify it to find all events previously found in Mróz et al. (2020a). Our condition in γ–η space is $\gamma \lt 0.9\,\mathrm{and}\,{\mathrm{log}}_{10}(0.9-\gamma )\gt -1.25\,{\mathrm{log}}_{10}(1/\eta )+0.75$.

3.1.2. Cuts Based on Modeling

As seen in Table 1, the initial cut on all data based on skewness–von Neumann space reduces the sample size by a factor of ∼3 × 10⁻⁴. We then fit the data to the PSPL model. In our modeling routine, we account for possible outliers in the data due to anomalous effects such as poor weather or corrupted data. We pick a fixed "lensing window" of 360 days during which a lensing event may take place (following the methodology of Mróz et al. 2017). We remove light curves for which fewer than six magnified points are located within this window, as well as light curves for which the remaining number of points is fewer than 30. These cuts ensure that we have a sufficient number of data points for modeling a microlensing event within the lensing window, as well as enough data points out the window, to determine whether the light curve is quiescent outside the lensing event. The latter is done to ensure the source was quiescent outside the lensing window and to discard the possibility of it being intrinsically variable.

We also remove events with an outburst magnitude (magnitude difference between peak of microlensing model and quiescent state) less than 0.2 mag. This removes false positives such as outbursting Be stars or anomalous weather conditions leading to photometric variations. We then calculate the reduced chi-squared statistic:

$$\begin{eqnarray}&&{\chi }_{\mathrm{red}}^{2}=\displaystyle \frac{1}{N-m}\sum _{i}^{N}\displaystyle \frac{{\left({F}_{\mathrm{model}}({t}_{i})-{F}_{\mathrm{data}}({t}_{i})\right)}^{2}}{{\sigma }_{i}^{2}}\end{eqnarray} \tag{ 4 }$$

where N is the total number of data points, m is the number of parameters in the fitted model, and F_model and F_data are the best-fit model flux and observed flux, respectively. We discard light curves for which ${\chi }_{\mathrm{red}}^{2}\lt 3$ both over the lensing window and over the entire light curve. We calculate this statistic for both cases to ensure to avoid false positives where a non-quiescent source undergoes a well-modeled outburst or situations where a non-variable source undergoes a poorly modeled outburst.

We then exclude events for which t₀ ± 0.3t_E is not fully located within the available data. This ensures that we sample enough of the light curve to assess its symmetry about t₀ and ensure it is a microlensing event and not an eruptive phenomenon with an asymmetric outburst. Models with u₀ > 1 would require amplitudes lower than ∼0.3 mag, which are difficult to disentangle from noise or false positives within our sample. Finally, we place cuts based on the best-fit characteristic timescale, t_E. Since the overall temporal baseline for ZTF DR5 is ∼1100 days, we exclude events with t_E > 500 days. We also exclude events with amplitudes less than 0.3 mag if they are longer than 80 days. This cut filters out long-period, low-amplitude variables.

After all these cuts, we are left with ∼1 × 10⁻⁶ of our original sample (see Table 1). We visually inspect the r-band raw photometry for false positives. We then request IPAC forced photometry of the remaining candidates in r, g, and i bands. Note that i-band photometry is only used to discard false positives such as long-period variable stars. Using both r- and g-band photometry, we exclude events that are not achromatic, such as supernovae and variable stars. While iterating this process over different series of cuts, we serendipitously found another microlensing event and included it as part of our final sample of 60 events—a sample size ∼10⁻⁷ of the initial set of light curves in ZTF DR5.

3.2. MCMC Parameter Exploration

We use Markov Chain Monte Carlo (MCMC) through the emcee package (Hogg & Foreman-Mackey 2018) as a way to obtain quantitative estimates of model parameters and their uncertainties for each of our sample microlensing events. Microlensing light curves exhibit a strong continuous degeneracy between t_E and u₀, where a long Einstein timescale can be compensated by decreasing the value of the impact parameter. There are also discrete degeneracies when parallax parameters, π_EN and π_EE, are introduced, which can then lead to two or four possible models.

Since MCMC provides a natural way to provide physical priors on our model as well as to quantitatively explore parameter degeneracies, we use it to provide model parameters for each event once forced photometry is obtained. We set flat priors on t_eff = u₀ t_E between 0 and 2000 days, and a flat prior on t₀ and for u₀ ≥ 0 (note that we allow u₀ < 0 in parallax models). If both r- and g-band data are available, we fit all data simultaneously. Since F(t) is linear in both F_s and F_b (Equation (1)), we need not include them in the likelihood function of the MCMC analysis and can simply extract their posterior values from the other model parameters. We do, however, include them in the prior to allow for blending:

$$\begin{eqnarray}{{ \mathcal L }}_{\mathrm{prior}}=\left\{\begin{array}{ll}1 & \mathrm{if}\,{F}_{b}\geqslant 0\\ \exp \left(-\displaystyle \frac{{F}_{b}^{2}}{2{\sigma }^{2}}\right) & \mathrm{if}\,{F}_{b}\lt 0\end{array}\right.\end{eqnarray} \tag{ 5 }$$

where $\sigma ={F}_{\min }/3$ and ${F}_{\min }$ is the flux corresponding to r = 21. In Section 4, we report credible intervals between the 16th and 84th percentiles for parameters u₀, t₀, t_E, and also π_EE and π_EN if we find the parallax effect to be statistically significant (see Section 3.3).

3.3. Events with Microlensing Parallax

Table 3 in the Appendix lists all 60 events found in ZTF DR5, along with model parameters resulting from the MCMC fit. We find that 22 of the 60 events were previously reported by Mróz et al. (2020a), leading to 38 new events. The locations of analyzed fields and events are presented in Figure 1.

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4.1. Detection Efficiencies

Once we obtain our final sample of 60 microlensing events, we identify all ZTF fields where events are located. In each field, we randomly select 100,000 indices corresponding to the observed light curve of a source within the field. Following the method of Mróz et al. (2020b), we then inject a simulated microlensing light curve taking place within the observing baseline of ZTF DR5, with parameters ${u}_{0},{t}_{0},\mathrm{log}{t}_{{\rm{E}}}$ selected from a flat distribution. We do not inject light curves with the microlensing parallax effect.

We then run our event selection methodology as described in Section 3.1 and see whether the event extracted passes our series of cuts or not. After running this over all simulated events, over all ZTF fields where we have found one of our 60 sample events, we construct efficiency curves shown in Figure 2. The efficiency is defined as the ratio of the number of detected events to the number of injected events for bins in t_E. Figure 1 shows the location in Galactic coordinates where all 60 microlensing events are located, and additionally highlights the fields for which detection efficiencies are plotted in Figure 2.

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In combination, those figures show that, on the whole, detection efficiencies are lower for events located closer to the Galactic center. This is a combined effect of the reduced amount of time that these low-decl. fields were observed by ZTF and non-optimal photometry in the crowded areas of this part of the Galaxy. Our simulations show that if a microlensing event takes place during a seasonal gap in observing (i.e., ZTF cannot observe every field of the sky continuously throughout the year), then our detection algorithm will fail to find it due to limited data.

Events with t_E between 1 and 10 days are hard to detect, as seen in Figure 2, leading to a sharply dropping efficiency with timescale, while efficiencies remain mostly flat for t_E between 10 and 100 days. Longer-timescale events with 2t_E approaching the entire observing window of ZTF DR5 (∼1100 days) become hard to detect and lead to a decreasing efficiency on the largest timescales.

4.2. Distribution of Einstein Timescales

Given detection efficiencies (ε_i for field i), we calculate the mean Einstein timescale:

$$\begin{eqnarray}&&\langle {t}_{{\rm{E}}}\rangle =\displaystyle \frac{\sum _{i}{t}_{E,i}{/\varepsilon }_{i}({t}_{E,i})}{\sum _{i}1/{\varepsilon }_{i}({t}_{E,i})}\end{eqnarray} \tag{ 6 }$$

where each efficiency is evaluated on the relevant Einstein timescale. Figure 3 shows the distribution of Einstein timescales, weighted by the reciprocal of detection efficiency to create a statistically corrected histogram. We obtain a mean Einstein timescale of 〈t_E〉 = 61.0 ± 8.3 days, demonstrating that, on average, Galactic plane microlensing events are about three times as long as Galactic bulge events, which have 〈t_E〉(bulge) = 22.5 ± 5.4 days (Mróz et al. 2017). This is in agreement with a study of the southern Galactic plane, which found 〈t_E〉 = 61.5 ± 5.0 days (Mróz et al. 2020b).

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4.3. Distribution of Events and Galactic Structure

Plotting the distribution of events as a function of Galactic longitude and latitude serves as an independent probe of Galactic structure. Figure 1 demonstrates that while we searched Galactic fields up to ∣b∣ < 20°, the majority of microlensing events are located within 10° of the Galactic plane.

As can be seen from Figure 4, the normalized number of events decreases with increasing (absolute) longitude and latitude, tracing the decreasing density of objects in the Galaxy in those regions. We emphasize that the distribution of the number of events in Figure 4 is statistically corrected from our calculations of detection efficiency from simulations. This corrects for the number of times ZTF actually observed a given field in the sky. Assuming an exponential distribution of microlensing events as a function of absolute longitude, $n({\ell })={n}_{0}{e}^{-| {\ell }| /{{\ell }}_{0}}$, we use maximum likelihood estimation to find a characteristic angular scale of ℓ₀ = 37° ± 4°, which is consistent with that found by Mróz et al. (2020b). Moreover, the right panel of Figure 4 shows that the normalized number of events found toward the Galactic midplane (∣b∣ ≈ 0°) decreases dramatically due to strong interstellar reddening. To represent extinction, E(B − V) is plotted, taken from Schlegel et al. (1998). This is in reasonable agreement with the results presented by Mróz et al. (2020b), but more detailed statistics, which would result from a larger data set, are needed to confidently conclude this is the case in ZTF data.

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Figure 5 shows the number of events as a function of Einstein timescale, but in three separate longitude bins: ℓ = 0°–20°, 20°–70°, and 70°–180°. These bins were chosen to keep an approximately equal number of events in each bin. The plots in Figure 5 show that the events at longitudes ℓ < 20° are shorter than those at longitudes ℓ > 20°. This is indicative of tracing events closer to the Galactic bulge, where distances to source and lens are larger and relative proper motions are higher—both contributing to an overall shorter Einstein timescale. Figure 5 suggests that further out in the Galactic plane there is a difference in the Einstein timescale between bins ℓ = 20°–70° and ℓ = 70°–180°, but the large error bars indicate that we do not have a large enough statistical sample to conclude there is a dependence of Einstein timescale on Galactic longitude for ℓ > 20°. With a ∼4 times larger sample size of 216 Galactic plane microlensing events, Mróz et al. (2020b) also found there was no significant correlation between Einstein timescale and Galactic coordinates within the Galactic plane. We also investigated whether there was a statistically significant dependence of Einstein timescale on Galactic latitude and found no significant trend given our current data set.

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4.4. Comparisons with Theoretical Models and Previous Work

We have shown that Galactic plane microlensing events are present in ZTF data and have compiled a list of 60 candidate events, including three that show signatures of the microlensing parallax effect. We presented model parameters for all events, of which the Einstein timescale, t_E, is also used to probe Galactic structure. By injecting simulated microlensing events into ZTF fields where we have found true events in the data, we calculate detection efficiencies that are used to correctly calculate the average timescale of all events: 〈t_E〉 = 61.0 ± 8.3 days.

We determine that, on the whole, Galactic plane microlensing events (t_E ∼ 60 days) are three times longer than events located in the Galactic bulge (t_E ∼ 20 days), consistent with prior studies. Furthermore, from our modest sample, we see signatures of Galactic structure, where the normalized number of events decreases exponentially as a function of Galactic longitude with a characteristic angular scale of ∼37°. Microlensing events at ℓ < 20° have shorter Einstein timescales than those at ℓ > 20°, demonstrating that we are probing the greater relative motion and larger distance to events at low longitudes closer to the Galactic bulge. A sharp decrease in events at ∣b∣ ≈ 0° is also indicative of strong reddening at the lowest latitudes of the Galactic plane due to interstellar dust.

Microlensing events taking place in the Galactic plane can now be found within large surveys such as OGLE-GVS, Gaia, and ZTF. Through the microlensing parallax effect (both Earth- and space-based), microlensing offers strong prospects for measuring the masses of dark objects in the disk of the Milky Way, particularly isolated objects.

This study is part of a two-part series. Low- to medium-resolution spectroscopy (R ∼ 300–5000) of the 60 candidates will be undertaken and reported. While we believe our detection algorithm has a high level of purity, spectroscopy will filter out the last possible false positives such as Be star outbursts or long-period variable stars. Via spectroscopy we will determine the distance to our events with low blending (F_s ≳ 0.7) and subsequently report the best-fit lens mass corresponding to each low-blend event, particularly if a significant parallax measurement is also available.

The authors thank the ZTF Variable Star Group for insightful discussions. A.C.R. acknowledges funding support from the Caltech Anthony Fellowship through the Division of Physics, Mathematics, and Astronomy.

This work is based on observations obtained with the Samuel Oschin Telescope 48 inch and the 60 inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. Major funding has been provided by the US National Science Foundation under grant No. AST-1440341 and by the ZTF partner institutions: the California Institute of Technology, the Oskar Klein Centre, the Weizmann Institute of Science, the University of Maryland, the University of Washington, Deutsches Elektronen-Synchrotron, the University of Wisconsin-Milwaukee, and the TANGO Program of the University System of Taiwan.

The ZTF forced-photometry service was funded under the Heising–Simons Foundation grant #12540303 (PI: Graham).

This work has 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.

We present a list of all 60 microlensing events in Table 2, ordered by coordinates, ZTF ID, and Gaia alert (if available; Hodgkin et al. 2013; Kruszyńska & Wyrzykowski 2018).

In Table 3, we present all model parameters from the MCMC fit including models fitting for parallax (if statistically significant). All errors are reported as the 16th and 84th percentiles of the posterior distribution. r_s and g_s are the source magnitudes in the r and g bands, respectively. f_s is the fractional contribution of the source to the total observed flux (i.e., f_s = F_s /(F_s + F_b )) where F_s is the source flux and F_b is the blended flux.

Table 3. List of Microlensing Events in ZTF Data with MCMC Modeling Parameters

ID	${t}_{0}\,(\mathrm{HJD}^{\prime} )$	tE (days)	u0	πEN	πEE	rs (mag)	fs,r	gs (mag)	fs,g	χ2/d.o.f.
ZTF19aabbuqn	${8506.17}_{-0.37}^{+0.39}$	${38.62}_{-7.68}^{+8.85}$	${0.281}_{-0.070}^{+0.106}$	⋯	⋯	${19.85}_{-0.46}^{+0.38}$	${0.26}_{-0.07}^{+0.10}$	${21.30}_{-0.46}^{+0.38}$	${0.28}_{-0.07}^{+0.11}$	831.4/413
ZTF19aainwvb	${8658.05}_{-0.44}^{+0.45}$	${160.12}_{-2.37}^{+2.41}$	${0.444}_{-0.011}^{+0.011}$	⋯	⋯	${18.28}_{-0.04}^{+0.04}$	${1.30}_{-0.06}^{+0.06}$	${19.39}_{-0.04}^{+0.04}$	${1.31}_{-0.06}^{+0.06}$	7819.5/2189
ZTF19aainwvb	${8625.27}_{-0.50}^{+0.52}$	${185.92}_{-3.91}^{+3.78}$	${0.128}_{-0.005}^{+0.005}$	$-{0.29}_{-0.01}^{+0.01}$	${0.00}_{-0.00}^{+0.00}$	${19.02}_{-0.04}^{+0.03}$	${0.64}_{-0.02}^{+0.01}$	${20.10}_{-0.04}^{+0.03}$	${0.67}_{-0.02}^{+0.02}$	4584.6/2189
ZTF19aainwvb	${8618.20}_{-0.66}^{+0.68}$	${333.45}_{-17.58}^{+20.21}$	${0.025}_{-0.006}^{+0.006}$	$-{0.17}_{-0.01}^{+0.01}$	$-{0.04}_{-0.00}^{+0.00}$	${19.76}_{-0.07}^{+0.07}$	${0.33}_{-0.02}^{+0.02}$	${20.85}_{-0.07}^{+0.07}$	${0.34}_{-0.02}^{+0.02}$	4452.5/2189
ZTF19aainwvb	${8618.27}_{-0.75}^{+0.75}$	${333.35}_{-17.97}^{+20.36}$	$-{0.025}_{-0.007}^{+0.007}$	${0.17}_{-0.01}^{+0.01}$	${0.04}_{-0.00}^{+0.00}$	${19.76}_{-0.07}^{+0.07}$	${0.33}_{-0.02}^{+0.02}$	${20.85}_{-0.07}^{+0.07}$	${0.34}_{-0.02}^{+0.02}$	4452.5/2189
ZTF19aainwvb	${8625.29}_{-0.49}^{+0.51}$	${185.85}_{-3.76}^{+3.73}$	$-{0.129}_{-0.005}^{+0.005}$	${0.29}_{-0.01}^{+0.01}$	$-{0.00}_{-0.00}^{+0.00}$	${19.02}_{-0.03}^{+0.03}$	${0.64}_{-0.01}^{+0.01}$	${20.10}_{-0.03}^{+0.03}$	${0.67}_{-0.02}^{+0.01}$	4584.6/2189
ZTF19adbsiat	${8915.50}_{-0.81}^{+0.81}$	${58.86}_{-4.85}^{+6.47}$	${0.573}_{-0.088}^{+0.091}$	⋯	⋯	${18.56}_{-0.26}^{+0.27}$	${0.73}_{-0.15}^{+0.13}$	${19.57}_{-0.25}^{+0.27}$	${0.72}_{-0.14}^{+0.13}$	792.6/908
ZTF19aatwaux	${8637.05}_{-0.34}^{+0.35}$	${50.25}_{-2.90}^{+4.01}$	${0.179}_{-0.024}^{+0.021}$	⋯	⋯	${19.13}_{-0.12}^{+0.15}$	${0.93}_{-0.10}^{+0.11}$	${20.50}_{-0.12}^{+0.15}$	${0.88}_{-0.09}^{+0.10}$	1155.7/432
ZTF19abpxurg	${8713.62}_{-0.04}^{+0.04}$	${25.86}_{-1.24}^{+1.39}$	${0.062}_{-0.006}^{+0.006}$	⋯	⋯	${19.34}_{-0.08}^{+0.09}$	${0.98}_{-0.07}^{+0.07}$	${20.55}_{-0.08}^{+0.09}$	${0.85}_{-0.06}^{+0.06}$	734.2/732
ZTF20aaukggm	${8956.33}_{-0.28}^{+0.30}$	${54.23}_{-2.86}^{+3.22}$	${0.094}_{-0.014}^{+0.014}$	⋯	⋯	${17.83}_{-0.10}^{+0.10}$	${0.88}_{-0.07}^{+0.07}$	${20.24}_{-0.10}^{+0.10}$	${0.77}_{-0.06}^{+0.06}$	1806.3/459
ZTF18ablrdcc	${8353.81}_{-0.35}^{+0.34}$	${56.56}_{-6.15}^{+8.15}$	${0.150}_{-0.030}^{+0.030}$	⋯	⋯	${20.24}_{-0.20}^{+0.22}$	${0.99}_{-0.20}^{+0.18}$	⋯	⋯	385.1/435
ZTF19aawchkq	${8633.36}_{-1.02}^{+1.03}$	${55.42}_{-13.82}^{+19.12}$	${0.198}_{-0.069}^{+0.108}$	⋯	⋯	${20.73}_{-0.56}^{+0.52}$	${0.14}_{-0.05}^{+0.08}$	⋯	⋯	405.2/398
ZTF19abbwpl	${8677.90}_{-0.20}^{+0.20}$	${30.42}_{-3.62}^{+3.61}$	${0.530}_{-0.084}^{+0.116}$	⋯	⋯	${18.02}_{-0.34}^{+0.27}$	${0.33}_{-0.06}^{+0.08}$	${20.17}_{-0.35}^{+0.28}$	${0.30}_{-0.06}^{+0.08}$	985.4/473
ZTF18ablrbkj	${8262.27}_{-0.98}^{+0.92}$	${104.45}_{-42.82}^{+125.13}$	${0.121}_{-0.072}^{+0.114}$	⋯	⋯	${21.82}_{-0.83}^{+1.03}$	${0.40}_{-0.23}^{+0.29}$	⋯	⋯	179.6/322
ZTF19aaonska	${8612.70}_{-0.22}^{+0.23}$	${68.74}_{-2.54}^{+2.65}$	${0.276}_{-0.017}^{+0.017}$	⋯	⋯	${19.09}_{-0.08}^{+0.08}$	${0.91}_{-0.06}^{+0.06}$	${22.13}_{-0.08}^{+0.08}$	${0.49}_{-0.03}^{+0.03}$	627.9/647
ZTF20aawyizf	${9004.36}_{-1.72}^{+1.52}$	${1024.09}_{-525.33}^{+2375.70}$	${0.029}_{-0.021}^{+0.032}$	⋯	⋯	${23.14}_{-0.81}^{+1.33}$	${0.02}_{-0.01}^{+0.02}$	⋯	⋯	302.3/469
ZTF19aaprbng	${8629.03}_{-1.28}^{+1.30}$	${209.78}_{-44.84}^{+61.52}$	${0.291}_{-0.077}^{+0.105}$	⋯	⋯	${20.16}_{-0.44}^{+0.41}$	${0.22}_{-0.06}^{+0.09}$	${21.55}_{-0.44}^{+0.41}$	${0.23}_{-0.06}^{+0.09}$	735.5/788
ZTF20aauodap	${8976.89}_{-0.35}^{+0.38}$	${69.77}_{-5.65}^{+8.49}$	${0.158}_{-0.023}^{+0.020}$	⋯	⋯	${19.69}_{-0.14}^{+0.19}$	${1.01}_{-0.14}^{+0.16}$	⋯	⋯	256.0/459
ZTF20aawanug	${8980.72}_{-0.05}^{+0.05}$	${54.16}_{-3.09}^{+3.41}$	${0.113}_{-0.009}^{+0.010}$	⋯	⋯	${18.09}_{-0.09}^{+0.09}$	${0.51}_{-0.03}^{+0.03}$	${19.64}_{-0.09}^{+0.09}$	${0.52}_{-0.03}^{+0.03}$	1378.6/738
ZTF19abhkrjx	${8699.74}_{-0.01}^{+0.01}$	${22.71}_{-0.42}^{+0.45}$	${0.120}_{-0.003}^{+0.003}$	⋯	⋯	${18.24}_{-0.03}^{+0.03}$	${1.15}_{-0.03}^{+0.03}$	${20.88}_{-0.03}^{+0.03}$	${0.15}_{-0.00}^{+0.00}$	2282.3/912
ZTF19acigmif	${8793.48}_{-0.69}^{+0.67}$	${44.70}_{-14.11}^{+17.04}$	${0.195}_{-0.070}^{+0.144}$	⋯	⋯	${19.54}_{-0.75}^{+0.54}$	${0.15}_{-0.05}^{+0.12}$	${21.27}_{-0.73}^{+0.53}$	${0.16}_{-0.06}^{+0.13}$	1296.2/965
ZTF19aaekacq	${8546.02}_{-0.56}^{+0.57}$	${69.35}_{-7.22}^{+7.14}$	${0.428}_{-0.085}^{+0.117}$	⋯	⋯	${18.10}_{-0.33}^{+0.27}$	${0.36}_{-0.07}^{+0.09}$	${19.04}_{-0.32}^{+0.26}$	${0.34}_{-0.06}^{+0.08}$	1382.3/846
ZTF19abibzvr	${8300.95}_{-0.39}^{+0.40}$	${30.27}_{-3.45}^{+6.61}$	${0.331}_{-0.085}^{+0.066}$	⋯	⋯	${20.26}_{-0.25}^{+0.40}$	${0.98}_{-0.26}^{+0.30}$	⋯	⋯	499.2/809
ZTF18abqbeqv	${8386.97}_{-1.29}^{+1.33}$	${68.68}_{-12.30}^{+16.96}$	${0.690}_{-0.197}^{+0.244}$	⋯	⋯	${17.80}_{-0.61}^{+0.59}$	${0.35}_{-0.14}^{+0.18}$	${18.81}_{-0.61}^{+0.59}$	${0.39}_{-0.15}^{+0.19}$	1928.3/975
ZTF20abkymiq	${9088.46}_{-0.06}^{+0.06}$	${83.77}_{-1.52}^{+1.58}$	${0.077}_{-0.002}^{+0.002}$	⋯	⋯	${18.57}_{-0.03}^{+0.03}$	${0.81}_{-0.02}^{+0.02}$	${21.38}_{-0.03}^{+0.03}$	${0.96}_{-0.02}^{+0.02}$	1033.5/914
ZTF20abaptby	${8991.77}_{-0.11}^{+0.11}$	${12.69}_{-0.71}^{+0.95}$	${0.261}_{-0.030}^{+0.028}$	⋯	⋯	${18.47}_{-0.13}^{+0.16}$	${0.86}_{-0.10}^{+0.10}$	⋯	⋯	631.1/813
ZTF19aamrjmu	${8579.63}_{-0.11}^{+0.11}$	${66.07}_{-2.92}^{+3.09}$	${0.133}_{-0.009}^{+0.009}$	⋯	⋯	${20.15}_{-0.08}^{+0.07}$	${0.74}_{-0.04}^{+0.04}$	${21.07}_{-0.08}^{+0.07}$	${0.84}_{-0.05}^{+0.05}$	1623.5/1722
ZTF19abijroe	${8695.88}_{-0.07}^{+0.07}$	${20.81}_{-1.77}^{+2.03}$	${0.284}_{-0.032}^{+0.034}$	⋯	⋯	${20.17}_{-0.16}^{+0.16}$	${1.58}_{-0.42}^{+0.37}$	⋯	⋯	644.3/719
ZTF19aavndrc	${8637.35}_{-0.08}^{+0.08}$	${74.89}_{-2.91}^{+3.12}$	${0.091}_{-0.005}^{+0.005}$	⋯	⋯	${19.96}_{-0.06}^{+0.07}$	${0.38}_{-0.02}^{+0.02}$	⋯	⋯	901.2/799
ZTF20abhmltf	${9044.66}_{-0.44}^{+0.44}$	${40.98}_{-2.08}^{+3.59}$	${0.404}_{-0.049}^{+0.034}$	⋯	⋯	${18.31}_{-0.13}^{+0.19}$	${0.89}_{-0.10}^{+0.13}$	${19.08}_{-0.12}^{+0.19}$	${0.87}_{-0.09}^{+0.12}$	841.8/700
ZTFJ1853.5-0415	${8291.99}_{-0.52}^{+0.52}$	${11.87}_{-0.58}^{+0.64}$	${0.811}_{-0.055}^{+0.033}$	⋯	⋯	${17.89}_{-0.08}^{+0.14}$	${0.94}_{-0.07}^{+0.11}$	⋯	⋯	1322.7/806
ZTF19aaxsdqz	${8676.11}_{-0.06}^{+0.06}$	${61.87}_{-1.97}^{+2.20}$	${0.177}_{-0.008}^{+0.008}$	⋯	⋯	${19.01}_{-0.05}^{+0.06}$	${1.03}_{-0.05}^{+0.05}$	${21.73}_{-0.05}^{+0.06}$	${0.74}_{-0.03}^{+0.03}$	730.7/674
ZTF19abcpukt	${8691.38}_{-0.00}^{+0.00}$	${446.70}_{-74.89}^{+141.70}$	${0.003}_{-0.001}^{+0.001}$	⋯	⋯	${21.51}_{-0.20}^{+0.30}$	${0.38}_{-0.06}^{+0.05}$	⋯	⋯	5193.3/791
ZTFJ1856.2+1007	${8367.43}_{-0.05}^{+0.05}$	${29.79}_{-4.01}^{+4.80}$	${0.051}_{-0.008}^{+0.010}$	⋯	⋯	${21.79}_{-0.19}^{+0.20}$	${0.16}_{-0.02}^{+0.03}$	${22.88}_{-0.19}^{+0.20}$	${0.19}_{-0.03}^{+0.03}$	777.3/932
ZTF18abhxjmj	${8249.16}_{-0.23}^{+0.22}$	${35.35}_{-1.21}^{+1.31}$	${0.256}_{-0.015}^{+0.015}$	⋯	⋯	${19.26}_{-0.08}^{+0.08}$	${1.64}_{-0.21}^{+0.20}$	${20.69}_{-0.07}^{+0.07}$	${1.62}_{-0.20}^{+0.19}$	703.0/903
ZTF19abgslgl	${8683.43}_{-0.35}^{+0.37}$	${37.33}_{-4.97}^{+6.17}$	${0.159}_{-0.035}^{+0.044}$	⋯	⋯	${21.08}_{-0.27}^{+0.27}$	${0.35}_{-0.06}^{+0.07}$	${21.73}_{-0.26}^{+0.25}$	${0.39}_{-0.06}^{+0.07}$	743.0/666
ZTF20aawxugf	${8969.91}_{-1.14}^{+1.08}$	${49.30}_{-3.82}^{+5.92}$	${0.500}_{-0.083}^{+0.061}$	⋯	⋯	${18.70}_{-0.19}^{+0.29}$	${0.78}_{-0.12}^{+0.15}$	${19.42}_{-0.19}^{+0.29}$	${0.87}_{-0.15}^{+0.18}$	822.3/718
ZTFJ1856.2-0110	${8352.71}_{-0.25}^{+0.26}$	${20.20}_{-6.54}^{+11.68}$	${0.137}_{-0.069}^{+0.124}$	⋯	⋯	${19.98}_{-0.72}^{+0.71}$	${0.19}_{-0.08}^{+0.15}$	${21.27}_{-0.73}^{+0.73}$	${0.25}_{-0.11}^{+0.18}$	222.3/994
ZTF20aawxtfq	${8975.61}_{-0.66}^{+0.62}$	${76.98}_{-16.61}^{+36.21}$	${0.096}_{-0.038}^{+0.042}$	⋯	⋯	${21.41}_{-0.41}^{+0.57}$	${0.04}_{-0.02}^{+0.02}$	${23.20}_{-0.40}^{+0.57}$	${0.02}_{-0.01}^{+0.01}$	1318.7/1035
ZTF19acctqyc	${8756.40}_{-0.93}^{+0.98}$	${39.21}_{-1.99}^{+2.47}$	${0.470}_{-0.044}^{+0.036}$	⋯	⋯	${19.47}_{-0.12}^{+0.16}$	${1.07}_{-0.14}^{+0.15}$	${20.84}_{-0.12}^{+0.15}$	${1.11}_{-0.14}^{+0.16}$	783.9/937
Gaia19drz/AT2019ood	${8750.29}_{-0.93}^{+0.95}$	${83.36}_{-11.20}^{+13.11}$	${0.331}_{-0.068}^{+0.089}$	⋯	⋯	${19.76}_{-0.34}^{+0.31}$	${0.50}_{-0.11}^{+0.11}$	${21.22}_{-0.35}^{+0.32}$	${0.60}_{-0.15}^{+0.13}$	623.6/930
ZTF18abmoxlq	${8322.09}_{-0.35}^{+0.36}$	${111.34}_{-20.33}^{+28.77}$	${0.168}_{-0.041}^{+0.049}$	⋯	⋯	${19.18}_{-0.33}^{+0.35}$	${0.26}_{-0.06}^{+0.07}$	${20.02}_{-0.33}^{+0.35}$	${0.28}_{-0.06}^{+0.07}$	1039.3/721
ZTF19abjtzvc	${8709.79}_{-0.39}^{+0.38}$	${98.32}_{-22.21}^{+35.35}$	${0.218}_{-0.068}^{+0.086}$	⋯	⋯	${20.63}_{-0.45}^{+0.48}$	${0.40}_{-0.12}^{+0.14}$	⋯	⋯	575.5/594
ZTF19aaoocwc	${8579.41}_{-0.61}^{+0.53}$	${52.02}_{-5.22}^{+7.04}$	${0.226}_{-0.045}^{+0.047}$	⋯	⋯	${19.97}_{-0.25}^{+0.28}$	${0.83}_{-0.18}^{+0.16}$	⋯	⋯	577.1/720
ZTF18abaqxrt	${8302.65}_{-0.20}^{+0.21}$	${33.44}_{-2.29}^{+3.27}$	${0.606}_{-0.080}^{+0.072}$	⋯	⋯	${16.34}_{-0.20}^{+0.24}$	${0.76}_{-0.12}^{+0.12}$	⋯	⋯	863.0/256
ZTF19aatudnj	${8636.82}_{-0.45}^{+0.47}$	${615.12}_{-206.47}^{+869.35}$	${0.027}_{-0.016}^{+0.015}$	⋯	⋯	${22.73}_{-0.47}^{+0.98}$	${0.02}_{-0.01}^{+0.01}$	${24.53}_{-0.47}^{+0.98}$	${0.02}_{-0.01}^{+0.01}$	1905.9/1169
ZTF18aazdbym	${8272.97}_{-0.26}^{+0.25}$	${20.28}_{-2.08}^{+2.89}$	${0.488}_{-0.095}^{+0.093}$	⋯	⋯	${18.15}_{-0.30}^{+0.34}$	${0.63}_{-0.14}^{+0.13}$	${18.99}_{-0.29}^{+0.33}$	${0.70}_{-0.16}^{+0.14}$	896.9/979
ZTF20abkyuyk	${9085.44}_{-0.07}^{+0.07}$	${49.56}_{-1.75}^{+1.84}$	${0.261}_{-0.014}^{+0.014}$	⋯	⋯	${18.38}_{-0.07}^{+0.07}$	${0.45}_{-0.02}^{+0.02}$	${19.76}_{-0.07}^{+0.07}$	${0.44}_{-0.02}^{+0.02}$	2420.3/1245
ZTF20aavmhsg	${8983.14}_{-0.09}^{+0.09}$	${46.43}_{-2.78}^{+3.01}$	${0.120}_{-0.010}^{+0.011}$	⋯	⋯	${19.74}_{-0.10}^{+0.10}$	${0.36}_{-0.02}^{+0.03}$	${20.90}_{-0.10}^{+0.10}$	${0.35}_{-0.02}^{+0.02}$	1022.8/1153
ZTFJ1928.7+3039	${8369.91}_{-0.21}^{+0.20}$	${50.10}_{-8.27}^{+11.62}$	${0.064}_{-0.015}^{+0.018}$	⋯	⋯	${22.07}_{-0.28}^{+0.31}$	${0.49}_{-0.09}^{+0.09}$	${23.48}_{-0.27}^{+0.30}$	${0.15}_{-0.03}^{+0.04}$	477.7/589
ZTF20abmxjsq	${9051.45}_{-0.51}^{+0.52}$	${115.51}_{-28.49}^{+56.04}$	${0.139}_{-0.053}^{+0.061}$	⋯	⋯	${21.64}_{-0.45}^{+0.57}$	${0.09}_{-0.04}^{+0.04}$	${23.37}_{-0.45}^{+0.57}$	${0.07}_{-0.03}^{+0.04}$	931.3/1120
ZTF20abrtvbz	${9088.92}_{-0.22}^{+0.22}$	${59.90}_{-7.62}^{+9.09}$	${0.117}_{-0.020}^{+0.024}$	⋯	⋯	${21.35}_{-0.22}^{+0.21}$	${0.17}_{-0.03}^{+0.03}$	${22.12}_{-0.22}^{+0.21}$	${0.15}_{-0.02}^{+0.03}$	1243.2/1146
ZTF19aavisrq	${8651.81}_{-0.01}^{+0.01}$	${104.92}_{-4.33}^{+4.62}$	${0.015}_{-0.001}^{+0.001}$	⋯	⋯	${20.69}_{-0.05}^{+0.05}$	${0.14}_{-0.01}^{+0.01}$	${21.71}_{-0.05}^{+0.05}$	${0.11}_{-0.00}^{+0.00}$	1446.4/1243
ZTF19acaagdx	${8762.59}_{-0.04}^{+0.04}$	${115.99}_{-8.00}^{+9.21}$	${0.010}_{-0.001}^{+0.001}$	⋯	⋯	${21.83}_{-0.09}^{+0.10}$	${0.11}_{-0.01}^{+0.01}$	${22.49}_{-0.08}^{+0.09}$	${0.12}_{-0.01}^{+0.01}$	1829.6/1461
ZTF20abohkdo	${9061.86}_{-0.28}^{+0.27}$	${29.66}_{-6.39}^{+8.17}$	${0.174}_{-0.048}^{+0.076}$	⋯	⋯	${21.07}_{-0.44}^{+0.39}$	${0.14}_{-0.04}^{+0.06}$	⋯	⋯	597.1/809
ZTF18abtopdh	${8367.88}_{-0.03}^{+0.03}$	${24.67}_{-1.69}^{+1.76}$	${0.062}_{-0.006}^{+0.007}$	⋯	⋯	${20.92}_{-0.10}^{+0.10}$	${0.34}_{-0.02}^{+0.02}$	${22.56}_{-0.11}^{+0.10}$	${0.27}_{-0.02}^{+0.02}$	852.3/1005
ZTF20abbynqb	${9045.89}_{-0.17}^{+0.17}$	${50.97}_{-3.39}^{+3.34}$	${0.385}_{-0.035}^{+0.043}$	⋯	⋯	${17.45}_{-0.16}^{+0.14}$	${0.39}_{-0.04}^{+0.04}$	${18.53}_{-0.16}^{+0.14}$	${0.36}_{-0.03}^{+0.04}$	1461.2/1149
ZTF20abbynqb	${9045.19}_{-0.18}^{+0.17}$	${31.58}_{-1.11}^{+1.89}$	${0.658}_{-0.051}^{+0.034}$	$-{0.97}_{-0.12}^{+0.15}$	$-{0.48}_{-0.05}^{+0.05}$	${16.55}_{-0.09}^{+0.15}$	${0.90}_{-0.07}^{+0.10}$	${17.62}_{-0.09}^{+0.15}$	${0.83}_{-0.06}^{+0.09}$	1379.2/1149
ZTF20abbynqb	${9045.20}_{-0.18}^{+0.17}$	${31.75}_{-1.23}^{+1.89}$	$-{0.655}_{-0.036}^{+0.053}$	${0.96}_{-0.16}^{+0.12}$	${0.48}_{-0.05}^{+0.05}$	${16.57}_{-0.10}^{+0.15}$	${0.89}_{-0.08}^{+0.10}$	${17.63}_{-0.10}^{+0.15}$	${0.82}_{-0.07}^{+0.09}$	1379.3/1149
ZTF20abxwenr	${9117.33}_{-0.01}^{+0.01}$	${162.56}_{-14.23}^{+18.47}$	${0.006}_{-0.001}^{+0.001}$	⋯	⋯	${22.05}_{-0.10}^{+0.12}$	${0.31}_{-0.02}^{+0.02}$	⋯	⋯	643.4/655
ZTF18absrqlr	${8362.83}_{-0.11}^{+0.12}$	${37.17}_{-2.06}^{+2.30}$	${0.310}_{-0.027}^{+0.028}$	⋯	⋯	${18.88}_{-0.12}^{+0.12}$	${0.66}_{-0.06}^{+0.05}$	${19.56}_{-0.12}^{+0.12}$	${0.72}_{-0.06}^{+0.06}$	1895.3/1380
ZTF19aavnrqt	${8722.08}_{-0.19}^{+0.20}$	${78.26}_{-0.63}^{+0.84}$	${0.642}_{-0.009}^{+0.006}$	⋯	⋯	${17.10}_{-0.02}^{+0.03}$	${1.00}_{-0.02}^{+0.02}$	${19.07}_{-0.02}^{+0.03}$	${0.72}_{-0.01}^{+0.01}$	2305.6/1314
ZTF19aavnrqt	${8722.32}_{-0.42}^{+0.57}$	${140.18}_{-41.93}^{+125.15}$	${0.431}_{-0.171}^{+0.165}$	${0.17}_{-0.04}^{+0.04}$	${0.23}_{-0.05}^{+0.04}$	${17.79}_{-0.55}^{+0.75}$	${0.53}_{-0.22}^{+0.21}$	${19.76}_{-0.55}^{+0.75}$	${0.38}_{-0.15}^{+0.17}$	2277.0/1314
ZTF19aavnrqt	${8722.56}_{-0.76}^{+1.26}$	${284.97}_{-169.15}^{+382.15}$	$-{0.257}_{-0.259}^{+0.105}$	$-{0.21}_{-0.07}^{+0.06}$	$-{0.23}_{-0.05}^{+0.07}$	${18.55}_{-1.06}^{+0.68}$	${0.26}_{-0.15}^{+0.32}$	${20.52}_{-1.06}^{+0.68}$	${0.19}_{-0.09}^{+0.25}$	2269.7/1314
ZTF19abftuld	${8727.95}_{-0.11}^{+0.12}$	${255.46}_{-45.10}^{+79.05}$	${0.072}_{-0.018}^{+0.017}$	⋯	⋯	${21.46}_{-0.24}^{+0.32}$	${0.14}_{-0.03}^{+0.03}$	${22.59}_{-0.24}^{+0.33}$	${0.14}_{-0.03}^{+0.03}$	3405.5/1295
ZTF20abvwhlb	${9090.35}_{-0.02}^{+0.02}$	${8.10}_{-0.24}^{+0.28}$	${0.247}_{-0.012}^{+0.010}$	⋯	⋯	${18.70}_{-0.05}^{+0.06}$	${1.05}_{-0.06}^{+0.06}$	${19.55}_{-0.05}^{+0.06}$	${1.04}_{-0.06}^{+0.06}$	1807.0/1886
ZTF18aaztjyd	${8289.74}_{-0.17}^{+0.18}$	${86.46}_{-8.97}^{+11.64}$	${0.101}_{-0.015}^{+0.015}$	⋯	⋯	${21.33}_{-0.16}^{+0.18}$	${0.66}_{-0.08}^{+0.07}$	${22.67}_{-0.16}^{+0.18}$	${0.47}_{-0.05}^{+0.05}$	574.3/718
ZTF18aayhjoe	${8279.00}_{-0.24}^{+0.23}$	${25.94}_{-1.29}^{+1.52}$	${0.536}_{-0.045}^{+0.044}$	⋯	⋯	${19.62}_{-0.13}^{+0.14}$	${1.15}_{-0.17}^{+0.16}$	${21.12}_{-0.13}^{+0.14}$	${1.04}_{-0.14}^{+0.13}$	2006.4/1985

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