The Zwicky Transient Facility (ZTF) is currently surveying the entire northern sky, including dense Galactic plane fields. Here, we present preliminary results of the search for gravitational microlensing events in the ZTF data collected from the beg
inning of the survey (March 20, 2018) through June 30, 2019.
We report observations of the binary microlensing event OGLE-2018-BLG-0022, provided by the ROME/REA Survey, which indicate that the lens is a low-mass binary star consisting of M3 (0.375+/-0.020 Msun) and M7 (0.098+/-0.005 Msun) components. The lens
is unusually close, at 0.998+/-0.047 kpc, compared with the majority of microlensing events, and despite its intrinsically low luminosity, it is likely that AO observations in the near future will be able to provide an independent confirmation of the lens masses.
We present an analysis of the microlensing event OGLE-2015-BLG-0232. This event is challenging to characterize for two reasons. First, the light curve is not well sampled during the caustic crossing due to the proximity of the full Moon impacting the
photometry quality. Moreover, the source brightness is difficult to estimate because this event is blended with a nearby K dwarf star. We found that the light curve deviations are likely due to a close brown dwarf companion (i.e., s = 0.55 and q = 0.06), but the exact nature of the lens is still unknown. We finally discuss the potential of follow-up observations to estimate the lens mass and distance in the future.
(abridged) Using the particularly long gravitational microlensing event OGLE-2014-BLG-1186 with a time-scale $t_mathrm{E}$ ~ 300 d, we present a methodology for identifying the nature of localised deviations from single-lens point-source light curves
, which ensures that 1) the claimed signal is substantially above the noise floor, 2) the inferred properties are robustly determined and their estimation not subject to confusion with systematic noise in the photometry, 3) there are no alternative viable solutions within the model framework that might have been missed. Annual parallax and binarity could be separated and robustly measured from the wing and the peak data, respectively. We find matching model light curves that involve either a binary lens or a binary source. Our binary-lens models indicate a planet of mass $M_2$ = (45 $pm$ 9) $M_oplus$, orbiting a star of mass $M_1$ = (0.35 $pm$ 0.06) $M_odot$, located at a distance $D_mathrm{L}$ = (1.7 $pm$ 0.3) kpc from Earth, whereas our binary-source models suggest a brown-dwarf lens of $M$ = (0.046 $pm$ 0.007) $M_odot$, located at a distance $D_mathrm{L}$ = (5.7 $pm$ 0.9) kpc, with the source potentially being a (partially) eclipsing binary involving stars predicted to be of similar colour given the ratios between the luminosities and radii. The ambiguity in the interpretation would be resolved in favour of a lens binary by observing the luminous lens star separating from the source at the predicted proper motion of $mu$ = (1.6 $pm$ 0.3) mas yr$^{-1}$, whereas it would be resolved in favour of a source binary if the source could be shown to be a (partially) eclipsing binary matching the obtained model parameters. We experienced that close binary source stars pose a challenge for claiming the detection of planets by microlensing in events where the source passes very close to the lens star hosting the planet.
We present the Signal Detection using Random-Forest Algorithm (SIDRA). SIDRA is a detection and classification algorithm based on the Machine Learning technique (Random Forest). The goal of this paper is to show the power of SIDRA for quick and accur
ate signal detection and classification. We first diagnose the power of the method with simulated light curves and try it on a subset of the Kepler space mission catalogue. We use five classes of simulated light curves (CONSTANT, TRANSIT, VARIABLE, MLENS and EB for constant light curves, transiting exoplanet, variable, microlensing events and eclipsing binaries, respectively) to analyse the power of the method. The algorithm uses four features in order to classify the light curves. The training sample contains 5000 light curves (1000 from each class) and 50000 random light curves for testing. The total SIDRA success ratio is $geq 90%$. Furthermore, the success ratio reaches 95 - 100$%$ for the CONSTANT, VARIABLE, EB, and MLENS classes and 92$%$ for the TRANSIT class with a decision probability of 60$%$. Because the TRANSIT class is the one which fails the most, we run a simultaneous fit using SIDRA and a Box Least Square (BLS) based algorithm for searching for transiting exoplanets. As a result, our algorithm detects 7.5$%$ more planets than a classic BLS algorithm, with better results for lower signal-to-noise light curves. SIDRA succeeds to catch 98$%$ of the planet candidates in the Kepler sample and fails for 7$%$ of the false alarms subset. SIDRA promises to be useful for developing a detection algorithm and/or classifier for large photometric surveys such as TESS and PLATO exoplanet future space missions.
For all exoplanet candidates, the reliability of a claimed detection needs to be assessed through a careful study of systematic errors in the data to minimize the false positives rate. We present a method to investigate such systematics in microlensi
ng datasets using the microlensing event OGLE-2013-BLG-0446 as a case study. The event was observed from multiple sites around the world and its high magnification (A_{max} sim 3000) allowed us to investigate the effects of terrestrial and annual parallax. Real-time modeling of the event while it was still ongoing suggested the presence of an extremely low-mass companion (sim 3M_oplus ) to the lensing star, leading to substantial follow-up coverage of the light curve. We test and compare different models for the light curve and conclude that the data do not favour the planetary interpretation when systematic errors are taken into account.
Context: Understanding the source of systematic errors in photometry is essential for their calibration. Aims: We investigate how photometry performed on difference images can be influenced by errors in the photometric scale factor. Methods: We explo
re the equations for difference image analysis (DIA) and we derive an expression describing how errors in the difference flux, the photometric scale factor and the reference flux are propagated to the object photometry. Results: We find that the error in the photometric scale factor is important, and while a few studies have shown that it can be at a significant level, it is currently neglected by the vast majority of photometric surveys employing DIA. Conclusions: Minimising the error in the photometric scale factor, or compensating for it in a post-calibration model, is crucial for reducing the systematic errors in DIA photometry.
Microlensing detections of cool planets are important for the construction of an unbiased sample to estimate the frequency of planets beyond the snow line, which is where giant planets are thought to form according to the core accretion theory of pla
net formation. In this paper, we report the discovery of a giant planet detected from the analysis of the light curve of a high-magnification microlensing event MOA-2010-BLG-477. The measured planet-star mass ratio is $q=(2.181pm0.004)times 10^{-3}$ and the projected separation is $s=1.1228pm0.0006$ in units of the Einstein radius. The angular Einstein radius is unusually large $theta_{rm E}=1.38pm 0.11$ mas. Combining this measurement with constraints on the microlens parallax and the lens flux, we can only limit the host mass to the range $0.13<M/M_odot<1.0$. In this particular case, the strong degeneracy between microlensing parallax and planet orbital motion prevents us from measuring more accurate host and planet masses. However, we find that adding Bayesian priors from two effects (Galactic model and Keplerian orbit) each independently favors the upper end of this mass range, yielding star and planet masses of $M_*=0.67^{+0.33}_{-0.13} M_odot$ and $m_p=1.5^{+0.8}_{-0.3} M_{rm JUP}$ at a distance of $D=2.3pm0.6$ kpc, and with a semi-major axis of $a=2^{+3}_{-1}$ AU. Finally, we show that the lens mass can be determined from future high-resolution near-IR adaptive optics observations independently from two effects, photometric and astrometric.
