ARUBA: An Architecture-Agnostic Balanced Loss for Aerial Object Detection

Deep neural networks tend to reciprocate the bias of their training dataset. In object detection, the bias exists in the form of various imbalances such as class, background-foreground, and object size. In this paper, we denote size of an object as the number of pixels it covers in an image and size imbalance as the over-representation of certain sizes of objects in a dataset. We aim to address the problem of size imbalance in drone-based aerial image datasets. Existing methods for solving size imbalance are based on architectural changes that utilize multiple scales of images or feature maps for detecting objects of different sizes. We, on the other hand, propose a novel ARchitectUre-agnostic BAlanced Loss (ARUBA) that can be applied as a plugin on top of any object detection model. It follows a neighborhood-driven approach inspired by the ordinality of object size. We evaluate the effectiveness of our approach through comprehensive experiments on aerial datasets such as HRSC2016, DOTAv1.0, DOTAv1.5 and VisDrone and obtain consistent improvement in performance.Comment: Accepted to WACV 202

SN 2016hil-- a Type II supernova in the remote outskirts of an elliptical host and its origin

Type II supernovae (SNe) stem from the core collapse of massive ($>8\ M_{\odot}$) stars. Owing to their short lifespan, we expect a very low rate of such events in elliptical host galaxies, where the star-formation rate is low, and which mostly consist of an old stellar population. SN 2016hil (iPTF16hil) is a Type II supernova located in the extreme outskirts of an elliptical galaxy at redshift$z=0.0608$(projected distance$27.2$kpc). It was detected near peak brightness ($M_{r} \approx -17$mag) 9 days after the last nondetection. SN 2016hil has some potentially peculiar properties: while presenting a characteristic spectrum, the event was unusually short lived and declined by$\sim 1.5$mag in$< 40$days, following an apparently double-peaked light curve. Its spectra suggest a low metallicity ($Z<0.4\ Z_{\odot}$). We place a tentative upper limit on the mass of a potential faint host at$\log(M/M_{\odot}) =7.27^{+0.43}_{-0.24}$ using deep Keck optical imaging. In light of this, we discuss the possibility of the progenitor forming locally, and other more exotic formation scenarios such as a merger or common-envelope evolution causing a time-delayed explosion. Further observations of the explosion site in the ultraviolet are needed in order to distinguish between the cases. Regardless of the origin of the transient, observing a population of such seemingly hostless Type II SNe could have many uses, including an estimate the number of faint galaxies in a given volume, and tests of the prediction of a time-delayed population of core-collapse SNe in locations otherwise unfavorable for the detection of such events.Comment: Comments are welcom

Progenitor, Precursor and Evolution of the Dusty Remnant of the Stellar Merger M31-LRN-2015

M31-2015-LRN is a likely stellar merger discovered in the Andromeda Galaxy in 2015. We present new optical to mid-infrared photometry and optical spectroscopy for this event. The transient brightened by ∼3 mag as compared to its progenitor. The complex precursor emission, which started ∼2 years before the nova event, may be explained by the binary undergoing Roche-lobe overflow. The dynamical mass loss from the outer Lagrange point L2 creates an optically thick outflow to power the observed brightening of the system. We find two possible periods of 16±0.3 and 28.1±1.4 days at different phases of the precursor lightcurve, possibly related to the geometry of the mass-loss from the binary. Although the progenitor spectral energy distribution shows no evidence of pre-existing warm dust in system, the remnant forms an optically thick dust shell 2−4 months after the outburst peak. The optical depth of the shell increases after 1.5 years, suggesting the existence of shocks that enhance the dust formation process. We propose that the merger remnant is likely an inflated giant obscured by a cooling shell of gas with mass ∼0.2 M⊙ ejected at the onset of the common envelope phase

On the Origin of SN 2016hil—A Type II Supernova in the Remote Outskirts of an Elliptical Host

Type II supernovae (SNe) stem from the core collapse of massive (>8 M ⊙) stars. Due to their short lifespan, we expect a very low rate of such events in elliptical hosts, where the star formation rate is low, and which are mostly comprised of an old stellar population. SN 2016hil (iPTF16hil) is an SN II located in the extreme outskirts of an elliptical galaxy at z = 0.0608 (projected distance 27.2 kpc). It was detected near peak (M_r ~ −17 mag) 9 days after the last non-detection. The event has some potentially peculiar properties: it presented an apparently double-peaked light curve, and its spectra suggest low metallicity content (Z < 0.4 Z ⊙). We place a tentative upper limit on the mass of a potential faint host at log M/M⊙ = 7.27^(+0.43)_(-0.24) using deep optical imaging from Keck/LRIS. In light of this, we discuss the possibility of the progenitor forming locally and other more exotic formation scenarios such as a merger or common-envelope evolution causing a time-delayed explosion. Further observations of the explosion site in the UV are needed in order to distinguish between the cases. Regardless of the origin of the transient, observing a population of such seemingly hostless SNe II could have many uses, including an estimate the amount of faint galaxies in a given volume, and tests of the prediction of a time-delayed population of core-collapse SNe in locations otherwise unfavorable for the detection of such events

Finding Anomalous Periodic Time Series: An Application to Catalogs of Periodic Variable Stars

Catalogs of periodic variable stars contain large numbers of periodic light-curves (photometric time series data from the astrophysics domain). Separating anomalous objects from well-known classes is an important step towards the discovery of new classes of astronomical objects. Most anomaly detection methods for time series data assume either a single continuous time series or a set of time series whose periods are aligned. Light-curve data precludes the use of these methods as the periods of any given pair of light-curves may be out of sync. One may use an existing anomaly detection method if, prior to similarity calculation, one performs the costly act of aligning two light-curves, an operation that scales poorly to massive data sets. This paper presents PCAD, an unsupervised anomaly detection method for large sets of unsynchronized periodic time-series data, that outputs a ranked list of both global and local anomalies. It calculates its anomaly score for each light-curve in relation to a set of centroids produced by a modified k-means clustering algorithm. Our method is able to scale to large data sets through the use of sampling. We validate our method on both light-curve data and other time series data sets. We demonstrate its effectiveness at finding known anomalies, and discuss the effect of sample size and number of centroids on our results. We compare our method to naive solutions and existing time series anomaly detection methods for unphased data, and show that PCAD's reported anomalies are comparable to or better than all other methods. Finally, astrophysicists on our team have verified that PCAD finds true anomalies that might be indicative of novel astrophysical phenomena

IPTF Search for An Optical Counterpart to Gravitational-Wave TransientT GW150914

The American Astronomical Society. All rights reserved..The intermediate Palomar Transient Factory (iPTF) autonomously responded to and promptly tiled the error region of the first gravitational-wave event GW150914 to search for an optical counterpart. Only a small fraction of the total localized region was immediately visible in the northern night sky, due both to Sun-angle and elevation constraints. Here, we report on the transient candidates identified and rapid follow-up undertaken to determine the nature of each candidate. Even in the small area imaged of 126 deg2, after extensive filtering, eight candidates were deemed worthy of additional follow-up. Within two hours, all eight were spectroscopically classified by the Keck II telescope. Curiously, even though such events are rare, one of our candidates was a superluminous supernova. We obtained radio data with the Jansky Very Large Array and X-ray follow-up with the Swift satellite for this transient. None of our candidates appear to be associated with the gravitational-wave trigger, which is unsurprising given that GW150914 came from the merger of two stellar-mass black holes. This end-to-end discovery and follow-up campaign bodes well for future searches in this post-detection era of gravitational waves

Flash Spectroscopy: Emission Lines from the Ionized Circumstellar Material Around &lt;10-Day-Old Type II Supernovae

The American Astronomical Society. All rights reserved.Supernovae (SNe) embedded in dense circumstellar material (CSM) may show prominent emission lines in their early-time spectra (≤10 days after the explosion), owing to recombination of the CSM ionized by the shock-breakout flash. From such spectra ("flash spectroscopy"), we can measure various physical properties of the CSM, as well as the mass-loss rate of the progenitor during the year prior to its explosion. Searching through the Palomar Transient Factory (PTF and iPTF) SN spectroscopy databases from 2009 through 2014, we found 12 SNe II showing flash-ionized (FI) signatures in their first spectra. All are younger than 10 days. These events constitute 14% of all 84 SNe in our sample having a spectrum within 10 days from explosion, and 18% of SNe II observed at ages <5 days, thereby setting lower limits on the fraction of FI events. We classified as "blue/featureless" (BF) those events having a first spectrum that is similar to that of a blackbody, without any emission or absorption signatures. It is possible that some BF events had FI signatures at an earlier phase than observed, or that they lack dense CSM around the progenitor. Within 2 days after explosion, 8 out of 11 SNe in our sample are either BF events or show FI signatures. Interestingly, we found that 19 out of 21 SNe brighter than an absolute magnitude MR = -18.2 belong to the FI or BF groups, and that all FI events peaked above MR = -17.6 mag, significantly brighter than average SNe II

Machine learning for the Zwicky transient facility

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective