arXiv subjects

Joshua S. Bloom

Publications and source records attributed to Joshua S. Bloom.

At least 73 records · Page 4Linked to original sources

arXiv2020

DECam-GROWTH Search for the Faint and Distant Binary Neutron Star and Neutron Star-Black Hole Mergers in O3a

Synoptic searches for the optical counterpart to a binary neutron star (BNS) or neutron star-black hole (NSBH) merger can pose significant challenges towards the discovery of kilonovae and performing multi-messenger science. In this work, we describe the advantage of a global multi-telescope network towards this end, with a particular focus on the key and complementary role the Dark Energy Camera (DECam) plays in multi-facility follow-up. We describe the Global Relay of Observatories Watching Transients Happen (GROWTH) Target-of-Opportunity (ToO) Marshal, a common web application we built to ingest events, plan observations, search for transient candidates, and retrieve performance summary statistics for all of the telescopes in our network. Our infrastructure enabled us to conduct observations of two events during O3a, S190426c and S190510g. Furthermore, our analysis of deep DECam observations of S190814bv conducted by the DESGW team, and access to a variety of global follow-up facilities allowed us to place meaningful constraints on the parameters of the kilonova and the merging binary. We emphasize the importance of a global telescope network in conjunction with a power telescope like DECam in performing searches for the counterparts to gravitational-wave sources.

astro-ph.HE↗

arXiv2019

GROWTH on S190814bv: Deep Synoptic Limits on the Optical/Near-Infrared Counterpart to a Neutron Star-Black Hole Merger

On 2019 August 14, the Advanced LIGO and Virgo interferometers detected the high-significance gravitational wave (GW) signal S190814bv. The GW data indicated that the event resulted from a neutron star--black hole (NSBH) merger, or potentially a low-mass binary black hole merger. Due to the low false alarm rate and the precise localization (23 deg$^2$ at 90\%), S190814bv presented the community with the best opportunity yet to directly observe an optical/near-infrared counterpart to a NSBH merger. To search for potential counterparts, the GROWTH collaboration performed real-time image subtraction on 6 nights of public Dark Energy Camera (DECam) images acquired in the three weeks following the merger, covering $>$98\% of the localization probability. Using a worldwide network of follow-up facilities, we systematically undertook spectroscopy and imaging of optical counterpart candidates. Combining these data with a photometric redshift catalog, we ruled out each candidate as the counterpart to S190814bv and we placed deep, uniform limits on the optical emission associated with S190814bv. For the nearest consistent GW distance, radiative transfer simulations of NSBH mergers constrain the ejecta mass of S190814bv to be $M_\mathrm{ej} < 0.04$~$M_{\odot}$ at polar viewing angles, or $M_\mathrm{ej} < 0.03$~$M_{\odot}$ if the opacity is $κ< 2$~cm$^2$g$^{-1}$. Assuming a tidal deformability for the neutron star at the high end of the range compatible with GW170817 results, our limits would constrain the BH spin component aligned with the orbital momentum to be $ χ< 0.7$ for mass ratios $Q < 6$, with weaker constraints for more compact neutron stars. We publicly release the photometry from this campaign at http://www.astro.caltech.edu/~danny/static/s190814bv.

astro-ph.HE↗

arXiv2019

GRB 180620A: Evidence for late-time energy injection

The early optical emission of gamma-ray bursts gives an opportunity to understand the central engine and first stages of these events. About 30\% of GRBs present flares whose origin is still a subject of discussion. We present optical photometry of GRB 180620A with the COATLI telescope and RATIR instrument. COATLI started to observe from the end of prompt emission at $T+39.3$~s and RATIR from $T+121.4$~s. We supplement the optical data with the X-ray light curve from \emph{Swift}/XRT. %The optical and X-ray light curves show very unusual behavior with features clearly beyond the standard fireball model. We observe an optical flare from $T+110$ to $T+550$~s, with a temporal index decay $α_\mathrm{O,decay}=1.32\pm 0.01$, and a $Δt/t=1.63$, which we interpret as the signature of a reverse shock component. After the initial normal decay the light curves show a long plateau from $T+500$ to $T+7800$~s both in X-rays and the optical before decaying again after an achromatic jet break at $T+7800$~s. Fluctuations are seen during the plateau phase in the optical. Adding to the complexity of GRB afterglows, the plateau phase (typically associated with the coasting phase of the jet) is seen in this object after the ``normal'' decay phase (emitted during the deceleration phase of the jet) and the jet break phase occurs directly after the plateau. We suggest that this sequence of events can be explained by a rapid deceleration of the jet with $t_d\lesssim 40$ s due to the high density of the environment ($\approx 100$ cm$^{-3}$) followed by reactivation of the central engine which causes the flare and powers the plateau phase.

astro-ph.HE↗

arXiv2019

The Two LIGO/Virgo Binary Black Hole Mergers on 2019 August 28 Were Not Strongly Lensed

The LIGO/Virgo gravitational wave events S190828j and S190828l were detected only 21 minutes apart, from nearby regions of sky, and with the same source classifications (binary black hole mergers). It is therefore natural to speculate that the two signals are actually strongly lensed images of the same merger. However, an estimate of the separation of the (unknown) positions of the two events requires them to be >10 deg apart, much wider than the arcsecond-scale separations that usually arise in extragalactic lensing. The large separation is much more consistent with two independent, unrelated events that occurred close in time by chance. We quantify the overlap between simulated pairs of lensed events, and use frequentist hypothesis testing to reject S190828j/l as a lensed pair at 99.8% confidence.

astro-ph.CO↗

arXiv2019

GROWTH on S190425z: Searching thousands of square degrees to identify an optical or infrared counterpart to a binary neutron star merger with the Zwicky Transient Facility and Palomar Gattini IR

The third observing run by LVC has brought the discovery of many compact binary coalescences. Following the detection of the first binary neutron star merger in this run (LIGO/Virgo S190425z), we performed a dedicated follow-up campaign with the Zwicky Transient Facility (ZTF) and Palomar Gattini-IR telescopes. The initial skymap of this single-detector gravitational wave (GW) trigger spanned most of the sky observable from Palomar Observatory. Covering 8000 deg$^2$ of the initial skymap over the next two nights, corresponding to 46\% integrated probability, ZTF system achieved a depth of $\approx$\,21 $m_\textrm{AB}$ in $g$- and $r$-bands. Palomar Gattini-IR covered 2200 square degrees in $J$-band to a depth of 15.5\,mag, including 32\% integrated probability based on the initial sky map. The revised skymap issued the following day reduced these numbers to 21\% for the Zwicky Transient Facility and 19\% for Palomar Gattini-IR. We narrowed 338,646 ZTF transient "alerts" over the first two nights of observations to 15 candidate counterparts. Two candidates, ZTF19aarykkb and ZTF19aarzaod, were particularly compelling given that their location, distance, and age were consistent with the GW event, and their early optical lightcurves were photometrically consistent with that of kilonovae. These two candidates were spectroscopically classified as young core-collapse supernovae. The remaining candidates were ruled-out as supernovae. Palomar Gattini-IR did not identify any viable candidates with multiple detections only after merger time. We demonstrate that even with single-detector GW events localized to thousands of square degrees, systematic kilonova discovery is feasible.

astro-ph.HE↗

arXiv2019

deepCR: Cosmic Ray Rejection with Deep Learning

Cosmic ray (CR) identification and replacement are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep learning based framework for CR identification and subsequent image inpainting based on the predicted CR mask. To demonstrate the effectiveness of this framework, we train and evaluate models on Hubble Space Telescope ACS/WFC images of sparse extragalactic fields, globular clusters, and resolved galaxies. We demonstrate that at a false positive rate of 0.5%, deepCR achieves close to 100% detection rates in both extragalactic and globular cluster fields, and 91% in resolved galaxy fields, which is a significant improvement over the current state-of-the-art method LACosmic. Compared to a multicore CPU implementation of LACosmic, deepCR CR mask predictions run up to 6.5 times faster on CPU and 90 times faster on a single GPU. For image inpainting, the mean squared errors of deepCR predictions are 20 times lower in globular cluster fields, 5 times lower in resolved galaxy fields, and 2.5 times lower in extragalactic fields, compared to the best performing non-neural technique tested. We present our framework and the trained models as an open-source Python project, with a simple-to-use API. To facilitate reproducibility of the results we also provide a benchmarking codebase.

astro-ph.IM↗

arXiv2019

GROWTH on S190510g: DECam Observation Planning and Follow-Up of a Distant Binary Neutron Star Merger Candidate

The first two months of the third Advanced LIGO and Virgo observing run (2019 April-May) showed that distant gravitational wave (GW) events can now be readily detected. Three candidate mergers containing neutron stars (NS) were reported in a span of 15 days, all likely located more than 100 Mpc away. However, distant events such as the three new NS mergers are likely to be coarsely localized, which highlights the importance of facilities and scheduling systems that enable deep observations over hundreds to thousands of square degrees to detect the electromagnetic counterparts. On 2019-05-10 02:59:39.292 UT the GW candidate S190510g was discovered and initially classified as a BNS merger with 98% probability. The GW event was localized within an area of 3462 deg2, later refined to 1166 deg2 (90%) at a distance of 227 +- 92 Mpc. We triggered Target of Opportunity observations with the Dark Energy Camera (DECam), a wide-field optical imager mounted at the prime focus of the 4m Blanco Telescope at CTIO in Chile. This Letter describes our DECam observations and our real-time analysis results, focusing in particular on the design and implementation of the observing strategy. Within 24 hours of the merger time, we observed 65% of the total enclosed probability of the final skymap with an observing efficiency of 94%. We identified and publicly announced 13 candidate counterparts. S190510g was re-classified 1.7 days after the merger, after our observations were completed, with a "binary neutron star merger" probability reduced from 98% to 42% in favor of a "terrestrial" classification.

astro-ph.HE↗

arXiv2019

Reverse Shock Emission Revealed in Early Photometry in the Candidate Short GRB 180418A

We present observations of the possible short GRB 180418A in $γ$-rays, X-rays, and in the optical. Early optical photometry with the TAROT and RATIR instruments show a bright peak ($\approx$ 14.2 AB mag) between $T+28$ and $T+90$ seconds that we interpret as the signature of a reversal shock. Later observations can be modeled by a standard forward shock model and show no evidence of jet break, allowing us to constrain the jet collimation to $θ_j> 7^\circ$. Using deep late-time optical observations we place an upper limit of $r>24$ AB mag on any underlying host galaxy. The detection of the afterglow in the \textit{Swift} UV filters constrains the GRB redshift to $z<1.3$ and places an upper bound on the $γ$-ray isotropic equivalent energy $E_{\rm{γ,iso}} < 3 \times 10^{51}$ erg. The properties of this GRB (e.g. duration, hardness ratio, energetic, and environment) lie at the intersection between short and long bursts, and we can not conclusively identify its type. We estimate that the probability that it is drawn from the population of short GRBs is 10\%-30\%.

astro-ph.HE↗

arXiv2019

GROWTH on S190426c. II. Real-Time Search for a Counterpart to the Probable Neutron Star-Black Hole Merger using an Automated Difference Imaging Pipeline for DECam

The discovery of a transient kilonova following the gravitational-wave event GW170817 highlighted the critical need for coordinated rapid and wide-field observations, inference, and follow-up across the electromagnetic spectrum. In the Southern hemisphere, the Dark Energy Camera (DECam) on the Blanco 4-m telescope is well-suited to this task, as it is able to cover wide-fields quickly while still achieving the depths required to find kilonovae like the one accompanying GW170817 to $\sim$500 Mpc, the binary neutron star horizon distance for current generation of LIGO/Virgo collaboration (LVC) interferometers. Here, as part of the multi-facility followup by the Global Relay of Observatories Watching Transients Happen (GROWTH) collaboration, we describe the observations and automated data movement, data reduction, candidate discovery, and vetting pipeline of our target-of-opportunity DECam observations of S190426c, the first possible neutron star--black hole merger detected via gravitational waves. Starting 7.5hr after S190426c, over 11.28\,hr of observations, we imaged an area of 525\,deg$^2$ ($r$-band) and 437\,deg$^2$ ($z$-band); this was 16.3\% of the total original localization probability and nearly all of the probability density visible from the Southern hemisphere. The machine-learning based pipeline was optimized for fast turnaround, delivering transient candidates for human vetting within 17 minutes, on average, of shutter closure. We reported nine promising counterpart candidates 2.5 hours before the end of our observations. Our observations yielded no detection of a bona fide counterpart to $m_z = 22.5$ and $m_r = 22.9$ at the 5$σ$ level of significance, consistent with the refined LVC positioning. We view these observations and rapid inferencing as an important real-world test for this novel end-to-end wide-field pipeline.

astro-ph.HE↗

arXiv2019

WFIRST: Enhancing Transient Science and Multi-Messenger Astronomy

Astrophysical transients have been observed for millennia and have shaped our most basic assumptions about the Universe. In the last century, systematic searches have grown from detecting handfuls of transients per year to over 7000 in 2018 alone. As these searches have matured, we have discovered both large samples of "normal" classes and new, rare classes. Recently, a transient was the first object observed in both gravitational waves and light. Ground-based observatories, including LSST, will discover thousands of transients in the optical, but these facilities will not provide the high-fidelity near-infrared (NIR) photometry and high-resolution imaging of a space-based observatory. WFIRST can fill this gap. With its survey designed to measure the expansion history of the Universe with Type Ia supernovae, WFIRST will also discover and monitor thousands of other transients in the NIR, revealing the physics for these high-energy events. Small-scale GO programs, either as a supplement to the planned survey or as specific target-of-opportunity observations, would significantly expand the scope of transient science that can be studied with WFIRST.

astro-ph.HE↗

arXiv2019

Cyberinfrastructure Requirements to Enhance Multi-messenger Astrophysics

The identification of the electromagnetic counterpart of the gravitational wave event, GW170817, and discovery of neutrinos and gamma-rays from TXS 0506+056 heralded the new era of multi-messenger astrophysics. As the number of multi-messenger events rapidly grow over the next decade, the cyberinfrastructure requirements to handle the increase in data rates, data volume, need for event follow up, and analysis across the different messengers will also explosively grow. The cyberinfrastructure requirements to enhance multi-messenger astrophysics will both be a major challenge and opportunity for astronomers, physicists, computer scientists and cyberinfrastructure specialists. Here we outline some of these requirements and argue for a distributed cyberinfrastructure institute for multi-messenger astrophysics to meet these challenges.

astro-ph.IM↗

arXiv2019

Multi-Messenger Astronomy with Extremely Large Telescopes

The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network.

astro-ph.HE↗

arXiv2019

Mapping the Interstellar Reddening and Extinction towards Baade's Window Using Minimum Light Colors of ab-type RR Lyrae Stars. Revelations from the De-reddened Color-Magnitude Diagrams

We have obtained repeated images of 6 fields towards the Galactic bulge in 5 passbands (u, g, r, i, z) with the DECam imager on the Blanco 4m telescope at CTIO. From over 1.6 billion individual photometric measurements in the field centered on Baade's window, we have detected 4877 putative variable stars. 474 of these have been confirmed as fundamental mode RR Lyrae stars, whose colors at minimum light yield line-of-sight reddening determinations as well as a reddening law towards the Galactic Bulge which differs significantly from the standard R_V = 3.1 formulation. Assuming that the stellar mix is invariant over the 3 square-degree field, we are able to derive a line-of-sight reddening map with sub-arcminute resolution, enabling us to obtain de-reddened and extinction corrected color-magnitude diagrams (CMD's) of this bulge field using up to 2.5 million well-measured stars. The corrected CMD's show unprecedented detail and expose sparsely populated sequences: e.g., delineation of the very wide red giant branch, structure within the red giant clump, the full extent of the horizontal branch, and a surprising bright feature which is likely due to stars with ages younger than 1 Gyr. We use the RR Lyrae stars to trace the spatial structure of the ancient stars, and find an exponential decline in density with Galactocentric distance. We discuss ways in which our data products can be used to explore the age and metallicity properties of the bulge, and how our larger list of all variables is useful for learning to interpret future LSST alerts.

astro-ph.GA↗

arXiv2018

The Fast, Luminous Ultraviolet Transient AT2018cow: Extreme Supernova, or Disruption of a Star by an Intermediate-Mass Black Hole?

Wide-field optical surveys have begun to uncover large samples of fast (t_rise < 5d), luminous (M_peak < -18), blue transients. While commonly attributed to the breakout of a supernova shock into a dense wind, the great distances to the transients of this class found so far have hampered detailed investigation of their properties. We present photometry and spectroscopy from a comprehensive worldwide campaign to observe AT2018cow (ATLAS18qqn), the first fast-luminous optical transient to be found in real time at low redshift. Our first spectra (<2 days after discovery) are entirely featureless. A very broad absorption feature suggestive of near-relativistic velocities develops between 3-8 days, then disappears. Broad emission features of H and He develop after >10 days. The spectrum remains extremely hot throughout its evolution, and the photospheric radius contracts with time (receding below R<10^14 cm after 1 month). This behaviour does not match that of any known supernova, although a relativistic jet within a fallback supernova could explain some of the observed features. Alternatively, the transient could originate from the disruption of a star by an intermediate-mass black hole, although this would require long-lasting emission of highly super-Eddington thermal radiation. In either case, AT2018cow suggests that the population of fast luminous transients represents a new class of astrophysical event. Intensive follow-up of this event in its late phases, and of any future events found at comparable distance, will be essential to better constrain their origins.

astro-ph.HE↗

arXiv2018

Multi-Messenger Astrophysics: Harnessing the Data Revolution

The past year has witnessed discovery of the first identified counterparts to a gravitational wave transient (GW 170817A) and a very high-energy neutrino (IceCube-170922A). These source identifications, and ensuing detailed studies, have realized longstanding dreams of astronomers and physicists to routinely carry out observations of cosmic sources by other than electromagnetic means, and inaugurated the era of "multi-messenger" astronomy. While this new era promises extraordinary physical insights into the universe, it brings with it new challenges, including: highly heterogeneous, high-volume, high-velocity datasets; globe-spanning cross-disciplinary teams of researchers, regularly brought together into transient collaborations; an extraordinary breadth and depth of domain-specific knowledge and computing resources required to anticipate, model, and interpret observations; and the routine need for adaptive, distributed, rapid-response observing campaigns to fully exploit the scientific potential of each source. We argue, therefore, that the time is ripe for the community to conceive and propose an Institute for Multi-Messenger Astrophysics that would coordinate its resources in a sustained and strategic fashion to efficiently address these challenges, while simultaneously serving as a center for education and key supporting activities. In this fashion, we can prepare now to realize the bright future that we see, beyond, through these newly opened windows onto the universe.

astro-ph.IM↗

arXiv2018

Spectra of Hydrogen-Poor Superluminous Supernovae from the Palomar Transient Factory

Most Type I superluminous supernovae (SLSNe-I) reported to date have been identified by their high peak luminosities and spectra lacking obvious signs of hydrogen. We demonstrate that these events can be distinguished from normal-luminosity SNe (including Type Ic events) solely from their spectra over a wide range of light-curve phases. We use this distinction to select 19 SLSNe-I and 4 possible SLSNe-I from the Palomar Transient Factory archive (including 7 previously published objects). We present 127 new spectra of these objects and combine these with 39 previously published spectra, and we use these to discuss the average spectral properties of SLSNe-I at different spectral phases. We find that Mn II most probably contributes to the ultraviolet spectral features after maximum light, and we give a detailed study of the O II features that often characterize the early-time optical spectra of SLSNe-I. We discuss the velocity distribution of O II, finding that for some SLSNe-I this can be confined to a narrow range compared to relatively large systematic velocity shifts. Mg II and Fe II favor higher velocities than O II and C II, and we briefly discuss how this may constrain power-source models. We tentatively group objects by how well they match either SN 2011ke or PTF12dam and discuss the possibility that physically distinct events may have been previously grouped together under the SLSN-I label.

astro-ph.HE↗

arXiv2017

A recurrent neural network for classification of unevenly sampled variable stars

Astronomical surveys of celestial sources produce streams of noisy time series measuring flux versus time ("light curves"). Unlike in many other physical domains, however, large (and source-specific) temporal gaps in data arise naturally due to intranight cadence choices as well as diurnal and seasonal constraints. With nightly observations of millions of variable stars and transients from upcoming surveys, efficient and accurate discovery and classification techniques on noisy, irregularly sampled data must be employed with minimal human-in-the-loop involvement. Machine learning for inference tasks on such data traditionally requires the laborious hand-coding of domain-specific numerical summaries of raw data ("features"). Here we present a novel unsupervised autoencoding recurrent neural network (RNN) that makes explicit use of sampling times and known heteroskedastic noise properties. When trained on optical variable star catalogs, this network produces supervised classification models that rival other best-in-class approaches. We find that autoencoded features learned on one time-domain survey perform nearly as well when applied to another survey. These networks can continue to learn from new unlabeled observations and may be used in other unsupervised tasks such as forecasting and anomaly detection.

astro-ph.IM↗

arXiv2016

cesium: Open-Source Platform for Time-Series Inference

Inference on time series data is a common requirement in many scientific disciplines and internet of things (IoT) applications, yet there are few resources available to domain scientists to easily, robustly, and repeatably build such complex inference workflows: traditional statistical models of time series are often too rigid to explain complex time domain behavior, while popular machine learning packages require already-featurized dataset inputs. Moreover, the software engineering tasks required to instantiate the computational platform are daunting. cesium is an end-to-end time series analysis framework, consisting of a Python library as well as a web front-end interface, that allows researchers to featurize raw data and apply modern machine learning techniques in a simple, reproducible, and extensible way. Users can apply out-of-the-box feature engineering workflows as well as save and replay their own analyses. Any steps taken in the front end can also be exported to a Jupyter notebook, so users can iterate between possible models within the front end and then fine-tune their analysis using the additional capabilities of the back-end library. The open-source packages make us of many use modern Python toolkits, including xarray, dask, Celery, Flask, and scikit-learn.

cs.MS↗