A5063792652- Astronomy and Astrophysical Research
- Galaxies: Formation, Evolution, Phenomena
- Gamma-ray bursts and supernovae
- Stellar, planetary, and galactic studies
- Astronomical Observations and Instrumentation
- Astrophysics and Cosmic Phenomena
- Radio Astronomy Observations and Technology
- Spectroscopy and Chemometric Analyses
- Remote Sensing in Agriculture
- Time Series Analysis and Forecasting
- Astrophysical Phenomena and Observations
- Astrophysics and Star Formation Studies
- Advanced Statistical Methods and Models
- Distributed and Parallel Computing Systems
- Computational Physics and Python Applications
- Adaptive optics and wavefront sensing
- Impact of Light on Environment and Health
- Analytical Chemistry and Chromatography
- Machine Learning and Algorithms
- Gaussian Processes and Bayesian Inference
- Big Data Technologies and Applications
- Cosmology and Gravitation Theories
- Advanced Data Storage Technologies
- Advanced Vision and Imaging
- Precipitation Measurement and Analysis
Carnegie Mellon University
2023-2025
Ruhr University Bochum
2019-2023
New York University
2014-2020
Pennsylvania State University
2014-2015
The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky over ten years repeated observation. However, exactly how LSST observations be taken (the observing strategy or "cadence") not yet finalized. In this dynamically-evolving community white paper, we explore detailed performance anticipated science expected depend on small changes strategy. Using...
Context. Open clusters (OCs) are popular tracers of the structure and evolutionary history Galactic disc. The OC population is often considered to be complete within 1.8 kpc Sun. recent Gaia Data Release 2 (DR2) allows latter claim challenged. Aims. We perform a systematic search for new OCs in direction Perseus using precise accurate astrometry from DR2. Methods. implemented coarse-to-fine method. First, we exploited spatial proximity fast density-aware partitioning sky via k -d tree domain...
Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on Vera C. Rubin Observatory (Rubin) will generate orders magnitude more discoveries transients variable stars than previous surveys. To prepare for this data deluge, we developed Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze development robust classifiers under LSST-like conditions nonrepresentative training set large photometric test...
Abstract Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by (photo-z) posterior probability density functions (PDFs). A plethora photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the comprehensive experiment comparing twelve algorithms applied to mock data produced forLarge Synoptic Survey Telescope The Rubin Observatory...
We use broadband photometry extending from the rest-frame UV to near-IR fit individual spectral energy distributions (SEDs) of 63 bright (L(Ly-alpha) > 10^43 ergs/s) Ly-alpha emitting galaxies (LAEs) in redshift range 1.9 < z 3.6. find that these LAEs are quite heterogeneous, with stellar masses span over three orders magnitude, 7.5 log M 10.5. Moreover, although most have small amounts extinction, some high-mass objects reddenings as large E(B-V) ~0.4. Interestingly, dusty optical depths...
In the past few years, several independent collaborations have presented cosmological constraints from tomographic cosmic shear analyses. These analyses differ in many aspects: datasets, and photometric redshift estimation algorithms, theory model assumptions, inference pipelines. To assess robustness of existing results, we present this paper a unified analysis four recent surveys: Deep Lens Survey (DLS), Canada-France-Hawaii Telescope Lensing (CFHTLenS), Science Verification data Dark...
Abstract Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches this problem have taken advantage complete phase coverage an event, limiting their use for triggering rapid follow-up ongoing phenomena. In work, we introduce a neural network with single recurrent layer designed explicitly early classification supernovae (SNe). Our algorithm leverages transfer learning account model misspecification, host-galaxy...
Abstract Evaluating the accuracy and calibration of redshift posteriors produced by photometric (photo- z ) estimators is vital for enabling precision cosmology extragalactic astrophysics with modern wide-field surveys. photo- on a per-galaxy basis difficult, however, as real galaxies have true but not posterior. We introduce PZFlow, Python package probabilistic forward modeling galaxy catalogs normalizing flows. For simulated there natural notion “true” that can be used validation. use...
Abstract As demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently Gaia data, broadband near-UV to near-IR stellar photometry can be used estimate distance, metallicity, interstellar dust extinction along line of sight for stars in Galaxy. Anticipating photometric catalogs tens billions from Rubin's Legacy Space Time (LSST), we present a Bayesian model pipeline that build on previous work handle LSST-sized datasets. Likelihood computations utilize MIST/Dartmouth...
We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons detection deblending algorithms based on a suite metrics. The package, named Blending Toolkit (BTK), serves as modular, flexible, easy-to-install, simple-to-use interface exploring analyzing systematic effects related to blended in cosmological surveys such the Vera Rubin Observatory Legacy Survey Space Time (LSST). BTK has three main components:...
As we observe a rapidly growing number of astrophysical transients, learn more about the diverse host galaxy environments in which they occur. Host information can be used to purify samples cosmological Type Ia supernovae, uncover progenitor systems individual classes, and facilitate low-latency follow-up rare peculiar explosions. In this work, develop novel data-driven methodology simulate time-domain sky that includes detailed modeling probability density function for multiple transient...
Abstract Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential large samples observations obtained from wide-field photometric surveys, such as Zwicky Transient Facility (ZTF) and Vera C. Rubin Observatory. Here, we present a classifier for SN that does not rely on redshift information still maintains comparable accuracy redshift-dependent classifiers. Our new package, Superphot+, uses parametric model extract meaningful features...
We compare the H-beta line strengths of 1.90 < z 2.35 star-forming galaxies observed with near-IR grism Hubble Space Telescope ground-based measurements Ly-alpha from HETDEX Pilot Survey and narrow-band imaging. By examining ratios 73 galaxies, we show that most systems at this epoch have a escape fraction below ~6%. confirm result by using stellar reddening to estimate effective logarithmic extinction emission (c_Hbeta = 0.5) measuring both luminosity functions in ~ 100,000 cubic Mpc volume...
The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light 2019 and commence its 10-year main survey 2022. revolutionize our understanding of changing sky, discovering measuring millions time-varying objects. In this challenge, we pose question: how well can objects sky that vary...
Abstract We present a Bayesian approach to the redshift classification of emission-line galaxies when only single emission line is detected spectroscopically. consider case surveys for high-redshift Ly α -emitting (LAEs), which have traditionally been classified via an inferred rest-frame equivalent width (EW; <?CDATA ${W}_{\mathrm{Ly}\alpha }$?> ) greater than 20 Å. Our method relies on known prior probabilities in measured luminosity functions and EW distributions galaxy populations,...
Abstract A reliable estimate of the redshift distribution n ( z ) is crucial for using weak gravitational lensing and large-scale structures galaxy catalogs to study cosmology. Spectroscopic redshifts dim numerous galaxies next-generation weak-lensing surveys are expected be unavailable, making photometric (photo- probability density functions (PDFs) next best alternative comprehensively encapsulating nontrivial systematics affecting photo- point estimation. The established stacked estimator...
Abstract Modern galaxy surveys produce redshift probability density functions (PDFs) in addition to traditional photometric (photo- z ) point estimates. However, the storage of photo- PDFs may present a challenge with increasingly large catalogs, as we face trade-off between accuracy subsequent science measurements and limitation finite resources. This paper presents qp , Python package for manipulating parameterizations one-dimensional PDFs, suitable PDF compression. We use investigate...
The scientific impact of current and upcoming photometric galaxy surveys is contingent on our ability to obtain redshift estimates for large numbers faint galaxies. In the absence spectroscopically confirmed redshifts, broad-band point (photo-$z$s) have been superseded by photo-$z$ probability density functions (PDFs) that encapsulate their nontrivial uncertainties. Initial applications PDFs in weak gravitational lensing studies cosmology obtained distribution function $\mathcal{N}(z)$...
Classification of transient and variable light curves is an essential step in using astronomical observations to develop understanding their underlying physical processes. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge low signal-to-noise data for which traditional labeling procedures are inappropriate. Probabilistic classification more appropriate but incompatible with metrics used on deterministic classifications....
This paper presents the results of Rubin Observatory Dark Energy Science Collaboration (DESC) 3x2pt tomography challenge, which served as a first step toward optimizing tomographic binning strategy for main DESC analysis. The task choosing an optimal scheme photometric survey is made particularly delicate in context metacalibrated lensing catalogue, only photometry from bands included metacalibration process (usually riz and potentially g) can be used sample definition. goal challenge was to...
Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine learning methods. Currently planned spectroscopic not be deep enough to produce a representative training sample for LSST, so we seek methods improve the photo-z estimates that arise from non-representative samples. Spectroscopic samples photo-z's biased towards redder, brighter galaxies, also tend at lower redshift than typical galaxy observed by leading poor with outlier...
Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential large samples observations obtained from wide-field photometric surveys, such as Zwicky Transient Facility (ZTF) and Vera C. Rubin Observatory. Here, we present a classifier for SN that does not rely on redshift information still maintains comparable accuracy redshift-dependent classifiers. Our new package, Superphot+, uses parametric model extract meaningful features multiband...
Abstract Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek methods improve the photo- estimates that arise from nonrepresentative samples. Spectroscopic samples 's biased toward redder, brighter galaxies, also tend at lower redshift than typical galaxy...
The Hobby-Eberly Dark Energy Experiment pilot survey identified 284 [O II] 3727 emitting galaxies in a 169 square-arcminute field of sky the redshift range 0 < z 0.57. This line flux limited sample provides bridge between studies local universe and higher-redshift surveys. We present an analysis star formation rates (SFRs) these as function stellar mass determined via spectral energy distribution fitting. emitters fall on "main sequence" star-forming with SFR decreasing at lower masses...