arXiv subjects

Yusra AlSayyad

Publications and source records attributed to Yusra AlSayyad.

15 recordsLinked to original sources

arXiv2026

The Vera C. Rubin Observatory Data Preview 1

We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detection catalogs, and ancillary data products. DP1 is based on 1792 optical near infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera LSSTComCam on the Simonyi Survey Telescope at the Summit Facility on Cerro Pach\'on Chile in late 2024. DP1 covers $\sim$15 deg$^2$ distributed across seven roughly equal-sized non-contiguous fields, each independently observed in six broad photometric bands $ugrizy$. The median FWHM of the point spread function across all bands is approximately 1.14 arcseconds, with the sharpest images reaching about 0.58 arcseconds. The 5$\sigma$ point source depths for coadded images in the deepest field the Extended Chandra Deep Field South are $u$ = 24.55, $g$ = 26.18, $r$ = 25.96, $i$ = 25.71, $z$ = 25.07, $y$ = 23.1. Other fields are no more than 2.2 magnitudes shallower in any band where they have nonzero coverage. DP1 contains approximately 2.3 million distinct astrophysical objects, of which 1.6 million are extended in at least one band in coadds and 431 solar system objects of which 93 are new discoveries. DP1 is approximately 3.5 TB in size and is available to Rubin data rights holders via the Rubin Science Platform a cloud based environment for the analysis of petascale astronomical data. While small compared to future LSST releases its high quality and diversity of data support a broad range of early science investigations ahead of full operations in 2026.

astro-ph.IM↗

arXiv2024

The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results

We present the final data from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project, a precursor to the SDSS-V Black Hole Mapper Reverberation Mapping program. This data set includes 11-year photometric and 7-year spectroscopic light curves for 849 broad-line quasars over a redshift range of 0.1 =0.62+-0.07 for the line dispersion measured from the RMS spectrum. The intrinsic scatter of individual virial factors is 0.31+-0.07 dex, indicating a factor of two systematic uncertainty in RM black hole masses. Our lag measurements reveal significant R-L relations for Hbeta and MgII at high redshift, consistent with the latest measurements based on heterogeneous samples. While we are unable to robustly constrain the slope of the R-L relation for CIV given the limited dynamical range in luminosity, we found substantially larger scatter in CIV lags at fixed L1350. Using the SDSS-RM lag sample, we derive improved single-epoch (SE) mass recipes for Hbeta, MgII and CIV, which are consistent with their respective RM masses as well as between the SE recipes from two different lines, over the luminosity range probed by our sample. The new Hbeta and MgII recipes are approximately unbiased estimators at given RM masses, but there are systematic biases in the CIV recipe. The intrinsic scatter of SE masses around RM masses is ~0.45 dex for Hbeta and MgII, increasing to ~0.58 dex for CIV.

astro-ph.GA↗

arXiv2022

Software Architecture and System Design of Rubin Observatory

Starting from a description of the Rubin Observatory Data Management System Architecture, and drawing on our experience with and involvement in a range of other projects including Gaia, SDSS, UKIRT, and JCMT, we derive a series of generic design patterns and lessons learned.

astro-ph.IM↗

arXiv2022

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.

astro-ph.IM↗

arXiv2021

Third Data Release of the Hyper Suprime-Cam Subaru Strategic Program

The paper presents the third data release of Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field multi-band imaging survey with the Subaru 8.2m telescope. HSC-SSP has three survey layers (Wide, Deep, and UltraDeep) with different area coverages and depths, designed to address a wide array of astrophysical questions. This third release from HSC-SSP includes data from 278 nights of observing time and covers about 670 square degrees in all five broad-band filters at the full depth ($\sim26$~mag at $5σ$) in the Wide layer. If we include partially observed area, the release covers 1,470 square degrees. The Deep and UltraDeep layers have $\sim80\%$ of the originally planned integration times, and are considered done, as we have slightly changed the observing strategy in order to compensate for various time losses. There are a number of updates in the image processing pipeline. Of particular importance is the change in the sky subtraction algorithm; we subtract the sky on small scales before the detection and measurement stages, which has significantly reduced false detections. Thanks to this and other updates, the overall quality of the processed data has improved since the previous release. However, there are limitations in the data (for example, the pipeline is not optimized for crowded fields), and we encourage the user to check the quality assurance plots as well as a list of known issues before exploiting the data. The data release website is https://hsc-release.mtk.nao.ac.jp/.

astro-ph.IM↗

arXiv2020

The LSST DESC Data Challenge 1: Generation and Analysis of Synthetic Images for Next Generation Surveys

Data Challenge 1 (DC1) is the first synthetic dataset produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST dataset. DC1 is comprised of $r$-band observations of 40 deg$^{2}$ to 10-year LSST depth. We present each stage of the simulation and analysis process: a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; b) reduction using a development version of the LSST Science Pipelines; and c) matching to the input cosmological catalog for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: i) survey properties have an impact of 50\% of the statistical uncertainty for the scales and models used in DC1 ii) a selection to eliminate artifacts in the catalogs is necessary to avoid biases in the measured clustering; iii) the presence of bright objects has a significant impact (2- to 6-$σ$) in the estimated power spectra at small scales ($\ell > 1200$), highlighting the impact of blending in studies at small angular scales in LSST;

astro-ph.IM↗

arXiv2019

Second Data Release of the Hyper Suprime-Cam Subaru Strategic Program

This paper presents the second data release of the Hyper Suprime-Cam Subaru Strategic Program, a wide-field optical imaging survey on the 8.2 meter Subaru Telescope. The release includes data from 174 nights of observation through January 2018. The Wide layer data cover about 300 deg^2 in all five broadband filters (grizy) to the nominal survey exposure (10min in gr and 20min in izy). Partially observed areas are also included in the release; about 1100 deg^2 is observed in at least one filter and one exposure. The median seeing in the i-band is 0.6 arcsec, demonstrating the superb image quality of the survey. The Deep (26 deg^2) and UltraDeep (4 deg^2) data are jointly processed and the UltraDeep-COSMOS field reaches an unprecedented depth of i~28 at 5 sigma for point sources. In addition to the broad-bands, narrow-band data are also available in the Deep and UltraDeep fields. This release includes a major update to the processing pipeline, including improved sky subtraction, PSF modeling, object detection, and artifact rejection. The overall data quality has been improved, but this release is not without problems; there is a persistent deblender problem as well as new issues with masks around bright stars. The user is encouraged to review the issue list before utilizing the data for scientific explorations. All the image products as well as catalog products are available for download. The catalogs are also loaded to a database, which provides an easy interface for users to retrieve data for objects of interest. In addition to these main data products, detailed galaxy shape measurements withheld from the Public Data Release 1 (PDR1) are now available to the community. The shape catalog is drawn from the S16A internal release, which has a larger area than PDR1 (160 deg^2). All products are available at the data release site, https://hsc-release.mtk.nao.ac.jp/.

astro-ph.IM↗

arXiv2018

An Overview of the LSST Image Processing Pipelines

The Large Synoptic Survey Telescope (LSST) is an ambitious astronomical survey with a similarly ambitious Data Management component. Data Management for LSST includes processing on both nightly and yearly cadences to generate transient alerts, deep catalogs of the static sky, and forced photometry light-curves for billions of objects at hundreds of epochs, spanning at least a decade. The algorithms running in these pipelines are individually sophisticated and interact in subtle ways. This paper provides an overview of those pipelines, focusing more on those interactions than the details of any individual algorithm.

astro-ph.IM↗

arXiv2018

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$σ$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $δ<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.

astro-ph↗

arXiv2017

The Hyper Suprime-Cam Software Pipeline

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

astro-ph.IM↗

arXiv2016

Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads

Scientific discoveries are increasingly driven by analyzing large volumes of image data. Many new libraries and specialized database management systems (DBMSs) have emerged to support such tasks. It is unclear, however, how well these systems support real-world image analysis use cases, and how performant are the image analytics tasks implemented on top of such systems. In this paper, we present the first comprehensive evaluation of large-scale image analysis systems using two real-world scientific image data processing use cases. We evaluate five representative systems (SciDB, Myria, Spark, Dask, and TensorFlow) and find that each of them has shortcomings that complicate implementation or hurt performance. Such shortcomings lead to new research opportunities in making large-scale image analysis both efficient and easy to use.

cs.DB↗

arXiv2015

The LSST Data Management System

The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800 times. The LSST is currently under construction on Cerro Pachón in Chile, and expected to enter operations in 2022. Once operational, the LSST will explore a wide range of astrophysical questions, from discovering "killer" asteroids to examining the nature of Dark Energy. The LSST will generate on average 15 TB of data per night, and will require a comprehensive Data Management system to reduce the raw data to scientifically useful catalogs and images with minimum human intervention. These reductions will result in a real-time alert stream, and eleven data releases over the 10-year duration of LSST operations. To enable this processing, the LSST project is developing a new, general-purpose, high-performance, scalable, well documented, open source data processing software stack for O/IR surveys. Prototypes of this stack are already capable of processing data from existing cameras (e.g., SDSS, DECam, MegaCam), and form the basis of the Hyper-Suprime Cam (HSC) Survey data reduction pipeline.

astro-ph.IM↗

arXiv2014

The SDSS-2MASS-WISE Ten Dimensional Stellar Color Locus

We present the fiducial main sequence stellar locus traced by 10 photometric colors observed by SDSS, 2MASS, and WISE. Median colors are determined using 1,052,793 stars with r-band extinction less than 0.125. We use this locus to measure the dust extinction curve relative to the r-band, which is consistent with previous measurements in the SDSS and 2MASS bands. The WISE band extinction coefficients are larger than predicted by standard extinction models. Using 13 lines of sight, we find variations in the extinction curve in H, Ks, and WISE bandpasses. Relative extinction decreases towards Galactic anti-center, in agreement with prior studies. Relative extinction increases with Galactic latitude, in contrast to previous observations. This indicates a universal mid-IR extinction law does not exist due to variations in dust grain size and chemistry with Galactocentric position. A preliminary search for outliers due to warm circumstellar dust is also presented, using stars with high signal-to-noise in the W3-band. We find 199 such outliers, identified by excess emission in Ks-W3. Inspection of SDSS images for these outliers reveals a large number of contaminants due to nearby galaxies. Six sources appear to be genuine dust candidates, yielding a fraction of systems with infrared excess of 0.12$\pm$0.05%.

astro-ph.SR↗

arXiv2012

A Multi-Survey Approach to White Dwarf Discovery

By selecting astrometric and photometric data from the Sloan Digital Sky Survey (SDSS), the L{é}pine & Shara Proper Motion North Catalog (LSPM-North), the Two Micron All Sky Survey (2MASS), and the USNO-B1.0 catalog, we use a succession of methods to isolate white dwarf candidates for follow-up spectroscopy. Our methods include: reduced proper motion diagram cuts, color cuts, and atmospheric model adherence. We present spectroscopy of 26 white dwarfs obtained from the CTIO 4m and APO 3.5m telescopes. Additionally, we confirm 28 white dwarfs with spectra available in the SDSS DR7 database but unpublished elsewhere, presenting a total of 54 WDs. We label one of these as a recovered WD while the remaining 53 are new discoveries. We determine physical parameters and estimate distances based on atmospheric model analyses. Three new white dwarfs are modeled to lie within 25 pc. Two additional white dwarfs are confirmed to be metal-polluted (DAZ). Follow-up time series photometry confirms another object to be a pulsating ZZ Ceti white dwarf.

astro-ph.SR↗

arXiv2009

A Cross-Correlation Analysis of Mg II Absorption Line Systems and Luminous Red Galaxies from the SDSS DR5

We analyze the cross-correlation of 2,705 unambiguously intervening Mg II (2796,2803A) quasar absorption line systems with 1,495,604 luminous red galaxies (LRGs) from the Fifth Data Release of the Sloan Digital Sky Survey within the redshift range 0.36<=z<=0.8. We confirm with high precision a previously reported weak anti-correlation of equivalent width and dark matter halo mass, measuring the average masses to be log M_h(M_[solar]h^-1)=11.29 [+0.36,-0.62] and log M_h(M_[solar]h^-1)=12.70 [+0.53,-1.16] for systems with W[2796A]>=1.4A and 0.8A<=W[2796A]<1.4A, respectively. Additionally, we investigate the significance of a number of potential sources of bias inherent in absorber-LRG cross-correlation measurements, including absorber velocity distributions and the weak lensing of background quasars, which we determine is capable of producing a 20-30% bias in angular cross-correlation measurements on scales less than 2'. We measure the Mg II - LRG cross-correlation for 719 absorption systems with v<60,000 km s^-1 in the quasar rest frame and find that these associated absorbers typically reside in dark matter haloes that are ~10-100 times more massive than those hosting unambiguously intervening Mg II absorbers. Furthermore, we find evidence for evolution of the redshift number density, dN/dz, with 2-sigma significance for the strongest (W>2.0A) absorbers in the DR5 sample. This width-dependent dN/dz evolution does not significantly affect the recovered equivalent width-halo mass anti-correlation and adds to existing evidence that the strongest Mg II absorption systems are correlated with an evolving population of field galaxies at z<0.8, while the non-evolving dN/dz of the weakest absorbers more closely resembles that of the LRG population.

astro-ph.CO↗