DMTN-102: LSST Alerts: Key Numbers
A quantitative review of the key numbers associated with the Legacy Survey of Space and Time (LSST) Alert Stream.
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Engineering topics
Jurić, Mario
Publications and source records attributed to Jurić, Mario.
DMTN-065: Data Management for LSST Special Programs
Special Programs are additional survey areas and/or observing strategies that are driven by specific science goals which build on, or are beyond, the core science pillars of the Wide Fast Deep Main Survey. In order to meet the requirements and enable science related to Special Programs, this document provides recommendations for Rubin Data Management regarding processing and serving data products for Special Programs. Hardware and processing boundaries on the potential diversity of data from Special Programs are discussed along with scenarios in which user-generated processing and data products might be needed to meet Special Programs' science goals.
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LSE-163: Data Products Definition Document
This document describes the data products and processing services to be delivered by the NSF-DOE Vera C. Rubin Observatory whilst performing the Legacy Survey of Space and Time (LSST). LSST will deliver three levels of data products and services. Prompt data products are computed and released within 24 hours of observation, and include images, difference images, catalogs of sources and objects detected in difference images, and catalogs of Solar System objects. Their primary purpose is to enable rapid follow-up of time-domain events. Data Release data products are computed during annual processing campaigns, and include well-calibrated single-epoch images, deep coadds, and catalogs of objects, sources, and forced sources, enabling static sky and precision time-domain science. The Science Platform will allow for the creation of User Generated data products and will enable science cases that greatly benefit from co-location of user processing and/or data within the Rubin Observatory Data Access Center. LSST will also devote 10% of observing time to programs with special cadence. Their data products will be created using the same software and hardware as Prompt and Data Release products. All data products will be made available using user-friendly databases and web services.
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Deep drilling in the time domain with DECam: survey characterization
ABSTRACT This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4-m Blanco telescope at the Cerro Tololo Inter-American Observatory (CTIO). During the first year of observations in 2021, >4000 images covering 21 deg2 (seven DECam pointings), with ∼40 epochs (nights) per field and 5 to 6 images per night per filter in g, r, i, and/or z have become publicly available (the proprietary period for this program is waived). We describe the real-time difference-image pipeline and how alerts are distributed to brokers via the same distribution system as the Zwicky Transient Facility (ZTF). In this paper, we focus on the two extragalactic deep fields (COSMOS and ELAIS-S1) characterizing the detected sources, and demonstrating that the survey design is effective for probing the discovery space of faint and fast variable and transient sources. We describe and make publicly available 4413 calibrated light curves based on difference-image detection photometry of transients and variables in the extragalactic fields. We also present preliminary scientific analysis regarding the Solar system small bodies, stellar flares and variables, Galactic anomaly detection, fast-rising transients and variables, supernovae, and active Galactic nuclei.
79 ASTRONOMY AND ASTROPHYSICS↗
LDM-151: Data Management Science Pipelines Design
The LSST Science Requirements Document (the LSST SRD) specifies a set of data product guidelines, designed to support science goals envisioned to be enabled by the LSST observing program. Following these guidelines, the details of these data products have been described in the LSST Data Products Definition Document (DPDD), and captured in a formal flow-down from the SRD via the LSST System Requirements (LSR), Observatory System Specifications (OSS), to the Data Management System Requirements (DMSR). The LSST Data Management subsystem's responsibilities include the design, implementation, deployment and execution of software pipelines necessary to generate these data products. This document describes the design of the scientific aspects of those pipelines.
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Photometric Redshifts with the LSST. II. The Impact of Near-infrared and Near-ultraviolet Photometry
Accurate photometric redshift (photo-z) estimates are essential to the cosmological science goals of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). In this work, we use simulated photometry for mock galaxy catalogs to explore how LSST photo-z estimates can be improved by the addition of near-infrared (NIR) and/or ultraviolet (UV) photometry from the Euclid, Wide-Field InfrarRed Survey Telescope (WFIRST), and/or Cosmological Advanced Survey Telescope for Optical and ultraviolet Research (CASTOR) space telescopes. Generally, we find that deeper optical photometry can reduce the standard deviation of the photo-z estimates more than adding NIR or UV filters but that additional filters are the only way to significantly lower the fraction of galaxies with catastrophically under- or overestimated photo-z. For Euclid, we find that the addition of JH 5σ photometric detections can reduce the standard deviation for galaxies with z > 1 (z > 0.3) by ∼20% (∼10%), and the fraction of outliers by ∼40% (∼25%). For WFIRST, we show how the addition of deep YJHK photometry could reduce the standard deviation by ≳50% at z > 1.5 and drastically reduce the fraction of outliers to just ∼2% overall. For CASTOR, we find that the addition of its UV- and u-band photometry could reduce the standard deviation by ∼30% and the fraction of outliers by ∼50% for galaxies with z < 0.5. We also evaluate the photo-z results within sky areas that overlap with both the NIR and UV surveys and when spectroscopic training sets built from the surveys’ small-area deep fields are used.
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LSE-319: LSST Science Platform Vision Document
This document defines and describes the "LSST Science Platform," a set of integrated web applications and services deployed at the LSST Data Access Centers (DACs) through which the scientific community will access, visualize, subset, and perform next-to-the-data analysis of the data collected by the Large Synoptic Survey Telescope (LSST). These services can be broken down to three different "Aspects": a web Portal, designed to provide essential data access and visualization services through a simple-to-use website, a Notebook environment, that will provide a Jupyter Notebook-like interface, based on JupyterLab, enabling next-to-the-data analysis, and an extensive set of Web APIs that the users will be able to use to remotely examine the LSST data set using tools they're already familiar with. This document lays out the high-level vision for the aforementioned Aspects and some associated backend services. It is intentionally brief, and meant to generally guide the flow-down of requirements and development of product specifications, prioritization, and plans for the Agile development of the relevant elements of the DM system.
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The Large Synoptic Survey Telescope as a Near-Earth Object discovery machine
Not Available
Jones, R. Lynne↗
Hypercalibration: A Pan-STARRS1-Based Recalibration of the Sloan Digital Sky Survey Photometry
In this paper, we present a recalibration of the Sloan Digital Sky Survey (SDSS) photometry with new flat fields and zero points derived from Pan-STARRS1. Using point-spread function (PSF) photometry of 60 million stars with 16 < r < 20, we derive a model of amplifier gain and flat-field corrections with per-run rms residuals of 3 millimagnitudes (mmag) in griz bands and 15 mmag in u band. The new photometric zero points are adjusted to leave the median in the Galactic north unchanged for compatibility with previous SDSS work. We also identify transient non-photometric periods in SDSS ("contrails") based on photometric deviations co-temporal in SDSS bands. Finally, the recalibrated stellar PSF photometry of SDSS and PS1 has an rms difference of {9, 7, 7, 8} mmag in griz, respectively, when averaged over 15' regions.
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The Milky Way tomography with Sloan Digital Sky Survey. V. Mapping the dark matter halo
We present robust constraints from the Sloan Digital Sky Survey (SDSS) on the shape and distribution of the dark matter halo within the Milky Way (MW). Using the number density distribution and kinematics of SDSS halo stars, we probe the dark matter distribution to heliocentric distances exceeding ∼10 kpc and galactocentric distances exceeding ∼20 kpc. Our analysis utilizes Jeans equations to generate two-dimensional acceleration maps throughout the volume; this approach is thoroughly tested on a cosmologically derived N-body+SPH simulation of a MW-like galaxy. We show that the known accelerations (gradients of the gravitational potential) can be successfully recovered in such a realistic system. Leveraging the baryonic gravitational potential derived by Bovy and Rix, we show that the gravitational potential implied by the SDSS observations cannot be explained, assuming Newtonian gravity, by visible matter alone: the gravitational force experienced by stars at galactocentric distances of ∼20 kpc is as much as three times stronger than what can be attributed to purely visible matter. We also show that the SDSS data provide a strong constraint on the shape of the dark matter halo potential. Within galactocentric distances of ∼20 kpc, the dark matter halo potential is well described as an oblate halo with axis ratio q{sub DM}{sup Φ}=0.7±0.1; this corresponds to an axis ratio q{sub DM}{sup ρ}∼0.4±0.1 for the dark matter density distribution. Because of our precise two-dimensional measurements of the acceleration of the halo stars, we can reject several MOND models as an explanation of the observed behavior.
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Measuring distances and reddenings for a billion stars: Toward a 3D dust map from Pan-STARRS 1
We present a method to infer reddenings and distances to stars based only on their broad-band photometry, and show how this method can be used to produce a three-dimensional (3D) dust map of the Galaxy. Our method samples from the full probability density function of distance, reddening, and stellar type for individual stars, as well as the full uncertainty in reddening as a function of distance in the 3D dust map. We incorporate prior knowledge of the distribution of stars in the Galaxy and the detection limits of the survey. For stars in the Pan-STARRS 1 (PS1) 3π survey, we demonstrate that our reddening estimates are unbiased and accurate to ∼0.13 mag in E(B – V) for the typical star. Based on comparisons with mock catalogs, we expect distances for main-sequence stars to be constrained to within ∼20%-60%, although this range can vary, depending on the reddening of the star, the precise stellar type, and its position on the sky. A later paper will present a 3D map of dust over the three quarters of the sky surveyed by PS1. Both the individual stellar inferences and the 3D dust map will enable a wealth of Galactic science in the plane. The method we present is not limited to the passbands of the PS1 survey but may be extended to incorporate photometry from other surveys, such as the Two Micron All Sky Survey, the Sloan Digital Sky Survey (where available), and in the future, LSST and Gaia.
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