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Register a new userMaximizing Science in the Era of LSST: A Community-Based Study of Needed US Capabilities
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Joan Najita
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The Large Synoptic Survey Telescope (LSST) will be a discovery machine for the astronomy and physics communities, revealing astrophysical phenomena from the Solar System to the outer reaches of the observable Universe. While many discoveries will be made using LSST data alone, taking full scientific advantage of LSST will require ground-based optical-infrared (OIR) supporting capabilities, e.g., observing time on telescopes, instrumentation, computing resources, and other infrastructure. This community-based study identifies, from a science-driven perspective, capabilities that are needed to maximize LSST science. Expanding on the initial steps taken in the 2015 OIR System Report, the study takes a detailed, quantitative look at the capabilities needed to accomplish six representative LSST-enabled science programs that connect closely with scientific priorities from the 2010 decadal surveys. The study prioritizes the resources needed to accomplish the science programs and highlights ways that existing, planned, and future resources could be positioned to accomplish the science goals.
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Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter.
The NASA LISA Study Team was tasked to study how NASA might support US scientists to participate and maximize the science return from the Laser Interferometer Space Antenna (LISA) mission. LISA is gravitational wave observatory led by ESA with NASA as a junior partner, and is scheduled to launch in 2034. Among our findings: LISA science productivity is greatly enhanced by a full-featured US science center and an open access data model. As other major missions have demonstrated, a science center acts as both a locus and an amplifier of research innovation, data analysis, user support, user training and user interaction. In its most basic function, a US Science Center could facilitate entry into LISA science by hosting a Data Processing Center and a portal for the US community to access LISA data products. However, an enhanced LISA Science Center could: support one of the parallel independent processing pipelines required for data product validation; stimulate the high level of research on data analysis that LISA demands; support users unfamiliar with a novel observatory; facilitate astrophysics and fundamental research; provide an interface into the subtleties of the instrument to validate extraordinary discoveries; train new users; and expand the research community through guest investigator, postdoc and student programs. Establishing a US LISA Science Center well before launch can have a beneficial impact on the participation of the broader astronomical community by providing training, hosting topical workshops, disseminating mock catalogs, software pipelines, and documentation. Past experience indicates that successful science centers are established several years before launch; this early adoption model may be especially relevant for a pioneering mission like LISA.
Tidal disruption events (TDEs) are rare, 10^(-7)/yr/Mpc^3 (Hung et al. 2018), yet the large survey volume of LSST implies a very large detection rate of 200/yr/(1000 deg^2) (van Velzen et al. 2011), a factor of 250 increase in the detection capability of the current generation of optical synoptic surveys, e.g. ZTF, ASAS-SN, Pan-STARRS, and ATLAS. The goal of this LSST cadence white paper is to determine which survey strategy will ensure the efficient selection and characterization of TDEs in the LSST Wide-Fast-Deep Survey transient alert stream. We conclude that the baseline cadence design fails to 1) measure the u-r color and color evolution of transients, a critical parameter for distinguishing TDEs from SNe, and to 2) catch the pre-peak light curves of transients, an essential measurement for probing their rise times, which are in turn a probe of black hole mass in TDEs. If we do not harvest the fruits of the LSST transient alert stream with photometric classification and early detections, both TDE and SN science will be greatly limited. Hence, we propose for a smart and colorful rolling cadence in the Wide-Fast Deep (WFD) Survey, that allows for efficient photometric transient classification from well sampled multi-band light curves, with the 20,000 deg^2 survey divided into eight 2500 deg^2 strips each observed for one year in Years 2-9, with the full WFD area observed in Years 1 & 10. This will yield a legacy sample of 200 TDEs per year with early detections in u, g, and r bands for efficient classification and full light curve characterization.
A community meeting on the topic of Radio Astronomy in the LSST Era was hosted by the National Radio Astronomy Observatory in Charlottesville, VA (2013 May 6--8). The focus of the workshop was on time domain radio astronomy and sky surveys. For the time domain, the extent to which radio and visible wavelength observations are required to understand several classes of transients was stressed, but there are also classes of radio transients for which no visible wavelength counterpart is yet known, providing an opportunity for discovery. From the LSST perspective, the LSST is expected to generate as many as 1 million alerts nightly, which will require even more selective specification and identification of the classes and characteristics of transients that can warrant follow up, at radio or any wavelength. The LSST will also conduct a deep survey of the sky, producing a catalog expected to contain over 38 billion objects in it. Deep radio wavelength sky surveys will also be conducted on a comparable time scale, and radio and visible wavelength observations are part of the multi-wavelength approach needed to classify and understand these objects. Radio wavelengths are valuable because they are unaffected by dust obscuration and, for galaxies, contain contributions both from star formation and from active galactic nuclei. The workshop touched on several other topics, on which there was consensus including the placement of other LSST Deep Drilling Fields, inter-operability of software tools, and the challenge of filtering and exploiting the LSST data stream. There were also topics for which there was insufficient time for full discussion or for which no consensus was reached, which included the procedures for following up on LSST observations and the nature for future support of researchers desiring to use LSST data products.
Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). It exhibits traditional astronomy broker features such as automatised ingestion, annotation, selection and redistribution of promising alerts for transient science. It is also designed to go beyond traditional broker features by providing real-time transient classification which is continuously improved by using state-of-the-art Deep Learning and Adaptive Learning techniques. These evolving added values will enable more accurate scientific output from LSST photometric data for diverse science cases while also leading to a higher incidence of new discoveries which shall accompany the evolution of the survey. In this paper we introduce Fink, its science motivation, architecture and current status including first science verification cases using the Zwicky Transient Facility alert stream.
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