Rubin Observatory LSST Transients and Variable Stars Roadmap

Hambleton, Kelly M.; Bianco, Federica B.; Street, Rachel; Bell, Keaton; Buckley, David; Graham, Melissa; Hernitschek, Nina; Lund, Michael B.; Mason, Elena; Pepper, Joshua; Prša, Andrej; Rabus, Markus; Raiteri, Claudia M.; Szabó, Róbert; Szkody, Paula; Andreoni, Igor; Antoniucci, Simone; Balmaverde, Barbara; Bellm, Eric; Bonito, Rosaria; Bono, Giuseppe; Botticella, Maria Teresa; Brocato, Enzo; Bučar Bricman, Katja; Cappellaro, Enrico; Carnerero, Maria Isabel; Chornock, Ryan; Clarke, Riley; Cowperthwaite, Phil; Cucchiara, Antonino; D’Ammando, Filippo; Dage, Kristen C.; Dall’Ora, Massimo; Davenport, James R. A.; de Martino, Domitilla; de Somma, Giulia; Di Criscienzo, Marcella; Di Stefano, Rosanne; Drout, Maria; Fabrizio, Michele; Fiorentino, Giuliana; Gandhi, Poshak; Garofalo, Alessia; Giannini, Teresa; Gomboc, Andreja; Greggio, Laura; Hartigan, Patrick; Hundertmark, Markus; Johnson, Elizabeth; Johnson, Michael; Jurkic, Tomislav; Khakpash, Somayeh; Leccia, Silvio; Li, Xiaolong; Magurno, Davide; Malanchev, Konstantin; Marconi, Marcella; Margutti, Raffaella; Marinoni, Silvia; Mauron, Nicolas; Molinaro, Roberto; Möller, Anais; Moniez, Marc; Muraveva, Tatiana; Musella, Ilaria; Ngeow, Chow-Choong; Pastorello, Andrea; Petrecca, Vincenzo; Piranomonte, Silvia; Ragosta, Fabio; Reguitti, Andrea; Righi, Chiara; Ripepi, Vincenzo; Rivera Sandoval, Liliana; Stassun, Keivan G.; Stroh, Michael; Terreran, Giacomo; Trimble, Virginia; Tsapras, Yiannis; van Velzen, Sjoert; Venuti, Laura; Vink, Jorick S.

doi:10.1088/1538-3873/acdb9a

Cited by 11 publications

(3 citation statements)

References 529 publications

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“…9 The Rubin Observatory will not resolve the cores of GCs as has been done by HST or MUSE. However, its wide field of view, its multicolor photometry, and the 10 yr duration of Rubin LSST would allow us to identify CVs in different parts of GCs through their variability (Hambleton et al 2023), including those residing in the outskirts, where very few have been identified so far.…”

Section: Resultsmentioning

confidence: 99%

Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics

Rivera Sandoval,

Belloni,

Ramos Arevalo

2024

ApJL

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Based on the current detectable cataclysmic variable (CV) population in Galactic globular clusters (GCs), we show that there is not a clear relation between the number of sources per unit of mass and the stellar encounter rate, the cluster mass, or the cluster central density. If any, only in the case of core-collapsed GCs could there be an anticorrelation with the stellar encounter rate. Our findings contrast with previous studies where clear positive correlations were identified. Our results suggest that correlations between faint X-ray sources, from which often conclusions for the CV population are drawn, and the GC parameters considered here, are likely influenced by other type of X-ray sources, including other types of compact binaries, which have X-ray luminosities similar to CVs. The findings presented here also suggest that the role of primordial systems is more important than previously believed and that dynamical formation has less influence in the current detectable CV population. The long-standing paradigm that GCs are efficient factories of CVs formed via dynamical interactions does not seem to be supported by current observations.

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Section: Resultsmentioning

confidence: 99%

Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics

Rivera Sandoval,

Belloni,

Ramos Arevalo

2024

ApJL

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“…The Large Synoptic Survey Telescope (Vera Rubin Telescope) will pursue another strategy by obtaining low-latency LCs for the whole sky (and the deep drilling field), namely, 10(3) days, but for hundreds of thousands of SNe Ia 31 (Ivezic et al 2008;LSST Science Collaboration et al 2009;Ivezić et al 2019;Hambleton et al 2023). It will observe >300,000 SNe Ia around z = 0.3-0.4 in its wide survey and >10,000 around z = 0.9-1.0 in deep fields (Rose et al 2021).…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Type Ia Supernova Progenitor Properties and their Host Galaxies

Chakraborty,

Sadler,

Hoeflich

et al. 2024

ApJ

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We present an eigenfunction method to analyze 161 visual light curves (LCs) of Type Ia supernovae (SNe Ia) obtained by the Carnegie Supernova Project to characterize their diversity and host-galaxy correlations. The eigenfunctions are based on the delayed-detonation (DD) scenario using three parameters: the LC stretch s determined by the amount of deflagration burning governing the 56Ni production, the main-sequence mass M MS of the progenitor white dwarf controlling the explosion energy, and its central density ρ c shifting the 56Ni distribution. Our analysis tool (Supernova Parameter Analysis Tool) extracts the parameters from observations and projects them into physical space using their allowed ranges (M MS ≤ 8 M ⊙, ρ c ≤ 7–8 × 109 g cm−3). The residuals between fits and individual LC points are ≈1%–3% for ≈92% of objects. We find two distinct M MS groups corresponding to a fast (≈4–65 Myr) and a slow(≈200–500 Myr) stellar evolution. Most underluminous SNe Ia have hosts with low star formation but high M MS, suggesting slow evolution times of the progenitor system. 91T-like SNe show very similar LCs and high M MS and are correlated to star formation regions, making them potentially important tracers of star formation in the early Universe out to z ≈ 4–11. Some ∼6% outliers with nonphysical parameters using DD scenarios can be attributed to superluminous SNe Ia and subluminous SNe Ia with hosts of active star formation. For deciphering the SNe Ia diversity and high-precision SNe Ia cosmology, the importance is shown for LCs covering out to ≈60 days past maximum. Finally, our method and results are discussed within the framework of multiple explosion scenarios, and in light of upcoming surveys.

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“…The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will spend 10 yr imaging the entire southern sky to unprecedented depth (Ivezić et al 2019). LSST promises to improve cosmological constraints by an order of magnitude (The LSST Dark Energy Science Collaboration et al 2018), dramatically expand our understanding of galaxy evolution (Robertson et al 2017), unveil the transient and variable sky (Hambleton et al 2023), and provide an inventory of the solar system of unprecedented completeness (Schwamb et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System

Crenshaw,

Connolly,

Meyers

et al. 2024

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The Vera C. Rubin Observatory will, over a period of 10 yr, repeatedly survey the southern sky. To ensure that images generated by Rubin meet the quality requirements for precision science, the observatory will use an active-optics system (AOS) to correct for alignment and mirror surface perturbations introduced by gravity and temperature gradients in the optical system. To accomplish this, Rubin will use out-of-focus images from sensors located at the edge of the focal plane to learn and correct for perturbations to the wave front. We have designed and integrated a deep-learning (DL) model for wave-front estimation into the AOS pipeline. In this paper, we compare the performance of this DL approach to Rubin’s baseline algorithm when applied to images from two different simulations of the Rubin optical system. We show the DL approach is faster and more accurate, achieving the atmospheric error floor both for high-quality images and low-quality images with heavy blending and vignetting. Compared to the baseline algorithm, the DL model is 40× faster, the median error 2× better under ideal conditions, 5× better in the presence of vignetting by the Rubin camera, and 14× better in the presence of blending in crowded fields. In addition, the DL model surpasses the required optical quality in simulations of the AOS closed loop. This system promises to increase the survey area useful for precision science by up to 8%. We discuss how this system might be deployed when commissioning and operating Rubin.

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Rubin Observatory LSST Transients and Variable Stars Roadmap

Cited by 11 publications

References 529 publications

Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics

Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics

Type Ia Supernova Progenitor Properties and their Host Galaxies

Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System

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