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Related papers: Supernova search with active learning in ZTF DR3

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We introduce the Hawai'i Supernova Flows project and present summary statistics of the first 1,217 astronomical transients observed, 668 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to…

Type Ia supernovae (SN Ia) have provided the first evidence for an accelerating universe and for the existence of an unknown ``dark energy'' driving this expansion. The 5-year Supernova Legacy Survey (SNLS) will deliver \~700 type Ia…

Astrophysics · Physics 2019-08-14 N. Palanque-Delabrouille

Active learning has emerged as a promising approach to reduce the substantial annotation burden in 3D object detection tasks, spurring several initiatives in outdoor environments. However, its application in indoor environments remains…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Jiangyi Wang , Na Zhao

The Zwicky Transient Facility (ZTF) is conducting a wide-field survey of the northern sky in three optical bands and the collaboration cosmology working group has released 3628 spectroscopically confirmed Type Ia supernovae (SNe Ia)…

Anomaly detection (AD) in images, identifying significant deviations from normality, is a critical issue in computer vision. This paper introduces a novel approach to dimensionality reduction for AD using pre-trained convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Tetiana Gula , João P C Bertoldo

Superluminous supernovae (SLSNe) are one of the most luminous stellar explosions known, yet they remain poorly understood. Because they are intrinsically rare, efficiently identifying them in the large alert streams produced by modern…

Instrumentation and Methods for Astrophysics · Physics 2026-04-17 E. Russeil , R. Lunnan , J. Peloton , S. Schulze , P. J. Pessi , D. Perley , J. Sollerman , A. Gkini , Y. Hu , T. -W. Chen , E. C. Bellm , T. X. Chen , B. Rusholme

Context. The SPHERE High-contrast Imaging survey for Exoplanets (SHINE) represents one of the largest direct imaging campaigns, targeting over 400 young, nearby stars with the goal of detecting and characterizing giant exoplanets and brown…

Earth and Planetary Astrophysics · Physics 2026-05-25 Carles Cantero Mitjans , Mariam Sabalbal , Olivier Absil , Marc Van Droogenbroeck , Damien Ségransan , Philippe Delorme

Large photometric surveys of transient phenomena, such as Pan-STARRS and LSST, will locate thousands to millions of type Ia supernova candidates per year, a rate prohibitive for acquiring spectroscopy to determine each candidate's type and…

Instrumentation and Methods for Astrophysics · Physics 2014-11-20 D. M. Scolnic , A. G. Riess , M. E. Huber , A. Rest , C. Stubbs , J. L. Tonry

We propose a new strategy of finding strongly-lensed supernovae (SNe) by monitoring known galaxy-scale strong-lens systems. Strongly lensed SNe are potentially powerful tools for the study of cosmology, galaxy evolution, and stellar…

Astrophysics of Galaxies · Physics 2018-09-19 Yiping Shu , Adam S. Bolton , Shude Mao , Xi Kang , Guoliang Li , Monika Soraisam

We report on the serendipitous observations of Solar System objects imaged during the High cadence Transient Survey (HiTS) 2014 observation campaign. Data from this high cadence, wide field survey was originally analyzed for finding…

We present a real-time stamp classifier of astronomical events for the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker. The classifier is based on a convolutional neural network, trained on alerts ingested from the…

The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…

Instrumentation and Methods for Astrophysics · Physics 2022-09-09 Venkitesh Ayyar , Robert Knop , Autumn Awbrey , Alexis Andersen , Peter Nugent

Deep neural networks (DNN) can achieve high performance when applied to In-Distribution (ID) data which come from the same distribution as the training set. When presented with anomaly inputs not from the ID, the outputs of a DNN should be…

Machine Learning · Computer Science 2021-10-08 Fangzhen Zhao , Chenyi Zhang , Naipeng Dong , Zefeng You , Zhenxin Wu

We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are…

Cosmology and Nongalactic Astrophysics · Physics 2025-07-22 DES Collaboration , T. M. C. Abbott , M. Acevedo , M. Aguena , A. Alarcon , S. Allam , O. Alves , A. Amon , F. Andrade-Oliveira , J. Annis , P. Armstrong , J. Asorey , S. Avila , D. Bacon , B. A. Bassett , K. Bechtol , P. H. Bernardinelli , G. M. Bernstein , E. Bertin , J. Blazek , S. Bocquet , D. Brooks , D. Brout , E. Buckley-Geer , D. L. Burke , H. Camacho , R. Camilleri , A. Campos , A. Carnero Rosell , D. Carollo , A. Carr , J. Carretero , F. J. Castander , R. Cawthon , C. Chang , R. Chen , A. Choi , C. Conselice , M. Costanzi , L. N. da Costa , M. Crocce , T. M. Davis , D. L. DePoy , S. Desai , H. T. Diehl , M. Dixon , S. Dodelson , P. Doel , C. Doux , A. Drlica-Wagner , J. Elvin-Poole , S. Everett , I. Ferrero , A. Ferté , B. Flaugher , R. J. Foley , P. Fosalba , D. Friedel , J. Frieman , C. Frohmaier , L. Galbany , J. García-Bellido , M. Gatti , E. Gaztanaga , G. Giannini , K. Glazebrook , O. Graur , D. Gruen , R. A. Gruendl , G. Gutierrez , W. G. Hartley , K. Herner , S. R. Hinton , D. L. Hollowood , K. Honscheid , D. Huterer , B. Jain , D. J. James , N. Jeffrey , E. Kasai , L. Kelsey , S. Kent , R. Kessler , A. G. Kim , R. P. Kirshner , E. Kovacs , K. Kuehn , O. Lahav , J. Lee , S. Lee , G. F. Lewis , T. S. Li , C. Lidman , H. Lin , U. Malik , J. L. Marshall , P. Martini , J. Mena-Fernández , F. Menanteau , R. Miquel , J. J. Mohr , J. Mould , J. Muir , A. Möller , E. Neilsen , R. C. Nichol , P. Nugent , R. L. C. Ogando , A. Palmese , Y. -C. Pan , M. Paterno , W. J. Percival , M. E. S. Pereira , A. Pieres , A. A. Plazas Malagón , B. Popovic , A. Porredon , J. Prat , H. Qu , M. Raveri , M. Rodríguez-Monroy , A. K. Romer , A. Roodman , B. Rose , M. Sako , E. Sanchez , D. Sanchez Cid , M. Schubnell , D. Scolnic , I. Sevilla-Noarbe , P. Shah , J. Allyn. Smith , M. Smith , M. Soares-Santos , E. Suchyta , M. Sullivan , N. Suntzeff , M. E. C. Swanson , B. O. Sánchez , G. Tarle , G. Taylor , D. Thomas , C. To , M. Toy , M. A. Troxel , B. E. Tucker , D. L. Tucker , S. A. Uddin , M. Vincenzi , A. R. Walker , N. Weaverdyck , R. H. Wechsler , J. Weller , W. Wester , P. Wiseman , M. Yamamoto , F. Yuan , B. Zhang , Y. Zhang

While significant advances have been made in photometric classification ahead of the millions of transient events and hundreds of supernovae (SNe) each night that the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will…

Instrumentation and Methods for Astrophysics · Physics 2025-09-12 Willow Fox Fortino , Federica B. Bianco , Pavlos Protopapas , Daniel Muthukrishna , Austin Brockmeier

The All-Sky Automated Survey for Supernovae (ASAS-SN) provides long baseline (${\sim}4$ yrs) $V-$band light curves for sources brighter than V$\lesssim17$ mag across the whole sky. We produced V-band light curves for a total of ${\sim}61.5$…

We present an overview of a deep transient survey of the COSMOS field with the Subaru Hyper Suprime-Cam (HSC). The survey was performed for the 1.77 deg$^2$ ultra-deep layer and 5.78 deg$^2$ deep layer in the Subaru Strategic Program over…

Using a combination of ground-based and HST imaging, we have constructed a catalog of 179 supernova remnants (SNRs) and SNR candidates in the nearby spiral galaxy M51. Follow-up spectroscopy of 66 of the candidates confirms 61 of these as…

Astrophysics of Galaxies · Physics 2021-02-24 P. Frank Winkler , Sadie C. Coffin , William P. Blair , Knox S. Long , Kip D. Kuntz
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