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Using three magnified Type Ia supernovae (SNe Ia) detected behind CLASH clusters, we perform a first pilot study to see whether standardizable candles can be used to calibrate cluster mass maps created from strong lensing observations. Such…

We present the snapshot distance method (SDM), a modern incarnation of a proposed technique for estimating the distance to a Type Ia supernova (SN Ia) from minimal observations. Our method, which has become possible owing to recent work in…

Cosmology and Nongalactic Astrophysics · Physics 2021-05-26 Benjamin E. Stahl , Thomas de Jaeger , WeiKang Zheng , Alexei V. Filippenko

A large-scale neutrino observatory based on Water-based Liquid Scintillator (WbLS) will be excellently suited for a measurement of the Diffuse Supernova Neutrino Background (DSNB). The WbLS technique offers high signal efficiency and…

Instrumentation and Detectors · Physics 2021-01-28 Julia Sawatzki , Michael Wurm , Daniel Kresse

Dynamic Vision Sensors (DVS) exhibit exceptional dynamic range and low power consumption, making them ideal for edge applications in the Internet of Video Things (IoVT). However, their output is often degraded by spurious Background…

Neural and Evolutionary Computing · Computer Science 2026-05-05 Yahan Yang , Pradeep Kumar Gopalakrishnan , Chang Chip Hong , Arindam Basu

We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-13 R. Kessler , D. Brout , C. B. D'Andrea , T. M. Davis , S. R. Hinton , A. G. Kim , J. Lasker , C. Lidman , E. Macaulay , A. Möller , M. Sako , D. Scolnic , M. Smith , M. Sullivan , B. Zhang , P. Andersen , J. Asorey , A. Avelino , J. Calcino , D. Carollo , P. Challis , M. Childress , A. Clocchiatti , S. Crawford , A. V. Filippenko , R. J. Foley , K. Glazebrook , J. K. Hoormann , E. Kasai , R. P. Kirshner , G. F. Lewis , K. S. Mandel , M. March , E. Morganson , D. Muthukrishna , P. Nugent , Y. -C. Pan , N. E. Sommer , E. Swann , R. C. Thomas , B. E. Tucker , S. A. Uddin , T. M. C. Abbott , S. Allam , J. Annis , S. Avila , M. Banerji , K. Bechtol , E. Bertin , D. Brooks , E. Buckley-Geer , D. L. Burke , A. Carnero Rosell , M. Carrasco Kind , J. Carretero , F. J. Castander , M. Crocce , L. N. da Costa , C. Davis , J. De Vicente , S. Desai , H. T. Diehl , P. Doel , T. F. Eifler , B. Flaugher , P. Fosalba , J. Frieman , J. Garcia-Bellido , E. Gaztanaga , D. W. Gerdes , D. Gruen , R. A. Gruendl , G. Gutierrez , W. G. Hartley , D. L. Hollowood , K. Honscheid , D. J. James , M. W. G. Johnson , M. D. Johnson , E. Krause , K. Kuehn , N. Kuropatkin , O. Lahav , T. S. Li , M. Lima , J. L. Marshall , P. Martini , F. Menanteau , C. J. Miller , R. Miquel , B. Nord , A. A. Plazas , A. Roodman , E. Sanchez , V. Scarpine , R. Schindler , M. Schubnell , S. Serrano , I. Sevilla-Noarbe , M. Soares-Santos , F. Sobreira , E. Suchyta , G. Tarle , D. Thomas , A. R. Walker , Y. Zhang

In the era of AI at the edge, self-driving cars, and climate change, the need for energy-efficient, small, embedded AI is growing. Spiking Neural Networks (SNNs) are a promising approach to address this challenge, with their event-driven…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Lennard Bodden , Franziska Schwaiger , Duc Bach Ha , Lars Kreuzberg , Sven Behnke

We present a data-driven method based on long short-term memory (LSTM) neural networks to analyze spectral time series of Type Ia supernovae (SNe Ia). The dataset includes 3091 spectra from 361 individual SNe Ia. The method allows for…

High Energy Astrophysical Phenomena · Physics 2022-05-09 Lei Hu , Xingzhuo Chen , Lifan Wang

The determination of the supernova (SN) rate is based not only on the number of detected events, but also on the properties of the parent galaxy population. This is the first paper of a series aimed at obtaining new, refined, SN rates from…

Cosmology and Nongalactic Astrophysics · Physics 2010-08-17 A. A. Hakobyan , A. R. Petrosian , G. A. Mamon , B. McLean , D. Kunth , M. Turatto , E. Cappellaro , F. Mannucci , R. J. Allen , N. Panagia , M. Della Valle

Current methods aggregate multi-level features or introduce edge and skeleton to get more refined saliency maps. However, little attention is paid to how to obtain the complete salient object in cluttered background, where the targets are…

Computer Vision and Pattern Recognition · Computer Science 2023-01-19 Ge Zhu , Jinbao Li , Yahong Guo

We review the appropriateness of using SNIa observations to detect potential signatures of anisotropic expansion in the Universe. We focus on Union2 and SNLS3 SNIa datasets and use the hemispherical comparison method to detect possible…

Cosmology and Nongalactic Astrophysics · Physics 2015-01-28 Jose Beltran Jimenez , Vincenzo Salzano , Ruth Lazkoz

Organic scintillators are widely used for fast neutron detection and spectroscopy. Several effects complicate the interpretation of results from detectors based upon these materials. First, fast neutrons will often leave a detector before…

Instrumentation and Detectors · Physics 2009-10-29 N. S. Bowden , P. Marleau , J. T. Steele , S. Mrowka , G. Aigeldinger , W. Mengesha

Multiply-imaged supernovae (SNe) provide a novel means of constraining the Hubble constant ($H_0$). Such measurements require a combination of precise models of the lensing mass distribution and an accurate estimate of the relative time…

Spiking Neural Networks (SNNs) are a biologically plausible neural network model with significant advantages in both event-driven processing and spatio-temporal information processing, rendering SNNs an appealing choice for energyefficient…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Jilong Luo , Shanlin Xiao , Yinsheng Chen , Zhiyi Yu

Radio Frequency Interference (RFI) poses a significant challenge in radio astronomy, arising from terrestrial and celestial sources, disrupting observations conducted by radio telescopes. Addressing RFI involves intricate heuristic…

Neural and Evolutionary Computing · Computer Science 2024-12-09 Nicholas J. Pritchard , Andreas Wicenec , Mohammed Bennamoun , Richard Dodson

We report the discovery of a Type Ia supernova (SNIa) at redshift z=1.55 with the infrared detector of the Wide Field Camera 3 (WFC3-IR) on the Hubble Space Telescope (HST). This object was discovered in CANDELS imaging data of the Hubble…

Recent studies try to use hyperspectral imaging (HSI) to detect foreign matters in products because it enables to visualize the invisible wavelengths including ultraviolet and infrared. Considering the enormous image channels of the HSI,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Dongeon Kim , YeongHyeon Park

We present a method using the SALT2 light curve fitter to determine the redshift of Type Ia supernovae in the Supernova Legacy Survey (SNLS) based on their photometry in g', r', i' and z'. On 289 supernovae of the first three years of SNLS…

To date, only two strongly lensed type Ia supernovae (SNIa) have been discovered with an isolated galaxy acting as the lens: iPTF16geu and SN Zwicky. The observed image fluxes for both lens systems were inconsistent with predictions from a…

Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe…

We present a cosmological analysis of the Lick Observatory Supernova Search (LOSS) Type Ia supernova (SN Ia) photometry sample introduced by Ganeshalingam et al. (2010). These SNe provide an effective anchor point to estimate cosmological…

Cosmology and Nongalactic Astrophysics · Physics 2013-07-04 Mohan Ganeshalingam , Weidong Li , Alexei V. Filippenko