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Type Ia supernovae (SNe Ia) play key roles in revealing the accelerating expansion of the universe, but our knowledge about their progenitors is still very limited. Here we report the discovery of a rigid dichotomy in circumstellar (CS)…

High Energy Astrophysical Phenomena · Physics 2019-09-25 Xiaofeng Wang , Jia Chen , Lifan Wang , Maokai Hu , Gaobo Xi , Yi Yang , Xulin Zhao , Wenxiong Li

The Hubble constant ($H_0$) is one of the fundamental parameters in cosmology, but there is a heated debate around the $>$4$\sigma$ tension between the local Cepheid distance ladder and the early Universe measurements. Strongly lensed Type…

Cosmology and Nongalactic Astrophysics · Physics 2022-03-14 S. Huber , S. H. Suyu , D. Ghoshdastidar , S. Taubenberger , V. Bonvin , J. H. H. Chan , M. Kromer , U. M. Noebauer , S. A. Sim , L. Leal-Taixé

We present the results of a novel new search of the first data-release from the Sloan Digital Sky Survey (SDSS-DR1) for the spectra of supernovae. The use of large spectroscopic galaxy surveys offers the prospect of obtaining improved…

Astrophysics · Physics 2009-11-10 Darren S. Madgwick , Paul Hewett , Daniel Mortlock , Lifan Wang

Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Nadeem Jabbar Chaudhry , M. Bilal Khan , M. Javaid Iqbal , Siddiqui Muhammad Yasir

We derive the rates of Type Ia supernovae (SNIa) over a wide range of redshifts using a complete sample from the IfA Deep Survey. This sample of more than 100 SNIa is the largest set ever collected from a single survey, and therefore…

Astrophysics · Physics 2009-11-13 Brian J. Barris , John L. Tonry

The Zwicky Transient Facility (ZTF) was expected to detect more than one strong gravitationally-lensed supernova (glSN) per year, but only one event was identified in the first four years of the survey. This work investigates selection…

High Energy Astrophysical Phenomena · Physics 2024-06-04 A. Sagués Carracedo , A. Goobar , E. Mörtsell , N. Arendse , J. Johansson , A. Townsend , S. Dhawan , J. Nordin , J. Sollerman , S. Schulze

The Zwicky Transient Facility SN Ia Data Release 2 (ZTF SN Ia DR2) contains more than 3,000 Type Ia supernovae (SNe Ia), providing the largest homogeneous low-redshift sample of SNe Ia. Having at least one spectrum per event, this data…

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to…

We present the first large-scale effort of creating composite spectra of high-redshift type Ia supernovae (SNe Ia) and comparing them to low-redshift counterparts. Through the ESSENCE project, we have obtained 107 spectra of 88…

Context. Observations of Type Ia supernovae (SNe Ia) can be used to derive accurate cosmological distances through empirical standardization techniques. Despite this success neither the progenitors of SNe Ia nor the explosion process are…

The rapid progress in image classification has been largely driven by the adoption of Graph Convolutional Networks (GCNs), which offer a robust framework for handling complex data structures. This study introduces a novel approach that…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Mustafa Mohammadi Gharasuie , Luis Rueda

In this work, we explore the cosmological consequences of the latest Type Ia supernova (SN Ia) data-set, Pantheon, by adopting the $wCDM$ model. The Pantheon data-set is the largest SN Ia samples till now, which contains 1048 supernovae on…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-13 Shuang Wang , Xiaolin Luo

Sub-visible particle analysis using flow imaging microscopy combined with deep learning has proven effective in identifying particle types, enabling the distinction of harmless components such as silicone oil from protein particles.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Utku Ozbulak , Michaela Cohrs , Hristo L. Svilenov , Joris Vankerschaver , Wesley De Neve

A quantitative data-driven comparison among supernovae (SNe) based on their spectral time series combined with multi-band photometry is presented. We use an unsupervised Random Forest algorithm as a metric on a set of 82 well-documented SNe…

High Energy Astrophysical Phenomena · Physics 2022-05-03 Ofek Bengyat , Avishay Gal-Yam

For image classification problems, various neural network models are commonly used due to their success in yielding high accuracies. Convolutional Neural Network (CNN) is one of the most frequently used deep learning methods for image…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Ilkay Sikdokur , Inci Baytas , Arda Yurdakul

We present the supernova (SN) sample and Type-Ia SN (SN Ia) rates from the Cluster Lensing And Supernova survey with Hubble (CLASH). Using the Advanced Camera for Surveys and the Wide Field Camera 3 on the Hubble Space Telescope (HST), we…

We present results from the Hubble Higher-z Supernova Search, the first space-based open field survey for supernovae (SNe). In cooperation with the Great Observatories Origins Deep Survey, we have used the Hubble Space Telescope with the…

GAIA is the ``super-Hipparcos'' satellite scheduled for launch in 2010 by the European Space Agency. It is a scanning satellite that carries out multi-colour, multi-epoch photometry on all objects brighter than 20th magnitude. We conduct…

Astrophysics · Physics 2009-11-07 V. Belokurov , N. W. Evans

Detection of cell nuclei in microscopic images is a challenging research topic, because of limitations in cellular image quality and diversity of nuclear morphology, i.e. varying nuclei shapes, sizes, and overlaps between multiple cell…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Mohammad Tofighi , Tiantong Guo , Jairam K. P. Vanamala , Vishal Monga