Low-Energy Supernovae Bounds on Sterile Neutrinos

Kavli Affiliate: Shunsaku Horiuchi | Summary:Sterile neutrinos can be produced through mixing with active neutrinos in the hot, dense core of a core-collapse supernova (SN). The standard bounds on the active-sterile mixing ($sin^2 θ$) from SN arise from SN1987A energy-loss, requiring $E_textloss<10^52~rm erg$. In this work, we discuss a novel bound on sterile neutrino parameter […]


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Phables: from fragmented assemblies to high-quality bacteriophage genomes

Kavli Affiliate: Robert Edwards | Authors: Vijini Mallawaarachchi, Michael J. Roach, Przemyslaw Decewicz, Bhavya Papudeshi, Sarah K Giles, Susanna R Grigson, George Bouras, Ryan D Hesse, Laura K Inglis, Abbey LK Hutton, Elizabeth A Dinsdale and Robert A Edwards | Summary: Microbial communities influence both human health and different environments. Viruses infecting bacteria, known as […]


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A rest-frame near-IR study of clumps in galaxies at 1 < z < 2 using JWST/NIRCam: connection to galaxy bulges

Kavli Affiliate: Luis C. Ho | First 5 Authors: Boris S. Kalita, John D. Silverman, Emanuele Daddi, Connor Bottrell, Luis C. Ho | Summary: A key question in galaxy evolution has been the importance of the apparent `clumpiness’ of high redshift galaxies. Until now, this property has been primarily investigated in rest-frame UV, limiting our […]


Continue.. A rest-frame near-IR study of clumps in galaxies at 1 < z < 2 using JWST/NIRCam: connection to galaxy bulges

A rest-frame near-IR study of clumps in galaxies at $1<z<2$ using JWST/NIRCam: connection to galaxy bulges

Kavli Affiliate: Luis C. Ho | First 5 Authors: Boris S. Kalita, John D. Silverman, Emanuele Daddi, Connor Bottrell, Luis C. Ho | Summary: A key question in galaxy evolution has been the importance of the apparent `clumpiness’ of high redshift galaxies. Until now, this property has been primarily investigated in rest-frame UV, limiting our […]


Continue.. A rest-frame near-IR study of clumps in galaxies at $1<z<2$ using JWST/NIRCam: connection to galaxy bulges

The Cosmic Ultraviolet Baryon Survey: Empirical Characterization of Turbulence in the Cool Circumgalactic Medium

Kavli Affiliate: Robert A. Simcoe | First 5 Authors: Hsiao-Wen Chen, Zhijie Qu, Michael Rauch, Mandy C. Chen, Fakhri S. Zahedy | Summary: This paper reports the first measurement of the relationship between turbulent velocity and cloud size in the diffuse circumgalactic medium (CGM) in typical galaxy halos at redshift z~0.4-1. Through spectrally-resolved absorption profiles […]


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Amalgame: Cosmological Constraints from the First Combined Photometric Supernova Sample

Kavli Affiliate: Richard Kessler | Summary:Future constraints of cosmological parameters from Type Ia supernovae (SNe Ia) will depend on the use of photometric samples, those samples without spectroscopic measurements of the SNe Ia. There is a growing number of analyses that show that photometric samples can be utilised for precision cosmological studies with minimal systematic […]


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Progress in Direct Measurements of the Hubble Constant

Kavli Affiliate: Wendy L. Freedman | First 5 Authors: Wendy L. Freedman, Barry F. Madore, , , | Summary: One of the most exciting and pressing issues in cosmology today is the discrepancy between some measurements of the local Hubble constant and other values of the expansion rate inferred from the cosmic microwave background (CMB) […]


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On the Comparison of AGN with GRMHD Simulations: II. M87

Kavli Affiliate: Roger Blandford | Summary:Horizon-scale observations of the jetted active galactic nucleus M87 are compared with simulations spanning a broad range of dissipation mechanisms and plasma content in three-dimensional general relativistic flows around spinning black holes. Observations of synchrotron radiation from radio to X-ray frequencies can be compared with simulations by adding prescriptions specifying […]


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Introspective Deep Metric Learning

Kavli Affiliate: Zheng Zhu | First 5 Authors: Chengkun Wang, Wenzhao Zheng, Zheng Zhu, Jie Zhou, Jiwen Lu | Summary: This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images. Conventional deep metric learning methods focus on learning a discriminative embedding to describe the semantic features of images, which ignore […]


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