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Abstract There is a long-standing discrepancy between the observed Galactic classical nova rate of ∼10 yr −1 and the predicted rate from Galactic models of ∼30–50 yr −1 . One explanation for this discrepancy is that many novae are hidden by interstellar extinction, but the degree to which dust can obscure novae is poorly constrained. We use newly available all-sky three-dimensional dust maps to compare the brightness and spatial distribution of known novae to that predicted from relatively simple models in which novae trace Galactic stellar mass. We find that only half (53%) of the novae are expected to bemore »Free, publicly-accessible full text available November 1, 2022
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A core collapse supernova occurs when exothermic fusion ceases in the core of a massive star, which is typically caused by exhaustion of nuclear fuel. Theory predicts that fusion could be interrupted earlier by merging of the star with a compact binary companion. We report a luminous radio transient, VT J121001+495647, found in the Very Large Array Sky Survey. The radio emission is consistent with supernova ejecta colliding with a dense shell of material, potentially ejected by binary interaction in the centuries before explosion. We associate the supernova with an archival x-ray transient, which implies that a relativistic jet wasmore »Free, publicly-accessible full text available September 3, 2022
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Context. Supernovae (SNe) Type Ibn are rapidly evolving and bright ( M R, peak ∼ −19) transients interacting with He-rich circumstellar material (CSM). SN 2018bcc, detected by the ZTF shortly after explosion, provides the best constraints on the shape of the rising light curve (LC) of a fast Type Ibn. Aims. We used the high-quality data set of SN 2018bcc to study observational signatures of the class. Additionally, the powering mechanism of SN 2018bcc offers insights into the debated progenitor connection of Type Ibn SNe. Methods. We compared well-constrained LC properties obtained from empirical models with the literature. We fit the pseudo-bolometricmore »
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In this paper, we discuss the outcomes of the follow-up campaign of SN 2018ijp, discovered as part of the Zwicky Transient Facility survey for optical transients. Its first spectrum shows similarities to broad-lined Type Ic supernovae around maximum light, whereas later spectra display strong signatures of interaction between rapidly expanding ejecta and a dense H-rich circumstellar medium, coinciding with a second peak in the photometric evolution of the transient. This evolution, along with the results of modeling of the first light-curve peak, suggests a scenario where a stripped star exploded within a dense circumstellar medium. The two main phases inmore »
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Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »Free, publicly-accessible full text available December 1, 2023
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Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed tomore »Free, publicly-accessible full text available December 1, 2023
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Free, publicly-accessible full text available April 1, 2023
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Free, publicly-accessible full text available May 1, 2023
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Free, publicly-accessible full text available May 1, 2023