相关论文: SNIF: The SuperNova Interactive Fitter

Spiking neural networks (SNNs) offer biologically inspired computation but remain underexplored for continuous regression tasks in scientific machine learning. In this work, we introduce and systematically evaluate Quadratic…

Visible and infrared image fusion (VIF) has gained significant attention in recent years due to its wide application in tasks such as scene segmentation and object detection. VIF methods can be broadly classified into traditional VIF…

In the present study, we systematically explore the effect of the radioactive 56Ni and its mixing properties in the ejecta on the plateau of Type IIP supernovae (SNe). We evaluate the importance of 56Ni in shaping light curves of SNe IIP by…

In November 2020, the Swift team announced a major update to the calibration of the UltraViolet and Optical Telescope (UVOT) data to correct for the gradual loss of sensitivity over time. Beginning in roughly 2015, the correction affected…

In response to a recently reported observation of evidence for two classes of Type Ia Supernovae (SNe Ia) distinguished by their brightness in the rest-frame near ultraviolet (NUV), we search for the phenomenon in publicly available…

We constructed 70 SuperNova IDentification (SNID; Blondin & Tonry 2007) supernova (SN) templates using 640 spectra of stripped-envelope core-collapse SNe (SESNe) published by Modjaz et al. (2014). Fifty-six SN templates which are…

Spiking Neural Networks (SNNs) offer notable advantages in biological plausibility and energy efficiency, making them promising candidates for building low-power Transformers. However, existing Spiking Transformers largely adhere to a…

Tin iodide phosphide (SnIP), an inorganic double-helix material, is a quasi-1D van der Waals semiconductor that shows promise in photocatalysis and flexible electronics. However, our understanding of the fundamental photophysics and charge…

We present the public release of the Complete History of Interaction-Powered Supernovae (CHIPS) code, suited to model a variety of transients that arise from interaction with a dense circumstellar medium (CSM). Contrary to existing…

Semantic analysis on visible (RGB) and infrared (IR) images has gained significant attention due to their enhanced accuracy and robustness under challenging conditions including low-illumination and adverse weather. However, due to the lack…

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network…

Several types of energetic supernovae, such as superluminous supernovae (SLSNe) and broad-line Ic supernovae (Ic-BL SNe), could be powered by the spin-down of a rapidly rotating magnetar. Currently, most models used to infer the parameters…

Type Ia Supernovae (SNeIa) provided the first evidence of an accelerated expansion of the universe and remain a valuable probe to cosmology. They are deemed standardizable candles due to the observed correlations between its luminosity and…

Rapidly evolving transients, or objects that rise and fade in brightness on timescales two to three times shorter than those of typical Type Ia or Type II supernovae (SNe), have uncertain progenitor systems and powering mechanisms. Recent…

We present theoretical UBVI- and bolometric light curves of SNe Ia for several explosion models, computed with our multi-group radiation hydro code. We employ our new corrected treatment for line opacity in the expanding medium. The results…

Observational cosmology employing optical surveys often require precise flux calibration. In this context we present SNIFS Calibration Apparatus (SCALA), a flux calibration system developed for the SuperNova Integral Field Spectrograph…

Infrared and visible image fusion (IVIF) is a fundamental task in multi-modal perception that aims to integrate complementary structural and textural cues from different spectral domains. In this paper, we propose FusionNet, a novel…

Spiking neural networks (SNNs) are promising brain-inspired energy-efficient models. Compared to conventional deep Artificial Neural Networks (ANNs), SNNs exhibit superior efficiency and capability to process temporal information. However,…

Combining the complementary benefits of frames and events has been widely used for object detection in challenging scenarios. However, most object detection methods use two independent Artificial Neural Network (ANN) branches, limiting…

Creating high-quality 3D models of clothed humans from single images for real-world applications is crucial. Despite recent advancements, accurately reconstructing humans in complex poses or with loose clothing from in-the-wild images,…