Related papers: SNIF: The SuperNova Interactive Fitter
Recent advances in the processing of thin-film LNOI have enabled low-loss photonic integrated circuits, modulators with improved half-wave voltage, electro-optic frequency combs and novel on-chip electro-optic devices, with applications…
The covalent functionalization of single-walled carbon nanotubes (SWNTs) with luminescent oxygen defects increases their brightness and enables their application as optical biosensors or fluorescent probes for in-vivo imaging in the…
We extend the Locally-Subdivided Neural Intersection Function (LSNIF) to support parameterized deformable and animated geometry. Our approach introduces a rest-space and deformed-space formulation inspired by meshless rendering, allowing…
Superluminous supernovae (SLSNe) are one of the most luminous stellar explosions known, yet they remain poorly understood. Because they are intrinsically rare, efficiently identifying them in the large alert streams produced by modern…
We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R $\sim100$) data. The goal of SNIascore is fully automated classification of SNe Ia with…
The SuperNova/Acceleration Probe (SNAP) will measure precisely the cosmological expansion history over both the acceleration and deceleration epochs and thereby constrain the nature of the dark energy that dominates our universe today. The…
We present multiband photometry of 60 spectroscopically-confirmed supernovae (SN): 39 SN II/IIP, 19 IIn, one IIb and one that was originally classified as a IIn but later as a Ibn. Forty-six have only optical photometry, six have only near…
Gas monitoring systems based on side-polished optical fibers (SPFs) coated with functional nanomaterials are gaining growing attention for their diverse applications. The response of these sensors is commonly interpreted in terms of…
Recent detection of gravitational waves from a binary-neutron star merger (GW170817) and the subsequent observations of electromagnetic counterparts provide a great opportunity to study the physics of compact binary mergers. The optical and…
Multi-modality image fusion (MMIF) combines complementary information from different image modalities to provide a comprehensive and objective interpretation of scenes. However, existing fusion methods cannot resist different weather…
We present an optimized conductance-based retina microcircuit simulator which transforms light stimuli into a series of graded and spiking action potentials through photo transduction. We use discrete retinal neuron blocks based on a…
The SINFONI instrument for ESO's VLT combines integral field spectroscopy and adaptive optics (AO). We discuss detailed simulations of the adaptive optics module. These simulations are aimed at assessing the AO module performance,…
The miniaturization of diagnostic devices that exploit optical detection schemes requires the design of light-sources combining small size, high performance for effective excitation of chromophores, and mechanical flexibility for easy…
Traffic object detection under variable illumination is challenging due to the information loss caused by the limited dynamic range of conventional frame-based cameras. To address this issue, we introduce bio-inspired event cameras and…
Detailed radiative transfer simulations of kilonovae are difficult to apply directly to observations; they only sparsely cover simulation parameters, such as the mass, velocity, morphology, and composition of the ejecta. On the other hand,…
Supernovae emit large fluxes of neutrinos which can be detected by detectors on Earth. Future tonne-scale detectors will be sensitive to several neutrino interaction channels, with thousands of events expected if a supernova emerges in the…
In this study, we introduce Convolutional Transformer Neural Collaborative Filtering (CTNCF), a novel approach aimed at enhancing recommendation systems by effectively capturing high-order structural information in user-item interactions.…
Neuromorphic chip refers to an unconventional computing architecture that is modelled on biological brains. It is ideally suited for processing sensory data for intelligence computing, decision-making or context cognition. Despite rapid…
We generate $\sim$ 100,000 model spectra of Type Ia Supernovae (SNIa) to form a spectral library for the purpose of building an Artificial Intelligence Assisted Inversion (AIAI) algorithm for theoretical models. As a first attempt, we…
The classification of supernovae (SNe) and its impact on our understanding of the explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming…