Related papers: An Algorithm to Compress Line-transition Data for …
Network compression is crucial to making the deep networks to be more efficient, faster, and generalizable to low-end hardware. Current network compression methods have two open problems: first, there lacks a theoretical framework to…
Our observations of TMC-1 with the Yebes 40 m radio telescope in the 31.0-50.3 GHz range allowed us to detect a group of unidentified lines, showing a complex line pattern indicative of an open-shell species. {}The observed frequencies of…
Quasi-forbidden electronic transitions in atoms and quasi-degenerate vibronic transitions in molecules serve as powerful probes of hypothetical temporal variations of fundamental constants. Computation of the sensitivity of a transition to…
Non-parametric two-sample tests based on energy distance or maximum mean discrepancy are widely used statistical tests for comparing multivariate data from two populations. While these tests enjoy desirable statistical properties, their…
A new run length encoding algorithm for lossless data compression that exploits positional redundancy by representing data in a two-dimensional model of concentric circles is presented. This visual transform enables detection of runs (each…
We present an algorithm for two-dimensional radiative transfer in axisymmetric, circumstellar media. The formal integration of the transfer equation is performed by a generalization of the short characteristics (SC) method to spherical…
In the first section we present the atomic part where a C2+ atomic target was prepared and used to generate theoretical data to investigate recombination lines arising from electron-ion collisions in thin plasma. R-matrix method was used to…
Higher resolution telescopes as well as 3D numerical simulations will require the development of detailed 3D radiative transfer calculations. Building upon our previous work we extend our method to include both continuum and line transfer.…
We generalise the SuperEasy linear response method, originally developed to describe massive neutrinos in cosmological $N$-body simulations, to any hot dark matter (HDM) species with arbitrary momentum distributions. The method uses…
The goal of this paper is to assess the utility of Reduced-Order Models (ROMs) developed from 3D physics-based models for predicting transient thermal power output for an enhanced geothermal reservoir while explicitly accounting for…
We compare the predictions of four different algorithms for the distribution of ionized gas during the Epoch of Reionization. These algorithms are all used to run a 100 Mpc/h simulation of reionization with the same initial conditions. Two…
Counting distinct permutations with replacement, especially when involving multiple subwords, is a longstanding challenge in combinatorial analysis, with critical applications in cryptography, bioinformatics, and statistical modeling. This…
An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows to understand important characteristics like thermodynamic,…
Compressing convolutional neural networks (CNNs) is essential for transferring the success of CNNs to a wide variety of applications to mobile devices. In contrast to directly recognizing subtle weights or filters as redundant in a given…
Gas-phase multiply charged proteins have been sympathetically cooled to translational temperatures below 1 K by Coulomb interaction with laser-cooled barium ions in a linear ion trap. In one case, an ensemble of 53 cytochrome c molecules…
The thermal radiative transfer (TRT) equations form an integro-differential system that describes the propagation and collisional interactions of photons. Computing accurate and efficient numerical solutions TRT are challenging for several…
Cosmological hydrogen recombination has recently been the subject of renewed attention because of its importance for predicting the power spectrum of cosmic microwave background anisotropies. It has become clear that it is necessary to…
Extensive rovibrational line lists are constructed for 12 isotopologues of carbon dioxide: $^{12}$C$^{16}$O$_2$, $^{13}$C$^{16}$O$_2$, $^{12}$C$^{17}$O$_2$, $^{13}$C$^{17}$O$_2$, $^{12}$C$^{18}$O$_2$, $^{13}$C$^{18}$O$_2$,…
Convolution neural network demonstrates great capability for multiple tasks, such as image classification and many others. However, much resource is required to train a network. Hence much effort has been made to accelerate neural network…
When computing cross-sections from a line list, the result depends not only on the line strength, but also the line shape, pressure-broadening parameters, and line wing cut-off (i.e., the maximum distance calculated from each line centre).…