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148 results for βentropyβ
Graphical Abstract for "Emergent family of Tsallis entropies from the π-deformed combinatorics"
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ENTROPY DR1. High-resolution near-UV/optical spectra of 2MASS J11151597+1937266
<h1>ENTROPY Data Release 1 (v2.0)</h1> <h2>Summary</h2> <p>The files in this data release consist of the flux-calibrated, stacked 1D spectum of the isolated, free-floating accreting planetary-mass object 2MASS J11151597+1937266 (2M1115). The data results from the high-resolution (R~50,000) observations by the Ultraviolet and Visual Echelle Spectrograph (UVES) at ESO's Very Large Telescope (VLT) in Chile, between 10-11 June 2023, taken as part of the ESO programme 0111.C-0166(A). This is the underlying data used for the analysis in the publication <a href="https://doi.org/10.1051/0004-6361/202450881" target="_blank" rel="noopener">Viswanath et al. (2024)</a> </p> <h2>Details of Observations</h2> <p>The observations of 2M1115 with UVES were carried out between 10-11 June 2023 (MJD 60105, 60106) as part of the ExoplaNeT accretion mOnitoring sPectroscopic surveY (ENTROPY) in #Dichroic 1 mode with both the blue (390 nm) and red (580 nm) arms using a 0.8 arcsec wide slit without AO or chopping.</p> <p>A total of four frames at 740 s exposure (NDIT=1) each were obtained across the two nights, giving a total integration time of 0.82 hr at an average seeing of 1.43 arcsec and an average airmass 1.416. The total wavelength range covered by the spectrum is 320–680 nm.</p> <h2>Target</h2> <p>Identifier: 2MASS J11151597+1937266</p> <p>ICRS RA (ep=2016.0): 168.816234 deg</p> <p>ICRA DEC (ep=2016.0): +19.623939 deg</p> <p>Distance: 45.21 +- 2.20 pc</p> <p>Age: 5-45 Myr</p> <p>Mass: 6(+8, -4) Mjup</p> <p>Radius: 1.5 +- 0.1 Rjup</p> <p>Effective Temperature: 1816 +- 63 K</p> <h2>Data reduction</h2> <p>Each of the 4 raw data frames from the original set of exposures from the 2 nights were bias subtracted and flat-field corrected using the calibration files from ESO. Inter-order background was also subtracted. Cosmic rays were accounted for by using a horizontal median filtering and masking out pixels higher than 10 times the local variance. The flux was extracted order by order using standard aperture photometry, which included the subtraction of sky background and telluric lines.</p> <p>The flux was calibrated based on the observations of a standard star taken contemporaneously with the same observing setup as the target, and was corrected for the relative slit loss (~4%) from seeing. Wavelength calibration was performed using the arc lamp spectrum and a Th–Ar line list. The wavelengths listed in the spectrum are in air. A barycentric velocity correction was applied to the wavelength calibration to transform the spectral reference system to that of the source. The stacked 1D spectrum available in this data release is obtained by taking the weighted average of the 4 individual spectra, with the weights determined from the respective photon noise.</p> <h2>Description of files</h2> <p>The data release in this second version consists of:</p> <p>a) 1 merged spectrum UVES-2023.06.10-11.2M1115.merged-spectra.txt covering the entire UVES range of these observations (320–680 nm). The flux for the overlapping wavelengths in adjacent orders of each arm were averaged to get a single flux value per wavelength. This allows for easy access of the entire spectral range of all arms together. The ASCII file has 4 columns:</p> <p>Column1 : Wavelength, in ångstrøm</p> <p>Column2 : Flux, in units ergs/s/cm2/ångstrøm</p> <p>Column3 : Flux_stddev, the weighted standard deviation of the flux across the 4 individual spectra, in units of ergs/s/cm2/ångstrøm (This is the recommended error bar)</p> <p>Column4 : Flux_phot_err, Average of the photometric uncertainties in flux across the 4 spectra, in units of ergs/s/cm2/ångstrøm</p> <p>b) The compressed file UVES-2023.06.10-11.2M1115.non-merged-spectra.zip contains one folder per each of the three arms (Blue, RedL, RedU). The folders include ASCII files containing the spectrum for individual orders of each arm, provided for the purpose of preserving the signal-to-noise ratio (S/N) of all orders. Some important emission lines like Hπ½ occur in both adjacent orders but at different signal strengths. Merging the orders by averaging the flux as in file (a) will suppress the S/N of such emission lines.</p> <p>The order numbers of the respective arms containing detected emission lines from 2M1115 can be found in Tables 2 and G.1 in <a href="https://doi.org/10.1051/0004-6361/202450881" target="_blank" rel="noopener">Viswanath et al. (2024)</a>. For the following Balmer lines detected in <a href="https://doi.org/10.1051/0004-6361/202450881">Viswanath et al. (2024)</a>, the corresponding rest wavelengths appear in two consecutive orders as indicated below:</p> <table> <tbody> <tr> <td><strong>Line</strong></td> <td><strong>Arm</strong></td> <td><strong>Orders</strong></td> <td><strong>Detection in Viswanath et al. (2024)</strong></td> </tr> <tr> <td>Hπ½</td> <td>RedL</td> <td>2, 3</td> <td>Both at > 3σ S/N </td> </tr> <tr> <td>Hγ</td> <td>Blue</td> <td>34, 35</td> <td>Both at > 3σ S/N </td> </tr> <tr> <td>Hδ</td> <td>Blue</td> <td>28, 29</td> <td>Only in 28</td> </tr> <tr> <td>H7</td> <td>Blue</td> <td>24, 25 </td> <td>Both, but only ~2σ S/N in 24</td> </tr> <tr> <td>H9</td> <td>Blue</td> <td>20, 21</td> <td>At only ~2σ S/N in both</td> </tr> </tbody> </table> <p> </p> <p>Each ASCII file has 4 columns with same description as in file (a). To plot the spectrum of all the orders of all the arms, the following python code can be used:</p> <p><code>import numpy as np</code><br><code>from glob import glob</code><br><code>from natsort import natsorted</code><br><code>arms = ['BLUE', 'REDL', 'REDU']</code><br><code>plt.figure()</code><br><code>for arm in arms:</code><br><code> files = natsorted(glob(f'UVES-2023.06.10-11.2M1115.non-merged-spectra/{arm}/*.txt'))</code><br><code> print(files)</code><br><code> for i in range(len(files)):</code><br><code> data = np.loadtxt(files[i])</code><br><code> plt.plot(data[:, 0], data[:, 1])</code><br><code>plt.show()</code></p> <pre> </pre> <p>c) 2M1115-Photometry.txt, an ASCII file containing the existing photometry for the target</p> <h2> </h2> <h2>Changes from previous version V1.0</h2> <p>The merged spectrum UVES-2023.06.10-11.2M1115.merged-spectra.txt in this version has been modified to preserve the original spectral resolution in the overlapping wavelegth regions. In V1.0, the corresponding regions had double the resolution due to an error in the interpolation method used.</p> <p>The non-merged spectra of the individual orders have been replaced in this version as a compressed zip folder (instead of .npz files) containing ASCII files for spectra of each individual order to facilitate easier data handling.</p> <p>The photometry file has been updated from that of last version with more information, including two additional filter bands (<em>Gaia</em> Gbp and Grp) as well as effective filter widths of all provided filter bands.</p>
Level statistics and entanglement entropy of Rydberg dressed bosons in a triple-well potential
<p>We study the signatures of quantum chaos in Rydberg dressed bosonic atoms held in a 1 triple-well potential. Dynamics of the bosons are governed by an extended Bose-Hubbard model (EBHM) where long-range nearest-neighbor and next-nearest-neighbor interactions are induced by laser coupling the ground state to Rydberg state. We analyze the level statistics of the EBHM for finite number N of atoms through numerical diagonalization. In the presence of a tilting potential, the level statistics are Poissonian distribution for weak dressed interaction. It becomes a Wigner-Dyson distribution for strong interaction, signifying the emergence of quantum chaos. A hybrid distribution is obtained when the dressed interaction is much stronger than the hopping rate. Using the Fock basis, we further calculate dynamical evolution of the entanglement entropy. The maximal value (upper bound) of the entanglement entropy is proved to depend on particle numbers in the form ln(N + 1). It is found that the maximum of the time-averaged entanglement entropy appears when the chaos is strong. The location of the maximum as a function of the dressed interaction and tilting potential is independent of atom number N.</p>
Theory of Maximum Entropy Production (MEP) and Its Application to Microwave Remote Sensing - Simultaneous Retrieval of Soil Moisture and Vegetation Water Content
<p>A theory of maximum entropy production (MEP) for electromagnetic wave propagation in dielectric materials is proposed and applied to simultaneously retrieving soil moisture (SM) and vegetation water content (VWC) from L-band microwave brightness temperature (TB). One representation of the MEP principle states that a non-equilibrium system corresponds to such a configuration of energy fluxes that minimizes a dissipation function under the constraint of energy conservation. The dissipation function for radiative transfer is formulated as an analogy of that for heat transfer. A new physical parameter, radiative inertia as an analogy of thermal inertia, is introduced to characterize radiative attenuation in dielectric media. The radiative inertia is parameterized in terms of the penetration depth of electromagnetic waves as a function of the complex dielectric constant. The MEP based retrieval algorithm predicts SM and VWC by minimizing the dissipation function under the constraint of the conservation of radiative energy. The retrievals of SM and VWC based on the MEP theory were validated against field observations in tropical and temperate forested regions of the Amazon and North America. The proof-of-concept analysis demonstrates the capability of the MEP algorithm for simultaneous retrievals of SM and VWC even for dense canopy (e.g. VWC > 5 kg m-2). The MEP method is a new theoretical framework for developing innovative remote sensing algorithms of the Earth system not limited to just microwave observations.</p><p>Note: We would appreciate if users contact us for the use of the data.</p>
Site entropy mapped to PB1 structure
<p>The influenza virus polymerase is central to influenza virus evolution. Adaptive mutations within the polymerase are often a prerequisite for efficient spread of novel animal-derived viruses in human populations. The polymerase also determines fidelity, and therefore the rate at which the virus will acquire mutations that lead to host range expansion, drug resistance, or antigenic drift. Despite its importance to viral replication and evolution, our understanding of the mutational effects and associated constraints on the influenza RNA-dependent RNA polymerase (RdRp) is relatively limited. We performed deep mutational scanning of the A/WSN/1933(H1N1) PB1, generating a library of 95.4% of amino acid substitutions at 757 sites. After accuracy filters, we were able to measure replicative fitness for 13,354 (84%) of all possible amino acid substitutions, and 13 were validated by results from pairwise competition assays. Functional and structural constraints were better revealed by individual sites involved in RNA or protein interactions than by major subdomains defined by sequence conservation. Mutational tolerance, as defined by site entropy, was correlated with evolutionary potential, as captured by diversity in available H1N1 sequences. Of 29 beneficial sites, many have either been identified in the natural evolution of PB1 or shown experimentally to have important impacts on replication and adaptation. Accessibility of amino acid substitutions by single nucleotide mutation was a key factor in determining whether mutations appeared in natural PB1 evolution. Our work provides a comprehensive map of mutational effects on a viral RdRp and a valuable resource for subsequent studies of influenza replication and evolution.</p>
Sensitivity analysis of the maximum entropy production method to model evaporation in boreal and temperate forests
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Site entropy mapped to PB1 structure
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Data from: Land use change through the lens of macroecology: insights from Azorean arthropods and the Maximum Entropy Theory of Ecology
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FIGURE 9. Maximum entropy model developed for D in A new species of Desmopachria Babington (Coleoptera: Dytiscidae) from Cuba with a prediction of its geographic distribution and notes on other Cuban species of the genus
FIGURE 9. Maximum entropy model developed for D. andreae sp. n. in Cuba. Values range from high (red areas) to low environmental suitability (blue areas).
Data for manuscript "Automatic detection of orientation entropy within scenes"
<p>Raw Neuropscan .cntΒ data for 15 participants with conditions and stimulus order described in the logbook for each participant.</p>
Data for "Deciphering the code of viral-host adaptation through maximum entropy models"
<p>Data needed to reproduce the figures of the paper "Deciphering the code of viral-host adaptation through maximum entropy models", following the instructions provided in <a href="https://github.com/adigioacchino/MENB_snakemake">this GitHub repository</a>.</p>
QMC Raw Data for Disentangling the Physics of the Attractive Hubbard Model via the Accessible and Symmetry-Resolved Entanglement Entropies
<p><strong>Data Summary</strong></p> <p>Raw data of 'Disentangling the Physics of the Attractive Hubbard Model via the Accessible and Symmetry-Resolved Entanglement Entropies'.</p> <p>The default Julia RNG generates random seeds, with the seed number corresponding to the last four digits of each file name..</p> <p>For more details, please check README.md on the GitHub repository.</p> <p>The scripts for processing the raw data are located in the data folder within the same repository.</p>
Microstructure and mechanical properties of mechanically-alloyed CoCrFeNi high-entropy alloys using low ball-to-powder ratio
<p>The main issue of this work was to analyse the microstructural evolution and mechanical properties of FCC high entropy alloy (HEA) when BPR (ball-to-powder ratio) was limited to 5:1. The motivation of our work is to increase the amount of milled fraction without losing efficiency of the milling process. Nowadays many papers describe HEAs by using powder metallurgy processes, but higher BPR is used. In consequence less amount of powder is milled in one period and the process is not effective enough from the industrial point of view.</p> <p>In this work four equiatomic CoCrFeNi samples were made by Mechanical Alloying plus Spark Plasma Sintering using different milling times: 10, 20, 30, 40 hours. We used 200 Φ5 mm WC balls and milled with intervals 15:15 minutes. Milling speed was 250 rpm. After the mechanical alloying has been finished samples were sintered by using Spark Plasma Sintering technique. We chose 950 °C as a process temperature with heating rate 100 °C/min. Sintering pressure was 50 MPa. Samples were then homogenise in 1050 °C for 12 hours. Then samples were water quenched.</p> <p>The densification of samples during sintering was in satisfied level, what was confirmed by relative densities of samples (>90 %) The microstructure observation of sintered samples revealed Cr-rich particles evenly distributed in samples volume. The number of particles decreases with increasing the milling time. Elements are randomly distributed in the matrix phase except a small Cr-depletion. XRD technique shows multiple FCC structure. As the milling time exceeds, the main FCC structure is promoted. Microhardness increased as a function of milling time. After annealing microstructures were almost out of Cr-rich phase. Only the biggest particles remained. EBSD revealed the grain size decrement as a function of milling time. Also X-ray diffractograms presented significant homogenisation of manufactured samples. Despite the microhardness decrease after heat treatment, the longest milled sample still possess very promising properties. Moreover hardness of samples is not indent’s size dependent (micro- and nanohardness).</p> <p>During milling time the particles are joining and fracturing many times. As a consequence elements are mixing and promoting the new phase(s) growing. We deduced that Hall-Petch effect is the most important factor determining better mechanical properties in longer milled samples. However the milling process need to be improvement. Cr-rich phase observed in sintered samples is the effect of low efficiency of the process, which might be improved by either smaller fraction of Cr at the beginning (premilling process) or increase the other process parameters (milling speed, sintering time).</p>
Supplementary material for "Shock-induced spallation in a nanocrystalline high-entropy alloy: An atomistic study"
<p>Data provided in this upload:</p> <ul> <li>Pictures and tables from "Shock-induced spallation in a nanocrystalline high-entropy alloy: An atomistic study" paper</li> <li>Excel-Charts used to create the graphs and tables</li> <li>Vzz data files from our dump files extracted using OVITO used to calculate the SWVs (position datapoints are the crucial part)</li> <li>The potential used for our simulations</li> <li>Readme with the following information: <ul> <li>Crucial parameters used in our simulations</li> <li>Captions of all the figures and tables used in order</li> <li>Additional information in regards to shock wave velocities (SWV) and their calculation, plus the necessary values</li> </ul> </li> </ul>
Data for `Memory of elastic collisions drives high minority spin and oscillatory entropy in underdamped chiral spinners'
<p>This dataset contains the tracked trajectories of spinners for both 18-spinner and 36-spinner systems. The MATLAB code evaluation.m evaluates physical quantities including rotational and translational energies, angular velocity distribution, accumulative spin, and mixing entropy evolution from the tracked trajectories. To view a particular experiment, uncomment the loading command at the beginning of the code evaluation.m.</p>
Automatic exhaustive calculations of large material space by Korringa-Kohn-Rostoker coherent approximation method --- Applied to equiatomic quaternary high entropy alloys
<p>Calculated data of equiatomic quaternary solid solution phase (high-entropy alloys) on local magnetic moment, total magnetization, magnetic phase transition temperature and residual resistivity.</p> <p>The data was added on October 28.</p>
Raw Data for Evidence for Isotropic s-Wave Superconductivity in High-Entropy Alloys
<p>Raw Data for the paper "Evidence for Isotropic s-Wave Superconductivity in High-Entropy Alloys".</p>
Selected data analysed in the JGR Atmosphere manuscript " An application of the maximum entropy production method in the WRF Noah land surface model"
<p>The control experiment (hereafter WRF-CTL) and the MEP experiment (hereafter WRF-MEP) simulations results interpolated to the observation stations. The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day, and the latest 24-hour outputs are provided.</p>
Multiscale Entropy Analysis of Retinal Signals Reveals Reduced Complexity in a Mouse Model of Alzheimer's Disease
<p>MEA recordings from wild-type and 5xFAD mice retinas used for the analyses in the manuscript "Multiscale Entropy Analysis of Retinal Signals Reveals Reduced Complexity in a Mouse Model of Alzheimer's Disease".</p>
Data for "Nanoparticle reinforced medium entropy CoCrFeNi produced by laser powder bed fusion: Microstructure evolution"
<p>Nanoparticle-reinforced metallic composites produced via laser powder bed fusion (LPBF) offer an economically feasible approach for obtaining high-strength near-net shaped critical components in automotive and aviation industries. This study investigates the equiatomic medium entropy alloy (MEA) CoCrFeNi manufactured by LPBF, incorporating two types of reinforcing particles, titanium nitride (TiN) and titanium oxide (TiO2), with varying sizes and volume concentrations. In this paper, we focus on analyzing the microstructure and texture evolution of all alloys, alongside examining the dissolution, precipitation and phase transitioning of the particles. TiN nanoparticles dissolve in the melt pool and uniformly precipitate as TiO2, forming novel core-shell nanoparticles resistant to coarsening. </p> <p>Here we share the STEM raw data files that were used in the analysis. We also share a general image analysis routine that used python based modules to measure the particle sizes and their volume fraction.</p> <p>In brief, we used the following steps for several images of each sample:<br>(a) Threshold the equalized grayscale image to create a binary image.<br>(b) Calculate the area fraction of the cleaned binary image.<br>(c) Detect contours in the binary image.<br>(d) Extract properties of circles from the contours, such as scaled diameter, and area.<br>(e) Draw circles on the original image using the detected contours.</p> <p><br>For TiN/5/800 samples containing multiple square-shaped particles, we assess the area of these squares and subsequently determine the diameter of a circle possessing an equivalent area.</p> <p>We also share the the raw file and the jupyter notebook for the 4DSTEM experiment conducted on the core-shell nanoparticle.</p>
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