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60 results for “parity”
Hunting for vampires and other unlikely forms of parity violation at the Large Hadron Collider: lhe files
<p>Parton-level simulations in the PV-mSME model with various values of lambdaPV and for the standard model (lambdaPV=0).</p> <p>This dataset includes one example lhe file generated by MadGraph for each sample used in the <a href="https://arxiv.org/abs/2205.09876">paper</a>.<br> <br> The MadGraph version and the modifications we make to its generated code are included in the code sharing dataset on <a href="https://github.com/Rupt/paper-hunting-vampires">git</a> and <a href="https://doi.org/10.5281/zenodo.6827723">Zenodo</a>.<br> <br> Main files are named `liv_3j_4j_${lambdaPV}_0.lhe.gz`, where lambdaPV is a floating point number with "." replaced with "p".<br> <br> Other files named `liv_rot_${hour}_0.lhe.gz ` are from the rotated PV-mSME from the appendix that studies the effect of a rotating planet. Each rotation in radians is <em>hour * 2 pi / 24 </em>(for discrete rotations in a 24 hour day).<br> <br> The suffix "_0" encodes that each was generated with the first in our sequence of random seeds.</p> <p>`sm_3j_4j_0.lhe.gz` is simulated from the Standard Model, which is physically equivalent to lambdaPV = 0.</p>
Data of "Single-Photon Distillation via a Photonic Parity Measurement Using Cavity QED"
<p>Data published in "<em>Single-Photon Distillation via a Photonic Parity Measurement Using Cavity QED</em>"</p> <p>Phys. Rev. Lett. <strong>122</strong>, 133603</p>
A geometry preserving, conservative, mesh-to-mesh isogeometric interpolation algorithm for spatial adaptivity of the multigroup, second-order even-parity form of the neutron transport equation
<p>In this paper a method is presented for the application of energy-dependent spatial meshes applied to the multigroup, second-order, even-parity form of the neutron transport equation using Isogeometric Analysis (IGA). The computation of the inter-group regenerative source terms is based on conservative interpolation by Galerkin projection. The use of Non-Uniform Rational B-splines (NURBS) from the original computer-aided design (CAD) model allows for efficient implementation and calculation of the spatial projection operations while avoiding the complications of matching different geometric approximations faced by traditional finite element methods (FEM). The rate-of-convergence was verified using the method of manufactured solutions (MMS) and found to preserve the theoretical rates when interpolating between spatial meshes of different refinements. The scheme’s numerical efficiency was then studied using a series of two-energy group pincell test cases where a significant saving in the number of degrees-of-freedom can be found if the energy group with a complex variation in the solution is refined more than an energy group with a simpler solution function. Finally, the method was applied to a heterogeneous, seven-group reactor pincell where the spatial meshes for each energy group were adaptively selected for refinement. It was observed that by refining selected energy groups a reduction in the total number of degrees-of-freedom for the same total L2 error can be obtained.</p>
Data for: Downscaled gridded global dataset for Gross Domestic Product (GDP) per capita at purchasing power parity (PPP) over 1990-2022
<p>This dataset provides a gridded dataset for GDP per capita at purchasing power parity (PPP) downscaled to an admin 2 level (43,501 admin units). The dataset is based on reported subnational admin data (from 89 countries and 2,708 subnational units) and spans three decades from 1990 to 2022. </p> <p>The dataset is presented in details in the following publication. <strong><em>Please cite this paper when using data. </em></strong></p> <p>Kummu, M., Kosonen, M. & Masoumzadeh Sayyar, S. 2025. Downscaled gridded global dataset for gross domestic product (GDP) per capita PPP over 1990–2022. Scientific Data 12: 178. <a href="https://doi.org/10.1038/s41597-025-04487-x" target="_blank" rel="noopener">https://doi.org/10.1038/s41597-025-04487-x</a></p> <p><strong>Code is available</strong> at: <a href="https://github.com/mattikummu/griddedGDPpc" target="_blank" rel="noopener">https://github.com/mattikummu/griddedGDPpc </a></p> <p> </p> <p><strong>The following data is given (formats in brackets)</strong></p> <ul> <li>GDP per capita (PPP) at admin 0 level (national) (GeoTIFF, gpkg, csv)</li> <li>GDP per capita (PPP) at admin 1 level (at the level of reporting, either admin 1 level or admin 0 level) (GeoTIFF, gpkg, csv)</li> <li>GDP per capita (PPP) at admin 2 level (downscaled from admin 1 level) (GeoTIFF, gpkg, csv)</li> <li>Total GDP (PPP), downscaled admin 2 level GDP per capita (PPP) multiplied by gridded population count, with three resolutions: 30 arc-sec, 5 arc-min, and 30 arc-min (GeoTIFF) </li> <li>Input data for the script that was used to generate the data above (code_input_data.zip). Code available at https://github.com/mattikummu/griddedGDPpc </li> </ul> <p><strong>Files are named as follows</strong><br><em>Format</em>: raster data (GeoTIFF) starts with rast_*, polygon data (gpkg) with polyg_*, and tabulated with tabulated_*. <br><em>Admin levels:</em> adm0 for admin 0 level, adm1 for admin 1 level, and adm2 for admin 2 level<br><em>Product type:</em> GDP per capita at purchasing power parity (PPP): _gdp_perCapita_; and total GDP at purchasing power parity (PPP): _gdp_tot_</p> <p> </p> <p><strong>Metadata </strong></p> <p><em>Grids for GDP per capita data:</em></p> <p>Resolution: 5 arc-min (0.083333333 degrees) (for admin 2 level also 30 arc-min, 0.5 degree, resolution is provided)</p> <p>Spatial extent: Lon: -180, 180; -90, 90 (xmin, xmax, ymin, ymax) </p> <p>Coordinate ref system: EPSG:4326 - WGS 84 </p> <p>Format: Multiband geotiff; each band for each year over 1990-2022 </p> <p>Unit: USD in 2017 international dollars</p> <p> </p> <p><em>Grids for total GDP:</em></p> <p>Resolution: 30 arc-sec, 5 arc-min or 30 arc-min</p> <p>Spatial extent: Lon: -180, 180; -90, 90 (xmin, xmax, ymin, ymax) </p> <p>Coordinate ref system: EPSG:4326 - WGS 84 </p> <p>Format: Multiband geotiff; each band for each year over 1990-2022 (5 arc-min, 30 arc-min) or for each five years 1990, 1995, ... 2015, 2020 (30 arc-sec)</p> <p>Unit: USD in 2017 international dollars</p> <p> </p> <p><em>Geospatial polygon (gpkg) files: </em></p> <p>Spatial extent: -180, 180; -90, 83.67 (xmin, xmax, ymin, ymax) </p> <p>Temporal extent: annual over 1990-2022</p> <p>Coordinate ref system: EPSG:4326 - WGS 84 </p> <p>Format: gkpk </p> <p>Unit: USD in 2017 international dollars</p>
Hunting for vampires and other unlikely forms of parity violation at the Large Hadron Collider: truth-jet and reco-jet datasets
<p>All truth-jet and reco-jet datasets used in the <a href="https://arxiv.org/abs/2205.09876">paper</a>.</p> <p><strong>Main</strong>: fragments are named `truth-jet_${MODEL}.tar.gz`, where MODEL is either `pv_msme_${lambdaPV}` (PV-mSME and lambdaPV is a floating point number with "." replaced with "p"), or `sm` for the Standard Model (lambdaPV = 0).</p> <p>Within each are three directories for the independent splits:</p> <ul> <li>train,</li> <li>test, and</li> <li>private_test.</li> </ul> <p> In the paper, we describe "test" as the validation set and "private_test" as the test set. Data in "private_test" were not used until models were finalized for the paper.<br> Within each of those are the processed results from simulations with different random seeds. They are independent shards which can be trivially combined.</p> <p>Each data file is in <a href="https://www.h5py.org/">h5</a> format. Its data are under the key "events" as an array with shape (n, 20). That last axis contains the reconstructed four-momenta of the hardest five jets in the order [Px, Py, Pz, E] * 5, with missing jets filled with zeros.</p> <p>Truth-jet files have additional keys "flavors" and "helicities". These contain truth-level flavour and helicity information, respectively. Their shape is (n, 5), where the last axis contains the zero-padded results. Flavours are encoded in the PDG ID scheme.</p> <p><strong>Rotated</strong>: Rotated PV-mSME data are in archives named `truth-jet-rot_${HOUR}.tar.gz`.<br> These have similar (train, test, private_test) structures as the others, but comprise parts of the same mixed model and should be combined by subsampling to a weighted average.</p> <p>HOUR is an integer rotation in [0, 23] for which the detector is rotated by an angle given in radians as HOUR * 2 pi / 24. This rotated dataset has lambdaPV=1. We demonstrate merging of these datasets in the code sharing (<a href="https://github.com/Rupt/paper-hunting-vampires">git</a>, <a href="https://doi.org/10.5281/zenodo.6827723">Zenodo</a>).</p>
Hunting for vampires and other unlikely forms of parity violation at the Large Hadron Collider: calo-image datasets for the standard model
<p>An example calo-image dataset used in the <a href="https://arxiv.org/abs/2205.09876">paper</a>: standard model.</p> <p>Each shard is named `calo-image_sm_${DATASET}_${INDEX}.tar.gz`. Each contains one data file. DATASET is in {train,test,private_test} to label the three independent splits for training, validation, and testing respectively. INDEX labels separate batches which should be trivially combined.</p> <p>Each data file is in <a href="https://www.h5py.org/">h5</a> format. Its data are under the key "entries" as an array with shape (n, 32, 32) corresponding to (event_index, eta, phi) for the n calorimeter images in an unrolled eta--phi surface.</p> <p> </p>
Hunting for vampires and other unlikely forms of parity violation at the Large Hadron Collider: calo-image datasets for lambdaPV=1
<p>An example calo-image dataset used in the <a href="https://arxiv.org/abs/2205.09876">paper</a>: PV-mSME with lambdaPV=1.</p> <p>Each shard is named `calo-image_pv_msme_1_${DATASET}_${INDEX}.tar.gz`. Each contains one data file. DATASET is in {train,test,private_test} to label the three independent splits for training, validation, and testing respectively. INDEX labels separate batches which should be trivially combined.</p> <p>Each data file is in <a href="https://www.h5py.org/">h5</a> format. Its data are under the key "entries" as an array with shape (n, 32, 32) corresponding to (event_index, eta, phi) for the n calorimeter images in an unrolled eta--phi surface.</p> <p> </p>
Fig. 3 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 3. Phenogram of the peptidemes (P) of eight Trypanosoma cruzi reference strains obtained using the SM coefficient and the UPGMA clustering algorithm, based on data from non-conserved proteins, as seen in SDS-PAGE analysis. The major peptidemes are indicated as mP 1 and mP 2. Their subgroups are identified on the right (P II, P VI, P I), and were numbered following their respective genetic types (TcII, TcVI, TcI), as currently used.
Fig. 1 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 1. Total protein profiles of eight Trypanosoma cruzi reference strains separated in 10% SDS-PAGE at 250 V, 25 mA, 90 min, and stained by Coomassie brilliant blue. The position of some conserved proteins is indicated on the right. M: molecular mass markers. (kDa) are indicated on the left.
Fig. 2 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 2. Diagrammatic representation of the twenty-two protein bands not shared by all Trypanosoma cruzi reference strains (nonconserved proteins), as visualized in SDS-PAGE. These bands were coded and analyzed by numerical taxonomy procedures. At the top is indicated the number of the major groups they belong, as identified by different approaches. The bands that were exclusive of one or more strains were highlighted with rectangles. M: molecular mass markers. (kDa) are indicated on the left.
Data for figures in the paper "Parity Violation in Resonant Inelastic Soft X-Ray Scattering at Entangled Core Holes"
<p>This dataset can be used to recreate the figures in the paper "Parity Violation in Resonant Inelastic Soft X-Ray<br>Scattering at Entangled Core Holes" (doi to be published when available). Additional data can be provided upon reasonable request to the corresponding author (Johan Söderström, Johan.Soderstrom@physics.uu.se)</p><p>November 13: Added new experimental data for Fig. 2B (the old experimental data is still available). The data is the same but binned somewhat differently and the background is differently subtracted. Use the new version if you want to reuse some of this data.</p>
Data for: A coupled optical waveguides system in a fluidic medium that elucidates different parity-time-symmetric phases
<p>This research introduces a novel methodology of harnessing liquids to facilitate the realization of parity-time (<em>PT</em>)- symmetric optical waveguides on highly integrated microscale platforms. Additionally, we propose a realistic and detailed fabrication process flow, demonstrating the practical feasibility of fabricating our optofluidic system, thereby bridging the gap between theoretical design and actual implementation. Extensive research has been conducted over the past two decades on <em>PT</em>-symmetric systems across various fields, given their potential to foster a new generation of compact, power-efficient sensors and signal processors with enhanced performance. Passive <em>PT</em>-symmetry in optics can be achieved by evanescently coupling two optical waveguides and incorporating an optically lossy material into one of the waveguides. The essential coupling distance between two optical waveguides in air is usually less than 500 nm for nearinfrared wavelengths and under 100 nm for ultraviolet wavelengths. This necessitates the construction of the coupling region via expensive and time-consuming electron beam lithography, posing a significant manufacturing challenge for the mass production of <em>PT</em>-symmetric optical systems. We propose a solution to this fabrication challenge by introducing liquids capable of dynamic flow between optical waveguides. This technique allows the attainment of evanescent wave coupling with coupling gap dimensions compatible with standard photolithography processes. Consequently, this paves the way for the cost-effective, rapid and large-scale production of <em>PT</em>-symmetric optofluidic systems, applicable across a wide range of fields.</p>
Data from: Pace and parity predict short-term persistence of small plant populations
<p>Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near-term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decreases when reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near-term odds of extinction. </p>
On-The-Fly Solving for Symbolic Parity Games using the mCRL2 toolset
<p>This artifact contains a set of mCRL2 specifications and formulas that are used to compare various on-the-fly solving techniques for symbolic parity games. The techniques are described in the paper "On-The-Fly Solving for Symbolic Parity Games" by Maurice Laveaux, Wieger Wesselink and Tim A.C. Willemse.</p>
Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofs --- Supplemental Material
<p>Supplemental material for the extended version of the paper "Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofs".</p>
Dataset of "Giant gate-controlled odd-parity magnetoresistance in one-dimensional channels with a magnetic proximity effect"
<p>According to Onsager’s principle, electrical resistance <em>R</em> of general conductors behaves as an even function of external magnetic field <em>B</em>. Only in special circumstances, which involve time reversal symmetry (TRS) broken by ferromagnetism, the odd component of <em>R</em> against <em>B</em> is observed. This unusual phenomenon, called odd-parity magnetoresistance (OMR), was hitherto subtle (< 2%) and hard to control by external means. Here, we report a giant OMR as large as 27% in edge transport channels of an InAs quantum well, which is magnetized by a proximity effect from an underlying ferromagnetic semiconductor (Ga,Fe)Sb layer. Combining experimental results and theoretical analysis using the linearized Boltzmann’s equation, we found that simultaneous breaking of both the TRS by the magnetic proximity effect (MPE) and spatial inversion symmetry (SIS) in the one-dimensional (1D) InAs edge channels is the origin of this giant OMR. We also demonstrated the ability to turn on and off the OMR using electrical gating of either TRS or SIS in the edge channels. These findings provide a deep insight into the 1D semiconducting system with a strong magnetic coupling.</p>
Supplementary Material of the research study "Towards Gender Parity: Analyzing the Women Participation in STEM"
<p><span>The files present data considered in the analysis of students graduated in Brazil, from 2010 to 2019, with the purpose of contrasting STEM and Not STEM courses. </span></p> <p><span>The data was derived from Higher Education Census [Inep,2021].</span></p> <p><span>For the classification of courses as STEM courses, it was used the definition given by the SAGA methodology [UNESCO, 2016, 2017b], which refers to the International Standard Classification of Education (ISCED). </span></p> <p><span>ISCED was then related to the International Standard Classification of Education for Graduate and Specialized Courses in Brazil (Cine Brazil) [Inep, 2021], which classifies Brazilian undergraduate courses and is referenced by the official classification of courses in the Higher Education Census [Inep,2021].</span></p> <p> </p> <p><strong><span>References</span></strong></p> <p><span>Inep (2021). </span><em><span>Censo da Educação Superior</span></em><span>. </span><span>Bras</span><span>í</span><span>lia, DF. Available at https://www.gov.br/inep/pt-br/areasde-atuacao/pesquisas-estatisticas-e-indicadores/censo-daeducacao-superior/censo-da-educacao-superior.</span></p> <p><span> </span><span>Inep (2021). </span><em><span>Cine Brasil</span></em><span>. Bras</span><span>í</span><span>lia, DF. </span><span>Available at https://www.gov.br/inep/pt-br/areas-eatuacao/</span></p> <p><span>pesquisas-estatisticas-e-indicadores/cinebrasil/cine-brasil.</span></p> <p><span> </span><span>UNESCO (2016). Measuring Gender Equality in Science and Engineering: the SAGA Science, Technology and Innovation Gender Objective List (STI GOL). Technical Report SAGA Working Paper 1, UNESCO, Paris.</span></p> <p><span> </span><span>UNESCO (2017b). Measuring Gender Equality in Science and Engineering: the SAGA Toolkit. Technical Report SAGA Working Paper 2, UNESCO, Paris.</span></p>
Parity-Odd-4PCF-regions
<p>Code for reproduction and region-based analysis of BOSS CMASS parity-odd-four-point function in Krolewski, May, Smith, Hopkins (2024)</p>
Simulation results for "Localized statistics decoding: A parallel decoding algorithm for quantum low-density parity-check codes"
<p>This dataset contains simulations results presented in the paper "Localized statistics decoding: A parallel decoding algorithm for quantum low-density parity-check codes".</p> <p>The files are in `csv` file format, with data easily processable using the python library `sinter`.</p>
Towards highly accurate calculations of parity violation in chiral molecules: relativistic coupled-cluster method including QED-effects
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Towards highly accurate calculations of parity violation in chiral molecules: relativistic coupled-cluster method including QED-effects", by Ayaki Sunaga and Trond Saue.</p>
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