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695 results for “topologies”
Date and codes for papar "Manifestation of topological gapless phase in two-dimensional chiral symmetric system through Loschmidt echo"
<p>The date and MATLAB codes of numerical calculations for the papar "Manifestation of topological gapless phase in two-dimensional chiral symmetric system through Loschmidt echo". The codes are runnable in the MATLAB version R2018a. </p>
Quantized electrical, thermal, and spin transports of non-Hermitian clean and dirty two-dimensional topological insulators and superconductors
<p>The module contains the code and data corresponding to the paper arXiv:2408.00763. The README.txt file contains the description as to how to navigate through the files.</p>
Spin waves and orbital contribution to ferromagnetism in a topological metal
<p>The dataset contains the data for the paper "Spin waves and orbital contribution to ferromagnetism in a topological metal". The data are stored in .txt or excel form.</p> <p>There are two folders:<br>The "experiment_data" folder contains the unprocessed (not corrected by self-absorption correction or polarization factors) RXIS and XAS spectra.</p> <p>The "figure_source_data" folder contains the processed data shown in the figures of the paper. The data processing (self-absorption correction or polarization factor correction) is described in the paper and supplementary information.</p> <p>----------------------------------------------<br>Under "experiment_data" folder:<br>-The "XAS" folder contains the XAS spectra collected at the ADRESS beamline of the Swiss Light Source.</p> <p>-The "XMCD_sample_surface" folder contains the XMCD scans across the sample surfaces with/without magnetic field</p> <p>-The "RIXS_spectra_SLS" folder contains the RIXS spectra collected at ADRESS beamline of Swiss Light Source. The spectral Intensity is normalized to 5 minutes per CCD, and there are 3 CCDs. The "resolution.txt" is the resolution function measured on a carbon tap for RIXS measurements at fixed scattering angle = 130 deg. "rixs_cl(cr)_H0L_x.txt" files are the momentum dependence RIXS along H0L direction with left(right)-hand circular polarization. x = -1, 1, 2,..., 9, 10 represents (H, 0, L) = (-0.163, 0, 1.92), (0.017, 0, 2.04), (0.042, 0, 2.03), (0.083, 0, 2.01), (0.123, 0, 1.97), (0.2, 0, 1.85), (0.239, 0, 1.77), (0.273, 0, 1.67), (0.307, 0, 1.56), (0.336, 0, 1.44), (0.39, 0, 1.17), respectively. Similar to "rixs_cl(cr)_HHL_x.txt" files, where x = 1, ..., 4 here represents (H, H, L) = (0.024, 0.024, 2.03), (0.071, 0.071, 1.97), (0.116, 0.116, 1.85), (0.158, 0.158, 1.67). For "rixs_cl(cr)_phi_x.txt" files, x = 1, 2, 3, 4, 5, 6 represents phi = 0, 30, 45, 60, 75, 90 deg. The file "rixs_cl_2theta_90_H0p2_L1p34.txt" contains the RIXS spectrum for (H, 0, L) = (0.2, 0, 1.34) and left-hand circular polarization measured with scattering angle 2theta = 90 deg, and the similar meanings for the rest. The "E_detuning_map" folder contains the data of incident energy detuning measurement.</p> <p>-"RIXS_spectra_ESRF" contains the RIXS spectra collected at ID32 of ESRF in names of "rixs_cl(cr)_HHL_x.txt". Here x = 1, 2, ..., 6 represents L = 2.1 1.9, 1.7, 1.5, 1.3, 1.1, respectively. The intensity is in units of counts/40 minutes.</p> <p>--------------------------------------------<br>The "figure_source_data" folder contains the experimental data plotted in Figure 2 - 5. </p>
Enhancement of topological regime in elongated Josephson junctions - code
<p>Here are the codes to generate the whole data of the paper.</p>
Topologies, Checkpoints, and Configurations for the paper "GVI-RL: Graph-Invariant RL for Attack Paths Discovery using Vulnerabilities Embedded with Large Language Models"
<p>This repository consists of the <strong>files</strong> related to the <strong>paper</strong> "GVI-RL: Graph-Invariant RL for Attack Paths Discovery using Vulnerabilities Embedded with Large Language Models". In particular, this repository contains tensorboard logs, topologies, checkpoints, seeds, and results to ensure reproducibility of the results of the paper.</p> <p>The results included are related to the training/validation and hyper-parameters optimization of the outcome multi-label classifier, the GVI-RL agent, and the world model.<br>The data folder contains also the topologies used in the study, the vulnerabilities data used to generate them and the dataset for multi-label classification.</p> <p>The README.md file describes the folders' structure.</p>
"Fruity" Dye-based Fluorescent Nanoparticles (dFONs): A Fully Organic Counterpart of Alloy and Core-Shell Metallic Nanoparticles. Tuning Topology to Maximize Nano-interfacial Promoted Fluorescence Enhancement
<p>Data set related to the production of the figures in the article "“Fruity” Dye-based Fluorescent Nanoparticles (dFONs): A Fully Organic Counterpart of Alloy and Core-Shell Metallic Nanoparticles. Tuning Topology to Maximize Nano-interfacial Promoted Fluorescence Enhancement" by Kurek et al.</p> <p> </p> <p>The data are in txt, lif and opju format, organised by figure and sub-figures and compressed. </p>
Robust gap closing and reopening in topological-insulator Josephson junctions - Dataset
<p>This dataset contains experimental and numerical data as presented in the revised manuscript 'Robust gap closing and reopening in topological-insulator<br>Josephson junctions' by Jakob Schluck, Ella Nikodem, Anton Montag, Alexander Ziesen, Mahasweta Bagchi, Fabian Hassler, and Yoichi Ando.</p> <p>The data presented in the experimental figures is given in csv files, where the physical quantities and their units are described in the headers.</p> <p>The matlab code used for generating the parameter sweeps presented in figure 3b and figure 5 can be found in the simulations folder.</p> <p>Regarding the data presented in figure 2a and 2b as well as supplementary figure S10, obtained by numerical simulations, please consider the following:</p> <p>simulation.py:<br> Program used for the Kwant-simulation. It produces the file 'data.npz'. N denotes<br> the number of points that have to be calculated along energy and phase.</p> <p>plot.py:<br> Program that uses 'data.npz' as input and produces the plot shown in the manuscript.</p> <p> The temperature is introduced by smearing the zero-temperature data with the Fermi<br> functions due to the lead.</p> <p> As the BCS peak is very sharp, we are not sure that we hit it for each value of the<br> phase. Because of this, we postprocess the data by a running average over 100 points<br> in the phase.</p> <p>data.npz:<br> Data-file in numpy format<br> The conductance for zero temperature is saved on a regular grid<br> 'xs': the energy values<br> 'ys': the phase values<br> 'data': the conductance values</p> <p> Note that the values in the file are obtained by a combination of different runs<br> where care have been taken to sample more points close to the BCS peak, followed<br> by an interpolation to bring the data on a regular grid. Because of the interpolation,<br> the values reported in the file 'data.npz' can slightly differ from the value obtained<br> by running simulation.py at the respective point.</p> <p> </p>
Images and lane topology annotations of signalised intersections in Sydney
<p>This repository conatins imagery data for signalised intersections in Sydney, labels of their lane topologies and code for training neural networks to replicate the lane topologies.</p>
Data for "Topological grain boundary segregation transitions"
<p>Cite as: Vivek Devulapalli et al. ,Topological grain boundary segregation transitions.Science386,420-424(2024). DOI:10.1126/science.adq4147<br><br>This repository contains the raw data from STEM imaging, EDS, and EELS experiments, the code used for GB simulations and theoretical calculations presented in the paper. </p> <p>=========================================================</p> <p>MDMC-SGC directory contains the MD/MC simulation in the semi-grand-canonical<br>ensemble (Fig. 4 of the paper).</p> <p><br>Fe-Ti-phase-diagram<br>===================</p> <p>First, the bulk concentration of Fe in Ti is calculated as a function<br>of the chemical potential difference Δµ between Fe and Ti. This is<br>required to calculate the grain boundary excess over the bulk.</p> <p>Here, it turns out that the bulk concentration is approximately zero<br>in the range of Δµ investigated.</p> <p><br>MD/MC simulations of grain boundaries<br>=====================================</p> <p>The following sample names map to the naming in the paper:</p> <p>* ABC: Ti ground state structure<br>* large-1cage-2300000: isolated cage<br>* larger-2cages-3200000: double cage<br>* large-02-10000220: one layer of cages<br>* large-01-10000367: second layer of cages forming</p> <p>Each directory contains subdirectories for all investigated Δµ. The<br>subdirectory `final-states` contains the final snapshots for each Δµ.</p> <p>The script `prepare.py` was used to set up the simulations (template<br>for the LAMMPS input file is `lmp.in.template`). The script<br>`collect.py` was used to extract the thermodynamic excess properties<br>of the grain boundaries, stored in the file `T_0300K.excess.dat` in<br>each subdirectory.</p> <p>The notebook `plot-excess.ipynb` can be used to plot the excess data.</p> <p>=========================================================</p> <p># GRand canonical Interface Predictor (GRIP)</p> <p>_Authors: [Enze Chen](https://enze-chen.github.io/) (Stanford University) and<br>[Timofey Frolov](https://people.llnl.gov/frolov2) (Lawrence Livermore National Laboratory)_ <br>_Version: 0.1.2024.01.21_</p> <p>An algorithm for performing grand canonical optimization (GCO) of interfacial<br>structure (e.g., grain boundaries) in crystalline materials.<br>It automates sampling of slab translations and reconstructions<br>along with vacancy generation and finite temperature molecular dynamics (MD).<br>The algorithm repeatedly samples different structures in two phases:<br> 1. Structure generation and manipulation is largely handled using the<br> [Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/).<br> 2. Molecular dynamics and static relaxations are currently performed using<br> [LAMMPS](https://www.lammps.org), although in principle other energy<br> evaluation methods (e.g., density functional theory in [VASP](https://www.vasp.at))<br> may be used.</p> <p>------</p> <p>## Dependencies<br>- [Python](https://www.python.org/) (3.6+)<br>- [NumPy](https://numpy.org/) (1.23.0)<br>- [ASE](https://wiki.fysik.dtu.dk/ase/) (3.22.1)<br>- [LAMMPS](https://www.lammps.org) (stable)</p> <p>_Optional_<br>- [pandas](https://pandas.pydata.org/) (1.5.3)<br>- [Matplotlib](https://matplotlib.org/stable/index.html) (3.5.3)</p> <p><br>## Usage</p> <p>Assuming the above libraries are installed, clone the repo and make the <br>appropriate modifications in `params.yaml` (see file for detailed comments), <br>including the path to the LAMMPS binary on your system.<br>If you wish, you can supply your own slabs for the bicrystal configuration as<br>POSCAR_LOWER and POSCAR_UPPER (in the [POSCAR](https://www.vasp.at/wiki/index.php/POSCAR)<br>file format).<br>Then call:<br>```python<br>python main.py<br>```<br>If you don't have LAMMPS or just want to test the script, you can run it with the `-d` flag.<br>See the `.examples` folder for a SLURM submission script for parallel execution (preferred).</p> <p><br>## File structure<br>- `main.py`: Script to launch everything.<br>- `params.yaml`: Simulation parameters; **you'll want to edit this.**<br>- `core`: Main classes (`Bicrystal`, `Simulation`, etc.)<br>- `utility`: Main helper functions (`utils.py`, `unique.py`, etc.)<br>- `simul_files`: Files for simulations (LAMMPS input files, etc.)<br>- `best`: All relaxed structures are stored here. The naming convention is:<br>`lammps_Egb_n_X-SHIFT_Y-SHIFT_X-REPS_Y-REPS_TEMP_STEPS`</p> <p><br>Duplicate files are periodically deleted by calling `clear_best()` in `utils/unique.py`.<br>The default method cleans about 1-3% of files on average.<br>Use the `-e` flag for more aggressive cleaning (>50%).<br>Use the `-s` flag to save the processed results to CSV from a pandas DataFrame.</p> <p>Results can be visualized by running `utils/plot_gco.py` and it generates a GCO plot<br>of $E_{\mathrm{gb}}$ vs. $n$.<br>The `.examples` folder has this plot for several boundaries.<br>By default executing this file will save both the results (CSV) and the figure (PNG) <br>to the same folder as the GRIP output files.</p> <p><br>## Citation<br>If you use GRIP in your work, we would appreciate a citation to the original manuscript:</p> <p>> Enze Chen, Tae Wook Heo, Brandon C. Wood, Mark Asta, and Timofey Frolov.<br>"Grand canonically optimized grain boundary phases in hexagonal close-packed titanium."<br>_arXiv:XXXX.YYYYY [cond-mat.mtrl-sci]_, 2024.</p> <p>or in BibTeX format:</p> <p>```<br>@article{chen_2024_grip,<br> author = {Chen, Enze and Heo, Tae Wook and Wood, Brandon C. and Asta, Mark and Frolov, Timofey},<br> title = {Grand canonically optimized grain boundary phases in hexagonal close-packed titanium},<br> year = {2024},<br> journal = {arXiv:XXXX.YYYYY [cond-mat.mtrl-sci]},<br> doi = {10.48550/arXiv.XXXX.YYYYY},<br>}<br>```</p> <p>=========================================================</p> <p> </p>
APPENDIX III. Bayesian inference topology of COI gene with posterior probability values. Numbers at the nodes represent posterior probability support, other nodes with red circles has> 95%. Terminals with locality specification are species prior for understand the description of I. crassa sp. nov. (★). in A new species of Ischnocnema (Anura: Brachycephalidae) from the mountainous region of Atlantic Forest, southeastern Brazil, with a new phylogeny and diagnose for Ischnocnema parva series
APPENDIX III. Bayesian inference topology of COI gene with posterior probability values. Numbers at the nodes represent posterior probability support, other nodes with red circles has> 95%. Terminals with locality specification are species prior for understand the description of I. crassa sp. nov. (★).
FIGURE 1. Topology showing the most parsimonious tree obtained from a heuristic search with 1,000 in A new species of Microthyrium from Yunnan, China
FIGURE 1. Topology showing the most parsimonious tree obtained from a heuristic search with 1,000 random taxon additions of the combined dataset of SSU and LSU sequences alignment using PAUP v. 4.0b10. The scale bar shows 10 changes. Bootstrap support values for maximum parsimony (MP) and maximum likelihood (ML) greater than 50% above the nodes. The values below the nodes are Bayesian posterior probabilities above 0.95. Hyphen ("-") indicates a value lower than 50% (BS) or 0.90 (PP). The original isolate numbers are noted after the species names. The tree is rooted to Schismatomma decolorans.
Research data supporting: K. Tashiro, K. Katayama, K. Tamaki, L. Pesce, N. Shimizu, H. Takagi, R. Haruki, R. Heenan, M. J. Hollamby, G. M. Pavan, S. Yagai, "Non-uniform Photoinduced Unfolding of Supramolecular Polymers Leading to Topological Block Nanofibers"
<p>Raw research data supporting the article K. Tashiro, K. Katayama, K. Tamaki, L. Pesce, N. Shimizu, H. Takagi, R. Haruki, R. Heenan, M. J. Hollamby, G. M. Pavan, S. Yagai, "Non-uniform Photoinduced Unfolding of Supramolecular Polymers Leading to Topological Block Nanofibers".</p>
FIGURE 182. Alternative topology obtained using implied weighting options, using different k in Systematic revision and phylogeny of the endemic southeastern Asian Pristaulacus comptipennis species group (Hymenoptera: Aulacidae) 2959
FIGURE 182. Alternative topology obtained using implied weighting options, using different k-values: a, k=1–7; b, k=1, 3–4, 6–7; c, k=2, 4–5; d, k=8, 18–20.
Figure 3. Maximum likelihood topologies. A, cytochrome oxidase 1 fragments. B, internal transcribed spacer fragment. C, combined data set. Bootstrap supports over 75 in Integrative taxonomy of Parasabella and Sabellomma (Sabellidae: Annelida) from Australia: description of new species, indication of cryptic diversity, and translocation of some species out of their natural distribution range
Figure 3. Maximum likelihood topologies. A, cytochrome oxidase 1 fragments. B, internal transcribed spacer fragment. C, combined data set. Bootstrap supports over 75% shown on nodes. Scale bar, average of nucleotide substitutions per site.
Figure 3. Alternative topologies for node A in A reanalysis of Parabuthus (Scorpiones: Buthidae) phylogeny with descriptions of two new Parabuthus species endemic to the Central Namib gravel plains, Namibia
Figure 3. Alternative topologies for node A (Fig. 2) retrieved by analysis with equal weights. See Table 2 for details.
Figure 10. Reference topology with mapped dermal sculpture characters showing a phylogenetic signal, continued. A, character 10. B, character 11. C, character 12. For character 12 in Sculpture and vascularization of dermal bones, and the implications for the physiology of basal tetrapods
Figure 10. Reference topology with mapped dermal sculpture characters showing a phylogenetic signal, continued. A, character 10. B, character 11. C, character 12. For character 12, the coloration is similar to that in Figure 9, whereas for character 10 (four character states) and 11 (three character states), the lightest shading refers to character state 1, and the increasingly darker shadings refer to the ascending character states. For definition of characters, see Appendix 2.
BMP (LBPA) topologies, parameters, configurations, and related scripts
<p>Contents:</p> <p>000README</p> <p>PDB files for LBPA configurations:<br> 2-2R-RLBPA.pdb<br> 2-2R-SLBPA.pdb<br> 2-2S-SLBPA.pdb</p> <p>3-3R-RLBPA.pdb<br> 3-3R-SLBPA.pdb<br> 3-3S-SLBPA.pdb</p> <p>Python script to check and convert R/S handedness:<br> check_chirals.py</p> <p>Slipids topologies:<br> Slipids_2-2LBPA.itp<br> Slipids_3-3LBPA.itp</p> <p>Charmm36 topologies:<br> top_all36_2-2LBPA.rtf<br> top_all36_3-3LBPA.rtf</p> <p>Notes:<br> 1) All bonded terms are already included in Slipids and the charges are calculated based on the protocol used in Slipid parametrization<br> See the comments in the itp files.</p> <p>2) One has to change the molecule name if one wants to simulate a mixture of 3-3 and 2-2 isomers.</p>
Dataset for: Multivascular networks and functional intravascular topologies within biocompatible hydrogels
<p>Dataset for:</p> <p>Multivascular networks and functional intravascular topologies within biocompatible hydrogels</p> <p>Bagrat Grigoryan1,∗, Samantha J. Paulsen1,∗, Daniel C. Corbett2,∗, Daniel W. Sazer1, Chelsea L. Fortin2, Alexander J. Zaita1, Paul T. Greenfield1, Nicholas J. Calafat1, John P. Gounley3, Anderson H. Ta1, Fredrik Johansson2, Amanda Randles3, Jessica E. Rosenkrantz4, Jesse D. Louis-Rosenberg4, Peter A. Galie5, Kelly R. Stevens2,†, Jordan S. Miller1,†</p> <p>1Department of Bioengineering, Rice University, Houston, TX 77005, USA 2Department of Bioengineering, University of Washington, Seattle, WA 98195, USA 3Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA 4Nervous System, Somerville, MA 02143, USA 5Department of Biomedical Engineering, Rowan University, Glassboro, NJ 08028, USA</p> <p>∗Equal contribution. †Corresponding authors. Email: ksteve@uw.edu (K.R.S.) and jmil@rice.edu (J.S.M.).</p> <p>Solid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex 3D transport regimes that have remained difficult to produce and study. We establish intravascular and multivascular design freedoms with photopolymerizable hydrogels using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels produced in minutes comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We further elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. In addition, we deployed structured biodegradable hydrogel carriers in a rodent model of hepatic disease to highlight the potential translational utility of this materials innovation.</p>
Observing the quantum topology of light
<p>Includes all experimental data and simulation data in the manuscript "Observing the quantum topology of light".</p>
Observing the quantum topology of light
<p>Includes all experimental data and simulation data in the manuscript "Observing the quantum topology of light"</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.