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Use when the user mentions 'HEPData' or asks to find experimental data, download data tables from HEP papers, get digitized plots, or retrieve cross-section measurements. HEPData contains data points behind figures in high-energy physics publications.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Flag anomalies and outliers in data using Bayesian inference. Use when the user asks to "flag the anomalies in this data", "which points are outliers", "find the anomalies", "flag outliers", "clean my data of outliers", "detect anomalies", "robust fit ignoring outliers", "mitigate RFI", "handle contaminated data", "anomaly detection", "outlier detection", or mentions flagging bad data points, anomaly-corrected likelihood, or epsilon mask.
Use this skill when the user asks to "create corner plots", "visualize posteriors", "plot chains", "analyze nested sampling output", "plot marginal distributions", "compare prior and posterior", "make triangle plots", or work with posterior samples from PolyChord, MultiNest, UltraNest, Cobaya, or other Bayesian inference tools. Provides complete guidance for creating publication-quality posterior visualizations from nested sampling or MCMC chains.
Guide for creating effective skills for fundamental physics research. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized scientific knowledge, research workflows, or physics tool integrations.
JAX-accelerated supernova bandflux calculation for light curve modeling. Use when the user asks to "compute bandflux", "calculate supernova flux", "fit light curves with JAX", "use SALT3 model", "create custom SED model", "set up supernova likelihood", or mentions jax-bandflux, SALT3Source, TimeSeriesSource, or supernova photometry. Provides installation guidance, synthetic data generation, and likelihood templates for SALT3 and custom SED models.
Use when the user mentions 'GWOSC', 'gravitational waves', 'LIGO', 'Virgo', or asks to find gravitational wave events, get event parameters, or download strain data. GWOSC provides open data from gravitational wave detectors.
Use when the user mentions 'Zenodo' or asks to find, search, or download datasets, software, or research artifacts with DOIs. Zenodo hosts scientific datasets, code releases, and supplementary materials from publications.
| name | hepdata |
| description | Use when the user mentions 'HEPData' or asks to find experimental data, download data tables from HEP papers, get digitized plots, or retrieve cross-section measurements. HEPData contains data points behind figures in high-energy physics publications. |
Search and download experimental data tables from HEPData, the high-energy physics data repository.
Requires: requests (pip install requests)
HEPData stores the actual data points behind plots and tables in HEP publications:
Data is linked to papers via INSPIRE IDs and available in multiple formats.
# Get record by HEPData ID
python scripts/hepdata.py ins1234567
# Get record by INSPIRE ID
python scripts/hepdata.py 1234567 --inspire
# Get record by arXiv ID
python scripts/hepdata.py 1907.12345 --arxiv
# List tables in a record
python scripts/hepdata.py 1234567 --inspire --tables
# Search by keywords
python scripts/hepdata.py --search "Higgs cross section"
# Search by reaction
python scripts/hepdata.py --search 'reactions:"P P --> TOP TOPBAR"'
# Search by collaboration
python scripts/hepdata.py --search "collaboration:ATLAS"
# Search by observable
python scripts/hepdata.py --search "observables:SIG"
# Limit results
python scripts/hepdata.py --search "dark matter" -n 5
reactions:"P P --> X" - Search by reactioncollaboration:NAME - Filter by collaboration (ATLAS, CMS, LHCb, etc.)observables:TYPE - Filter by observable typecmenergies:13000 - Center-of-mass energy in GeVkeywords:term - Search keywords# List available tables first
python scripts/hepdata.py 1234567 --inspire --tables
# Download specific table as CSV
python scripts/hepdata.py 1234567 --inspire --download "Table 1" --format csv
# Download all tables as YAML
python scripts/hepdata.py 1234567 --inspire --download --format yaml
# Download to specific directory
python scripts/hepdata.py 1234567 --inspire --download "Table 1" -o ./data/
csv - Comma-separated values (default)yaml - YAML format (HEPData native)json - JSON formatroot - ROOT fileyoda - YODA format (for Rivet)HEPData accepts three types of identifiers:
| Flag | Type | Example |
|---|---|---|
| (none) | HEPData ID | ins1234567 |
--inspire | INSPIRE recid | 1234567 |
--arxiv | arXiv ID | 1907.12345 |
python scripts/hepdata.py <inspire_id> --inspirepython scripts/hepdata.py <id> --inspire --tablespython scripts/hepdata.py <id> --inspire --download "Table 1" -f csv# Find ATLAS SUSY limits
python scripts/hepdata.py --search "collaboration:ATLAS SUSY exclusion"
# Download the limit data
python scripts/hepdata.py 1234567 --inspire --download "Exclusion contour" -f csv
# Find Higgs measurements
python scripts/hepdata.py --search "Higgs cross section 13 TeV"
# Download measurement table
python scripts/hepdata.py 1234567 --inspire --download "Cross section" -f csv
Download data points to compare with your theoretical predictions:
import pandas as pd
data = pd.read_csv("Table_1.csv")
# Plot data vs your theory
Use together with the inspire skill: