physics-research

name	physics-research
description	Use when the work is a physical measurement, a fit, an error budget, a detector or instrument analysis, or a simulation that has to agree with known physics. Covers dimensional checks, CODATA constants, Type A/B uncertainty and coverage factors, chi-square and covariance, systematics and blind analysis, HDF5/ROOT/FITS data and the arXiv/Zenodo/HEPData archives.
version	1.0.0
author	Remedy
tags	["research","physics","metrology","uncertainty","fitting","simulation"]
requires	[]
tools	["analysis_env","analysis_run","analysis_ledger","stats_assumptions","stats_effect_size","manuscript_build","lit_search","lit_fetch","cite_add","cite_check","skill_activate","file_read","file_write","repo_search"]
triggers	["\\b(systematic uncertaint\\w+|statistical uncertaint\\w+|error budget|error propagation|dimensional analysis|units check)\\b","\\b(Monte[- ]Carlo (?:event|generator)|GEANT4?|ROOT (?:file|tree|macro)|detector (?:calibration|response|acceptance))\\b","\\b(blind(?:ed)? analysis|look[- ]elsewhere effect|five sigma|5\\s?sigma|goodness[- ]of[- ]fit|chi[- ]?squared per (?:dof|degree))\\b","\\b(hep-(?:ex|ph|th|lat)|cond-mat|astro-ph|gr-qc|quant-ph|nucl-(?:ex|th))\\b"]

Physics research

Activate research-method first: skill_activate(skill="research-method"). That pack owns question framing, evidence standards, preregistration, citation honesty and how to say "we do not know". Do not restate it. What follows is only what physics does differently.

Order of operations

1. Dimensions before numbers. Reduce every term of the expression to base SI dimensions (M, L, T, I, temperature, N, J). Every summand must match, and the result must match the quantity claimed. A dimensional mismatch is findable in thirty seconds; a missing 2*pi is not, so also evaluate one limiting case whose answer is already known.
2. Constants from CODATA, never from memory. Take values and standard uncertainties from the NIST Fundamental Physical Constants dataset and record which CODATA adjustment year you used. Since the 2019 SI redefinition c, h, e, k_B and N_A are exact by definition; G and particle masses are measured and carry uncertainties. Never type a constant from recall into a result the owner will publish.
3. Uncertainty model before you fit. Per input, decide Type A (evaluated from repeated observations) or Type B (calibration certificate, datasheet tolerance, digitiser resolution, a published value). Write the list down before touching the data — see references/uncertainty-propagation.md.
4. Fit, then interrogate the fit (below).
5. Systematics last and hardest — references/systematics-and-blinding.md.
6. Reproduce. Every number that reaches the paper comes out of analysis_run, so the ledger holds argv, input hashes and artifact hashes. analysis_ledger(action="verify") is how you show a figure still matches the data it came from.

Quoting a result

value ± u means nothing until the reader is told what the ± is. State the standard uncertainty u (k=1) or the expanded U with its coverage factor k and the approximate coverage probability; give statistical and systematic parts separately; state correlations between quoted quantities. Round the uncertainty to one or two significant figures first, then round the value to the same decimal place — no more digits than the uncertainty supports, and no fewer. Units on every axis, table column and abstract number.

Fitting

• Least squares is maximum likelihood only for Gaussian errors. Counting data wants a Poisson likelihood; do not chi-square bins with a handful of entries.
• Report chi-square per degree of freedom with the dof and the p-value. chi2/dof near 1 says the residuals are consistent with the errors you quoted — it does not say the model is right, and chi2/dof well below 1 usually means the errors are overstated.