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ZENODO
Software . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Python code for Figure 2: (nS)-state contact scaling of the information-gauge shift in hydrogenic spectroscopy

Authors: Lee, Ju Hyung;

Python code for Figure 2: (nS)-state contact scaling of the information-gauge shift in hydrogenic spectroscopy

Abstract

This repository contains the Python script used to generate Figure 2 of the manuscript Prepared-State Hydrogenic Spectroscopy as a Null Test of Information-Gauge Entanglement Couplings. The figure illustrates the benchmark (nS)-state contact scaling of an information-gauge spin-entanglement response in hydrogenic (2S-nS) transitions. The script computes and plots the benchmark frequency shift A_{\rm IG}\left(2^{-3}-n^{-3}\right),] using (A_{\rm IG}=2.0,{\rm mHz}), corresponding to the hydrogen 21-cm benchmark sensitivity scale discussed in the manuscript. It also converts the shift into an energy scale using (h=4.135667696\times10^{-15},{\rm eV,s}), showing that the asymptotic (n\rightarrow\infty) value corresponds to (\delta\nu_\infty=0.250,{\rm mHz}) or (\delta E_\infty\simeq1.03\times10^{-18},{\rm eV}). The code generates publication-ready PDF and PNG outputs: fig2_nS_contact_scaling_PLA.pdf fig2_nS_contact_scaling_PLA.png The plot is intended as a benchmark sensitivity visualization, not as a model-independent exclusion. The robust feature illustrated by the figure is the (n^{-3}) contact-scaling pattern for (S)-states and the absence of a contact shift for (\ell\neq0) states. Keywordshydrogenic spectroscopy; hyperfine structure; information-gauge field; entanglement; Ramsey spectroscopy; null test; Python; matplotlib; benchmark sensitivity; effective field theory

Keywords

hydrogenic spectroscopy; hyperfine structure; information-gauge field; entanglement; Ramsey spectroscopy; null test; Python; matplotlib; benchmark sensitivity; effective field theory

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average