MétaCan
Menu
Back to cohort
Record W4409692343 · doi:10.1088/0256-307x/42/5/053705

Quantum Simulation of Two-Dimensional U(1) Gauge Theory in Rydberg and Rydberg-Dressed Atom Arrays

2025· article· en· W4409692343 on OpenAlexafffund
Zheng Zhou, Yan Zheng, Changle Liu, Yan Chen, Xue‐Feng Zhang

Bibliographic record

VenueChinese Physics Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersFundamental Research Funds for the Central UniversitiesInstitut Périmètre de physique théoriqueNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaMinistry of Colleges and UniversitiesCentre Scientifique et Technique du BâtimentNational Key Research and Development Program of ChinaRenmin University of ChinaIndustry CanadaNational Natural Science Foundation of ChinaNational Science FoundationWestlake University
KeywordsRydberg atomRydberg formulaPhysicsGauge (firearms)Atom (system on chip)Rydberg constantQuantumAtomic physicsQuantum mechanicsMaterials scienceComputer science

Abstract

fetched live from OpenAlex

Abstract Simulating U(1) quantum gauge theories with spatial dimensions greater than one is of great physical significance. Here we propose a simple realization of U(1) gauge theory with Rydberg and Rydberg-dressed atom arrays. Within the experimentally accessible range, we find that the various aspects of the U(1) gauge theory can be well simulated, such as the emergence of topological sectors, incommensurability, and the Rokhsar–Kivelson point that hosts deconfined charge excitations and degenerate topological sectors. Our proposal is promising to implement experimentally and exhibits pronounced quantum dynamics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.260
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueChinese Physics LettersSame topicCold Atom Physics and Bose-Einstein CondensatesFrench-language works237,207