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Record W7106822945 · doi:10.5281/zenodo.17718328

Ultra-High Fidelity Disorder-Free 2D Floquet Time Crystal with Imaginary Spiral Twist: 5000-Period Simulation and 1M-Gate Validation on IBM Sherbrooke

2025· preprint· W7106822945 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Language
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsFloquet theoryFidelityLattice (music)QubitDegenerate energy levelsQuantum computerWave functionTwist

Abstract

fetched live from OpenAlex

I demonstrate a universal, passively stabilized logical qubit encoded in the degenerate Néel-cat subspace of a clean 2D Floquet system. Mean-field product-state evolution of a $30\times30$ lattice under disorder-free global drive with imaginary spiral twist $iJ\sin(\theta_{ij})\sigma^z_i\sigma^z_j$ yields full wavefunction fidelity 0.995741 after 5000 periods ($\omega\approx20$ Hz) with stabilizer fluctuations $\sim$0.001. The identical global-RF Hamiltonian, compiled with TKET, is executed on a 9-qubit patch of IBM Sherbrooke (127-qubit Eagle processor), achieving $\sim$1.05 million physical gate depth. Direct measurement on four marked physical qubits gives classical state fidelity $0.305\pm0.018$. For codes supported on the even-parity (cat) subspace, the tight lower bound of Gilchrist et al. (Phys. Rev. A 71, 062310, 2005) and subsequent cat-qubit literature yields logical fidelity $F_L \geq 1 - \frac{(1-F_c)^2}{2}$, giving $F_L \geq 0.76$ (central value) and $F_L \geq 0.71$ at 99\% confidence — surpassing all previously demonstrated bosonic codes at comparable overhead. Clear period-doubling response confirms robust discrete time-crystal order deep in the NISQ regime, with immediate applications to low-frequency isotope and chiral separation.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.991
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.243
Teacher spread0.226 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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