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Record W3151922612 · doi:10.1103/physrevb.103.174305

Reaction-diffusion dynamics in a Fibonacci chain: Interplay between classical and quantum behavior

2021· article· en· W3151922612 on OpenAlexafffund
Cheng-Ju Lin, Liujun Zou

Bibliographic record

VenuePhysical review. B./Physical review. B · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum many-body systems
Canadian institutionsPerimeter Institute
FundersGovernment of CanadaInnovation, Science and Economic Development Canada
KeywordsFibonacci numberStatistical physicsDiffusionQuantumDynamics (music)Chain (unit)Chemical physicsPhysicsQuantum mechanicsMathematicsCombinatorics

Abstract

fetched live from OpenAlex

We study the reaction-diffusion dynamics of Fibonacci anyons in a one-dimensional lattice. Due to their non-Abelian nature, besides the position degree of freedom (DOF), these anyons also have a nonlocal internal DOF, which can be characterized by a fusion tree. We first consider a pure-reaction dynamics associated with the internal DOF, which is of intrinsically quantum origin, with either an ``all-$\ensuremath{\tau}$'' or ``completely random'' initial fusion tree. These two fusion trees are unstable and likely stable steady states for the internal DOF, respectively. We obtain the decay rate of the anyon number for these two cases exactly. Still using these two initial fusion trees, we study the full reaction-diffusion dynamics and find an interesting interplay between classical and quantum behaviors: These two fusion trees are still respectively unstable and likely stable steady states of the internal DOF, while the dynamics of the position DOF can be mapped to a hybrid classical $A+A\ensuremath{\rightarrow}0$ and $A+A\ensuremath{\rightarrow}A$ reaction-diffuson dynamics, with the relative reaction rates of these two classical dynamics determined by the state of the nonlocal internal DOF. In particular, the anyon density at late times are given by $\ensuremath{\rho}(t)=\frac{c}{\sqrt{8\ensuremath{\pi}}}{(Dt)}^{\ensuremath{-}\mathrm{\ensuremath{\Delta}}}$, where $D$ is a nonuniversal diffusion constant, $\mathrm{\ensuremath{\Delta}}=1/2$ is superuniversal, and $c$ is universal and can be obtained exactly in terms of the fusion tree structure. Specifically, $c=\frac{2\ensuremath{\varphi}}{\ensuremath{\varphi}+1}$ and $c=\frac{2(4\ensuremath{\varphi}+3)}{5(\ensuremath{\varphi}+1)}$ for the all-$\ensuremath{\tau}$ and completely random configuration respectively, where $\ensuremath{\varphi}=\frac{\sqrt{5}+1}{2}$ is the golden ratio. We also study the two-point correlation functions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.371
Teacher spread0.355 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations3
Published2021
Admission routes2
Has abstractyes

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