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Record W2088074200 · doi:10.1063/1.1319655

Random walk and diffusion of hard spherical particles in quenched systems: Reaching the continuum limit on a lattice

2000· article· en· W2088074200 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStatistical physicsLattice (music)Curse of dimensionalityRandom walkMonte Carlo methodAnomalous diffusionPhoton transport in biological tissueLimit (mathematics)DiffusionMathematicsPhysicsCondensed matter physicsMathematical analysisDynamic Monte Carlo methodQuantum mechanicsStatisticsDirect simulation Monte CarloComputer scienceInnovation diffusion

Abstract

fetched live from OpenAlex

Lattice Monte Carlo methods are widely used to study diffusion problems such as the random walk of a probe particle among fixed obstacles. However, the diffusion coefficient D found with such methods generally depends on the type of lattice used. In order to obtain experimentally relevant results, one often needs to consider the continuum limit, i.e., the limit where the size of the lattice parameter is infinitely small compared to the size of both the probe particle and the obstacles. A numerical procedure to reach this limit for a single particle diffusing between quenched impenetrable obstacles is presented. As an example, the case of a system of periodic spherical obstacles is treated and a general relation between the diffusion coefficient D, the total obstructed volume f, and the dimensionality d of the problem is proposed.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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