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Record W3017195916 · doi:10.1063/1.5144233

Modeling escape from a one-dimensional potential well at zero or very low temperatures

2020· article· en· W3017195916 on OpenAlexaff
Chungho Cheng, G. Salina, Niels Grønbech‐Jensen, James A. Blackburn, M. Lucci, M. Cirillo

Bibliographic record

VenueJournal of Applied Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDissipationForcing (mathematics)PhysicsThermalZero (linguistics)Statistical physicsInitial value problemDouble-well potentialThermodynamicsMechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

The process of activation from a one-dimensional potential is systematically investigated in zero and nonzero temperature conditions. The features of the potential are traced through statistical escape from its wells, whose depths are tuned in time by a forcing term. The process is carried out for the damped pendulum system imposing specific initial conditions on the potential variable. While the escape properties can be derived from the standard Kramers theory for relatively high values of the dissipation, for very low dissipation, these deviate from this theory by being dependent on the details of the initial conditions and the time dependence of the forcing term. The observed deviations have regular dependencies on initial conditions, temperature, and loss parameter itself. It is shown that failures of the thermal activation model are originated at low temperatures and very low dissipation, by the initial conditions and intrinsic, namely, T = 0, characteristic oscillations of the potential-generated dynamical equation.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.553

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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