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Record W1940512992 · doi:10.1088/1367-2630/17/8/083061

Localization and delocalization for strong disorder in one-dimensional continuous potentials

2015· article· en· W1940512992 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNew Journal of Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversité de MontréalMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPhysicsDelocalized electronAnderson localizationLimit (mathematics)UncorrelatedNonlinear systemDimension (graph theory)WavelengthStatistical physicsQuantum mechanicsMathematical analysisStatisticsCombinatoricsMathematics

Abstract

fetched live from OpenAlex

In one-dimension and for discrete uncorrelated random potentials, such as\ntight binding models, all states are localized for any disorder strength. This\nis in contrast to continuous random potentials, where we show here that\nregardless of the strength of the random potential, we have delocalization in\nthe limit where the roughness length goes to zero. This result was obtained by\nderiving an expression for the localization length valid for all disorder\nstrengths. We solved a nonlinear wave equation, whose average over disorder\nyields the localization properties of the desired linear wave equation. Our\nresults, not only explain the origin of the difficulty to observe localization\nin certain physical systems, but also show that maximum localization occurs\nwhen the roughness length is comparable to the wavelength, which is relevant\nto many experiments in a random medium.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.260

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 head0.022
GPT teacher head0.254
Teacher spread0.232 · 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