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Record W1867125714 · doi:10.1103/physrevb.66.014110

Equation of state and the Hugoniot of laser shock-compressed deuterium: Demonstration of a basis-function-free method for quantum calculations

2002· article· en· W1867125714 on OpenAlexaff
M. W. C. Dharma‐wardana, F. Perrot

Bibliographic record

VenuePhysical review. B, Condensed matter · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsEquation of stateShock (circulatory)CompressibilityPath integral Monte CarloPhysicsDeuteriumElectronQuantumShock wavePath integral formulationThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

In most density functionals the energy is a functional of the electron density $n(\stackrel{\ensuremath{\rightarrow}}{r})$ and a function of the nuclear positions ${R}_{i}.$ We consider, a functional of both$n(\stackrel{\ensuremath{\rightarrow}}{r})$ and the nuclear density $\ensuremath{\rho}(\stackrel{\ensuremath{\rightarrow}}{r})=\ensuremath{\sum}\ensuremath{\delta}(\stackrel{\ensuremath{\rightarrow}}{r}\ensuremath{-}{R}_{i}).$ In reducing the two Kohn--Sham equations, a classical mapping valid for interacting electrons is invoked. The exchange-correlation is nonlocal and free of self-interaction errors. As a challenging application, we calculate the equation of state and the shock Hugoniot of deuterium relevant to topical shock experiments. The calculated Hugoniot is quite close to the SESAME and path-integral Monte Carlo Hugoniots. We also treat the nonequilibrium case, which is extremely difficult for standard methods. Here the ${\mathrm{D}}^{+}$ are assumed to be hotter than the electrons, and lead to the soft Hugoniots similar to those seen in the laser-shock data. The softening arises from hot ${\mathrm{D}}^{+}--e$ pairs occurring close to the zero of the electron chemical potential.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.797

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)0.0010.000

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 head0.024
GPT teacher head0.273
Teacher spread0.249 · 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 designBench or experimental
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

Citations39
Published2002
Admission routes1
Has abstractyes

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