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Record W2891391873 · doi:10.1103/physrevb.99.104308

Cooling arbitrary near-critical systems using hyperbolic quenches

2019· article· en· W2891391873 on OpenAlexaff
Prahar Mitra, Matteo Ippoliti, R. N. Bhatt, S. L. Sondhi, Kartiek Agarwal

Bibliographic record

VenuePhysical review. B./Physical review. B · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum many-body systems
Canadian institutionsMcGill University
FundersBasic Energy SciencesU.S. Department of EnergyKavli Institute for Theoretical Physics, University of California, Santa BarbaraUniversity of California, Santa BarbaraNational Science Foundation
KeywordsPhysicsConformal symmetryConformal field theoryExcited stateGround stateQuantum field theoryVacuum stateQuantum mechanicsMathematical physicsEffective field theoryScalar fieldConformal mapGeometryMathematics

Abstract

fetched live from OpenAlex

We describe a quench protocol that allows the rapid preparation of ground states of arbitrary interacting conformal field theories in $1+1$ dimensions. We start from the ground state of a related gapped relativistic quantum field theory and consider sudden quenches along the spacelike trajectories ${t}^{2}\ensuremath{-}{x}^{2}={T}_{0}^{2}$ (parameterized by ${T}_{0}$) to a conformal field theory. Using only arguments of symmetry and conformal invariance, we show that the post-quench stress-energy tensor of the conformal field theory is uniquely constrained up to an overall scaling factor. Crucially, the geometry of the quench necessitates that the system approach the vacuum energy density over all space except the singular lines $x=\ifmmode\pm\else\textpm\fi{}t$. The above arguments are verified using an exact treatment of the quench for the Gaussian scalar field theory (equivalently the Luttinger liquid), and numerically for the quantum $O(N)$ model in the large-$N$ limit. Additionally, for the Gaussian theory, we find in fact that even when starting from certain excited states, the quench conserves entropy, and is thus also suitable for rapidly preparing excited states. Our methods serve as a fast, alternative route to reservoir-based cooling to prepare quantum states of interest.

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), Insufficient payload (model declined to judge)
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 score0.881
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.023
GPT teacher head0.373
Teacher spread0.350 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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