Universal Aspects of Entanglement in Quantum Many-Body Systems
Bibliographic record
Abstract
One of the most intriguing phenomena in quantum mechanics is the existence of entanglement, which measures quantum correlations without any classical analog. Entanglement not only plays a crucial role in the development of quantum technology, but also provides profound insights to the study of quantum many-body systems, a field that focuses on the physical properties of systems constituted of a macroscopic number of interacting quantum particles. This dissertation aims to characterize the universal properties of quantum many-body systems from their entanglement structure, and the content can be broadly divided into two parts. The first part focuses on the phenomena of quantum chaos and its breakdown due to the presence of an extensive number of conservation laws. Both systems in and out of equilibrium will be discussed from the aspect of entanglement. In the second part, motivated by the search of non-trivial quantum phases whose universal properties are governed by quantum mechanics despite at a finite (i.e. non-zero) temperature, we will characterize the entanglement structure of quantum systems described by Gibbs states at finite temperatures. In particular, we will discuss a novel entanglement-based diagnostic for non-trivial quantum phases that can survive thermal fluctuations. Such a study broadens the conventional scope of quantum phases that are only defined at zero temperature and may reveal insights into the development of quantum devices that are immune to thermal decoherence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".