Quasi-particles in conformal field theoryThis paper was presented at the Theory CANADA 4 conference, held at the Centre de Recherches Mathématiques at the Université de Montréal, Québec, Canada on 4–7 June 2008.
Bibliographic record
Abstract
After recalling some basing features of conformal field theory, we present an elementary introduction to the description of the states in the irreducible modules of the minimal models. The characters, which encode the state content of each module, are easily constructed from the representation theory of the Virasoro algebra and they take the form of infinite alternating sums. On the other hand, the relation between the minimal models and particular statistical models has led to the discovery of alternative expressions for the characters, which are positive definite. These entail a (yet to be fully worked out) quasi-particle description of the space of states, via a filling process with restrictions akin to the exclusion principle. The simplest class of positive characters, pertaining to the ℳ(2,p) models, is presented, and its underlying combinatorial aspects are spelled out. A natural conformal field theoretical interpretation of its quasi-particles is presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".