A Deep Dive into Classical and Topological CFT Thermodynamics in Lifshitz and Hyperscaling Violating Black Holes
Bibliographic record
Abstract
Abstract To effectively utilize the AdS/CFT correspondence, a precise set of rules must be established to guide the translation of computed quantities in the gravitational sector into their CFT counterparts, and vice versa. This framework is commonly referred to as the holographic dictionary. The formulation of such dictionaries opens a two‐way gateway, allowing researchers to extend theoretical principles and findings from one domain into the other for further exploration and study. The development of a holographic dictionary for Lifshitz black holes and hyperscaling violation (HSV) models has provided an essential foundation for studying CFT thermodynamics and phase behavior of these black holes. Based on this framework, the study will investigate their thermodynamic properties using two distinct approaches. In the first step, the work adopts the classical and traditional method, identifying critical points to examine the behavior of the free energy function as a function of temperature near the critical boundary. By analyzing its behavior, the work will study phase transitions and then proceed to evaluate the stability of the models. In the next step, to compare both methodologies and highlight their equivalence—particularly demonstrating the accessibility of the topological method compared to the classical approach—the study will analyze phase behavior through the lens of topological charges.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".