GENERALIZED UNCERTAINTY PRINCIPLE EFFECTS ON NEUTRON STAR EQUATION OF STATE AND THERMAL PROPERTIES
Bibliographic record
Abstract
We investigate how the Generalised Uncertainty Principle (GUP) affects neutron star structure and cooling. By modifying the equations of state to include GUP effects at extremely high densities through momentum-dependent corrections to the relativistic Fermi gas model, we compute mass-radius relations and thermal evolution curves. Using advanced numerical techniques, we solve the Tolman-Oppenheimer-Volkoff and thermal transport equations together. Our results show that GUP introduces observable changes, especially in cooling behaviour and radius estimates. We compare our findings with NICER data from PSR J0030+0451 and PSR J0740+6620, as well as gravitational wave events like GW170817 and GW190425. This comparison enables us to place a tight upper bound on the GUP parameter, , making it the strongest astrophysical constraint to date. Our work highlights neutron stars as powerful tools for testing quantum gravity, setting the stage for future investigations using multi-messenger astronomy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".