Removing the big rip singularity from anisotropic universe in super string theory
Bibliographic record
Abstract
Recently, various observational data predict the possibility that dark energy could be in the form of phantom field. The positive phantom-energy density grows without limit with the expansion of the Universe and leads to a big-rip singularity at a finite future time. The main question arises: what is the origin of the big rip singularity in a four-dimensional Universe? To answer this question, in this paper, we propose a new model in super string theory that allows taking into account the Dirac and vector string tachyon in addition to the scalar one, which stretches between branes and antibranes. In this model, scalar and Dirac string tachyons cancel each other’s effects and the only effect induced by the vector tachyon can be observed in density and pressures of the universe. We observe that different scale factors, pressures, and dark energy equation of state parameters are produced in different directions because of inhomogeneous tachyon dynamics and consequently one anisotropic universe is formed. Also, these observations are given in terms of effective tachyon potential and the separation between branes and antibranes. Thus, we have shown that the expansion of the anisotropic Universe is controlled by the vector string tachyon and evolves from the non-phantom phase to the phantom one and consequently, the phantom-dominated era of the universe accelerates and ends up in a big-rip singularity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".