Exact solutions for generalized variable-coefficients Ginzburg-Landau equation: Application to Bose-Einstein condensates with multi-body interatomic interactions
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Bibliographic record
Abstract
We present a double-mapping method (D-MM), a natural combination of a similarity with F-expansion methods, for obtaining general solvable nonlinear evolution equations. We focus on variable-coefficients complex Ginzburg-Landau equations (VCCGLE) with multi-body interactions. We show that it is easy by this method to find a large class of exact solutions of Gross-Pitaevskii and Gross-Pitaevskii-Ginzburg equations. We apply the D-MM to investigate the dynamics of Bose-Einstein condensation with two- and three-body interactions. As a surprising result, we obtained that it is very easy to use the built D-MM to obtain a large class of exact solutions of VCCGLE with two-body interactions via a generalized VCCGLE with two- and three-body interactions containing cubic-derivative terms. The results show that the proposed method is direct, concise, elementary, and effective, and can be a very effective and powerful mathematical tool for solving many other nonlinear evolution equations in physics.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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