Excitation of muonic molecules ddμ and dtμ by super-intense attosecond soft X-ray laser pulses: Shaped post-laser-pulse muonic oscillations and enhancement of nuclear fusion
Bibliographic record
Abstract
The quantum dynamics of muonic molecular ions ddμ and dtμ excited by linearly polarized along the molecular (z)-axis super-intense laser pulses is studied beyond the Born–Oppenheimer approximation by the numerical solution of the time-dependent Schrödinger equation within a three-dimensional model, including the internuclear distance R and muon coordinates z and ρ. The peak-intensity of the super-intense laser pulses used in our simulations is I0 = 3.51 × 1022 W/cm2 and the wavelength is λl = 5 nm. In both ddμ and dtμ, expectation values 〈z〉 and 〈 ρ 〉 of muon demonstrate "post-laser-pulse" oscillations after the ends of the laser pulses. In ddμ post-laser-pulse z-oscillations appear as shaped nonoverlapping "echo-pulses". In dtμ post-laser-pulse muonic z-oscillations appear as comparatively slow large-amplitude oscillations modulated with small-amplitude pulsations. The post-laser-pulse ρ-oscillations in both ddμ and dtμ appear, for the most part, as overlapping "echo-pulses". The post-laser-pulse oscillations do not occur if the Born–Oppenheimer approximation is employed. Power spectra generated due to muonic motion along both optically active z and optically passive ρ degrees of freedom are calculated. The fusion probability in dtμ can be increased by more than 11 times by making use of three sequential super-intense laser pulses. The energy released from the dt fusion in dtμ can by more than 20 GeV exceed the energy required to produce a usable muon and the energy of the laser pulses used to enhance the fusion. The possibility of power production from the laser-enhanced muon-catalyzed fusion is discussed.
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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 | 0.000 |
| 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) | 0.002 | 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".