Observation of light-driven band structure via multiband high-harmonic spectroscopy
Bibliographic record
Abstract
Abstract Intense light–matter interactions have revolutionized our ability to probe and manipulate quantum systems at sub-femtosecond timescales 1 , opening routes to the all-optical control of electronic currents in solids at petahertz rates 2–7 . Such control typically requires electric-field amplitudes in the range of almost volts per angstrom, when the voltage drop across a lattice site becomes comparable to the characteristic bandgap energies. In this regime, intense light–matter interaction induces notable modifications to the electronic and optical properties 8–10 , dramatically modifying the crystal band structure. Yet, identifying and characterizing such modifications remain an outstanding problem. As the oscillating electric field changes within the driving field’s cycle, does the band structure follow and how can it be defined? Here we address this fundamental question, proposing all-optical spectroscopy to probe the laser-induced closing of the bandgap between adjacent conduction bands. Our work reveals the link between nonlinear light–matter interactions in strongly driven crystals and the sub-cycle modifications in their effective band structure.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".