Lightwave-controlled band engineering in quantum materials
Bibliographic record
Abstract
Stacking and twisting atom-thin sheets create superlattice structures with unique emergent properties, while tailored light fields can manipulate coherent electron transport on ultrafast timescales. The unification of these two approaches may lead to ultrafast creation and manipulation of band structure properties, which is a crucial objective for the advancement of quantum technology. Here, we address this by demonstrating a tailored lightwave-driven analogue to twisted layer stacking. This results in sub-femtosecond control of time-reversal symmetry breaking and thereby band structure engineering in a hexagonal boron nitride monolayer. The results practically demonstrate the realization of the topological Haldane model in an insulator. Twisting the lightwave relative to the lattice orientation enables switching between band configurations, providing unprecedented control over the magnitude and location of the band gap, and curvature. A resultant asymmetric population at complementary quantum valleys lead to a measurable valley Hall current, detected via optical harmonic polarimetry. The universality and robustness of the demonstrated sub-femtosecond control opens a new way to band structure engineering on the fly paving a way towards large-scale ultrafast quantum devices for real-world applications.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".