Attosecond transient interferometry
Bibliographic record
Abstract
Abstract Attosecond transient absorption resolves the instantaneous response of a quantum system as it interacts with a laser field, by mapping its sub-cycle dynamics onto the absorption spectrum of attosecond pulses. However, the quantum dynamics are imprinted in the amplitude, phase and polarization state of the attosecond pulses. Here we introduce attosecond transient interferometry and measure the transient phase, as we follow its evolution within the optical cycle. We demonstrate how such phase information enables us to decouple the multiple quantum paths induced in a light-driven system, isolating their coherent contribution and retrieving their temporal evolution. Applying attosecond transient interferometry reveals the Stark shift dynamics in helium and retrieves long-term electronic coherences in neon. Finally, we present a vectorial generalization of our scheme, theoretically demonstrating the ability to isolate the underlying anomalous current in light-driven topological materials. Our scheme provides a direct insight into the interplay of light-induced dynamics and topology. Attosecond transient interferometry holds the potential to considerably extend the scope of attosecond metrology, revealing the underlying coherences in light-driven complex systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".