Internal mechanical dissipation mechanisms in amorphous silicon
Bibliographic record
Abstract
Using activation-relaxation technique nouveau (artn), we search for two-level systems (TLSs) in models of amorphous silicon ($a$-Si). The TLSs are mechanisms related to internal mechanical dissipation and represent the main source of noise in the most sensitive frequency range of the largest gravitational wave detectors as well as one of the main sources of decoherence in many quantum computers. We show that in $a$-Si, the majority of the TLSs of interest fall into two main categories: bond-defect hopping, where neighbors exchange a topological defect, and Wooten-Winer-Weaire bond exchange. The distribution of these categories depends heavily on the preparation schedule of the $a$-Si. We use our results to compute the mechanical loss in amorphous silicon, leading to a loss angle of ${10}^{\ensuremath{-}3}$ at room temperature, decreasing to ${10}^{\ensuremath{-}4}$ at 150 K in some configurations. Our modeling results indicate that multiple classes of events can cause experimentally relevant TLSs in disordered materials and therefore multiple attenuation strategies might be needed to reduce their impact.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".