Qubit-mediated energy transfer between thermal reservoirs: Beyond the Markovian master equation
Bibliographic record
Abstract
We study qubit-mediated energy transfer between two electron reservoirs by adopting a numerically exact influence functional path-integral method. This nonperturbative technique allows us to study the system's dynamics beyond the weak coupling limit. Our simulations for the energy current indicate that perturbative-Markovian master equation predictions significantly deviate from exact numerical results already at intermediate coupling $\ensuremath{\pi}\ensuremath{\rho}{\ensuremath{\alpha}}_{j,{j}^{\ensuremath{'}}}\ensuremath{\gtrsim}0.4$, where $\ensuremath{\rho}$ is the metal (Fermi sea) density of states, taken as a constant, and ${\ensuremath{\alpha}}_{j,{j}^{\ensuremath{'}}}$ is the scattering potential energy of electrons, between the $j$ and ${j}^{\ensuremath{'}}$ states. Perturbative Markovian master equation techniques should be therefore used with caution beyond the strictly weak subsystem-bath coupling limit, especially when a quantitative knowledge of transport characteristics is desired.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".