Mixing of quantum states under Markovian dissipation and coherent control
Bibliographic record
Abstract
Given any two quantum states $\ensuremath{\rho}$ and $\ensuremath{\sigma}$ in Hilbert spaces of equal dimension satisfying the majorization condition $\ensuremath{\rho}\ensuremath{\succ}\ensuremath{\sigma}$, it is always possible to transform $\ensuremath{\rho}\ensuremath{\mapsto}\ensuremath{\sigma}$ by a unital quantum map. In fact, any such transformation can be achieved just by means of noisy operations, i.e., by access to maximally mixed ancillary states and unitary transformations that act jointly in the system-ancilla space. Here, we investigate the possible transitions between states (i.e., the induced preorder of states) when one restricts the unitary control to the quantum system alone and replaces the maximally mixed ancillas with a Markovian master equation, represented by a unital Lindbladian. As a main result, we find necessary and sufficient conditions for the Lindbladian dissipation to have the same converting power as that of noisy operations, i.e., any transformation $\ensuremath{\rho}\ensuremath{\mapsto}\ensuremath{\sigma}$ is possible if and only if $\ensuremath{\rho}\ensuremath{\succ}\ensuremath{\sigma}$.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".