A new operational interpretation of relative entropy and trace distance between quantum states
Bibliographic record
Abstract
In this paper we present a new operational interpretation of relative-entropy between quantum states in the form of the following protocol. P: Alice gets to know the eigen-decomposition of a quantum state $\rho$. Bob gets to know the eigen-decomposition of a quantum state $\sigma$. Both Alice and Bob know $c= S(\rho || \sigma)$, the relative entropy between $\rho$ and $\sigma$ and an error parameter $\epsilon$. Alice and Bob use shared entanglement and after communication of $O((c +1)/\epsilon^4)$ bits from Alice to Bob, Bob ends up with a quantum state $\rho'$ such that $F(\rho, \rho') \geq 1 - \epsilon$, where $F$ represents fidelity. This result can be considered as a non-commutative generalization of a result due to Braverman and Rao [2011] where they considered the special case when $\rho$ and $\sigma$ are classical probability distributions. We use protocol P to obtain an alternate proof of a direct-sum result for entanglement assisted quantum one-way communication complexity for all relations, which was first shown by Jain, Radhakrishnan and Sen [2005, 2008]. We also present a variant of protocol in which Bob has some side information about the state with Alice. We show that in such a case, the amount of communication can be further reduced, based on the side information that Bob has. Our second result provides a new operational meaning to trace distance between quantum states in the form of a protocol which can be viewed as a quantum analogue of the classical correlated-sampling protocol, which is widely used, for example by Holenstein [2007] in his proof of a parallel-repetition theorem for two-player one-round games. Recently Dinur, Steurer and Vidick [2013] have shown another version of a quantum correlated sampling protocol different from our protocol, and used it in their proof of a parallel-repetition theorem for two-prover one-round entangled projection games.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.006 | 0.023 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".