Simple communication complexity separation from quantum state antidistinguishability
Bibliographic record
Abstract
A set of n pure quantum states is called antidististinguishable if there exists an n-outcome measurement that never outputs the outcome 'k' on the kth quantum state.We describe sets of quantum states for which any subset of three states is antidistinguishable and use this to produce a two-player communication task that can be solved with log d qubits, but requires one-way communication of at least log(4/3)(d -1) -1 ≈ 0.415(d -1) -1 classical bits.The advantages of the approach are that the proof is simple and self-contained -not needing, for example, to rely on hard-to-establish prior results in combinatorics -and that with slight modifications, nontrivial bounds can be established in any dimension 3. The task can be framed in terms of the separated parties solving a relation.We show, however, that for this particular task, the separation disappears if two-way classical communication is allowed, or if the task need only be solved with bounded error.Finally, we state a conjecture regarding antidistinguishability of sets of states, and provide some supporting numerical evidence.If the conjecture holds, then there is a two-player communication task that can be solved with log d qubits, but requires exact one-way communication of (d log d ) classical bits.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".