Supporting Data for PRX Quantum (Universal Adapters between quantum LDPC codes)
Bibliographic record
Abstract
Quantum LDPC surgery using auxiliary graph construction. This data accompanies arXiv:2410.03628 . The goal is to illustrate the code deformation/logical measurement scheme presented in the paper. The two small quantum LDPC codes used as examples to illustrate the scheme are [[98,6,12]] bivariate bicyclic code [[200,20,10]] lifted product code This data contains Parity check matrices (Hx and Hz) for the original quantum LDPC codes, deformed quantum LDPC codes, to- measure logicals Z_1, Z_2, Z_3 individually, as well as - measure Z_1 Z_2 jointly (multi-code), and - measure Z_1 Z_3 jointly (intra-code). Input graph and Output matrices for SkipTree algorithm (sparse basis transformation to the canonical repetition code) proposed in this paper. The code deformation scheme presented in this paper preserves code distance and maintains sparsity in the deformed quantum code.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".