Experimental Realization of Decoherence-Free Subspace in Neutron Interferometry
Bibliographic record
Abstract
A decoherence-free subspace (DFS) is an important class of quantum-error-correcting (QEC) codes that have been proposed for fault-tolerant quantum computation. The applications of QEC techniques, however, are not limited to quantum-information processing (QIP). Here we demonstrate how QEC codes may be used to improve experimental designs of quantum devices to achieve noise suppression. In particular, neutron interferometry is used as a test bed to show the potential for adding quantum error correction to quantum measurements. We built a five-blade neutron interferometer that incorporates both a standard Mach-Zender configuration and a configuration based on a DFS. Experiments verify that the DFS interferometer is protected against low-frequency mechanical vibrations. We anticipate these improvements will increase the range of applications for matter-wave interferometry.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".