Measuring environmental quantum noise exhibiting a nonmonotonic spectral shape.
Bibliographic record
Abstract
Understanding the physical origin of noise affecting quantum systems is important for nearly every quantum application. Quantum-noise spectroscopy has been used in various quantum systems, such as superconducting qubits, nitrogen-vacancy centers, and trapped ions. Traditional spectroscopy methods are usually efficient in measuring noise spectra with mostly monotonically decaying contributions. However, there are important scenarios in which the noise spectrum is broadband and nonmonotonous, thus posing a challenge to existing noise-spectroscopy schemes. Here we compare several methods for noise spectroscopy: spectral decomposition based on the Carr-Purcell-Meiboom-Gill sequence, the recently presented dynamic sensitivity control (DYSCO) sequence, and a modified DYSCO sequence with a Gaussian envelope (gDYSCO). The performance of the sequences is quantified by analytic and numeric determination of the frequency resolution, bandwidth, and sensitivity, revealing a supremacy of gDYSCO to reconstruct nontrivial features. Using an ensemble of nitrogen-vacancy centers in diamond coupled to a high-density C-13-nuclear-spin environment, we experimentally confirm our findings. The combination of the schemes presented offers potential to record high-quality noise spectra as a prerequisite to generate quantum systems unlimited by their spin-bath environment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".