Influence of random telegraph noise on quantum bit gate operation
Bibliographic record
Abstract
We consider the problem of analyzing spin-flip qubit gate operation in the presence of Random Telegraph Noise (RTN). Our compressive approach is the following. By using the Feynman disentangling operators method, we calculate the spin-flip probability of qubit driven by different kinds of composite pulses, e.g., Constant pulse (C-pulse), Quantum Well pulse (QW-pulse), and Barrier Potential pulse (BP-pulse) in the presence of RTN. When composite pulses and RTN act in the x-direction and z-direction respectively, we calculate the optimal time to achieve perfect spin-flip probability of qubit. We report that the highest fidelity of spin-flip qubit can be achieved by using C-pulse, followed by BP-pulse and QW-pulse. For a more general case, we have tested several pulse sequences for achieving high fidelity quantum gates, where we use the pulses acting in different directions. From the calculations, we find that high fidelity of qubit gate operation in the presence of RTN is achieved when QW-pulse, BP-pulse, and C-pulse act in the x-direction, y-direction, and z-direction, respectively. We extend our investigations for multiple QW and BP pulses while choosing the C-pulse amplitude constant in the presence of RTN. The results of calculation show that 98.5% fidelity can be achieved throughout the course of RTN that may be beneficial for quantum error correction.
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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 | 0.000 |
| 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".