Fast transition-edge sensors suitable for photonic quantum computing
Bibliographic record
Abstract
Photon-number resolving transition-edge sensors (TESs) with near unity system detection efficiency enable novel approaches to quantum computing, for example, heralding robust Gottesman–Kitaev–Preskill qubit states. Increasing the speed of the detectors increases the rate at which these states can be heralded. In addition, depending on the details of the scheme, faster detectors can reduce the complexities of the hardware implementation. In previous work, we demonstrated that adding a small amount of gold between the tungsten film and silicon substrate can increase thermal conductance and reduce detector recovery time. In that study, the readout electronics imposed limitations on stable biasing conditions of the TES detector, and the TES could only be biased at higher than ideal values. In this report, we demonstrate the operation of the TES illuminated by a heavily attenuated pulsed laser running at 1 MHz repetition rate and examine the limits to adding gold to speed up device recovery times using a higher bandwidth readout system. The best performance was achieved by combining a 15×15μm2 tungsten TES with 5μm3 of gold, which resulted in a recovery time faster than 250 ns, with an energy resolution of 0.25 eV full-width at half maximum at 0.8 eV photon energy.
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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".