Silicon <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> -center hyperfine structure and memory protection schemes
Bibliographic record
Abstract
Combining the long-coherence of spin qubits and the capability to transmit information and entanglement through photons, spin-photon interfaces (SPIs) are a promising platform for networked quantum computation and long-distance quantum communication. SPIs that possess local `memory' qubits in addition to the optically coupled `communication' qubit can improve remote entanglement fidelities through brokered entanglement schemes and entanglement purification. In these schemes, it is critical to protect the memory qubit from decoherence during entanglement operations on the communications qubit. Silicon, a platform with mature microelectronic and nanophotonic fabrication, is host to the T centre, an SPI with emission in the telecommunications O-band that directly integrates with silicon nanophotonics. Cavity-coupled T centres are a platform for brokered entanglement distribution in silicon photonic circuits and over long-distance optical fibre links. The T centre's electron and nuclear spin qubits are an intrinsic register of communication and memory qubits respectively, with anisotropic hyperfine coupling. In this work we determine the T centre's hydrogen hyperfine coupling tensor. We also introduce schemes to protect against dephasing or eliminate relaxation of the T centre's hydrogen memory qubit during optical excitation. These results address a key challenge for practical T centre quantum networks.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.011 |
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 source (direct Gemma or distilled Codex), 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".