Thermocompression bonding technology for multilayer superconducting quantum circuits
Bibliographic record
Abstract
Extensible quantum computing architectures require a large array of quantum bits operating with low error rates. A quantum processor based on superconducting devices can be scaled up by stacking microchips that perform wiring, shielding, and computational functionalities. In this article, we demonstrate a vacuum thermocompression bonding technology that utilizes thin indium films as a welding agent to attach pairs of lithographically patterned chips. At 10 mK, we find a specific dc bond resistance of 49.2 μΩ cm2. We show good transmission up to 6.8 GHz in a tunnel-capped, bonded device as compared to a similar uncapped device. Finally, we fabricate and measure a set of tunnel-capped superconducting resonators, demonstrating that our bonding technology can be used in quantum computing applications.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".