lpGBT: Low-Power Radiation-Hard Multipurpose High-Speed Transceiver ASIC for High-Energy Physics Experiments
Bibliographic record
Abstract
Commissioning of detector systems for the high-luminosity large Hadron collider (HL-LHC) is scheduled to take place between 2026 and 2028 at CERN. Application-specific integrated circuits (ASICs) for those systems have been in intense development over the past ten years. Some of those ASICs, as is the case of the low-power gigabit transceiver (lpGBT) described in this work, have now been produced in industrial quantities and have been fully qualified for operation in the HL-LHC environments that require, where the innermost detectors are concerned, radiation hardness over 1 MGy. The lpGBT is a multifunctional device, enabling data transmission between the off-detector and the on-detector systems. Data can be transmitted from the detector at 5.12 and 10.24 Gb/s and to the detector at 2.56 Gb/s. It implements data rate-configurable electrical links to communicate with the front-end ASICs and low-speed serial and parallel buses for experiment control. A set of analog functions for monitoring and control of the physics detectors is also included. This article describes the functionality and the architecture of the lpGBT ASIC and reports on its radiation hardness characterization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".