The Phase-2 electronics upgrade of the ATLAS liquid argon calorimeter system
Bibliographic record
Abstract
The LHC high-luminosity upgrade in 2024–2026 requires the associated detectors to operate at luminosities about 5–7 times larger than assumed in their original design. The pile-up is expected to increase to up to 200 events per proton bunch-crossing. The current readout of the ATLAS liquid argon calorimeters does not provide sufficient buffering and bandwidth capabilities to accommodate the hardware triggers requirements imposed by these harsh conditions. Furthermore, the expected total radiation doses are beyond the qualification range of the current front-end electronics. For these reasons an almost complete replacement of the front-end and off-detector readout system is foreseen for the 182,468 readout channels. The new readout system will be based on a free-running architecture, where calorimeter signals are amplified, shaped and digitized by on-detector electronics, then sent at 40 MHz to the off-detector electronics for further processing. Results from the design studies on the performance of the components of the readout system are presented, as well as the results of the tests of the first prototypes.
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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 | 0.000 | 0.000 |
| 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) | 0.014 | 0.007 |
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".