A pipeline controller for the ATLAS calorimeter
Bibliographic record
Abstract
One approach to the front-end readout of the ATLAS liquid argon calorimeter is to store data locally in analog pipeline memories at the LHC beam-crossing frequency of 40 MHz. Proto-type pipeline chips using switched capacitor arrays which meet the ATLAS readout requirements exist. These new chips are capable of simultaneous read and write operations, and allow random access to storage locations. To utilize these essential design features requires a substantial amount of fast control and address bookkeeping logic. We have designed a controller capable of operating the pipelines as analog random access memories and that satisfies the ATLAS readout requirements. The pipeline controller manages the data of 256 time samples and provides dead-time free operation up to a trigger rate of 100 kHz, when reading out five time samples per event. This operation allows 2 /spl mu/s for the output reconstruction amplifiers to settle and should be sufficient to achieve the required 13-bit resolution. We are currently proto-typing a second PC-board version of our controller. The implementation of an integrated version based on the same design is in progress.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 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".