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A Full Calorimeter Image Reaches the Trigger in 25.9 Microseconds
An 8-bit FPGA CNN rejected 99.34 percent of a recorded background sample at nominal 95 percent signal efficiency within the adopted latency budget.
Summary
An 8-bit FPGA CNN rejected 99.34 percent of a recorded background sample at nominal 95 percent signal efficiency within the adopted latency budget.
A lossless space-to-depth transform and quantization-aware training shrink full-granularity calorimeter inference for FPGA execution. On 100,000 test events, the board measured 17.9 microseconds for CNN inference and a projected 25.9 microseconds end to end, below the study's 32-microsecond budget. The result is a KOTO-oriented proof of principle, not a deployed trigger claim.
Why it matters
An 8-bit FPGA CNN rejected 99.34 percent of a recorded background sample at nominal 95 percent signal efficiency within the adopted latency budget.
Limits and context
- The result is a KOTO-oriented proof of principle, not a deployed trigger claim.
Key claims
An 8-bit FPGA CNN rejected 99.34 percent of a recorded background sample at nominal 95 percent signal efficiency within the adopted latency budget.
Qualification: The result is a KOTO-oriented proof of principle, not a deployed trigger claim.
Evidence: source-2026-10-28-020
Sources
- arXiv preprint 2610.36720, original v1arXiv · primary research
Corrections
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