Speaker
Description
Quality control of front-end electronics is a critical but labor-intensive step in large-scale neutrino detector deployments. Expert knowledge must be applied consistently across thousands of channels, often in remote or underground environments where turnaround time directly impacts commissioning schedules. We present an agentic LLM-based workflow that automates this process end-to-end.
The system is built around a sequential multi-agent pipeline: a hardware monitor gate, a DAQ agent that acquires multi-channel ADC waveforms, a QC analysis agent that detects per-channel anomalies, and a diagnostic agent that maps findings to actionable remediation steps using retrieval-augmented generation over detector documentation and external tool integrations via the Model Context Protocol. A final cataloging agent writes a structured run record and streams a human-readable narrative report.
We describe the overall design philosophy and architecture, discuss how the agentic pattern naturally maps onto the sequential, gate-checked structure of a QC procedure, and present results on simulated waveforms with injected faults. We also discuss plans to deploy this workflow for qualifying detector subsystems.
| Contribution types | Standard talk (20min + 5min Q/A) |
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