{
  "abstract": "High-bandwidth plasma diagnostics increasingly provide inputs to machine learning and signal-processing algorithms intended for real-time tokamak control, but the complete path from diagnostic sampling to control-system handoff is difficult to commission because of their sampling rates. We develop a packet-level digital hardware twin for the megahertz diagnostic edge-AI architecture. The simulator represents a 64-channel, 1 MHz beam emission spectroscopy (BES) diagnostic embedded in a 96-channel dual-carrier acquisition system, two 48-channel streams with SPAD0 sample counters, 10 GbE Hardware UDP transport, packet loss and network jitter, FPGA parsing and dual-carrier alignment, causal preprocessing and edge inference, a compact Ethernet result packet, receiver-side shared state, and a 1 kHz PCS-like control cycle. Binary UDP payloads and PCAP files are generated rather than emulating transport only at the array level. With a baseline of 20 samples per packet, each carrier generates 50,000 packets s$^{-1}$ and 100 MB s$^{-1}$ of user payload. A 110 ms reference run produces 11,000 HUDP packets; an intentionally dropped 20-sample packet is detected by the sample-counter continuity logic and invalidates the two overlapping 128-sample inference windows without silent interpolation. For valid windows, the configured engineering latency model gives a median last-input-to-shared-memory latency of 91.6 us and a 99th percentile of 108.1 us. A separate operating-system loopback test sends binary FPGA-result datagrams through a UDP receiver into POSIX shared memory and preserves packet sequence and CRC for 20/20 packets. Interactive GUI interfaces expose timing, packetization, network faults, inference thresholds, and control-state inspection. The framework provides a reproducible environment for testing diagnostic-to-accelerator interfaces and fail-safe behavior for deployment on fusion devices.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.33994",
  "author_total": 9,
  "authors": [
    {
      "name": "Semin Joung"
    },
    {
      "name": "Abhilasha Dave"
    },
    {
      "name": "Luca Scomparin"
    },
    {
      "name": "Filipp Khabanov"
    },
    {
      "name": "Zheng Yan"
    },
    {
      "name": "Benedikt Geiger"
    },
    {
      "name": "George McKee"
    },
    {
      "name": "Ryan N. Coffee"
    },
    {
      "name": "David R. Smith"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dgvfy70npawyx.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.33994",
  "fulltext_url": null,
  "id": "dgvfy70npawyx",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.33994",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "physics.plasm-ph"
    ],
    [
      "openalex",
      "3106|Magnetic confinement fusion research"
    ]
  ],
  "openalex": "W7214740906",
  "pdf_url": "https://arxiv.org/pdf/2609.33994",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dgvfy70npawyx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:12Z",
      "native_id": "2609.33994",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.33994"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.plasm-ph",
      "subfield": "plasma"
    }
  ],
  "title": "A packet-level digital hardware twin for commissioning megahertz diagnostic edge AI and plasma control system integration in tokamaks",
  "title_text": "A packet-level digital hardware twin for commissioning megahertz diagnostic edge AI and plasma control system integration in tokamaks",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:12Z",
  "url": "https://research.draconitic.com/paper/dgvfy70npawyx",
  "venue": "arXiv",
  "versions": []
}