תמונות העטיפה

שמור ב:
מידע ביבליוגרפי
מחבר ראשי: B, Britt
פורמט: Recurso digital
שפה:
יצא לאור: Zenodo 2025
נושאים:
optically pumped magnetometer
OPM denoising
real-time magnetic feedback
fusion plasma control
common-mode rejection
power-line notch
causal Savitzky-Golay
edge signal processing
low-latency filtering
quantum sensor noise reduction
tokamak diagnostics
magnetic gradient estimation
OPM real-time denoising
causal filtering
fusion magnetic diagnostics
recursive IIR notch
Savitzky-Golay online
edge quantum sensing
low-latency feedback
tokamak control
python
cli tool
single-file script
גישה מקוונת:https://doi.org/10.5281/zenodo.18100507
תגים: הוספת תג
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תוכן הענינים:
  • <pre><code>edge_quantum_noise_filter.py v1.0 — Causal Real-Time OPM Denoising with Gradient Estimation Features • Zero extra setup — single file (numpy + matplotlib + scipy) • Fully causal/online pipeline for hard real-time edge use • Spatial common-mode rejection across array • Stateful recursive IIR notch (lfilter, no lookahead) • Causal Savitzky-Golay via rolling buffer • New: Inter-sensor ∇B gradient computation (MHD mode localization proxy) • Synthetic multi-sensor data with realistic noise • Five-panel visualization + SNR improvement reporting Dependencies • Requires numpy>=1.21 • Requires matplotlib>=3.5 — only for --plot • Requires scipy>=1.8 Intended for fusion magnetics teams deploying OPM arrays for low-latency, high-fidelity magnetic feedback in next-gen tokamaks requiring zero-lookahead processing. Real usage: python edge_quantum_noise_filter.py python edge_quantum_noise_filter.py --duration 15 --sensors 12 --power-line 60 python edge_quantum_noise_filter.py --no-plot # headless mode Made by Britt (2025) — MIT License</code></pre>

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