Widefield Diamond Quantum Sensing with Neuromorphic Vision Sensors
At a Glance
Section titled âAt a Glanceâ| Metadata | Details |
|---|---|
| Publication Date | 2023-11-08 |
| Journal | Advanced Science |
| Authors | Zhiyuan Du, Madhav Gupta, Feng Xu, Kai Zhang, Jiahua Zhang |
| Institutions | Nano and Advanced Materials Institute, Max Planck Institute for Solid State Research |
| Citations | 9 |
| Analysis | Full AI Review Included |
Executive Summary
Section titled âExecutive SummaryâThis research introduces a novel approach for widefield Nitrogen Vacancy (NV) diamond quantum sensing by integrating a neuromorphic vision sensor (event camera), achieving significant performance gains over traditional frame-based methods (e.g., EMCCD).
- Temporal Resolution Improvement: The event-based method achieved a 13x improvement in temporal resolution, reducing the total sensing time for a complete Optically Detected Magnetic Resonance (ODMR) scan from 1.82 s (frame-based) to 0.14 s.
- Data Compression and Latency Reduction: By encoding fluorescence intensity changes as sparse events (âspikesâ), data volume was drastically reduced from 35 MB to 363 KB, resulting in a latency reduction from 26 ms to 220 ”s.
- Precision Maintenance: The event-based approach maintained comparable precision in detecting the ODMR resonance frequency (0.034 MHz) relative to the highly specialized frame-based method (0.031 MHz).
- Enhanced Signal Quality: The unique working principle, which ignores static background signals, resulted in a significantly higher temporal Signal-to-Background Ratio (SBRt = 10 vs. 1 for frame-based).
- Dynamic Monitoring Demonstrated: The technology successfully tracked dynamically modulated laser heating of gold nanoparticles on the diamond surface, achieving 0.28 s temporal resolution and 0.5 K temperature precision.
- Future Integration: This development paves the way for intelligent quantum sensors by enabling high-precision, low-latency widefield sensing suitable for integration with emerging memory devices and in-sensor processing.
Technical Specifications
Section titled âTechnical Specificationsâ| Parameter | Value | Unit | Context |
|---|---|---|---|
| Sensing Time (Event-Based) | 0.14 | s | Total time for complete ODMR scan (10 loops) |
| Sensing Time (Frame-Based) | 1.82 | s | Total time for complete ODMR scan (EMCCD) |
| ODMR Precision (Event) | 0.034 | MHz | Standard deviation of resonance frequency (f0) |
| ODMR Precision (Frame) | 0.031 | MHz | Standard deviation of resonance frequency (f0) |
| Data Amount (Event) | 363 | KB | Data transferred per complete ODMR measurement |
| Data Amount (Frame) | 35 | MB | Data transferred per complete ODMR measurement |
| Latency (Event) | 220 | ”s | Data readout and transfer overhead |
| Latency (Frame) | 26 | ms | Data readout and transfer overhead |
| Temporal SBR (SBRt) | 10 | - | Event-based method |
| Spatial SBR (SBR) | 194 | - | Event-based method |
| Dynamic Range | 120 | dB | Neuromorphic sensor capability |
| Temperature Temporal Resolution | 0.28 | s | Dynamic temperature tracking |
| Temperature Precision | 0.5 | K | Static temperature measurement |
| NV Concentration (Sample) | 670 | ”m-3 | Element Six SC Plate CVD diamond |
| Thermal Susceptibility (dD/dT) | 74 | kHz/°C | Used for temperature calculation |
Key Methodologies
Section titled âKey MethodologiesâThe event-based ODMR measurement relies on a specialized setup and a unique data processing protocol to leverage the high temporal resolution of the neuromorphic sensor.
- Sample and Setup: A commercial CVD diamond sample (<100> orientation) with a uniform NV distribution was used. The surface was coated with gold nanoparticles (AuNPs) synthesized using a NaOH/Tetrakis (hydroxymethyl) phosphonium chloride process for localized laser heating.
- Sensing Hardware: A standard widefield quantum diamond microscope setup (532 nm green laser, MW antenna) was modified to replace the conventional EMCCD camera with an off-the-shelf neuromorphic vision sensor (Prophesee EVK1-Gen 3.1 VGA).
- MW Frequency Modulation: Unlike frame-based methods that use discrete frequency steps, the MW frequency was swept continuously in a linear chirp manner across the resonance range (e.g., 70 ms sweep time).
- Event Generation: Each pixel in the neuromorphic sensor operates independently, generating a âpositive spikeâ when the fluorescence intensity increases by a predefined threshold (Cth) and a ânegative spikeâ when it decreases. This process only records changes, eliminating static background data.
- Spectrum Reconstruction: The raw spatial-temporal event stream is processed by calculating the event density (λe(t)), which is inversely proportional to the time interval (Ît) between events. This density directly encodes the derivative of the original Lorentzian fluorescence spectrum (Iâlog(f)).
- Precision Enhancement: To mitigate noise and time delay effects, the MW sweep was performed in both forward and backward directions, and the resulting resonance frequencies were averaged (f0*).
- Dynamic Thermometry Protocol: For dynamic measurements, a 637 nm red heating laser was modulated using an electrically-rotated linear polarizer (LPNIRE 100-B) to induce a continuous cosine square pattern of heating power, allowing the system to track rapid temperature shifts via the corresponding ODMR frequency shift.
Commercial Applications
Section titled âCommercial ApplicationsâThe low-latency, high-speed widefield quantum sensing enabled by neuromorphic sensors is critical for applications requiring real-time spatial mapping of physical quantities.
- Biomedical and Neuro-Sensing:
- Mapping neuronal action potentials and magnetic fields in biological systems with high temporal fidelity.
- Monitoring rapid, localized temperature changes related to cell activity or drug delivery.
- Condensed Matter Physics:
- Ultrafast monitoring and manipulation of magnetic phenomena, such as magnetic skyrmions and domain wall dynamics.
- Spin-assisted super-resolution imaging requiring high-speed data acquisition.
- Micro- and Nano-Electronics Inspection:
- High-speed widefield magnetic field mapping for integrated circuit (IC) inspection and failure analysis.
- Monitoring rapid thermal transients in microelectronic devices due to high thermal conductivity of diamond substrates.
- Intelligent Quantum Sensors:
- Development of next-generation quantum sensors featuring in-sensor processing capabilities, potentially integrating with electronic synapse devices for near-sensor algorithm execution.
- High-Speed Metrology:
- Real-time tracking of dynamic processes (e.g., vibration, fast flow sorting) where conventional frame rates are insufficient.
View Original Abstract
Abstract Despite increasing interest in developing ultrasensitive widefield diamond magnetometry for various applications, achieving high temporal resolution and sensitivity simultaneously remains a key challenge. This is largely due to the transfer and processing of massive amounts of data from the frameâbased sensor to capture the widefield fluorescence intensity of spin defects in diamonds. In this study, a neuromorphic vision sensor to encode the changes of fluorescence intensity into spikes in the optically detected magnetic resonance (ODMR) measurements is adopted, closely resembling the operation of the human vision system, which leads to highly compressed data volume and reduced latency. It also results in a vast dynamic range, high temporal resolution, and exceptional signalâtoâbackground ratio. After a thorough theoretical evaluation, the experiment with an offâtheâshelf event camera demonstrated a 13Ă improvement in temporal resolution with comparable precision of detecting ODMR resonance frequencies compared with the stateâofâtheâart highly specialized frameâbased approach. It is successfully deploy this technology in monitoring dynamically modulated laser heating of gold nanoparticles coated on a diamond surface, a recognizably difficult task using existing approaches. The current development provides new insights for highâprecision and lowâlatency widefield quantum sensing, with possibilities for integration with emerging memory devices to realize more intelligent quantum sensors.