Inherently unpredictable beam steering for quantum LiDAR

TL;DR

The paper tackles the problem that conventional quantum LiDAR beam steering is predictable, limiting stealth. It introduces quantum-enhanced parallel LiDAR (QEP-LiDAR) that leverages temporal-spectral correlations from spontaneous four-wave mixing to render the probe direction inherently unpredictable until the heralding photon is measured, mapping frequency to direction via a diffraction grating and using time-of-flight for ranging. The key contributions include a noise-resilience framework linking $SNR_C$, $SNR_Q$, and $E_{SNR}$, an experimental demonstration of parallel target detection with up to $E_{SNR}\approx 10^3$ under noisy conditions, and a system achieving $2.2$ cm distance resolution and $0.144°$ angular resolution. This work establishes a new paradigm for quantum-enhanced sensing with stealth capabilities and broad implications for quantum metrology, secure communications, and beyond.

Abstract

Quantum LiDAR offers noise resilience and stealth observation capabilities in low-light conditions. In prior demonstrations, the telescope pointing was raster-scanned, making the observation direction predictable from the pointing direction. However, while Quantum LiDAR can enable stealth observation, operational stealth is enhanced by inherently unpredictable beam steering. Here, we introduce a novel stealth beam steering method that is fundamentally immune to prediction. In a photon pair, the probe photon undergoes diffraction in an unpredictable direction at a grating due to wavelength randomness. The arrival time of the heralding photon, delayed by propagation through a dispersive medium, enables the determination of the probe photon's diffraction direction. Our method successfully detects multiple targets in parallel, demonstrating up to a 1000-fold enhancement in signal-to-noise ratio compared to classical LiDAR. This breakthrough establishes a new paradigm for quantum-enhanced sensing, with far-reaching implications for quantum metrology, secure communications, and beyond.

Figures (5)

• Figure 1: Schematic diagrams of quantum-enhanced parallel light detection and ranging (QEP-LiDAR). (a) Spectral diagram of spontaneous four-wave mixing (SpFWM), where $f_{\mathrm{p}}$ denote the frequency of pump photons, and $f_{\mathrm{pr, i}}$ and $f_{\mathrm{h, i}}$ (for $\mathrm{i}=1,2,\ldots$) represent the frequencies of signal (probe) and idler (heralding) photons, respectively. (b) Temporal distribution of SpFWM-generated photons relative to the pump time ($\tau_{\mathrm{p}}$). (c) Temporal separation of photons after passing through a dispersive medium with a constant group velocity dispersion. $\tau^\prime_{\mathrm{ref}}$ is the reference time for the pump light to pass through the dispersion medium. (d) Spatial separation of probe photons by a diffraction grating, where $\theta \left( f \right)$ indicates the direction of each photon as a function of its frequency. (e) Schematic of distance measurement to targets using the QEP-LiDAR method, where $t_d$ is the temporal delay between heralding and probe photons.
• Figure 2: Experimental setup. (a) Pump: ps pulsed laser, BS: beam splitter, BF: bandpass filter, Fiber spool: Corning SMF-28 (25.248 km), Noise source: amplified spontaneous emission source, PD: InGaAs photodetector, TCSPC: time-correlated single photon counter, SNSPD: superconducting nanowire single-photon detector, DG: diffraction grating, Circ.: circulator. Coll.: collimating lens. The inset shows the waveguide cross-section and the computed intensity profile of the optical mode. (b) Front view of the targets as seen precisely above the grid. The blurry region on the right side of the image is the DG, which is out of focus. (c) Top view of the targets.
• Figure 3: Measured coincidence counts of QEP-LiDAR system. (a)-(b) Scatter plots of CCs with probe photon arrival time on the X-axis and heralding photon arrival time on the Y-axis. (a) when the probe photons are directly detected on SNSPD ch. 2 and, (b) when the probe photons are sent to free space targets. (c)-(d) Scatter plots of CCs with target distance on the X-axis and target direction on the Y-axis. (c) when the probe photons are directly detected on SNSPD ch. 2 and, (d) when the probe photons are sent to free space targets. The maximum CC along the x-axis is marked with a red dot using a Gaussian fit. The data was accumulated for 60 s with a coupled pump peak power of 52.3±1.4 mW.
• Figure 4: Noise resilience experiment. Measured CC distributions for 60 s with target distance on the X-axis and target direction on the Y-axis, (a) when noise is off, (b) when noise is at $+8.2 \, \mathrm{dB}$, (c) when noise is at $+19.0 \, \mathrm{dB}$, and (d) when noise is at $+29.1 \, \mathrm{dB}$.
• Figure 5: $\mathbf{SNR}_\mathbf{Q}$(color), $\mathbf{SNR}_\mathbf{C}$(black), and corresponding $\mathbf{E}_\mathbf{SNR}$ against the noise intensity in various coupled pump peak powers. Signal-to-noise ratio for quantum and classical methods and its quantum enhancement: Blue and black squares: $26.9 \pm 1.4 \, \mathrm{mW}$, green and black triangles: $52.3 \pm 1.4 \, \mathrm{mW}$, and red and black circles: $103.1 \pm 2.9 \, \mathrm{mW}$. (a) target 1, (b) target 2, (c) target 3, (d) target 4 and, (e) target 5.