Quantum rangefinding

Transmission of quantum-secured images

The secure transmission of an image can be accomplished by encoding the image information, securely communicating this information, and subsequently reconstructing the image. Alternatively, here we show how the image itself can be directly transmitted while ensuring that the presence of any eavesdropper is revealed in a way akin to quantum key distribution (QKD). We achieve this transmission using a photon-pair source with the deliberate addition of a thermal light source as background noise. One photon of the pair illuminates the object, which is masked from an eavesdropper by adding indistinguishable thermal photons, the other photon of the pair acts as a time reference with which the intended recipient can preferentially filter the image carrying photons from the background. These reference photons are themselves made sensitive to the presence of an eavesdropper by traditional polarisation-based QKD encoding. Interestingly the security verification is performed in the two-dimensional polarisation-basis, but the image information is encoded in a much higher-dimensional, hence information-rich, pixel basis. In our example implementation, our image comprises of 152 independent pixels. Beyond the secure transmission of images, our approach to the distribution of secure high-dimensional information may offer new high-bandwidth approaches to QKD.

Demonstration of quantum-enhanced rangefinding robust against classical jamming

We demonstrate a quantum-enhanced lidar capable of performing confident target detection and rangefinding in the presence of strong, time-varying classical noise whilst operating with over five orders of magnitude separation between signal and background levels and target reflectivities down to -52 dB. We use a log-likelihood-based framework to introduce a new protocol for dynamic background tracking, verifying resilience of our system to both fast- and slow-modulation jamming in regimes where a classical illumination-based system fails to find a target. These results demonstrate the advantage of exploiting quantum correlations for lidar applications, providing a clear route to implementation in real-world scenarios.

Robotic Vectorial Field Alignment for Spin-Based Quantum Sensors

Developing practical quantum technologies will require the exquisite manipulation of fragile systems in a robust and repeatable way. As quantum technologies move toward real world applications, from biological sensing to communication in space, increasing experimental complexity introduces constraints that can be alleviated by the introduction of new technologies. Robotics has shown tremendous progress in realizing increasingly smart, autonomous, and highly dexterous machines. Here, a robotic arm equipped with a magnet is demonstrated to sensitize an NV center quantum magnetometer in challenging conditions unachievable with standard techniques. Vector magnetic fields are generated with 1° angular and 0.1 mT amplitude accuracy and determine the orientation of a single stochastically-aligned spin-based sensor in a constrained physical environment. This work opens up the prospect of integrating robotics across many quantum degrees of freedom in constrained settings, allowing for increased prototyping speed, control, and robustness in quantum technology applications.

Hiding images in noise

A limitation of free-space optical communications is the ease with which the information can be intercepted. This limitation can be overcome by hiding the information within background optical noise. We demonstrate the transfer of images over free-space using a photon-pair source emitting two correlated beams. One of these beams contains image information, to which noise is added, and the other correlated beam is used as a heralding trigger so that the intended recipient can differentiate this image signal from the background noise. The system uses spontaneous parametric down-conversion to create photon-pairs with a wide spectral bandwidth and a gated intensified camera to extract the image from the background noise. The high-dimensionality of the image space means that the information content can be many bits per detected photon, whereas the heralding photon can be restricted to a single spatial-mode within a secure fiber which itself could be protected against interception by traditional low-dimensionality quantum key protocols.

Light detection and ranging with entangled photons

Single-photon light detection and ranging (LiDAR) is a key technology for depth imaging through complex environments. Despite recent advances, an open challenge is the ability to isolate the LiDAR signal from other spurious sources including background light and jamming signals. Here we show that a time-resolved coincidence scheme can address these challenges by exploiting spatio-temporal correlations between entangled photon pairs. We demonstrate that a photon-pair-based LiDAR can distill desired depth information in the presence of both synchronous and asynchronous spurious signals without prior knowledge of the scene and the target object. This result enables the development of robust and secure quantum LiDAR systems and paves the way to time-resolved quantum imaging applications.

Gaussian state-based quantum illumination with simple photodetection

Proofs of the quantum advantage available in imaging or detecting objects under quantum illumination can rely on optimal measurements without specifying what they are. We use the continuous-variable Gaussian quantum information formalism to show that quantum illumination is better for object detection compared with coherent states of the same mean photon number, even for simple direct photodetection. The advantage persists if signal energy and object reflectivity are low and background thermal noise is high. The advantage is even greater if we match signal beam detection probabilities rather than mean photon number. We perform all calculations with thermal states, even for non-Gaussian conditioned states with negative Wigner functions. We simulate repeated detection using a Monte-Carlo process that clearly shows the advantages obtainable.