Quantum imagers have been demonstrated in the laboratory by several groups. However, there are many practical concerns that must be considered in order to make such a system as successful as classical imagers in field applications. Consequently, we develop a model for signal-to-noise ratio (SNR) to estimate the performance of a quantum imager in comparison with that of the classical case. We assume simple architectures for both systems with components in the two as common to each other as possible. Comparisons between the imagers are made under conditions of solar background for ranges up to 2 km. The performance of quantum imager is shown to be superior to that of the classical case under conditions of narrow joint (or coincidence) detection windows and very strong pumping of the spontaneous parametric downconverter illumination source, for which the degree of photon entanglement may be severely degraded.
Quantum imagers have been demonstrated in the laboratory by several groups. However, there are many practical concerns that must be considered in order to make such a system as successful as classical imagers in field applications. Consequently, we develop a model for signal-to-noise ratio (SNR) to estimate the performance of a quantum imager in comparison with that of the classical case. We assume simple architectures for both systems with components in the two as common to each other as possible. Comparisons between the imagers are made under conditions of solar background for ranges up to 2 km. The performance of quantum imager is shown to be superior to that of the classical case under conditions of narrow joint (or coincidence) detection windows and very strong pumping of the spontaneous parametric downconverter illumination source, for which the degree of photon entanglement may be severely degraded.
Quantum illumination is an idea for detection of targets in the presence of a noisy background using a photon pair that is entangled in some degree of freedom, such as frequency. This paper provides a simple and illustrative proof-of-concept setup of a quantum illumination investigation. Detection and imaging is investigated in the optical regime using a correlated source and the performance of classical illumination and quantum illumination are compared for detection and imaging experiments. The quantum advantage is demonstrated in the acquired data and possible application spaces and technological requirements are identified for developing practical systems.
Quantum lidar leverages the quantum properties of light to gain advantages over classical lidar, such as enhancing range accuracy and reducing the emitted optical power needed to detect a target. The low optical power makes quantum lidar especially attractive for minimizing the probability of being detected by an adversary. Various quantum sources have been considered for quantum lidar; however, a practical comparison between such widely different systems is challenging. Here, we develop a theoretical model tailored to quantum lidar for stealth ranging and imaging, and compare the performance of such systems using an attenuated pulsed laser, a quantum dot single-photon source, and a spontaneous parametric down-conversion correlated photon pair source. To ensure a fair comparison, all sources employ time correlations for detection and are equalized in terms of optical power and detectability by an adversary. Furthermore, we demonstrate the limitation of the signal-to-noise ratio (SNR) as a sole metric, as it ignores the acquisition time required to confidently identify a target. To address the limitation of SNR, we supplement this metric with receiver operating characteristic (ROC) curves. With the inclusion of ROC curves, we find that the pulsed laser and the quantum dot single-photon source outperform the correlated photon pair source when an adversary possesses a non-photon-number-resolving detector. In contrast, when facing a photon-number-resolving detector, the quantum dot single-photon source remains optimal while the correlated photon pair source outperforms the pulsed laser. Our findings demonstrate that the use of a correlated photon pair source for quantum lidar does not always outperform alternative sources with equal SNR and optical power. Finally, using ROC curves, we establish the practical range limitations of quantum lidar.
We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantum ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.
Imaging is the estimation of the spatial distribution of a physical object by measuring the optical radiation it emits, or by making use of an optical wave that interacts with the object, via reflection or transmission, for example, before being measured by a detector. The resolution of an imaging system is limited by the inability to localize the optical field at points of the object. Under otherwise ideal conditions, resolution is limited by diffraction. The sensitivity of an imaging system is limited by the uncertainty in the measurement. Under ideal conditions, this is determined by photon noise, which depends on the statistical fluctuations of the light. In conventional imaging systems, an extended detector, such as a CCD camera or an array detector, measures the spatial distribution of the optical intensity, which is proportional to the photon flux density. In interferometric systems, the spatial distribution of the optical field is inferred from measurements of the optical intensity. With the emergence of coherence theory, imaging systems based on measurements of the second-order coherence function at pairs of points in the detection plane were developed. An example is the imaging of an incoherent object based on the van Cittert-Zernike theorem. Imaging systems based on measurement of intensity correlation, or the photon coincidence rate, at pairs of points, were developed in the 1960s. A classic example of the photon-correlation imaging of an object emitting thermal light is stellar imaging using a Hanbury-Brown-Twiss intensity-correlation interferometer. More recently, two-photon light, which may be generated via spontaneous parametric downconversion in a second-order nonlinear optical crystal, has been used for imaging. This type of two-photon (or biphoton) imaging, which has come to be called quantum imaging, is also based on the measurement of photon coincidence by the use of photon-counting array detectors or by scanning two photon-counting detectors at pairs of points. To compare the resolution and sensitivity of imaging systems based on the aforementioned types of measurements, it is necessary to derive expressions for the measured quantities in terms of the object distribution. The point-spread functions based on such expressions can be used to assess the resolution. One measure of the sensitivity of the imaging process is the signal-to-noise ratio (SNR) of the measured variables. The statistical nature of the light source must be known in order to determine the SNR. The purpose of this chapter is to compare the resolution and sensitivity of photon-correlation imaging systems that make use of thermal light and two-photon light. We will henceforth refer to these two imaging modalities as classical and quantum photon-correlation imaging, or simply classical and quantum imaging, respectively. Clearly, light in other quantum states can also be used for imaging.
This article presents a comprehensive analysis of two classes of quantum radars, including quantum direct-detection and quantum-entangled noise radars. In the first case, inspired by the well-established concept of single-photon LiDARs, we investigated the performance of single-photon radars, in which state-of-the-art single microwave-photon detectors are employed to enhance the detection sensitivity and enable the detection of weaker signals. We derived analytical expressions for the maximum detection range of both classes of quantum radars in terms of the Lambert W function, by considering all relevant system, target, and environmental parameters. Our formulation facilitates direct comparison of noise radars with direct-detection radars and suggests that a quantum-entangled noise radar can be regarded as an enhanced direct-detection radar with an effective threshold signal-to-noise ratio. Furthermore, we applied this framework to classical-correlated noise radars and defined the parameter range enhancement factor (REF) to quantify the superiority of quantum-entangled noise radars over their classical counterparts. Moreover, we introduced a rule-of-thumb for approximating the REF. We also examined the influence of limitations imposed by various microwave detection technologies. Our analysis shows that the conventional antennas limit the potential benefits of quantum-entangled noise radar systems. We also demonstrated that the optimal detection method for these radars is a microwave detector based on a quantum transducer combined with a single optical-photon detector. We showed that, with the current technology, implementing a quantum-entangled noise radar with the maximum detection range on the order of few kilometers is possible. Finally, we explored the potential applications of quantum-entangled noise radars.
How can quantum mechanics deliver better imaging performance? Parametric down-conversion sources produce pairs of photons that are correlated in many degrees of freedom, including their spatial positions. By using a camera to detect these pairs of photons it is possible configure imaging systems that can either beat the classical resolution limit or the classical noise limit. We demonstrate how a simple down-conversion source based on a laser and non-linear crystal can be combined with an EMCCD camera to achieve either of these outcomes. Firstly, when both photons pass through the sample, we show a full-field, resolution-enhancing scheme, based on the centroid estimation of the photon pairs. By optimising the software control of the EMCCD camera running in the photon-sparse regime we achieve a resolution enhancement over the equivalent classical limit. Secondly, we show a similar scheme but where only one of the two photons pass through the sample and the other acts as a reference, in this case the ratio of the two resulting images eliminates the background noise of the camera, and background light, achieving an increase in image contrast.