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Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

Resolution enhancement of imaging systems by quantum phase amplification

Yanchun Yin, D. French, Igor Jovanovic

Published May 13, 2011• 0 citations
Publisher

Abstract

A novel quantum phase amplification (QPA) technique is proposed to enhance the spatial resolution of passive imaging systems, without the commensurate increase of the aperture size. The key component of this approach is the production of phase-amplified light, a squeezed state of the electromagnetic field that can be generated in phase-sensitive three-wave mixing (PSTWM). We have established the theoretical basis for QPA using PSTWM and theoretically derived the conditions for the operation of the ubiquitous PSTWM realized by using standard laser technology. In our approach sub-Rayleigh imaging can be explored to perform the super-resolution enhancement of remotely sensed data. We applied the PSTWM to improve the distinguishability of two point sources in several scenarios. In addition, detector segmentation was modeled to optimize the signal-to-noise ratio.

DOI
10.1117/12.882803

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A novel quantum phase amplification (QPA) technique is proposed to enhance the spatial resolution of passive imaging systems, without the commensurate increase of the aperture size. The key component of this approach is the production of phase-amplified light, a squeezed state of the electromagnetic field that can be generated in phase-sensitive three-wave mixing (PSTWM). We have established the theoretical basis for QPA using PSTWM and theoretically derived the conditions for the operation of the ubiquitous PSTWM realized by using standard laser technology. In our approach sub-Rayleigh imaging can be explored to perform the super-resolution enhancement of remotely sensed data. We applied the PSTWM to improve the distinguishability of two point sources in several scenarios. In addition, detector segmentation was modeled to optimize the signal-to-noise ratio.
The Rayleigh criterion sets a classical limit on the resolution of optical imaging systems, which brings challenges in remote sensing of spatial information. According to the Rayleigh criterion, only a limited control of resolution can be accomplished by adjusting the optical wavelength or aperture diameter. The resolvability of optical imaging systems can also be represented in terms of the signal-to-noise ratio (SNR). The optical parametric amplier (OPA) is a common nonlinear device used in a variety of applications, such as imaging, quantum information, and ultrafast laser science. It has been shown that when the OPA is operated as a phase-sensitive amplifier (PSA), no quantum noise is added thus preserving the SNR. In this thesis, the hypothesis testing from the classical information theory has been applied to the problem of distinguishing distant point sources. It is numerically demonstrated that an improvement of resolution beyond the classical limit and SNR enhancement could be achieved by utilizing the PSA operated in spatial domain. Plasma diagnostics deducts information of important parameters (such as temperature, plasma density and confinement) in magnetic confinement fusion (MCF) reactions. Interferometer can be used to measure the refractive index of plasma which is correlated with the plasma density. A Mach-Zehnder type interferometer enhanced by the PSA is studied. It has been found that the effect of the PSA is to increase the minimum resolvable interference fringe shift caused by plasma density perturbation so that a better resolution of the interferogram can be obtained. This method may enable significant improvement in plasma density measurement.
Classical information theory can be used to quantify the resolution performance of optical imaging systems. When an optical parametric amplifier (OPA) operated as a phase-sensitive amplifier (PSA) in the transverse spatial domain is used for point source imaging, the angular resolution improvement can approach the de Broglie resolution (i.e. Heisenberg limit). In this paper, classical information theory is employed to quantify the signal-to-noise ratio (SNR) improvement for both an ideal and a realistic multimode PSA applied to the problem of sub-Rayleigh imaging. When only considering the noise originating from the detector, the SNR improvement is found to scale quadratically as a function of the PSA gain, in the limit of noise power comparable to signal power. Differences in performance of an ideal PSA and a realistic PSA are discussed.
The phase-sensitive amplification (PSA) with an injected squeezed vacuum field is theoretically investigated in quantum-enhanced laser detection and ranging (LADAR) receiver. The theoretical model of the amplified process is derived to investigate the quantum fluctuations in detail. A new method of mitigating the unflat gain of nonideal PSA is proposed by adjusting the squeezed angle of the squeezed vacuum field. The simulation results indicate that signal-noise ratio (SNR) of system can be efficiently improved and close to the ideal case by this method. This research will provide an important potential in the applications of quantum-enhanced LADAR receiver.
Remote sensing has evolved as a key technology for space exploration and earth observation since its emergence in the 1960s, offering precise, macroscopic, and dynamic capabilities. Despite its advancements, challenges remain in meeting the demands for high-resolution detection due to limitations in aperture size expansion and detector performance, quantum noise posing a fundamental issue. A novel quantum remote sensing approach using optical field quantization and squeezed state light is explored to overcome these obstacles, promising enhanced imaging quality and signal-to-noise ratio. This paper presents a principle prototype of this approach, experimental outcomes, and discusses future prospects in quantum remote sensing.
Far-field optical imaging inevitably involves low-pass spatial filtering, limiting the resolution. Moreover, conventional imaging suppresses high spatial frequency components close to the cutoff, making them invisible under noise, particularly the shot noise arising from discrete and random nature of quantum light. Here we propose and implement a method for reducing the effect of this noise by optically pre-processing the incoming light prior to detection, thereby optimizing the quantum measurement performed on it. Our scheme, termed Fourier Domain Division (FDD), partitions the Fourier plane into multiple regions for independent detection and subsequent post-processing for image reconstruction. By analyzing the quantum and classical Fisher information, we show that our method is advantageous with respect to direct imaging for high spatial-frequency components. As a result, the number of photons required to achieve a certain signal-to-noise-ratio in the Fourier domain is reduced, thus enhancing the overall resolution in the photon-starved regime. We demonstrate our method in microscopy, achieving 5-fold improvement of Fisher information on high spatial-frequency components. Unlike active super-resolution methods, FDD is passive, making it broadly applicable in microscopy and other imaging scenarios where active illumination is impractical, including astronomy and remote sensing. Our work establishes a general strategy for designing quantum optimized superresolution imaging systems, bridging fundamental quantum limits, practical image analysis and computer vision applications.