Related papers: Spatial Mode Correction of Single Photons using Ma…
Scattering by atmospheric turbulence is one of the main challenges in creating long free-space optical links, and specifically links of entangled photons. Classical compensation methods are hard to apply to entangled photons, due to…
Linear optical networks are fundamental to the advancement of quantum technologies, including quantum computing, communication, and sensing. The accurate characterization of these networks, described by unitary matrices, is crucial to their…
In practical applications to free-space quantum communications, the utilization of active beam coupling and stabilization techniques offers notable advantages, particularly when dealing with limited detecting areas or coupling into…
Optical computing has gained significant attention as a potential solution to the growing computational demands of machine learning, particularly for tasks requiring large-scale data processing and high energy efficiency. Optical systems…
For single image defocus deblurring, acquiring well-aligned training pairs (or training triplets), i.e., a defocus blurry image, an all-in-focus sharp image (and a defocus blur map), is a challenging task for developing effective deblurring…
Detectors inherently capable of resolving photon numbers have undergone a significant development recently, and this is expected to affect multiplexed periodic single-photon sources where such detectors can find their applications. We…
Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires…
Metasurfaces are a key photonic platform to manipulate classical light using sub-wavelength structures with designer optical response. Static metasurfaces have recently entered the realm of quantum photonics, showing their ability to tailor…
We study both manipulation and detection of two-mode spatial quantum states of light by means of a reconfigurable integrated device built in an electro-optical material in a Kolgelnik-Schmidt configuration, which provides higher error…
Estimation of an optical beam's transverse displacement is a canonical imaging problem fundamental to numerous optical imaging and sensing tasks. Quantum enhancements to the measurement precision in this problem have been studied…
One of the main characteristics of optical imaging systems is the spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical…
Photons are ideal carriers of quantum information, as they can be easily created and can travel long distances without being affected by decoherence. For this reason, they are well suited for quantum communication. However, the interaction…
We show that instantaneous spatial singular modes of light in a dynamically evolving, turbulent atmosphere offer significantly improved high-fidelity signal transmission as compared to standard encoding bases corrected by adaptive optics.…
Restoring images distorted by atmospheric turbulence is a ubiquitous problem in long-range imaging applications. While existing deep-learning-based methods have demonstrated promising results in specific testing conditions, they suffer from…
As the success of Generative Adversarial Networks (GANs) on natural images quickly propels them into various real-life applications across different domains, it becomes more and more important to clearly understand their limitations.…
We define a class of multi-mode single photon states suitable for quantum information applications. We show how standard amplitude modulation techniques may be used to control the pulse shape of single photon states.
Atmospheric turbulence generally limits free-space optical (FSO) communications, and this problem is severely exacerbated when implementing highly sensitive and spectrally efficient coherent detection. Specifically, turbulence induces power…
We propose the first general framework to automatically correct different types of geometric distortion in a single input image. Our proposed method employs convolutional neural networks (CNNs) trained by using a large synthetic distortion…
Reprogrammable linear optical circuits are essential elements of photonic quantum technology implementations. Integrated optics provides a natural platform for tunable photonic circuits, but faces challenges when high dimensions and high…
Due to coherent population oscillation (CPO) effect, we theoretically examine the generation and manipulation of Laguerre-Gaussian beams in terms of phase and amplitude modulation respectively in semiconductor quantum dots (SQDs). The…