Related papers: Machine learning based joint polarization and phas…
Optical approaches for wavefront shaping traditionally rely on phase modulation through holographic techniques. Shaping the phase determines a wave's diffraction and hence its intensity distribution in space. We instead show that shaping…
Quantum key distribution (QKD) is a cryptographic protocol to enable two parties to share a secure key string, which can be used in one-time pad cryptosystem. There has been an ongoing surge of interest in implementing long-haul…
In this paper, we present a fully fiber-based one-way Quantum Key Distribution (QKD) system implementing the Gaussian-Modulated Coherent States (GMCS) protocol. The system employs a double Mach-Zehnder Interferometer (MZI) configuration in…
Experimental progress in qubit manufacturing calls for the development of new theoretical tools to analyze quantum data. We show how an unsupervised machine-learning technique can be used to understand short-range entangled many-qubit…
The generalization of quasi-phase-matching using polarization beating and of multimode quasi-phase-matching (MMQPM) for the generation of high-order harmonics is explored, and a method for achieving polarization beating is proposed. If two…
Recent years have witnessed a growing interest in using machine learning to predict and identify phase transitions in various systems. Here we adopt convolutional neural networks (CNNs) to study the phase transitions of Vicsek model,…
Continuous-variable quantum key distribution (CV-QKD) is realized with coherent detection and is therefore very suitable for a cost-efficient implementation. The major challenge in CV-QKD is mitigation of laser phase noise at a signal to…
Continuous-variable (CV) quantum key distribution (QKD) allows for quantum secure communication with the benefit of being close to existing classical coherent communication. In recent years, CV QKD protocols using a discrete number of…
We present a physical scheme for implementing quantum phase estimation via weakly coupled double quantum-dot molecules embedded in a microcavity. During the same process of implementation, we can also realize the calibration of a timepiece…
A high-speed Gaussian modulated continuous-variable quantum key distribution (CVQKD) with a local local oscillator (LLO) is experimentally demonstrated based on pilot-tone-assisted phase compensation. In the proposed scheme, the…
Measurement-device-independent quantum key distribution (MDI-QKD) closes all the security loopholes in the detection system and is a promising solution for secret key sharing. Polarization encoding is the most common QKD encoding scheme, as…
A polarization degenerate microcavity containing charge-controlled quantum dots (QDs) enables equal coupling of all polarization degrees of freedom of light to the cavity QED system, which we explore through resonant laser spectroscopy. We…
Quantization and Knowledge distillation (KD) methods are widely used to reduce memory and power consumption of deep neural networks (DNNs), especially for resource-constrained edge devices. Although their combination is quite promising to…
Silicon-based polarization-encoding quantum key distribution (QKD) has been widely studied, owing to its low cost and robustness. However, prior studies have utilized off-chip devices to demodulate the quantum states or perform polarization…
We present a supervised machine learning-based method using convolutional neural networks to estimate the covariance matrix of Gaussian quantum states in the presence of thermal noise. Unlike computationally intensive density matrix…
TDM-based polarization and differential phase control with 35ps PMD tolerance and 20krad/s tracking speed is demonstrated. 600ns intervals are reserved for QKD and for 0{\deg}- and 45{\deg}-polarized pilot signals. ECLs are modulated…
Phase correlations are an under-explored vulnerability in QKD. Here, we present an experimental and simulated characterization of correlations arising from electro-optic phase encoding, over repetition rates up to the GHz level. To mitigate…
We present a machine-learning method for predicting sharp transitions in a Hamiltonian phase diagram by extrapolating the properties of quantum systems. The method is based on Gaussian Process regression with a combination of kernels chosen…
We present a pilot-assisted coherent intradyne reception methodology for CV-QKD with true local oscillator. An optically phase-locked reference tone, prepared using carrier-suppressed optical single-sideband modulation, is multiplexed in…
Phase estimation is known to be a robust method for single-qubit gate calibration in quantum computers, while Bayesian estimation is widely used in devising optimal methods for learning in quantum systems. We present Bayesian phase…