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Accurate forecasting of photovoltaic power is essential for reliable grid integration, yet remains difficult due to highly variable irradiance, complex meteorological drivers, site geography, and device-specific behavior. Although…

Polarizations of single-photon pulses have been controlled with long-term stability of more than 10 hours by using an active feedback technique for auto-compensation of unpredictable polarization scrambling in long-distance fiber.…

Quantum Physics · Physics 2007-05-23 Guang Wu , Jie Chen , Yao Li , Heping Zeng

Quantum phase estimation (QPE) is the key subroutine of several quantum computing algorithms as well as a central ingredient in quantum computational chemistry and quantum simulation. While QPE strategies have focused on the estimation of a…

Quantum Physics · Physics 2021-07-26 Valentin Gebhart , Augusto Smerzi , Luca Pezzè

Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, non-fault…

We propose and experimentally demonstrate a method of polarization-sensitive quantitative phase imaging using two photo detectors. Instead of recording wide-field interference patterns, finding the modulation patterns maximizing focused…

Optics · Physics 2018-11-14 Seungwoo Shin , Kyeoreh Lee , Zahid Yaqoob , Peter T. C. So , Yongkeun Park

A photonics-assisted joint communication-radar system is proposed and experimentally demonstrated, by introducing a quadrature phase-shift keying (QPSK)-sliced linearly frequency-modulated (LFM) signal. An LFM signal is carrier-suppressed…

Signal Processing · Electrical Eng. & Systems 2022-06-08 Shi Wang , Dingding Liang , Yang Chen

Quantum Key Distribution (QKD) offers unconditional security in principle. Many QKD protocols have been proposed and demonstrated to ensure secure communication between two authenticated users. Continuous variable (CV) QKD offers many…

Continuous-variable (CV) quantum systems provide a versatile platform for quantum information processing, in which quantum states can be represented in the quadrature phase space. In realistic implementations, environmental noise, primarily…

Quantum Physics · Physics 2026-03-11 Jingpeng Zhang , Shengyong Li , Jie Han , Qianchuan Zhao , Jing Zhang , Zeliang Xiang

Quantum key distribution (QKD) is a cryptographic technique that uses quantum mechanical principles to enable secure key exchange. Practical deployment of QKD requires robust, cost-effective systems that can operate in challenging field…

Quantum Physics · Physics 2026-04-07 Rui Guan , Jingchun Yu , Zhaoyun Li , Hongbo Xie , Yuxing Wei , Sen Li , Jing Wen , Xiaodong Liang , Yanwei Li , Kejin Wei

The state of polarization and the carrier phase drift dynamically during transmission in a random fashion in coherent optical fiber communications. The typical digital signal processing solution to mitigate these impairments consists of two…

Information Theory · Computer Science 2024-01-25 Cristian B. Czegledi , Erik Agrell , Magnus Karlsson , Pontus Johannisson

A gate sequence of single-qubit transformations may be condensed into a single microwave pulse that maps a qubit from an initialized state directly into the desired state of the composite transformation. Here, machine learning is used to…

Quantum Physics · Physics 2025-07-18 Jaden Nola , Uriah Sanchez , Anusha Krishna Murthy , Elizabeth Behrman , James Steck

A growing number of experimental set-ups in cavity optomechanics exploit periodically driven fields. However, such set-ups are not amenable to analysis using simple, yet powerful, closed-form expressions of linearized optomechanics, which…

Quantum Physics · Physics 2018-01-03 E. B. Aranas , M. Javed Akram , Daniel Malz , T. S. Monteiro

We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using…

Materials Science · Physics 2013-02-25 Albert P. Bartok , Michael J. Gillan , Frederick R. Manby , Gabor Csanyi

We use deep-learning strategies to study the 2D percolation model on a square lattice. We employ standard image recognition tools with a multi-layered convolutional neural network. We test how well these strategies can characterise…

Disordered Systems and Neural Networks · Physics 2022-04-01 Djénabou Bayo , Andreas Honecker , Rudolf A. Römer

We introduce a trainable coded modulation scheme that enables joint optimization of the bit-wise mutual information (BMI) through probabilistic shaping, geometric shaping, bit labeling, and demapping for a specific channel model and for a…

Information Theory · Computer Science 2020-04-15 Fayçal Ait Aoudia , Jakob Hoydis

In this paper, phase correction and amplitude compensation are introduced to a previously developed mixed domain method (MDM), which is only accurate for modeling wave propagation in weakly heterogeneous media. Multiple reflections are also…

Medical Physics · Physics 2020-07-15 Juanjuan Gu , Yun Jing

A cross-benchmark has been done on three critical aspects, data imputing, feature selection and regression algorithms, for machine learning based chemical vapor deposition (CVD) virtual metrology (VM). The result reveals that linear feature…

Machine Learning · Computer Science 2021-07-29 Yunsong Xie , Ryan Stearrett

Using an approximate analytical solution of the Cahn-Hilliard equation describing the coalescence during a first order phase transition, we compute the characteristic time for one step of period doubling in Langer's self similar scenario…

Other Condensed Matter · Physics 2009-11-13 Simon Villain-Guillot

A continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) protocol using squeezed states is proposed where the two legitimate partners send Gaussian-modulated squeezed states to an untrusted third party to…

Quantum Physics · Physics 2014-11-20 Yi-Chen Zhang , Zhengyu Li , Song Yu , Wanyi Gu , Xiang Peng , Hong Guo

Motivated by the need for accurate frequency information, a novel algorithm for estimating the fundamental frequency and its rate of change in three-phase power systems is developed. This is achieved through two stages of Kalman filtering.…

Machine Learning · Statistics 2016-03-10 Sayed Pouria Talebi , Danilo P. Mandic