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Accurate financial volatility forecasting is crucial but challenged by the non-linear, highly correlated nature of market data. Recently, quantum computing has emerged as a promising paradigm for solving complex high-dimensional sampling…

Machine Learning · Computer Science 2026-05-07 Yixiong Chen

Quantum embedding methods have recently developed significantly to model large molecular structures. This work proposes a novel wave function theory in density functional theory (WTF-in-DFT) embedding scheme based on pair-coupled cluster…

Chemical Physics · Physics 2024-01-10 Rahul Chakraborty , Katharina Boguslawski , Paweł Tecmer

An ab-initio analysis based on coupled mode theory (CMT) is applied to describe the interaction dynamics of high dielectric resonators (DRs) with its containing aqueous solution. We prove that the coupling mechanism is reciprocal. Such…

Applied Physics · Physics 2020-08-25 Sameh. Y. Elnaggar , Chinmoy Saha , Yahia. M. M. Antar

This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet…

Networking and Internet Architecture · Computer Science 2007-08-13 Sajad Sadough , Mahieddine Ichir , Emmanuel Jaffrot , Pierre Duhamel

Normal mean-variance mixture distributions are widely applied to simplify a model's implementation and improve their computational efficiency under the Maximum Likelihood (ML) approach. Especially for distributions with normal mean-variance…

Methodology · Statistics 2015-06-18 Thanakorn Nitithumbundit , Jennifer S. K. Chan

Continuous variable entanglement can be produced in nonlinear systems or via interference of squeezed states. In many of optical systems, such as parametric down conversion or interference of optical squeezed states, production of two…

Fast robust methods for calculating likelihoods from CMB observations on small scales generally rely on approximations based on a set of power spectrum estimators and their covariances. We investigate the optimality of these approximation,…

Cosmology and Nongalactic Astrophysics · Physics 2009-11-06 Samira Hamimeche , Antony Lewis

The rotating wave approximation (RWA) is ubiquitous in the analysis of driven and coupled resonators. However, the limitations of the RWA seem to be poorly understood and in some cases the RWA disposes of essential physics. We investigate…

Quantum Physics · Physics 2024-06-13 Daniel Sank , Mostafa Khezri , Sergei Isakov , Juan Atalaya

Restricted Boltzmann machines (RBMs) are endowed with the universal power of modeling (binary) joint distributions. Meanwhile, as a result of their confining network structure, training RBMs confronts less difficulties (compared with more…

Machine Learning · Computer Science 2015-10-22 Sai Zhang

Reliable detection and quantification of quantum entanglement, particularly in high-spin or many-body systems, present significant computational challenges for traditional methods. This study examines the effectiveness of ensemble machine…

Quantum Physics · Physics 2025-07-18 M. Y. Abd-Rabbou , Amr M. Abdallah , Ahmed A. Zahia , Ashraf A. Gouda , Cong-Feng Qiao

Machine learning (ML) has found widespread application over a broad range of important tasks. To enhance ML performance, researchers have investigated computational architectures whose physical implementations promise compactness,…

Signal Processing · Electrical Eng. & Systems 2022-06-09 Shukai Ma , Thomas M. Antonsen , Steven M. Anlage , Edward Ott

We propose and demonstrate localized mode coupling as a viable dispersion engineering technique for phase-matched resonant four-wave mixing (FWM). We demonstrate a dual-cavity resonant structure that employs coupling-induced frequency…

Optics · Physics 2023-07-19 Cale M. Gentry , Xiaoge Zeng , Milos A. Popovic

Prediction of spatio-temporal chaotic systems is important in various fields, such as Numerical Weather Prediction (NWP). While data assimilation methods have been applied in NWP, machine learning techniques, such as Reservoir Computing…

Machine Learning · Computer Science 2020-06-26 Futo Tomizawa , Yohei Sawada

In this paper, we show how we can combine Electromagnetics (EM) with signal processing algorithms to enhance the image resolution over that can be realized by using Electromagnetics techniques alone. We discuss several signal processing…

Optics · Physics 2013-05-14 Xiang Gu , Chiara Pelletti , Raj Mittra , Yunhua Zhang

Approximated numerical techniques, for the solution of the elastic wave scattering problem over semi-infinite domains are reviewed. The approximations involve the representation of the half-space by a boundary condition described in terms…

Computational Engineering, Finance, and Science · Computer Science 2014-10-14 Nicolás Guarín-Zapata , Juan Gómez , Juan Jaramillo

We investigate the controllable generation of robust photon entanglement with a circuit cavity electromechanical system, consisting of two superconducting coplanar waveguide cavities (CPWC's) capacitively coupled by a nanoscale mechanical…

Quantum Physics · Physics 2013-10-30 Peng-Bo Li , Shao-Yan Gao , Fu-Li Li

In the first part of the paper a generalized theoretical approach towards beam coupling impedances and stretched-wire measurements is introduced. Applied to a circular symmetric setup, this approach allows to estimate the systematic…

Accelerator Physics · Physics 2015-01-27 Uwe Niedermayer , Lewin Eidam , Oliver Boine-Frankenheim

A quantum repeater scheme based on cavity-QED and quantum error correction of channel loss via rotation-symmetric bosonic codes (RSBC) is proposed to distribute atomic entangled states over long distances without memories and at high clock…

Quantum Physics · Physics 2024-08-21 Pei-Zhe Li , Peter van Loock

Scattering of electromagnetic waves in billiard-like systems has become a standard experimental tool of studying properties associated with Quantum Chaos. Random Matrix Theory (RMT) describing statistics of eigenfrequencies and associated…

Disordered Systems and Neural Networks · Physics 2021-05-11 Yan V Fyodorov

Turbulence Models represent the workhorse for simulations used in engineering design and analysis. Despite their low computational cost and robustness, these models suffer from substantial predictive uncertainty, most of which is epistemic.…

Fluid Dynamics · Physics 2025-09-05 Minghan Chu , Weicheng Qian
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