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A theoretical study of the performance of single-mode coupled spontaneous parametric downconversion sources is proposed, which only requires very few assumptions of practical interest : narrow-bandwidth and quasi-degenerate collinear…

This paper proposes a new robust control method for quantum systems with uncertainties involving sliding mode control (SMC). Sliding mode control is a widely used approach in classical control theory and industrial applications. We show…

Quantum Physics · Physics 2009-11-03 Daoyi Dong , Ian R. Petersen

Graphical models are useful tools for describing structured high-dimensional probability distributions. Development of efficient algorithms for generating unbiased and independent samples from graphical models remains an active research…

Quantum Physics · Physics 2026-04-02 Nico Piatkowski , Christa Zoufal

Random sampling is a technique for signal acquisition which is gaining popularity in practical signal processing systems. Nowadays, event-driven analog-to-digital converters make random sampling feasible in practical applications. A process…

Data Structures and Algorithms · Computer Science 2015-10-08 Jacek Pierzchlewski , Thomas Arildsen

We present a new method for the spectral characterization of pulsed twin beam sources in the high gain regime, using cascaded stimulated emission. We show an implementation of this method for a ppKTP spontaneous parametric down-conversion…

Spectroscopy is the most important method for probing the structure of molecules. However, predicting molecular spectra on classical computers is computationally expensive, with the most accurate methods having a cost that grows…

Quantum Physics · Physics 2025-10-06 Liam P. Flew , Ivan Kassal

Robust control design for quantum systems has been recognized as a key task in the development of practical quantum technology. In this paper, we present a systematic numerical methodology of sampling-based learning control (SLC) for…

Systems and Control · Computer Science 2016-11-17 Daoyi Dong , Chunlin Chen , Ruixing Long , Bo Qi , Ian R. Petersen

We prove that the results of a finite set of general quantum measurements on an arbitrary dimensional quantum system can be simulated using a polynomial (in measurements) number of hidden-variable states. In the limit of infinitely many…

Quantum Physics · Physics 2008-11-11 Borivoje Dakic , Milovan Suvakov , Tomasz Paterek , Caslav Brukner

Gaussian states, operations, and measurements are central building blocks for continuous-variable quantum information processing which paves the way for abundant applications, especially including network-based quantum computation and…

Quantum Physics · Physics 2021-07-06 Mengzhen Zhang

Numerical simulations have become an important tool to understand and predict non-perturbative phenomena in particle physics. In this article we attempt to present a general overview over the field. First, the basic concepts of lattice…

High Energy Physics - Lattice · Physics 2010-12-17 F. Karsch , E. Laermann

Spontaneous parametric downconversion is an essential technique in quantum optics experiments. In this paper, various quasi-phase-matching processes in several typical periodically polarized nonlinear materials are analyzed and calculated.…

Quantum Physics · Physics 2022-07-12 Xi-Yu Liu , Ya-Fei Yu , Zheng-Jun Wei , Tian-Ming Zhao , Jin-Dong Wang

Direct spectral characterization of a quantum photon-pair source usually involves cumbersome, costly, and time-consuming detection issues. In this study, we experimentally characterize the spectral properties of a type-II phase-matched…

Spectroscopy underpins modern scientific discovery across diverse disciplines. While experimental spectroscopy probes material properties through scattering or radiation measurements, computational spectroscopy combines theoretical models…

Simulation studies are indispensable for evaluating statistical methods and ubiquitous in statistical research. The most common simulation approach is parametric simulation, where the data-generating mechanism (DGM) corresponds to a…

This paper proposes a novel parallel stochastic gradient descent (SGD) method that is obtained by applying parallel sets of SGD iterations (each set operating on one node using the data residing in it) for finding the direction in each…

Machine Learning · Computer Science 2013-11-05 Dhruv Mahajan , S. Sathiya Keerthi , S. Sundararajan , Leon Bottou

In this paper we present a method to generate independent samples for a general random variable, either continuous or discrete. The algorithm is an extension of the acceptance-rejection method, and it is particularly useful for kinetic…

Numerical Analysis · Mathematics 2016-08-24 Farzin Barekat , Russel Caflisch

Quantum process tomography is a useful tool for characterizing quantum processes. This task is essential for the development of different areas, such as quantum information processing. In this work, we present a protocol for selective…

Quantum Physics · Physics 2025-04-22 Virginia Feldman , Ariel Bendersky

Spontaneous downconversion is a versatile source for correlated biphotons that has been employed in many quantum sensing and imaging experiments. Spatially-resolved photon-counting detectors allow to access a large number of modes, posing…

Instrumentation and Detectors · Physics 2019-11-26 Ermes Toninelli , Paul-Antoine Moreau , Thomas Gregory , Miles J. Padgett

We propose a framework for simulating the real-time dynamics of quantum field theories (QFTs) using continuous-variable quantum computing (CVQC). Focusing on ($1+1$)-dimensional $\varphi^4$ scalar field theory, the approach employs the…

Quantum Physics · Physics 2025-09-03 Steven Abel , Michael Spannowsky , Simon Williams

Compensation for parameter dispersion is a significant challenge for control of inhomogeneous quantum ensembles. In this paper, we present a systematic methodology of sampling-based learning control (SLC) for simultaneously steering the…

Quantum Physics · Physics 2014-04-15 Chunlin Chen , Daoyi Dong , Ruixing Long , Ian R. Petersen , Herschel A. Rabitz