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Modular tensor categories are generalizations of the representation categories of quantum groups at roots of unity axiomatizing the properties necessary to produce 3-dimensional TQFTs. Although other constructions have since been found,…

Quantum Algebra · Mathematics 2007-05-23 Eric C. Rowell

In quantum-state tomography on sources with quantum degrees of freedom of large Hilbert spaces, inference of quantum states of light for instance, a complete characterization of the quantum states for these sources is often not feasible…

Quantum Physics · Physics 2013-11-14 Yong Siah Teo , Jaroslav Rehacek , Zdenek Hradil

A quantum walk places a traverser into a superposition of both graph location and traversal "spin." The walk is defined by an initial condition, an evolution determined by a unitary coin/shift-operator, and a measurement based on the…

Quantum Physics · Physics 2015-11-25 Marko A. Rodriguez , Jennifer H. Watkins

A major question for condensed matter physics is whether a solid-state quantum computer can ever be built. Here we discuss two different schemes for quantum information processing using semiconductor nanostructures. First, we show how…

Quantum Physics · Physics 2016-09-08 John H. Reina , Luis Quiroga , Neil F. Johnson

We present a theory of quantized radiation fields described in terms of q-deformed harmonic oscillators. The creation and annihilation operators satisfy deformed commutation relations and the Fock space of states is constructed in this…

High Energy Physics - Theory · Physics 2007-05-23 P. Narayana Swamy

Ideas from deformation quantization applied to algebras with one generator lead to methods to treat a nonlinear flat connection. It provides us elements of algebras to be parallel sections. The moduli space of the parallel sections is…

Quantum Algebra · Mathematics 2007-11-26 Hideki Omori , Yoshiaki Maeda , Naoya Miyazaki , Akira Yoshioka

Quantum neural networks promise to extend the power of machine learning into the quantum domain, with potential applications ranging from automatic recognition of quantum states to the control of quantum devices. However, their physical…

Quantum Physics · Physics 2026-04-15 Julien Dudas , Baptiste Carles , Elie Gouzien , Julie Grollier , Danijela Marković

Gaussian graphical models (GGMs) are widely used for statistical modeling, because of ease of inference and the ubiquitous use of the normal distribution in practical approximations. However, they are also known for their limited modeling…

Machine Learning · Statistics 2016-11-22 Qinliang Su , Xuejun Liao , Chunyuan Li , Zhe Gan , Lawrence Carin

Gaussian quantum channels have recently attracted a growing interest, since they may lead to a tractable approach to the generally hard problem of evaluating quantum channel capacities. However, the analysis performed so far has always been…

Quantum Physics · Physics 2010-02-18 Nicolas J. Cerf , Julien Clavareau , Jérémie Roland , Chiara Macchiavello

This paper aims to explore the inherent connection among Heisenberg groups, quantum Fourier transform and (quasiprobability) distribution functions. Distribution functions for continuous and finite quantum systems are examined first as a…

Mathematical Physics · Physics 2015-05-18 Manas K. Patra , Samuel L. Braunstein

The q-deformed traces and orbits for the two parametric quantum groups $GL_{qp}(2)$ and $GL_{qp}(1|1)$ are defined. They are subsequently used in the construction of $q$-orbit invariants for these groups. General $qp$-(super)oscillator…

High Energy Physics - Theory · Physics 2009-11-10 A. P. Isaev , R. P. Malik

A characterisation of the quantum stochastic bounded generators of irreversible quantum state evolutions is given. This suggests the general form of quantum stochastic evolution equation with respect to the Poisson (jumps), Wiener…

Probability · Mathematics 2007-05-23 V. P. Belavkin

Group equivariant neural networks have been explored in the past few years and are interesting from theoretical and practical standpoints. They leverage concepts from group representation theory, non-commutative harmonic analysis and…

Machine Learning · Computer Science 2020-05-01 Carlos Esteves

Fully convolutional networks are robust in performing semantic segmentation, with many applications from signal processing to computer vision. From the fundamental principles of variational quantum algorithms, we propose a feasible pure…

Quantum Physics · Physics 2021-10-06 Yusui Chen , Wenhao Hu , Xiang Li

The intrinsic probabilistic nature of quantum mechanics invokes endeavors of designing quantum generative learning models (QGLMs). Despite the empirical achievements, the foundations and the potential advantages of QGLMs remain largely…

Quantum Physics · Physics 2022-08-08 Yuxuan Du , Zhuozhuo Tu , Bujiao Wu , Xiao Yuan , Dacheng Tao

The past few years have seen a revived interest in quantum geometrical characterizations of band structures due to the rapid development of topological insulators and semi-metals. Although the metric tensor has been connected to many…

Mesoscale and Nanoscale Physics · Physics 2023-03-07 Adrien Bouhon , Abigail Timmel , Robert-Jan Slager

As the rapidly evolving field of machine learning continues to produce incredibly useful tools and models, the potential for quantum computing to provide speed up for machine learning algorithms is becoming increasingly desirable. In…

Quantum Physics · Physics 2024-04-02 Anthony M. Smaldone , Gregory W. Kyro , Victor S. Batista

Activation of quantum capacity is a surprising phenomenon according to which the quantum capacity of a certain channel may increase by combining it with another channel with zero quantum capacity. Superactivation describes an even more…

Quantum Physics · Physics 2019-03-29 Youngrong Lim , Ryuji Takagi , Gerardo Adesso , Soojoon Lee

Partial symplectic conditional and joint probability representations of quantum mechanics are considered. The correspondence rules for most interesting physical operators are found and the expressions of the dual symbols of operators are…

Quantum Physics · Physics 2024-06-12 Ya. A. Korennoy , V. I. Man'ko

Implicit neural representations have shown potential in various applications. However, accurately reconstructing the image or providing clear details via image super-resolution remains challenging. This paper introduces Quantum Fourier…

Quantum Physics · Physics 2025-04-29 Hongni Jin , Gurinder Singh , Kenneth M. Merz
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