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Quantum mechanics is formulated as a geometric theory on a Hilbert manifold. Images of charts on the manifold are allowed to belong to arbitrary Hilbert spaces of functions including spaces of generalized functions. Tensor equations in this…

Quantum Physics · Physics 2015-05-13 Alexey A. Kryukov

Implicit neural representations (INRs) have become a powerful paradigm for continuous signal modeling and 3D scene reconstruction, yet classical networks suffer from a well-known spectral bias that limits their ability to capture…

Quantum Physics · Physics 2025-12-16 Yeray Cordero , Paula García-Molina , Fernando Vilariño

We show how Cauchy's Integral Formula and the ideas of Dunford's Holomorphic Functional Calculus (for unbounded operators) can be used to compute the Vacuum Characteristic Function (Quantum Fourier Transform) of quantum random variables…

Mathematical Physics · Physics 2024-07-08 Andreas Boukas

Quantum Field Theory (QFT) represents a vast generalization of Quantum Mechanics (QM), as it deals with systems that have an infinite number of degrees of freedom. The Stone-von Neumann theorem, which establishes the equivalence of…

Mathematical Physics · Physics 2023-07-13 Ahmed Halawani

The kinematics of many mechanical systems encountered in robotics and other fields, such as single-bearing attitude estimation and SLAM, are naturally posed on homogeneous spaces: That is, their state lies in a smooth manifold equipped with…

Systems and Control · Electrical Eng. & Systems 2021-07-13 Pieter van Goor , Tarek Hamel , Robert Mahony

In this thesis, we investigate whether quantum algorithms can be used in the field of machine learning for both long and near term quantum computers. We will first recall the fundamentals of machine learning and quantum computing and then…

Quantum Physics · Physics 2021-11-08 Jonas Landman

To study operator algebras with symmetries in a wide sense we introduce a notion of {\em relative convolution operators} induced by a Lie algebra. Relative convolutions recover many important classes of operators, which have been already…

funct-an · Mathematics 2008-02-03 Vladimir V. Kisil

The popular qubit framework has dominated recent work on quantum kernel machine learning, with results characterising expressivity, learnability and generalisation. As yet, there is no comparative framework to understand these concepts for…

Quantum Physics · Physics 2024-12-18 Laura J. Henderson , Rishi Goel , Sally Shrapnel

We introduce a class of linear maps irreducibly covariant with respect to the finite group generated by the Weyl operators. This group provides a direct generalization of the quaternion group. In particular, we analyze the irreducibly…

Mathematical Physics · Physics 2018-04-20 Katarzyna Siudzińska , Dariusz Chruściński

We study the fundamental properties of the quantum f-relative entropy, where f(.) is an operator convex function. We give the equality conditions under monotonicity and joint convexity, and these conditions are more general than, since they…

Quantum Physics · Physics 2012-05-22 Naresh Sharma

Quantum Implicit Neural Representations (QINRs) include components for learning and execution on gate-based quantum computers. While QINRs recently emerged as a promising new paradigm, many challenges concerning their architecture and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Shuteng Wang , Christian Theobalt , Vladislav Golyanik

Let w: Map(X,Y;f) -> Y denote a general evaluation fibration. Working in the setting of rational homotopy theory via differential graded Lie algebras, we identify the long exact sequence induced on rational homotopy groups by w in terms of…

Algebraic Topology · Mathematics 2007-05-23 Gregory Lupton , Samuel Bruce Smith

K-frame theory was recently introduced to reconstruct elements from the range of a bounded linear operator K in a separable Hilbert space. This significant property is worthwhile especially in some problems arising in sampling theory. Some…

Functional Analysis · Mathematics 2017-05-30 Fahimeh Arabyani Neyshaburi , Ghadir Mohajeri Minaei , Ehsan Anjidani

The non-relativistic version of the multi-temporal quantization scheme of relativistic particles in a family of non-inertial frames (see hep-th/0502194) is defined. At the classical level the description of a family of non-rigid…

High Energy Physics - Theory · Physics 2009-11-11 David Alba

Developing and deploying advanced Quantum Repeater (QR) technologies will be necessary to scale quantum networks to longer distances. Depending on the error mitigation mechanisms adopted to suppress loss and errors, QRs are typically…

Quantum Physics · Physics 2025-12-30 Chuen Hei Chan , Charu Jain , Ezra Kissel , Wenji Wu , Edwin Barnes , Sophia E. Economou , Inder Monga

Framed quiver moduli parametrize stable pairs consisting of a quiver representation and a map to a fixed graded vector space. Geometric properties and explicit realizations of framed quiver moduli for quivers without oriented cycles are…

Algebraic Geometry · Mathematics 2007-05-23 Markus Reineke

Quantum Field Theory with fields as Operator Valued Distributions with adequate test functions, -the basis of Epstein-Glaser approach known now as Causal Perturbation Theory-, is recalled. Its recent revival is due to new developments in…

Mathematical Physics · Physics 2007-05-23 Pierre Ca Grange , Ernst Werner

We construct relational observables in group field theory (GFT) in terms of covariant positive operator-valued measures (POVMs), using techniques developed in the context of quantum reference frames. We focus on matter quantum reference…

General Relativity and Quantum Cosmology · Physics 2025-09-03 Luca Marchetti , Edward Wilson-Ewing

We show that networks of quantum frames of reference, in which one frame may be used to produce multiple other frames that in their turn prepare systems which may interact with one another, have counterintuitive properties that make…

Quantum Physics · Physics 2026-03-27 Daniel Collins , Carolina Moreira Ferrera , Ismael L. Paiva , Sandu Popescu

The basic idea of quantum computing is surprisingly similar to that of kernel methods in machine learning, namely to efficiently perform computations in an intractably large Hilbert space. In this paper we explore some theoretical…

Quantum Physics · Physics 2019-02-06 Maria Schuld , Nathan Killoran