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In quantum computing, knowing the symmetries a given system or state obeys or disobeys is often useful. For example, Hamiltonian symmetries may limit allowed state transitions or simplify learning parameters in machine learning…

Quantum Physics · Physics 2024-07-26 Margarite L. LaBorde , Soorya Rethinasamy , Mark M. Wilde

We introduce the notion of geometric pseudo-quantisation based on geometric quantisation with a weakened curvature condition. We show how such a structure arises naturally from simple deformations of the symplectic structure and pullbacks…

Mathematical Physics · Physics 2025-11-25 Kerr Maxwell

Random Projection is a foundational research topic that connects a bunch of machine learning algorithms under a similar mathematical basis. It is used to reduce the dimensionality of the dataset by projecting the data points efficiently to…

Machine Learning · Computer Science 2017-10-10 Mahmoud Nabil

Quantum computation is the suitable orthogonal encoding of possibly holistic functional properties into state vectors, followed by a projective measurement.

Quantum Physics · Physics 2016-05-10 Karl Svozil

The basic elements of the geometric approach to a consistent quantization formalism are summarized, with reference to the methods of the old quantum mechanics and the induced representations theory of Lie groups. A possible relationship…

Mathematical Physics · Physics 2011-11-08 M. Grigorescu

Building on a recent proposal for a quantum reduction to spherical symmetry from full loop quantum gravity, we investigate the relation between a quantisation of spherically symmetric general relativity and a reduction at the quantum level.…

General Relativity and Quantum Cosmology · Physics 2016-07-29 Norbert Bodendorfer , Antonia Zipfel

The present article is primarily a review of the projection-operator approach to quantize systems with constraints. We study the quantization of systems with general first- and second-class constraints from the point of view of…

High Energy Physics - Theory · Physics 2007-05-23 John R. Klauder

In the current era of noisy quantum devices, there is a need for quantum algorithms that are efficient and robust against noise. Towards this end, we introduce the projected cooling algorithm for quantum computation. The projected cooling…

The metric known to be relevant for standard quantization procedures receives a natural interpretation and its explicit use simultaneously gives both physical and mathematical meaning to a (coherent-state) phase-space path integral, and at…

Quantum Physics · Physics 2007-05-23 John R. Klauder

Classical shadow tomography is a sample-efficient technique for characterizing quantum systems and predicting many of their properties. Circuit cutting is a technique for dividing large quantum circuits into smaller fragments that can be…

Quantum Physics · Physics 2024-05-21 Daniel T. Chen , Zain H. Saleem , Michael A. Perlin

An attempt is made to formulate quantum mechanics (QM) in physical rather than in mathematical terms. It is argued that the appropriate conceptual framework for QM is "contextual objectivity", which includes an objective definition of the…

Quantum Physics · Physics 2016-09-08 Philippe Grangier

Current and imminent quantum hardware lacks reliability and applicability due to noise and limited qubit counts. Quantum circuit cutting -- a technique dividing large quantum circuits into smaller subcircuits with sizes appropriate for the…

Quantum Physics · Physics 2022-12-05 Daniel Chen , Betis Baheri , Vipin Chaudhary , Qiang Guan , Ning Xie , Shuai Xu

We consider a general symplectic transformation (also known as linear canonical transformation) of quantum-mechanical observables in a quantized version of a finite-dimensional system with configuration space isomorphic to $ \mathbb{R}^{q}…

Quantum Physics · Physics 2021-03-17 Jakub Káninský

Projection algorithms are well known for their simplicity and flexibility in solving feasibility problems. They are particularly important in practice due to minimal requirements for software implementation and maintenance. In this work, we…

Optimization and Control · Mathematics 2020-04-14 Minh N. Dao , Hung M. Phan

Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gausians. Here we summarize these results and illustrate them by a wide variety of experiments on synthetic…

Machine Learning · Computer Science 2013-01-18 Sanjoy Dasgupta

In this paper, a new approximate syllogistic reasoning schema is described that expands some of the approaches expounded in the literature into two ways: (i) a number of different types of quantifiers (logical, absolute, proportional,…

Artificial Intelligence · Computer Science 2014-11-27 M. Pereira-Fariña , Juan C. Vidal , F. Díaz-Hermida , A. Bugarín

Quantization with coherent states allows to " quantize " any space X of parameters. In the case where X is a phase space, this leads to the usual quantum mechanics. But the procedure is much more general, and does not require a symplectic,…

Mathematical Physics · Physics 2007-05-23 Marc Lachieze Rey , Jean-Pierre Gazeau , Eric Huguet , Jacques Renaud , Tarik Garidi

As quantum technologies advance, the ability to generate increasingly large quantum states has experienced rapid development. In this context, the verification and estimation of large entangled systems represents one of the main challenges…

Quantum Physics · Physics 2022-03-30 Joshua Morris , Valeria Saggio , Aleksandra Gočanin , Borivoje Dakić

The algebraic method of singular reduction is applied for non regular group action on manifolds which provides singular symplectic spaces. The problem of deformation quantization of the singular surfaces is the focus. For some examples of…

Mathematical Physics · Physics 2017-06-27 Victor Palamodov

The effectiveness of projection methods for solving systems of linear inequalities is investigated. It is shown that they have a computational advantage over some alternatives and that this makes them successful in real-world applications.…

Optimization and Control · Mathematics 2009-12-23 Y. Censor , W. Chen , P. L. Combettes , R. Davidi , G. T. Herman