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The real time evolution of quantum field theory models can be calculated order by order in perturbation theory. For $\lambda \phi^4$ models, the perturbative series have a zero radius of convergence which in part motivated the design of…

Quantum Physics · Physics 2023-03-13 Robert Maxton , Yannick Meurice

We present a novel form of relativistic quantum mechanics and demonstrate how to solve it using a recently derived unitary perturbation theory, within partial wave analysis. The theory is tested on a relativistic problem, with two spinless,…

Quantum Physics · Physics 2021-08-11 Scott E. Hoffmann

Accurate determination of carrier transport properties in two-dimensional (2D) materials is critical for designing high-performance nano-electronic devices and quantum information platforms. While first-principles calculations effectively…

Mesoscale and Nanoscale Physics · Physics 2020-12-04 Sathwik Bharadwaj , Ashwin Ramasubramaniam , L. R. Ram-Mohan

This article reviews recent research towards a universal light-matter interface. Such an interface is an important prerequisite for long distance quantum communication, entanglement assisted sensing and measurement, as well as for scalable…

Quantum Physics · Physics 2011-11-04 Christine A. Muschik , Hanna Krauter , Klemens Hammerer , Eugene S. Polzik

This essay considers a simple model of observers that are influenced by the world around them. Consistent quantification of information about such influences results in a great deal of familiar physics. The end result is a new perspective…

Quantum Physics · Physics 2013-08-16 Kevin H. Knuth

Quantum computers take advantage of interfering quantum alternatives in order to handle problems that might be too time consuming with algorithms based on classical logic. Developing quantum computers requires new ways of thinking beyond…

Quantum Physics · Physics 2014-09-10 W. C. Parke

Recently Quantum Computation has generated a lot of interest due to the discovery of a quantum algorithm which can factor large numbers in polynomial time. The usefulness of a quantum com puter is limited by the effect of errors. Simulation…

Quantum Physics · Physics 2007-05-23 Kevin M. Obenland , Alvin M. Despain

In this note we demonstrate that a quantum-like interference picture could appear as a statistical effect of interference of deterministic particles, i.e. particles that have trajectories and obey deterministic equations, if one introduces…

Quantum Physics · Physics 2007-05-23 Andrei Khrennikov , Yaroslav Volovich

We propose an improved scheme of perturbation theory based on our exact solution [An Min Wang, quant-ph/0611216] in general quantum systems independent of time. Our elementary start-point is to introduce the perturbing parameter as late as…

Quantum Physics · Physics 2007-05-23 An Min Wang

Counting the number of clusters, when these clusters overlap significantly is a challenging problem in machine learning. We argue that a purely mathematical quantum theory, formulated using the path integral technique, when applied to…

Machine Learning · Computer Science 2020-01-14 Rohit R Muthyala , Davi Geiger , Zvi M. Kedem

A large spectrum of problems in classical physics and engineering, such as turbulence, is governed by nonlinear differential equations, which typically require high-performance computing to be solved. Over the past decade, however, the…

Fluid Dynamics · Physics 2024-06-10 Felix Tennie , Sylvain Laizet , Seth Lloyd , Luca Magri

In a large variety of quantum mechanical systems, we show that the full non-perturbative expression for energy eigenvalues, containing all orders of perturbative, non-perturbative and quasi-zero-mode terms, may be generated directly from…

High Energy Physics - Theory · Physics 2014-04-04 Gerald V. Dunne , Mithat Unsal

We investigate decoherence effects in the recently suggested quantum computation scheme using weak nonlinearities, strong probe coherent fields, detection and feedforward methods. It is shown that in the weak-nonlinearity-based quantum…

Quantum Physics · Physics 2007-05-23 Hyunseok Jeong

Quantum theory exhibits various nonclassical features, such as measurement incompatibility, contextuality, steering, and Bell nonlocality, which distinguish it from classical physics. These phenomena are often studied separately, but they…

Quantum Physics · Physics 2026-05-25 Tim Achenbach , Andreas Bluhm , Leevi Leppäjärvi , Ion Nechita , Martin Plávala

Recently there has been much interest in deriving the quantum formalism and the set of quantum correlations from simple axioms. In this paper, we provide a step-by-step derivation of the quantum formalism that tackles both these problems…

Quantum Physics · Physics 2023-03-10 Alisson Tezzin

We demonstrate the feasibility of a nonperturbative analysis of quantum field theory in the worldline formalism with the help of an efficient numerical algorithm. In particular, we compute the effective action for a super-renormalizable…

High Energy Physics - Theory · Physics 2009-11-11 H. Gies , J. Sánchez--Guillén , R. A. Vázquez

This paper demonstrates that a computer aided perturbation theory can easily be realized by use of a cumulant approach. In contrast to a recent alternative formulation on the basis of Wegner's flow equation method the present approach can…

Strongly Correlated Electrons · Physics 2009-11-10 S. Sykora , A. Huebsch , K. W. Becker

A distance measure is presented between two unitary propagators of quantum systems of differing dimensions along with a corresponding method of computation. A typical application is to compare the propagator of the actual (real) process…

Quantum Physics · Physics 2007-05-23 Robert L. Kosut , Matthew Grace , Constantin Brif , Herschel Rabitz

Quantum theory (QT) has been confirmed by numerous experiments, yet we still cannot fully grasp the meaning of the theory. As a consequence, the quantum world appears to us paradoxical. Here we shed new light on QT by being based on two…

Quantum Physics · Physics 2019-05-21 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

There are two major approaches to building good machine learning algorithms: feeding lots of data into large models, or picking a model class with an ''inductive bias'' that suits the structure of the data. When taking the second approach…

Quantum Physics · Physics 2023-12-08 Kaitlin Gili , Guillermo Alonso , Maria Schuld