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We investigate probabilistic transformations of quantum states from a `source' set to a `target' set of states. Such transforms have many applications. They can be used for tasks which include state-dependent cloning or quantum state…

Quantum Physics · Physics 2015-06-05 Vedran Dunjko , Erika Andersson

When a quantum many-particle system exists on a randomly diluted lattice, its intrinsic thermal and quantum fluctuations coexist with geometric fluctuations due to percolation. In this paper, we explore how the interplay of these…

Statistical Mechanics · Physics 2017-08-23 Thomas Vojta , J. A. Hoyos

We investigate the transition from quantum to classical mechanics using a one-dimensional free particle model. In the classical analysis, we consider the initial positions and velocities of the particle drawn from Gaussian distributions.…

Quantum Physics · Physics 2024-05-30 E. Aldo Arroyo

The von Neumann trace form of quantum statistical mechanics is transformed to an integral over classical phase space. Formally exact expressions for the resultant position-momentum commutation function are given. A loop expansion for wave…

Quantum Physics · Physics 2018-11-07 Phil Attard

While quantum computers assume existence of state preparation process $|0\rangle$, CPT symmetry of physics says that performing such process in CPT symmetry perspective, e.g. reversing used EM impulses ($V(t)\to V(-t)$), we should get its…

General Physics · Physics 2024-08-13 Jarek Duda

We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local…

Chaotic Dynamics · Physics 2017-03-09 Stephen C Creagh , Gabriele Gradoni , Timo Hartmann , Gregor Tanner

We discuss the advantages of using the approximate quantum Fourier transform (AQFT) in algorithms which involve periodicity estimations. We analyse quantum networks performing AQFT in the presence of decoherence and show that extensive…

Quantum Physics · Physics 2009-10-30 Adriano Barenco , Artur Ekert , Kalle-Antti Suominen , Päivi Törmä

We study how time-dependent energy fluctuations impact the dynamical quantum phase transitions (DQPTs) following a noisy ramped quench of the transverse magnetic field in a quantum Ising chain. By numerically solving the stochastic…

Statistical Mechanics · Physics 2025-01-13 R. Jafari , A. Langari , S. Eggert , Henrik Johannesson

We argue that the complex numbers are an irreducible object of quantum probability. This can be seen in the measurements of geometric phases that have no classical probabilistic analogue. Having complex phases as primitive ingredient…

General Relativity and Quantum Cosmology · Physics 2014-11-17 Charis Anastopoulos

The basic random $k$-SAT problem is: Given a set of $n$ Boolean variables, and $m$ clauses of size $k$ picked uniformly at random from the set of all such clauses on our variables, is the conjunction of these clauses satisfiable? Here we…

Combinatorics · Mathematics 2019-06-13 Joel Larsson , Klas Markström

In the continuum limit (large number of qubits), adiabatic quantum algorithms display a remarkable similarity to sweeps through quantum phase transitions. We find that transitions of second or higher order are advantageous in comparison to…

Quantum Physics · Physics 2015-06-26 Ralf Schützhold , Gernot Schaller

We investigate the long-range statistical correlations, whereby discuss the nature of the undermining interacting/ noninteracting domains and associated phase transitions under variations of the quark mass and the mass scale that…

High Energy Physics - Lattice · Physics 2019-08-19 Bhupendra Nath Tiwari

In many situations, the statistical properties of wave systems with chaotic classical limits are well-described by random matrix theory. However, applications of random matrix theory to scattering problems require introduction of system…

Statistical Mechanics · Physics 2013-05-29 James A. Hart , Thomas M. Antonsen , Edward Ott

As a compact representation of joint probability distributions over a dependence graph of random variables, and a tool for modelling and reasoning in the presence of uncertainty, Bayesian networks are of great importance for artificial…

Quantum Physics · Physics 2020-10-06 Michael de Oliveira , Luis Soares Barbosa

Quantum fluctuations or other moments of a state contribute to energy expectation values and can imply interesting physical effects. In quantum cosmology, they turn out to be important for a discussion of density bounds and instabilities of…

General Relativity and Quantum Cosmology · Physics 2014-07-02 Martin Bojowald

Using the random matrix description of open quantum chaotic systems we calculate in closed form the universal autocorrelation function and the probability distribution of the total photodissociation cross section in the regime of quantum…

Condensed Matter · Physics 2009-10-31 Yan V. Fyodorov , Yoram Alhassid

We address the question as to why, in the semiclassical limit, classically chaotic systems generically exhibit universal quantum spectral statistics coincident with those of Random Matrix Theory. To do so, we use a semiclassical resummation…

Chaotic Dynamics · Physics 2009-06-11 Jonathan P. Keating , Sebastian Müller

A simple model for open quantum systems is analyzed with Random Matrix Theory. The system is coupled to the continuum in a minimal way. In this paper we see the effect of opening the system on the level statistics, in particular the…

Nuclear Theory · Physics 2015-01-12 Declan Mulhall

We classify phases of a bosonic lattice model based on the computational complexity of classically simulating the system. We show that the system transitions from being classically simulable to classically hard to simulate as it evolves in…

Number partitioning is one of the classical NP-hard problems of combinatorial optimization. It has applications in areas like public key encryption and task scheduling. The random version of number partitioning has an "easy-hard" phase…

Disordered Systems and Neural Networks · Physics 2007-05-23 Stephan Mertens
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