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Minimization of the expectation value of energy under the constraints imposed by the uncertainty principle can be a convenient method of solving quantum-mechanical problems.

Quantum Physics · Physics 2012-06-08 A. K. Khitrin

It is shown that neutrino oscillation processes can be consistently described in the framework of quantum field theory. Namely, the oscillating electron survival probabilities in experiments with neutrino detection by charged-current and…

High Energy Physics - Phenomenology · Physics 2018-05-09 Vadim O. Egorov , Igor P. Volobuev

We present a brief review of the impact of the Heisenberg uncertainty relations on quantum optics. In particular we demonstrate how almost all coherent and nonclassical states of quantum optics can be derived from uncertainty relations.

Quantum Physics · Physics 2015-06-26 G. S. Agarwal

Statistical modeling of physical laws connects experiments with mathematical descriptions of natural phenomena. The modeling is based on the probability density of measured variables expressed by experimental data via a kernel estimator. As…

Information Theory · Computer Science 2007-07-13 Igor Grabec

We study a generalization of the original Einstein-Podolsky-Rosen thought experiment. It is essentially a delayed choice experiment as applied to entangled particles. The basic idea is: given two observers sharing position-momentum…

Quantum Physics · Physics 2007-05-23 R. Srikanth

We study the formulation of the uncertainty principle in quantum mechanics in terms of entropic inequalities, extending results recently derived by Bialynicki-Birula [1] and Zozor et al. [2]. Those inequalities can be considered as…

Probability · Mathematics 2009-04-14 Steeve Zozor , Mariela Portesi , Christophe Vignat

The interplay of Anderson localisation and decoherence results in intricate dynamics but is notoriously difficult to simulate on classical computers. We develop the framework for a quantum simulation of such an open quantum system making…

Quantum Physics · Physics 2020-08-19 Max Hunter-Gordon , Zsolt Szabó , Robert A. Nyman , Florian Mintert

Entropic uncertainty is a well-known concept to formulate uncertainty relations for continuous variable quantum systems with finitely many degrees of freedom. Typically, the bounds of such relations scale with the number of oscillator…

Quantum Physics · Physics 2022-03-14 Stefan Floerchinger , Tobias Haas , Markus Schröfl

The uncertainty principle, originally formulated by Heisenberg, dramatically illustrates the difference between classical and quantum mechanics. The principle bounds the uncertainties about the outcomes of two incompatible measurements,…

Quantum Physics · Physics 2011-03-02 Mario Berta , Matthias Christandl , Roger Colbeck , Joseph M. Renes , Renato Renner

We address the problem of interference using the Heisenberg picture and highlight some new aspects through the use of pre-selection, post-selection, weak measurements, and modular variables, We present a physical explanation for the…

Quantum Physics · Physics 2015-05-14 Jeff Tollaksen , Yakir Aharonov , Aharon Casher , Tirzah Kaufherr , Shmuel Nussinov

The effects of particle discreteness in N-body simulations of Lambda Cold Dark Matter (LambdaCDM) are still an intensively debated issue. In this paper we explore such effects, taking into account the scatter caused by the randomness of the…

Astrophysics · Physics 2009-11-13 Alessandro B. Romeo , Oscar Agertz , Ben Moore , Joachim Stadel

In neutrino oscillation experiments, neutrino interactions at the detector are simulated using event generators which attempt to reflect our understanding of nuclear physics. We study the impact of different neutrino interactions and…

High Energy Physics - Phenomenology · Physics 2014-04-23 Pilar Coloma , Patrick Huber , Chun-Min Jen , Camillo Mariani

The problem of a correct description of the physical phenomena of the Heisenberg uncertainty relation is solved by using a variable hidden in Newtonian mehcanics.

General Physics · Physics 2012-03-30 Jae-Hyung Myung

Simulations of complex turbulent flow are part and parcel of the engineering design process. Eddy viscosity based turbulence models represent the workhorse for these simulations. The underlying simplifications in eddy viscosity models make…

Fluid Dynamics · Physics 2024-05-15 Minghan Chu , Weicheng Qian

We study the quantum-mechanical uncertainty relation originating from the successive measurement of two observables $\hat{A}$ and $\hat{B}$, with eigenvalues $a_n$ and $b_m$, respectively, performed on the same system. We use an extension…

Quantum Physics · Physics 2020-06-02 Ady Mann , Pier A. Mello , Michael Revzen

The interpretation of dark matter direct detection experiments is complicated by the fact that neither the astrophysical distribution of dark matter nor the properties of its particle physics interactions with nuclei are known in detail. To…

High Energy Physics - Phenomenology · Physics 2017-02-06 Felix Kahlhoefer , Sebastian Wild

The effects of mixedness and entanglement on the lower bound and tightness of the entropic uncertainty in the Heisenberg model with Dzyaloshinski-Moriya (DM) interaction have been investigated. It is found that the mixedness can reflect the…

Quantum Physics · Physics 2017-02-22 Xiao Zheng , Guo-Feng Zhang

Event centric approaches to modeling physics have gained traction in recent decades. In this work, we present a first principles approach to this idea, which assumes nothing but the existence of causal networks of events and their…

General Physics · Physics 2023-06-28 Sam Powers , Dejan Stojkovic

In astrophysical scenarios with large neutrino density, like supernovae and the early universe, the presence of neutrino-neutrino interactions can give rise to collective flavor oscillations in the out-of-equilibrium collective dynamics of…

Quantum Physics · Physics 2021-09-08 Benjamin Hall , Alessandro Roggero , Alessandro Baroni , Joseph Carlson

We consider the problem of performing Bayesian inference in probabilistic models where observations are accompanied by uncertainty, referred to as "uncertain evidence." We explore how to interpret uncertain evidence, and by extension the…

Machine Learning · Statistics 2023-01-27 Andreas Munk , Alexander Mead , Frank Wood