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Related papers: Probabilistic interpretation of mechanical motion

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Probabilistic description of results of measurements and its consequences for understanding quantum mechanics are discussed. It is shown that the basic mathematical structure of quantum mechanics like the probability amplitude, Born rule,…

Quantum Physics · Physics 2007-05-23 L. Skala , V. Kapsa

This paper concerns instruction sequences that contain probabilistic instructions, i.e. instructions that are themselves probabilistic by nature. We propose several kinds of probabilistic instructions, provide an informal operational…

Programming Languages · Computer Science 2014-10-02 J. A. Bergstra , C. A. Middelburg

There are considered some corollaries of certain hypotheses on the observation process of microphenomena. We show that an enlargement of the phase space and of its motion group and an account for the diffusion motions of microsystems in the…

Quantum Physics · Physics 2007-05-23 E. M. Beniaminov

Motion correlation interfaces are those that present targets moving in different patterns, which the user can select by matching their motion. In this paper, we re-formulate the task of target selection as a probabilistic inference problem.…

Human-Computer Interaction · Computer Science 2021-02-09 Eduardo Velloso , Carlos Hitoshi Morimoto

In quantum mechanics, outcomes of measurements on a state have a probabilistic interpretation while the evolution of the state is treated deterministically. Here we show that one can also treat the evolution as being probabilistic in nature…

Quantum Physics · Physics 2009-11-10 J. Oppenheim , B. Reznik

This is a guide to the mathematical theory of Brownian motion and related stochastic processes, with indications of how this theory is related to other branches of mathematics, most notably the classical theory of partial differential…

Probability · Mathematics 2018-02-28 Jim Pitman , Marc Yor

For autonomous agents to successfully operate in real world, the ability to anticipate future motions of surrounding entities in the scene can greatly enhance their safety levels since potentially dangerous situations could be avoided in…

Machine Learning · Computer Science 2019-06-04 Yeping Hu , Wei Zhan , Liting Sun , Masayoshi Tomizuka

A wide range of physical problems can be described by randomly-oriented linear trajectories, including any system of objects, organisms, particles, or rays that follow a linear path. Dependent upon the particular random variables that…

Probability · Mathematics 2014-01-03 Gregory T. Clement

Recent results suggest that quantum mechanical phenomena may be interpreted as a failure of standard probability theory and may be described by a Bayesian complex probability theory.

Quantum Physics · Physics 2007-05-23 Saul Youssef

A commonly-used representation for motion prediction of actors is a sequence of waypoints (comprising positions and orientations) for each actor at discrete future time-points. While this approach is simple and flexible, it can exhibit…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Zhaoen Su , Chao Wang , Henggang Cui , Nemanja Djuric , Carlos Vallespi-Gonzalez , David Bradley

Quantum theory expresses the observable relations between physical properties in terms of probabilities that depend on the specific context described by the "state" of a system. However, the laws of physics that emerge at the macroscopic…

Quantum Physics · Physics 2016-06-06 Holger F. Hofmann

We present a method for incorporating a stochastic point of view into physics exercises of mathematics education. The core of our method is the randomization of some inputs, the system model used does not differ from what we would use in…

Physics Education · Physics 2025-09-16 Matyas Barczy , Imre Kocsis , Csaba Gábor Kézi

In a recently proposed interpretation of quantum mechanics, U. Mohrhoff advocates original and thought-provoking views on space and time, the definition of macroscopic objects, and the meaning of probability statements. The interpretation…

Quantum Physics · Physics 2015-06-09 Louis Marchildon

A probabilistic interpretation of one-particle relativistic quantum mechanics is proposed. Quantum Action Principle formulated earlier is used for to make the dynamics of the Minkowsky time variable of a particle to be classical. After…

Quantum Physics · Physics 2010-12-09 Natalia Gorobey , Alexander Lukyanenko , Inna Lukyanenko

Time evolution of macroscopic systems is re-examined primarily through further analysis and extension of the equation of motion for the density matrix $\rho(t)$. Because $\rho$ contains both classical and quantum-mechanical probabilities it…

Statistical Mechanics · Physics 2009-11-10 W. T. Grandy

It is shown that physical mechanics for pointlike bodies can be effectively modeled in terms of the action of transformation groups that act as symmetries of the solutions of systems of differential equations that describe the integrability…

General Relativity and Quantum Cosmology · Physics 2007-08-14 D. H. Delphenich

The probabilistic interpretation of Laplace transforms is used to help to describe the Laplace Transform $L(s)$ of improper random variables. In particular, busy periods in queueing models are examined. The value of $L(0)$ is explained in…

Probability · Mathematics 2021-08-10 Janhavi Prabhu , Myron Hlynka

The Everett interpretation of quantum mechanics divides naturally into two parts: first, the interpretation of the structure of the quantum state, in terms of branching, and second, the interpretation of this branching structure in terms of…

Quantum Physics · Physics 2021-03-09 Simon Saunders

A rule to assign a physical meaning to Lagrange multipliers is discussed. Examples from mechanics, statistical mechanics and quantum mechanics are given.

Physics Education · Physics 2007-05-23 Hasan Karabulut

A cyclic random motion at finite velocity with orthogonal directions is considered in the plane and in $\mathbb{R}^3$. We obtain in both cases the explicit conditional distributions of the position of the moving particle when the number of…

Probability · Mathematics 2020-01-01 E. Orsingher , R. Garra , A. I. Zeifman