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Related papers: Inverse Time-Dependent Quantum Mechanics

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This brief article gives an overview of quantum mechanics as a {\em quantum probability theory}. It begins with a review of the basic operator-algebraic elements that connect probability theory with quantum probability theory. Then quantum…

Quantum Physics · Physics 2020-02-04 Hendra I. Nurdin

I describe a method of inferring the past of quantum observables given the initial state and the subsequent measurement results using Wigner quasi-probability representations. The method is proved to be compatible with logic for large…

Quantum Physics · Physics 2014-04-02 Mankei Tsang

Quantum dynamics can be driven by measurement. By constructing measurements that gain no information, effective unitary evolution can be induced on a quantum system, for example in ancilla driven quantum computation. In the non-ideal case…

Quantum Physics · Physics 2015-06-19 Daniel K. L. Oi

This paper extends the work of Clarke [1] on the Bayesian foundations of the biomagnetic inverse problem. It derives expressions for the expectation and variance of the a posteriori source current probability distribution given a prior…

Medical Physics · Physics 2009-10-31 R. Hasson , S. J. Swithenby

Although the laws of classical physics are deterministic, thermodynamics gives rise to an arrow of time through irreversible processes. In quantum mechanics the unitary nature of the time evolution makes it intrinsically reversible, however…

We present a new procedure for quantum state reconstruction based on weak continuous measurement of an ensemble average. By applying controlled evolution to the initial state new information is continually mapped onto the measured…

Quantum Physics · Physics 2009-11-10 Andrew Silberfarb , Poul S. Jessen , Ivan H. Deutsch

We study quantum measurement retrodiction using the principle of minimum change. For quantum-to-classical measurement channels, we show that all standard quantum divergences select the same retrodictive update, yielding a unique and…

Quantum Physics · Physics 2025-11-27 Jiaxi Kuang , Kensei Torii , Francesco Buscemi

A modified version of relational quantum mechanics is developed based on the three following ideas. An observer can develop an internally consistent description of the universe but it will, of necessity, differ in particulars from the…

History and Philosophy of Physics · Physics 2020-11-30 B. K. Jennings

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time M and continuous wave function arise…

Mathematical Physics · Physics 2015-06-19 William Sulis

Through extended consideration of two wide classes of case studies -- dilute gases and linear systems -- I explore the ways in which assumptions of probability and irreversibility occur in contemporary statistical mechanics, where the…

Statistical Mechanics · Physics 2021-04-23 David Wallace

In a variety of scientific applications we wish to characterize a physical system using measurements or observations. This often requires us to solve an inverse problem, which usually has non-unique solutions so uncertainty must be…

Geophysics · Physics 2022-05-19 Xin Zhang , Muhammad Atif Nawaz , Xuebin Zhao , Andrew Curtis

Inverse analysis, such as model calibration, often suffers from a lack of informative data in complex real-world scenarios. The standard remedy, designing new experimental setups, is often costly and time-consuming, while readily available…

Computational Engineering, Finance, and Science · Computer Science 2026-01-16 Lea J. Haeusel , Jonas Nitzler , Lea J. Köglmeier , Wolfgang A. Wall

We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective. Our results are in accord with earlier work by…

Quantum Physics · Physics 2009-11-11 Mark Srednicki

We consider stochastic and open quantum systems with a finite number of states, where a stochastic transition between two specific states is monitored by a detector. The long-time counting statistics of the observed realizations of the…

Quantum Physics · Physics 2014-03-27 M. Bruderer , L. D. Contreras-Pulido , M. Thaller , L. Sironi , D. Obreschkow , M. B. Plenio

We propose a quantum inverse iteration algorithm which can be used to estimate the ground state properties of a programmable quantum device. The method relies on the inverse power iteration technique, where the sequential application of the…

Quantum Physics · Physics 2020-01-22 Oleksandr Kyriienko

Machine learning methods for computational imaging require uncertainty estimation to be reliable in real settings. While Bayesian models offer a computationally tractable way of recovering uncertainty, they need large data volumes to be…

Machine Learning · Computer Science 2020-08-24 Francesco Tonolini , Jack Radford , Alex Turpin , Daniele Faccio , Roderick Murray-Smith

Quantum systems are exceedingly difficult to engineer because they are sensitive to various types of noises. In particular, time-dependent noises are frequently encountered in experiments but how to overcome them remains a challenging…

Quantum Physics · Physics 2022-05-06 Xiaodong Yang , Xinfang Nie , Tao Xin , Dawei Lu , Jun Li

The question about the existence of so-called ``hidden'' variables in quantum mechanics and the perception of the completeness of quantum mechanics are two sides of the same coin. Quantum analytical mechanics constitutes a completion of…

Quantum Physics · Physics 2026-05-01 Wolfgang Paul

A subjective survey of stochastic models of quantum mechanics is given along with a discussion of some key radiative processes, the clues they offer, and the difficulties they pose for this program. An electromagnetic basis for deriving…

Quantum Physics · Physics 2015-06-26 Mark P. Davidson

Bayesian methods are particularly effective for addressing inverse problems due to their ability to manage uncertainties inherent in the inference process. However, employing these methods with costly forward models poses significant…

Computational Engineering, Finance, and Science · Computer Science 2025-10-30 G. Robalo Rei , C. P. Schmidt , J. Nitzler , M. Dinkel , W. A. Wall