Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1403.3189

Wigner function and the probability representation of quantum states

Margarita A. Man'ko·Vladimir I. Man'ko
View original source ↗Read source document ↗Export metadata ↓

Abstract

The relation of the Wigner function with the fair probability distribution called tomographic distribution or quantum tomogram associated with the quantum state is reviewed. The connection of the tomographic picture of quantum mechanics with the integral Radon transform of the Wigner quasidistribution is discussed. The Wigner--Moyal equation for the Wigner function is presented in the form of kinetic equation for the tomographic probability distribution both in quantum mechanics and in the classical limit of the Liouville equation. The calculation of moments of physical observables in terms of integrals with the state tomographic probability distributions is constructed having a standard form of averaging in the probability theory. New uncertainty relations for the position and momentum are written in terms of optical tomograms suitable for direct experimental check. Some recent experiments on checking the uncertainty relations including the entropic uncertainty relations are discussed.

Explore related subjects

quant-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Margarita A. Man'ko, Vladimir I. Man'ko. 2014-03-13. Wigner function and the probability representation of quantum states. https://doi.org/10.1051/epjconf%2F20147804002

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Fermionic magic resources in disordered quantum spin chains

Fermionic non-Gaussianity quantifies a quantum state's deviation from a classically tractable free-fermionic description, constituting a necessary resource for computational quantum advantage. Here we use fermionic antiflatness (FAF) to measure this deviation across ergodic and many-body localized (MBL) regimes. We focus on the paradigmatic disordered spin-$1\!/2$ XXZ chain and its impurity variant with local interactions. Across highly excited eigenstates, FAF evolves from typical-state behavior at weak disorder to strongly suppressed values deep in the MBL regime, with volume-law scaling in the XXZ chain and an area-law bound in the impurity setting. Rare long-range cat-like eigenstates exhibit a pronounced enhancement of FAF, making it a sensitive diagnostic of mechanisms proposed to destabilize MBL. Starting from product states, we find that in the MBL regime FAF grows slowly in time, approaching saturation via a power-law relaxation. Overall, our results show that MBL suppresses fermionic non-Gaussianity, and the associated complexity beyond free fermions, while ergodicity restores it, motivating explorations of fermionic non-Gaussianity in other ergodicity-breaking phenomena.

quant-ph↗
arXiv2026

Progressive Binarization - Pauli Correlation Encoding: a Continuation Method for Constrained Optimization

Pauli Correlation Encoding (PCE) reduces the qubit requirements of quantum optimization by embedding the problem variables into the expectation values of Pauli observables, so that the number of qubits can be much smaller than the number of variables. PCE has not yet been studied for constrained optimization. We extend it to constrained combinatorial problems, using the budget-constrained MinCut as a case study, and show that the standard formulation fails to reliably enforce the constraint: feasibility hinges on the binarization of the encoded variables, which depends sensitively on hyperparameters that are hard to tune and do not transfer across instances. To address this, we introduce Progressive-Binarization PCE (PB-PCE), an adaptive continuation scheme that progressively increases the binarization parameter while re-optimizing the circuit from the previous solution, driving the variables towards the binary domain. PB-PCE attains near-complete constraint satisfaction (88--100\%) and smaller cut sizes than standard PCE, with a number of stages (10--20) essentially independent of problem size, solving instances of up to 300 variables with only 9-qubit circuits.

quant-ph↗
arXiv2026

A quantum model for synchronizing finite state transition systems

We propose a quantum model for finding a resetting input sequence (RS) which can take a finite state transition system (FA), to particular state independent of its current state. The complexity of finding such sequences for various types of FA can be NP-Hard or even PSPACE-Complete. To this end, we represent the FA states, inputs, and transition function in quantum space. Accordingly, we propose a model to represent the execution of an input sequence of a particular length $l$ starting form an initial FA state. The model is extended considering the application in superposition of all input sequences of length $l$ to an initial state of the FA. The model is further extended considering the application of all input sequences to all initial states of the FA capturing for every input sequence the collection (ordered list) of states reached by applying the sequence to all states of the FA. The amplitude amplification algorithm is then used as it combines similar collections of reached states while preserving all input sequences that reach these collections. A Grover search for a reached collection where its elements correspond to the same FA state provides a RS for the FA. Our approach offers a quadratic gain over the exponential complexity of traditional brute-force method, which is the only method that can be applied to a general FA class.

quant-ph↗