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Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the…

Quantum Physics · Physics 2024-12-19 Kevin Lively , Tim Bode , Jochen Szangolies , Jian-Xin Zhu , Benedikt Fauseweh

We discuss recent findings about properties of quantum nonequilibrium steady states. In particular we focus on transport properties. It is shown that the time dependent density matrix renormalization method can be used successfully to find…

Quantum Physics · Physics 2011-11-15 Marko Znidaric

We compute direct current (dc) thermoelectric transport coefficients in strongly coupled quantum field theories without long lived quasiparticles, at finite temperature and charge density, and disordered on long wavelengths compared to the…

High Energy Physics - Theory · Physics 2015-10-30 Andrew Lucas

Transport phenomena play a crucial role in modern physics and applied sciences. Examples include the dissipation of energy across a large system, the distribution of quantum information in optical networks, and the timely modeling of…

We use first-principle Quantum Monte-Carlo (QMC) simulations and numerical exact diagonalization to analyze the low-frequency charge carrier mobility within a simple tight-binding model of molecular organic semiconductors on a…

Materials Science · Physics 2025-07-23 Pavel Buividovich , Johann Ostmeyer , Alessandro Troisi

In Part I of this two-part series, the reverse perturbation method for shearing simple liquids [Phys. Rev. E 59, 4894 (1999)] was extended to systems of interacting particles with time-discrete stochastic dynamics. For verification, in this…

Soft Condensed Matter · Physics 2019-10-16 Arash Nikoubashman , Thomas Ihle

In this review, we survey the current progress in computing transport properties in semimetals which harbour non-Fermi liquid phases. We first discuss the widely-used Kubo formalism, which can be applied to the effective theory describing…

Strongly Correlated Electrons · Physics 2024-08-28 Ipsita Mandal , Hermann Freire

Through periodic Training we can gradually buildup a reproducible responses in a disordered system where plasticity dominates over elasticity as is known in classical amorphous materials and soft matter 1, 6. Here we show that a similar…

Mesoscale and Nanoscale Physics · Physics 2026-01-01 Madhuri Mukhopadhyay

We study the transport properties of ultrathin disordered nanowires in the neighborhood of the superconductor-metal quantum phase transition. To this end we combine numerical calculations with analytical strong-disorder renormalization…

Disordered Systems and Neural Networks · Physics 2010-10-07 Adrian Del Maestro , Bernd Rosenow , J. A. Hoyos , Thomas Vojta

Quantum computing has opened new opportunities to tackle complex machine learning tasks, for instance, high-dimensional data representations commonly required in intelligent transportation systems. We explore quantum machine learning to…

Machine Learning · Computer Science 2025-09-09 Bara Rababah , Bilal Farooq

In this chapter we explore the connection between mesoscopic physics and quantum computing. After giving a bibliography providing a general introduction to the subject of quantum information processing, we review the various approaches that…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 D. P. DiVincenzo , G. Burkard , D. Loss , E. V. Sukhorukov

Transport engineering has significant potential to benefit from quantum computing. The rise of intelligent transport systems, autonomous vehicles, and the Internet of Things has created an unprecedented demand for efficient information…

Quantum Physics · Physics 2026-03-13 Lachlan Oberg , Paul Corry , Moji Ghadimi , Ashish Bhaskar

Particle transport and localization phenomena in condensed-matter systems can be modeled using a tight-binding lattice Hamiltonian. The ideal experimental emulation of such a model utilizes simultaneous, high-fidelity control and readout of…

In transport experiments the quantum nature of matter becomes directly evident when changes in conductance occur only in discrete steps, with a size determined solely by Planck's constant h. The observations of quantized steps in the…

A new theoretical method is introduced to study coherent electron transport in an interacting multilevel quantum dot. The method yields the correct behavior both in the limit of weak and strong coupling to the leads, giving a unified…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 A. Levy Yeyati , F. Flores , A. Martin-Rodero

We investigate theoretically the thermoelectric transport through a circuit implementation of the three-channel "charge" Kondo model quantum simulator [Z. Iftikhar et al., Science 360, 1315 (2018)]. The universal temperature scaling law of…

Mesoscale and Nanoscale Physics · Physics 2020-07-09 T. K. T. Nguyen , M. N. Kiselev

Monte Carlo statistical ray-tracing methods are commonly employed to simulate carrier transport in nanostructured materials. In the case of a large degree of nanostructuring and under linear response (small driving fields), these…

Mesoscale and Nanoscale Physics · Physics 2023-02-09 Pankaj Priyadarshi , Neophytos Neophytou

Nonlinear electronic transport has emerged as a powerful probe of the quantum geometry in topological quantum materials, where the band topology and broken symmetries facilitate power law current voltage responses beyond Ohms law. While…

The physics of non-zero temperature dynamics and transport near quantum-critical points is discussed by a detailed study of the O(N)-symmetric, relativistic, quantum field theory of a N-component scalar field in $d$ spatial dimensions. A…

Strongly Correlated Electrons · Physics 2025-09-08 Subir Sachdev

Transport-dominated partial differential equation models have been used extensively over the past two decades to describe various collective migration phenomena in cell biology and ecology. To understand the behaviour of these models (and…

Numerical Analysis · Mathematics 2025-05-05 Johan Marguet , Raluca Eftimie , Alexei Lozinski