no code implementations • 4 Mar 2024 • Kevin Shen, Bernhard Jobst, Elvira Shishenina, Frank Pollmann
The potential impact of quantum machine learning algorithms on industrial applications remains an exciting open question.
no code implementations • 26 Jun 2023 • Sheng-Hsuan Lin, Olivier Kuijpers, Sebastian Peterhansl, Frank Pollmann
Tensor networks have recently found applications in machine learning for both supervised learning and unsupervised learning.
1 code implementation • 21 Apr 2021 • Sheng-Hsuan Lin, Frank Pollmann
Simulating quantum many-body dynamics on classical computers is a challenging problem due to the exponential growth of the Hilbert space.
no code implementations • 15 Dec 2020 • Umberto Borla, Bhilahari Jeevanesan, Frank Pollmann, Sergej Moroz
In particular limits the model reduces to (i) pure $\mathbb{Z}_2$ even and odd gauge theories, (ii) free fermions in a static background of deconfined $\mathbb{Z}_2$ gauge fields, (iii) the kinetic Rokhsar-Kivelson quantum dimer model at a generic dimer filling.
Strongly Correlated Electrons Quantum Gases Superconductivity High Energy Physics - Lattice High Energy Physics - Theory
no code implementations • 24 Aug 2020 • Sheng-Hsuan Lin, Rohit Dilip, Andrew G. Green, Adam Smith, Frank Pollmann
The current generation of noisy intermediate scale quantum computers introduces new opportunities to study quantum many-body systems.
Quantum Physics Mesoscale and Nanoscale Physics Strongly Correlated Electrons
no code implementations • 1 Apr 2020 • Johannes Feldmeier, Pablo Sala, Giuseppe de Tomasi, Frank Pollmann, Michael Knap
The presence of global conserved quantities in interacting systems generically leads to diffusive transport at late times.
Strongly Correlated Electrons Quantum Physics
no code implementations • 11 Oct 2019 • Adam Smith, Bernhard Jobst, Andrew G. Green, Frank Pollmann
The simulation that we perform is easily scalable and is a practical demonstration of the utility of near-term quantum computers for the study of quantum phases of matter and their transitions.
Strongly Correlated Electrons Mesoscale and Nanoscale Physics Quantum Physics
no code implementations • 2 Aug 2019 • Leon Schoonderwoerd, Frank Pollmann, Gunnar Möller
As a concrete example, we numerically explore the physics at flux density $n_{\phi} = 3/11$, where we show evidence that a direct transition occurs between a CI and a $\nu = 1/3$ Laughlin state, which we characterise in terms of its critical, topological and entanglement properties.
Strongly Correlated Electrons Mesoscale and Nanoscale Physics
1 code implementation • 14 Jun 2019 • Adam Smith, M. S. Kim, Frank Pollmann, Johannes Knolle
Universal quantum computers are potentially an ideal setting for simulating many-body quantum dynamics that is out of reach for classical digital computers.
Quantum Physics Mesoscale and Nanoscale Physics Strongly Correlated Electrons
no code implementations • 13 Feb 2019 • Michael P. Zaletel, Frank Pollmann
Tensor network states (TNS) are a promising but numerically challenging tool for simulating two-dimensional (2D) quantum many-body problems.
Strongly Correlated Electrons Quantum Physics
2 code implementations • 30 Apr 2018 • Johannes Hauschild, Frank Pollmann
Tensor product state (TPS) based methods are powerful tools to efficiently simulate quantum many-body systems in and out of equilibrium.
Strongly Correlated Electrons
1 code implementation • 26 Dec 2012 • Jonas A. Kjäll, Michael P. Zaletel, Roger S. K. Mong, Jens H. Bardarson, Frank Pollmann
We study the ground state phase diagram of the quantum spin-2 XXZ chain in the presence of on-site anisotropy using a matrix-product state based infinite system density-matrix-renormalization-group (iDMRG) algorithm.
Strongly Correlated Electrons