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Simulating groundstate and dynamical quantum phase transitions on a superconducting quantum computer.
Dborin, James; Wimalaweera, Vinul; Barratt, F; Ostby, Eric; O'Brien, Thomas E; Green, A G.
Affiliation
  • Dborin J; London Centre for Nanotechnology, University College London, Gordon St., London, WC1H 0AH, UK.
  • Wimalaweera V; London Centre for Nanotechnology, University College London, Gordon St., London, WC1H 0AH, UK.
  • Barratt F; Department of Physics, University of Massachusetts, Amherst, MA, 01003, USA.
  • Ostby E; Google Quantum AI, 80636, Munich, Germany.
  • O'Brien TE; Google Quantum AI, 80636, Munich, Germany.
  • Green AG; London Centre for Nanotechnology, University College London, Gordon St., London, WC1H 0AH, UK. andrew.green@ucl.ac.uk.
Nat Commun ; 13(1): 5977, 2022 Oct 10.
Article in En | MEDLINE | ID: mdl-36216839
ABSTRACT
The phenomena of quantum criticality underlie many novel collective phenomena found in condensed matter systems. They present a challenge for classical and quantum simulation, in part because of diverging correlation lengths and consequently strong finite-size effects. Tensor network techniques that work directly in the thermodynamic limit can negotiate some of these difficulties. Here, we optimise a translationally invariant, sequential quantum circuit on a superconducting quantum device to simulate the groundstate of the quantum Ising model through its quantum critical point. We further demonstrate how the dynamical quantum critical point found in quenches of this model across its quantum critical point can be simulated. Our approach avoids finite-size scaling effects by using sequential quantum circuits inspired by infinite matrix product states. We provide efficient circuits and a variety of error mitigation strategies to implement, optimise and time-evolve these states.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2022 Document type: Article Affiliation country: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2022 Document type: Article Affiliation country: Reino Unido