Your browser doesn't support javascript.
loading
Mitigating Depolarizing Noise on Quantum Computers with Noise-Estimation Circuits.
Urbanek, Miroslav; Nachman, Benjamin; Pascuzzi, Vincent R; He, Andre; Bauer, Christian W; de Jong, Wibe A.
Afiliação
  • Urbanek M; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
  • Nachman B; Physics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
  • Pascuzzi VR; Physics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
  • He A; Physics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
  • Bauer CW; Physics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
  • de Jong WA; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
Phys Rev Lett ; 127(27): 270502, 2021 Dec 31.
Article em En | MEDLINE | ID: mdl-35061411
ABSTRACT
A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit and then correcting the output of the target circuit using the estimated rate. The method is experimentally validated on a simulation of the Heisenberg model. We find that our approach in combination with readout-error correction, randomized compiling, and zero-noise extrapolation produces close to exact results even for circuits containing hundreds of CNOT gates. We also show analytically that zero-noise extrapolation is improved when it is applied to the output of our method.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Phys Rev Lett Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Phys Rev Lett Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos