Suppression of quantum coherence: Noise effect

Lee, C F, Johnson, N F, Rodríguez, F +1 more

We discuss the effect of correlated noise on the robustness of quantum coherent phenomena. First we consider a simple, toy model to illustrate the effect of such correlations on the decoherence process. Then we show how decoherence rates can be suppressed using a Parrondo-like effect. Finally, we report the results of many-body calculations in which an experimentally-measurable quantum coherence phenomenon is significantly enhanced by non-Markovian dynamics arising from the noise source.

CHIU FAN LEE, NEIL F. JOHNSON, FERNEY RODRIGUEZ +1 more

We discuss the effect of correlated noise on the robustness of quantum coherent phenomena. First we consider a simple, toy model to illustrate the effect of such correlations on the decoherence process. Then we show how decoherence rates can be suppressed using a Parrondo-like effect. Finally, we report the results of many-body calculations in which an experimentally-measurable quantum coherence phenomenon is significantly enhanced by non-Markovian dynamics arising from the noise source.

Yiyu Zhou, Dmitri V. Voronine, Marlan O. Scully

吉隆 谷村

Daimon Shunsuke

Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise causes fatal errors and messes up the calculation. In order to maximize the functionality of quantum computers, it is essential to design quantum circuits that suppress the effects of noise. In this research, we developed a deep reinforcement learning AI that searches for quantum circuits that are less affected by noise. Using the developed AI, we succeeded in generating quantum circuits that achieve quantum Fourier transform while suppressing the effects of noise.