PIRSA:24010097

Video URL

https://pirsa.org/24010097

Effect of non-unital noise on random circuit sampling

Kuroiwa, K. (2024). Effect of non-unital noise on random circuit sampling. Perimeter Institute for Theoretical Physics. https://pirsa.org/24010097

Kuroiwa, Kohdai. Effect of non-unital noise on random circuit sampling. Perimeter Institute for Theoretical Physics, Jan. 29, 2024, https://pirsa.org/24010097 

          @misc{ scivideos_PIRSA:24010097,
            doi = {10.48660/24010097},
            url = {https://pirsa.org/24010097},
            author = {Kuroiwa, Kohdai},
            keywords = {Other Physics},
            language = {en},
            title = {Effect of non-unital noise on random circuit sampling},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2024},
            month = {jan},
            note = {PIRSA:24010097 see, \url{https://scivideos.org/pirsa/24010097}}
          }

Kohdai Kuroiwa Perimeter Institute for Theoretical Physics

Talk numberPIRSA:24010097
DOI10.48660/24010097
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

In this work, drawing inspiration from the type of noise present in real hardware, we study the output distribution of random quantum circuits under practical non-unital noise sources with constant noise rates. We show that even in the presence of unital sources like the depolarizing channel, the distribution, under the combined noise
channel, never resembles a maximally entropic distribution at any depth. To show this, we prove that the output distribution of such circuits never anticoncentrates — meaning it is never too "flat" — regardless of the depth of the circuit. This is in stark contrast to the behavior of noiseless random quantum circuits or those with only unital noise, both
of which anticoncentrate at sufficiently large depths. As consequences, our results have interesting algorithmic implications on both the hardness and easiness of noisy random circuit sampling, since anticoncentration is a critical property exploited by both state-of-the-art classical hardness and easiness results. This talk is based on arXiv:2306.16659.

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