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YMSC-BIMSA Quantum Information Seminar
YMSC-BIMSA Quantum Information Seminar
Complexity of tensor network simulation for noisy quantum circuits
Complexity of tensor network simulation for noisy quantum circuits
Organizers
Speaker
Time
Friday, June 12, 2026 4:00 PM - 5:30 PM
Venue
Shuangqing-B626
Online
Zoom 230 432 7880
(BIMSA)
Abstract
We aim to rigorously address how local noise affects classical simulability of quantum dynamics benchmarked by tensor-network methods. Using operator entanglement entropy (OEE) as a unifying criterion, we prove the following:
(1) For single-qubit depolarizing noise on 1D local circuits, the existence of whole-trajectory error-bounded matrix product operator (MPO) with $\mathrm{poly}(n)$ complexity. (2) For general single-qubit noise in 1D brickwall circuits, we identify the contractivity conditions for the existence of $\mathrm{poly}(n)$ bond-dimension MPO approximations in average and in the worst case. (3) We further extend above results to higher dimensions, yielding $\mathrm{poly}(n)$ average boundary-bond dimensions for projected entangled pair operators~(PEPO) across every cut. Our results establish a rigorous connection between certain noise models, circuit types, and their classical simulability.
(1) For single-qubit depolarizing noise on 1D local circuits, the existence of whole-trajectory error-bounded matrix product operator (MPO) with $\mathrm{poly}(n)$ complexity. (2) For general single-qubit noise in 1D brickwall circuits, we identify the contractivity conditions for the existence of $\mathrm{poly}(n)$ bond-dimension MPO approximations in average and in the worst case. (3) We further extend above results to higher dimensions, yielding $\mathrm{poly}(n)$ average boundary-bond dimensions for projected entangled pair operators~(PEPO) across every cut. Our results establish a rigorous connection between certain noise models, circuit types, and their classical simulability.
Speaker Intro
Song Cheng is an Associate Professor at the Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA). He holds a PhD in theoretical physics from the Institute of Physics, CAS, and previously served as an Assistant Professor at the Center of Quantum Computing in Pengcheng Laboratory. His current research focuses on investigating the relationship between machine learning, quantum many-body physics, and quantum computing through tensor networks.