2021/06/29 by Danylo Lykov, Yuri Alexeev, Lykov, Danylo +1 · 1 citation
Computer Science · Physics and Astronomy · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Physical sciences #Parallel Computing and Optimization Techniques #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #cs.DS #quant-ph
paper · pdf · doi:10.48550/arxiv.2106.15740
arxiv created 2021/06/29 · openalex publication_date 2021/06/29 · arxiv updated 2021/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
In this work we present two techniques that tremendously increase the performance of tensor-network based quantum circuit simulations. The techniques are implemented in the QTensor package and benchmarked using Quantum Approximate Optimization Algorithm (QAOA) circuits. The techniques allowed us to increase the depth and size of QAOA circuits that can be simulated. In particular, we increased the QAOA depth from 2 to 5 and the size of a QAOA circuit from 180 to 244 qubits. Moreover, we increased the speed of simulations by up to 10 million times. Our work provides important insights into how various techniques can dramatically speed up the simulations of circuits.