Tensor Network Quantum Simulator With Step-Dependent Parallelization
arXiv:2012.02430
Abstract
In this work, we present a new large-scale quantum circuit simulator. It is based on the tensor network contraction technique to represent quantum circuits. We propose a novel parallelization algorithm based on \stepslice . In this paper, we push the requirement on the size of a quantum computer that will be needed to demonstrate the advantage of quantum computation with Quantum Approximate Optimization Algorithm (QAOA). We computed 210 qubit QAOA circuits with 1,785 gates on 1,024 nodes of the the Cray XC 40 supercomputer Theta. To the best of our knowledge, this constitutes the largest QAOA quantum circuit simulations reported to this date.
Cited by in corpus (13)
- Quantum computing for finance
- MQT Bench: Benchmarking Software and Design Automation Tools for Quantum Computing
- Parameter Transfer for Quantum Approximate Optimization of Weighted MaxCut
- Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
- Classical symmetries and the Quantum Approximate Optimization Algorithm
- Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction
- Exploiting Symmetry Reduces the Cost of Training QAOA
- Error Mitigation for Deep Quantum Optimization Circuits by Leveraging Problem Symmetries
- Numerical Evidence for Exponential Speed-up of QAOA over Unstructured Search for Approximate Constrained Optimization
- Performance Evaluation and Acceleration of the QTensor Quantum Circuit Simulator on GPUs
- Simulation Paths for Quantum Circuit Simulation with Decision Diagrams
- Embedding Learning in Hybrid Quantum-Classical Neural Networks
- Estimating the randomness of quantum circuit ensembles up to 50 qubits