An adaptive algorithm for quantum circuit simulation
arXiv:1911.12242 · doi:10.1103/PhysRevA.101.042335
Abstract
Efficient simulation of quantum computers is essential for the development and validation of near-term quantum devices and the research on quantum algorithms. Up to date, two main approaches to simulation were in use, based on either full state or single amplitude evaluation. We propose an algorithm that efficiently interpolates between these two possibilities. Our approach elucidates the connection between quantum circuit simulation and partial evaluation of expressions in tensor algebra.
arXiv comment10 pages, 11 figures
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Cited by in corpus (13)
- Contracting Arbitrary Tensor Networks: General Approximate Algorithm and Applications in Graphical Models and Quantum Circuit Simulations
- Sampling Frequency Thresholds for Quantum Advantage of Quantum Approximate Optimization Algorithm
- Quantum Divide and Compute: Exploring The Effect of Different Noise Sources
- Fast Simulation of High-Depth QAOA Circuits
- Performance Evaluation and Acceleration of the QTensor Quantum Circuit Simulator on GPUs
- Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation
- Tensor networks for quantum computing
- Embedding Learning in Hybrid Quantum-Classical Neural Networks
- Estimating the randomness of quantum circuit ensembles up to 50 qubits
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- Importance of Diagonal Gates in Tensor Network Simulations
- On the Optimal Linear Contraction Order of Tree Tensor Networks, and Beyond
- A Synthesis of Hidden Subgroup Quantum Algorithms and Quantum Chemical Dynamics