Constructing Optimal Contraction Trees for Tensor Network Quantum Circuit Simulation
Author:
Affiliation:
1. University of Delaware,Department of Computer and Information Sciences,Newark,DE,USA
2. Argonne National Laboratory,Computational Science Division,Argonne,IL,USA
3. Univcrsity of California Santa Barbara,Santa Barbara,California,USA
Funder
NSF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9926284/9926287/09926353.pdf?arnumber=9926353
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Minimum Cost Loop Nests for Contraction of a Sparse Tensor with a Tensor Network;Proceedings of the 36th ACM Symposium on Parallelism in Algorithms and Architectures;2024-06-17
2. GPU-acceleration of tensor renormalization with PyTorch using CUDA;Computer Physics Communications;2024-01
3. Tensor shape search for efficient compression of tensorized data and neural networks;Applied Soft Computing;2023-12
4. Alignment between initial state and mixer improves QAOA performance for constrained optimization;npj Quantum Information;2023-11-27
5. Fast Simulation of High-Depth QAOA Circuits;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12
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