TY - GEN
T1 - A PEPS Plugin for TNQVM
AU - Chundury, Srikar
AU - Lietz, Justin
AU - Coello Perez, Eduardo Antonio
AU - Shehata, Amir
AU - Suh, In Saeng
AU - Mueller, Frank
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This work introduces an extension to the Tensor Network Quantum Virtual Machine (TNQVM) tool, enhancing the existing stack of ExaScale Tensor Network (ExaTN), ExaScale Accelerator (XACC), and TNQVM. It features a new plugin that enables efficient simulation of a Projected Entangled Pair State (PEPS), a 2D tensor network. To improve simulation efficiency for PEPS, we have implemented the snake boundary contraction algorithm. By integrating this capability into the existing stack, we enhance the overall functionality and versatility of the framework. We tested this new PEPS topology for a simple GHZ bell-pair generation quantum circuit and saw that its runtime is very close to that of the MPS topology. We estimate that the real potential of the PEPS topology becomes discernible when quantum circuits with multidimensional entanglement are simulated using tensor networks. In such cases, 1D tensor networks fail to represent or contract them efficiently.
AB - This work introduces an extension to the Tensor Network Quantum Virtual Machine (TNQVM) tool, enhancing the existing stack of ExaScale Tensor Network (ExaTN), ExaScale Accelerator (XACC), and TNQVM. It features a new plugin that enables efficient simulation of a Projected Entangled Pair State (PEPS), a 2D tensor network. To improve simulation efficiency for PEPS, we have implemented the snake boundary contraction algorithm. By integrating this capability into the existing stack, we enhance the overall functionality and versatility of the framework. We tested this new PEPS topology for a simple GHZ bell-pair generation quantum circuit and saw that its runtime is very close to that of the MPS topology. We estimate that the real potential of the PEPS topology becomes discernible when quantum circuits with multidimensional entanglement are simulated using tensor networks. In such cases, 1D tensor networks fail to represent or contract them efficiently.
KW - Pro-jected Entangled Pair State
KW - Quantum Circuit Simulation
KW - Quantum Computing
KW - Quantum Software En-gineering
KW - Tensor Networks
UR - http://www.scopus.com/inward/record.url?scp=85180010993&partnerID=8YFLogxK
U2 - 10.1109/QCE57702.2023.10293
DO - 10.1109/QCE57702.2023.10293
M3 - Conference contribution
AN - SCOPUS:85180010993
T3 - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
SP - 383
EP - 384
BT - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
A2 - Muller, Hausi
A2 - Alexev, Yuri
A2 - Delgado, Andrea
A2 - Byrd, Greg
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Quantum Computing and Engineering, QCE 2023
Y2 - 17 September 2023 through 22 September 2023
ER -