Variational preparation of thermofield double states for SYK models via multi-angle QAOA: sequential angle pruning for circuit reduction
Abstract
Variational preparation of thermofield double (TFD) states can require deep quantum circuits, particularly for interacting many-body systems. Reducing these circuits while retaining high fidelity is therefore crucial for TFD-state preparation on noisy quantum processors. We study this problem by applying the multi-angle quantum approximate optimization algorithm (ma-QAOA) to TFD-state preparation and introducing two top-down sequential angle-pruning algorithms. Starting from the optimized initial ma-QAOA circuit, both algorithms sequentially remove Pauli-string evolutions with small optimized angles and reoptimize the remaining parameters after each removal. We apply these algorithms to Gaussian and binary Sachdev--Ye--Kitaev (SYK) models in both dense and sparse cases. We find that ma-QAOA prepares the target TFD states with high fidelity and that sequential small-angle pruning retains high fidelity while reducing the circuit depth, particularly at low temperature. Moreover, using the post-reoptimization cost in sequential small-angle pruning further improves the fidelity. For the binary sparse N=10 SYK model at β=10, 88.8%--92.1% of the nonlocal Pauli-string evolutions are removed while retaining an average fidelity of approximately 95%. Finally, we propose extensions of the sequential pruning algorithms toward quantum--classical hybrid implementation.
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BibTeX
@misc{ashfaq2026variational,
title = {{Variational preparation of thermofield double states for SYK models via multi-angle QAOA: sequential angle pruning for circuit reduction}},
author = {Haji Muhammad Husnain Ashfaq and Moongul Byun and Keun-Young Kim},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.02793},
eprint = {2609.02793},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.02793},
}
RIS
TY - UNPB
TI - Variational preparation of thermofield double states for SYK models via multi-angle QAOA: sequential angle pruning for circuit reduction
AU - Haji Muhammad Husnain Ashfaq
AU - Moongul Byun
AU - Keun-Young Kim
PY - 2026
DA - 2026/09/02
PB - arXiv
DO - 10.48550/arxiv.2609.02793
UR - https://arxiv.org/abs/2609.02793
AB - Variational preparation of thermofield double (TFD) states can require deep quantum circuits, particularly for interacting many-body systems. Reducing these circuits while retaining high fidelity is therefore crucial for TFD-state preparation on noisy quantum processors. We study this problem by applying the multi-angle quantum approximate optimization algorithm (ma-QAOA) to TFD-state preparation and introducing two top-down sequential angle-pruning algorithms. Starting from the optimized initial ma-QAOA circuit, both algorithms sequentially remove Pauli-string evolutions with small optimized angles and reoptimize the remaining parameters after each removal. We apply these algorithms to Gaussian and binary Sachdev--Ye--Kitaev (SYK) models in both dense and sparse cases. We find that ma-QAOA prepares the target TFD states with high fidelity and that sequential small-angle pruning retains high fidelity while reducing the circuit depth, particularly at low temperature. Moreover, using the post-reoptimization cost in sequential small-angle pruning further improves the fidelity. For the binary sparse N=10 SYK model at β=10, 88.8%--92.1% of the nonlocal Pauli-string evolutions are removed while retaining an average fidelity of approximately 95%. Finally, we propose extensions of the sequential pruning algorithms toward quantum--classical hybrid implementation.
ER -