Scalable Quantum Monte Carlo Method for Polariton Chemistry via Mixed Block Sparsity and Tensor Hypercontraction Method
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| Format: | Preprint |
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2025
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| _version_ | 1866918318448836608 |
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| author | Zhang, Yu |
| author_facet | Zhang, Yu |
| contents | We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of Cholesky decomposition (CD) of electron repulsion integrals in molecular ensembles and employs tensor hypercontraction (THC) to efficiently compress low-rank Cholesky blocks. By representing the Cholesky vectors in a mixed format, keeping high-rank blocks in block-sparse form and compressing low-rank blocks with THC, we reduce the scaling of exchange-energy evaluation from quartic to robust cubic in the number of molecular orbitals, while lowering memory from cubic toward quadratic. Benchmark analyses on one-, two-, and three-dimensional molecular ensembles (up to ~1,200 orbitals) show that: a) the number of nonzeros in Cholesky tensors grows linearly with system size across dimensions; b) the average numerical rank increases sublinearly and does not saturate at these sizes; and (c) rank heterogeneity-some blocks nearly full rank and many low rank, naturally motivating the proposed mixed block sparsity and THC scheme for efficient calculation of exchange energy. We demonstrate that the mixed scheme yields cubic CPU-time scaling with favorable prefactors and preserves AFQMC accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11634 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scalable Quantum Monte Carlo Method for Polariton Chemistry via Mixed Block Sparsity and Tensor Hypercontraction Method Zhang, Yu Chemical Physics Quantum Physics We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of Cholesky decomposition (CD) of electron repulsion integrals in molecular ensembles and employs tensor hypercontraction (THC) to efficiently compress low-rank Cholesky blocks. By representing the Cholesky vectors in a mixed format, keeping high-rank blocks in block-sparse form and compressing low-rank blocks with THC, we reduce the scaling of exchange-energy evaluation from quartic to robust cubic in the number of molecular orbitals, while lowering memory from cubic toward quadratic. Benchmark analyses on one-, two-, and three-dimensional molecular ensembles (up to ~1,200 orbitals) show that: a) the number of nonzeros in Cholesky tensors grows linearly with system size across dimensions; b) the average numerical rank increases sublinearly and does not saturate at these sizes; and (c) rank heterogeneity-some blocks nearly full rank and many low rank, naturally motivating the proposed mixed block sparsity and THC scheme for efficient calculation of exchange energy. We demonstrate that the mixed scheme yields cubic CPU-time scaling with favorable prefactors and preserves AFQMC accuracy. |
| title | Scalable Quantum Monte Carlo Method for Polariton Chemistry via Mixed Block Sparsity and Tensor Hypercontraction Method |
| topic | Chemical Physics Quantum Physics |
| url | https://arxiv.org/abs/2510.11634 |