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arXiv 2602.05069quant-phphysics.chem-ph
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近反铁性自由电子结构哈密顿量表示及下界证明

Near-frustration-free electronic structure Hamiltonian representations and lower bound certificates

Google Quantum AI(谷歌量子人工智能);Florida State University(佛罗里达州立大学)

Nicholas C. Rubin, Guang Hao Low, A. Eugene DePrince

AI总结:

本文提出了一种基于SOS层次的电子结构哈密顿量表示方法,通过连接SOS分解与v2RDM理论,实现了对称性约束的严格执行,并验证了其在提高量子算法性能方面的有效性。

摘要:

基于平方和(SOS)层次的哈密顿量表示提供了对基态能量的严格下界,并促进了高效经典和量子模拟算法的设计。本工作提出一个统一框架,将SOS分解与变分二体简正密度矩阵(v2RDM)理论联系起来。我们证明了“加权”SOS假设自然地恢复了v2RDM程序的对偶,使粒子数和自旋等对称性约束能够严格执行。我们为海丁格模型和电子结构哈密顿量提供了显式的SOS构造,从无自旋近似到全秩2展开。我们还强调了与块不变对称性偏移的理论联系。在分子系统和铁硫簇上的数值验证证明了这些近反铁性自由表示的有效性,展示了其在提高谱间隙放大和减少块编码成本方面的应用价值。

英文摘要:

Hamiltonian representations based on the sum-of-squares (SOS) hierarchy provide rigorous lower bounds on ground-state energies and facilitate the design of efficient classical and quantum simulation algorithms. This work presents a unified framework connecting SOS decompositions with variational two-particle reduced density matrix (v2RDM) theory. We demonstrate that the ``weighted'' SOS ansatz naturally recovers the dual of the v2RDM program, enabling the strict enforcement of symmetry constraints such as particle number and spin. We provide explicit SOS constructions for the Hubbard model and electronic structure Hamiltonians, ranging from spin-free approximations to full rank-2 expansions. We also highlight theoretical connections to block-invariant symmetry shifts. Numerical benchmarks on molecular systems and Iron-Sulfur clusters validate these near frustration-free representations, demonstrating their utility in improving spectral gap amplification and reducing block encoding costs in quantum algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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