论文标题
分区功能估计：量子和量子启发算法
Partition Function Estimation: Quantum and Quantum-Inspired Algorithms
论文作者
论文摘要
我们提出了两种算法，一种量子和一种经典，用于估计量子自旋汉密尔顿人的分区功能。前者是DQC1（具有一个干净量子考虑的确定性量子计算）算法，第一个用于复杂温度。对于实际温度，后者实现了与最先进的DQC1算法相当的性能[Chowdhury等。物理。修订版A 103，032422（2021）]。我们的这两种算法都将汉密尔顿分解为线性组合的输入。我们表明，对于给定的哈密顿人来说，这种分解为DQC1 hard，为估计分区功能的硬度提供了新的见解。
We present two algorithms, one quantum and one classical, for estimating partition functions of quantum spin Hamiltonians. The former is a DQC1 (Deterministic quantum computation with one clean qubit) algorithm, and the first such for complex temperatures. The latter, for real temperatures, achieves performance comparable to a state-of-the-art DQC1 algorithm [Chowdhury et al. Phys. Rev. A 103, 032422 (2021)]. Both our algorithms take as input the Hamiltonian decomposed as a linear combination Pauli operators. We show this decomposition to be DQC1-hard for a given Hamiltonian, providing new insight into the hardness of estimating partition functions.
