Lawrence Berkeley National Lab, Berkeley, CA, USA.
University of Maryland, College Park, MD, USA.
Sci Rep. 2023 Feb 3;13(1):1986. doi: 10.1038/s41598-023-28317-5.
Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects arise at the nano-scale, these systems are difficult to simulate on classical computers. Quantum computers can efficiently simulate quantum many-body systems, yet current quantum algorithms for calculating thermal properties of these systems incur significant computational costs in that they either prepare the full thermal state on the quantum computer, or they must sample a number of pure states from a distribution that grows with system size. Canonical thermal pure quantum (TPQ) states provide a promising path to estimating thermal properties of quantum materials as they neither require preparation of the full thermal state nor require a growing number of samples with system size. Here, we present an algorithm for preparing canonical TPQ states on quantum computers. We compare three different circuit implementations for the algorithm and demonstrate their capabilities in estimating thermal properties of quantum materials. Due to its increasing accuracy with system size and flexibility in implementation, we anticipate that this method will enable finite temperature explorations of relevant quantum materials on near-term quantum computers.
纳米材料的热性质不仅对深入理解凝聚态系统至关重要,而且对开发应用于科研和工业的新型材料也至关重要。由于量子效应对纳米尺度的系统有重要影响,这些系统很难在经典计算机上进行模拟。量子计算机可以有效地模拟量子多体系统,但目前用于计算这些系统热性质的量子算法在计算成本方面存在很大的问题,因为它们要么在量子计算机上准备完整的热态,要么必须从随系统大小而增长的分布中采样多个纯态。正则热纯量子(TPQ)态为估计量子材料的热性质提供了一条很有前途的途径,因为它们既不需要准备完整的热态,也不需要随系统大小增加采样数量。在这里,我们提出了一种在量子计算机上制备正则 TPQ 态的算法。我们比较了该算法的三种不同电路实现,并展示了它们在估计量子材料热性质方面的能力。由于该方法的精度随系统大小而增加,并且在实现方面具有灵活性,我们预计该方法将使近地量子计算机能够对相关量子材料进行有限温度的探索。