Algorithmic Quantum Simulations of Quantum Thermodynamics

• URL: http://arxiv.org/abs/2511.22898v1
• Date: Fri, 28 Nov 2025 06:06:23 GMT
• Title: Algorithmic Quantum Simulations of Quantum Thermodynamics
• Authors: Yangsen Ye, Jue Nan, Dong Chen, Torsten V. Zache, Qingling Zhu, Yiming Zhang, Yuan Li, Xiawei Chen, Chong Ying, Chen Zha, Sirui Cao, Shaowei Li, Shaojun Guo, Haoran Qian, Hao Rong, Yulin Wu, Kai Yan, Feifan Su, Hui Deng, Yu Xu, Jin Lin, Ming Gong, Fusheng Chen, Gang Wu, Yong-Heng Huo, Chao-Yang Lu, Cheng-Zhi Peng, Xiaobo Zhu, Xiaopeng Li, Jian-Wei Pan,
• Abstract summary: We develop protocols for simulating quantum thermodynamics on quantum hardware through quantum kernel function expansion (QKFE)<n>These protocols are demonstrated by simulating transverse field Ising and XY models with superconducting qubits.<n>Our approach provides a general framework for computing thermodynamic potentials on programmable quantum devices.
• Score: 22.18998680528792
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Characterizing quantum phases-of-matter at finite-temperature is essential for understanding complex materials and large-scale thermodynamic phenomena. Here, we develop algorithmic protocols for simulating quantum thermodynamics on quantum hardware through quantum kernel function expansion (QKFE), producing the free energy as an analytic function of temperature with uniform convergence. These protocols are demonstrated by simulating transverse field Ising and XY models with superconducting qubits. In both analogue and digital implementations of the QKFE algorithms, we exhibit quantitative agreement of our quantum simulation experiments with the exact results. Our approach provides a general framework for computing thermodynamic potentials on programmable quantum devices, granting access to key thermodynamic properties such as entropy, heat capacity and criticality, with far-reaching implications for material design and drug development.

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