近日，英国赫瑞瓦特大学Petar Tadi?团队研究了量子多体系统的粗粒度自举。相关论文发表在2026年2月23日出版的《高能物理杂志》上。

研究组提出了一种全新的计算框架，将粗粒化技术与自举方法相结合，用于研究量子多体系统。该方法能够高效地计算无限量子自旋链中任何局域可观测量在零温和有限温期望值的严格上下界。这是通过使用张量网络对自举约束（包括正定性、平移不变性、运动方程以及能量-熵平衡不等式）进行粗粒化来实现的。粗粒化技术使人们能够利用比以前更大子系统的约束条件，从而获得比未经粗粒化时更严格的界限。

附：英文原文

Title: Coarse-grained bootstrap of quantum many-body systems

Author: Cho, Minjae, Nancarrow, Colin Oscar, Tadi, Petar, Xin, Yuan, Zheng, Zechuan

Issue&Volume: 2026-02-23

Abstract: We present a new computational framework combining coarse-graining techniques with bootstrap methods to study quantum many-body systems. The method efficiently computes rigorous upper and lower bounds on both zero- and finite-temperature expectation values of any local observables of infinite quantum spin chains. This is achieved by using tensor networks to coarse-grain bootstrap constraints, including positivity, translation invariance, equations of motion, and energy-entropy balance inequalities. Coarse-graining allows access to constraints from significantly larger subsystems than previously possible, yielding tighter bounds compared to those obtained without coarse-graining.

DOI: 10.1007/JHEP02(2026)222

Source: https://link.springer.com/article/10.1007/JHEP02(2026)222