囚禁离子量子信息处理中信息擦除与能量耗散关系的研究

在信息擦除等量子操作中，能量消耗不可避免，如何量化处理能量消耗与信息擦除之间的关系是量子信息处理中的一个重要物理问题。囚禁离子体系作为量子信息处理的优良实验系统受到广泛关注，然而其自身的热力学性质却鲜有人关注，特别是与信息擦除等相关的最小能耗理论。本项目拟通过结合量子热力学方法和开放系统理论来分析囚禁离子量子信息处理中的能量消耗物理机制，建立该体系的第一个量子热力学模型，探究信息处理中的最低能耗策略。本项目拟开展以下几个方面的研究：1）研究囚禁离子体系内量子操作过程中熵、信息以及能量等物理量之间的转换关系，建立量子热力学模型。2）结合离子实验，研究信息擦除与最小能耗关系。3）研究开放系统下系统的量子热力学性质。本项目着眼于理论结合实验，将深化对囚禁离子体系内量子操作热力学性质的理解与认识，有助于发展新的优化信息处理方案，为降低大规模量子信息处理中的能量消耗提供理论参考。

When erasing quantum information, one has to pay energy. As a result, how to quantify the relation between energy consumption and information erasure becomes an important physical problem in quantum information processing. As an excellent experimental system for quantum information processing, the trapped ion system has attracted extensive attention. However, its thermodynamic properties have received little attention, especially the theory of minimum energy consumption, such as the information erasure. By combining the quantum thermodynamics method and the open system theory, this project intends to analyze the physical mechanism of energy consumption in the quantum information processing for the trapped ion system and establishes the first quantum thermodynamics model of the system, and studies the minimum energy consumption scheme in the information processing. The project mainly carries out following issues: 1) studying the interconversion relationship among entropy, information, quantum correlation, energy and other physical quantities in quantum operations for the trapped ion system and developing quantum thermodynamic model; 2) Combined with the ion experiment, study the relation between information erasing and minimum energy consumption; 3) studying the quantum thermodynamic properties of trapped-ion system in the open system condition. Combined with experiments, the project will help us deepen the understanding and cognition of thermodynamic properties of quantum operations within the trapped-ion system, develop new optimized information processing scheme, and provide a theoretical reference for reducing energy consumption in the large-scale quantum information processing system.