Bach Bao Gia, Kundu Akash, Acharya Tamal, Sarkar Aritra
Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City 70000, Vietnam.
Quantum Intelligence Research Team, Department of Quantum & Computer Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.
Entropy (Basel). 2023 May 7;25(5):763. doi: 10.3390/e25050763.
This work applies concepts from algorithmic probability to Boolean and quantum combinatorial logic circuits. The relations among the statistical, algorithmic, computational, and circuit complexities of states are reviewed. Thereafter, the probability of states in the circuit model of computation is defined. Classical and quantum gate sets are compared to select some characteristic sets. The reachability and expressibility in a space-time-bounded setting for these gate sets are enumerated and visualized. These results are studied in terms of computational resources, universality, and quantum behavior. The article suggests how applications like geometric quantum machine learning, novel quantum algorithm synthesis, and quantum artificial general intelligence can benefit by studying circuit probabilities.
这项工作将算法概率的概念应用于布尔和量子组合逻辑电路。回顾了状态的统计、算法、计算和电路复杂度之间的关系。此后，定义了计算电路模型中状态的概率。比较了经典和量子门集以选择一些特征集。列举并可视化了这些门集在时空受限设置下的可达性和可表达性。从计算资源、通用性和量子行为方面研究了这些结果。本文提出，通过研究电路概率，几何量子机器学习、新型量子算法合成和量子通用人工智能等应用如何能够从中受益。
