量子类比建模：一种预测语言行为的通用量子计算算法
Quantum Analogical Modeling: A General Quantum Computing Algorithm for Predicting Language Behavior
摘要：
本文提出了一个通用的量子算法，可以应用于任何经典的计算机程序。每个计算步骤都使用可逆算子来编写，但这些算子仍然是经典的，因为量子比特的值只有0和1。这种对量子态的经典限制允许复制量子位，这是进行一般经典计算的必要要求。量子算法的并行处理由于量子比特的叠加而得以进行，这是该算法严格量子力学的唯一方面。对系统的测量使叠加态崩溃，只留下一个可以观察到的状态。在大多数情况下，由于测量而造成的信息损失是不可接受的。但是，语言学动机的类比建模（AM）理论提出，语言行为的概率性质可以准确地建模在所有可能的上下文（称为超上下文）的同时分析，提供一个选择一个单一的超上下文从那些超上下文是同质的行为（即，超上下文，不允许增加的不确定性）。每个同质超背景的振幅与其出现频率成正比，因此选择一个特定超背景来预测系统行为的概率与其频率的平方成正比。
英文摘要：
This paper proposes a general quantum algorithm that can be applied to any classical computer program. Each computational step is written using reversible operators, but the operators remain classical in that the qubits take on values of only zero and one. This classical restriction on the quantum states allows the copying of qubits, a necessary requirement for doing general classical computation. Parallel processing of the quantum algorithm proceeds because of the superpositioning of qubits, the only aspect of the algorithm that is strictly quantum mechanical. Measurement of the system collapses the superposition, leaving only one state that can be observed. In most instances, the loss of information as a result of measurement would be unacceptable. But the linguistically motivated theory of Analogical Modeling (AM) proposes that the probabilistic nature of language behavior can be accurately modeled in terms of the simultaneous analysis of all possible contexts (referred to as supracontexts) providing one selects a single supracontext from those supracontexts that are homogeneous in behavior (namely, supracontexts that allow no increase in uncertainty). The amplitude for each homogeneous supracontext is proportional to its frequency of occurrence, with the result that the probability of selecting one particular supracontext to predict the behavior of the system is proportional to the square of its frequency.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
