量子计算与图像识别
Quantum Computations and Images Recognition
摘要：
量子并行性的应用通常与考虑具有巨维态空间的量子系统有关。n量子比特寄存器可以用具有2^n个分量的复向量来描述（它属于量子比特空间的n次张量幂）。例如，对于量子计算机的数字因式分解算法，对于密码学的一些实际应用，n可以是大约几百。进一步描述的应用使用了量子系统的一些其他性质，并且它们不需要如此巨大的状态数。术语“图像识别”在这里用于一些广泛类别的问题。例如，我们有一组一些对象V_i和“似然”函数：F（V，W）< F（V，V）= 1如果我们有一些“噪声”或“失真”的图像W，我们可以说W的识别是V_i，如果F（W，V_i）对于一些V_i接近1。
英文摘要：
The using of quantum parallelism is often connected with consideration of quantum system with huge dimension of space of states. The n-qubit register can be described by complex vector with 2^n components (it belongs to n'th tensor power of qubit spaces). For example, for algorithm of factorization of numbers by quantum computer n can be about a few hundreds for some realistic applications for cryptography. The applications described further are used some other properties of quantum systems and they do not demand such huge number of states. The term "images recognition" is used here for some broad class of problems. For example, we have a set of some objects V_i and function of "likelihood": F(V,W) < F(V,V) = 1 If we have some "noisy" or "distorted" image W, we can say that recognition of W is V_i, if F(W,V_i) is near 1 for some V_i.
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。
