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arXiv quant-ph/0401127quant-phq-bio.NC
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神经网络中的量子计算

Quantum computing in neural networks

P. Gralewicz

摘要:

根据量子理论的统计解释,量子计算机通过将n个量子比特编码为2n pbits(随机二进制变量)来形成一类特殊的概率机器(PM)。这提高了使用PM进行大规模量子计算的可能性,特别是使用具有概率信息处理能力的神经网络。限制自己到一个特定的模型,我们构建和数值研究实现通用量子门的神经电路的性能。还提供了建议的编码方案的生理上的兼容性的讨论。

英文摘要:

According to the statistical interpretation of quantum theory, quantum computers form a distinguished class of probabilistic machines (PMs) by encoding n qubits in 2n pbits (random binary variables). This raises the possibility of a large-scale quantum computing using PMs, especially with neural networks which have the innate capability for probabilistic information processing. Restricting ourselves to a particular model, we construct and numerically examine the performance of neural circuits implementing universal quantum gates. A discussion on the physiological plausibility of proposed coding scheme is also provided.

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。

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