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High-Concentration Chemical Computing Techniques for Solving Hard-To-Solve Problems, and Their Relation to Numerical Optimization, Neural Computing, Reasoning Under Uncertainty, and Freedom Of Choice

机译:解决难以解决问题的高浓度化学计算技术及其与数值优化,神经计算,不确定性推理和自由选择的关系

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摘要

Chemical computing -- using chemical reactions to perform computations -- is a promising way to solve computationally intensive problems. Chemical computing is promising because it has the potential of using up to 10^{23} molecules as processors working in parallel -- and thus, has a potential of an enormous speedup. Unfortunately, for hard-to-solve (NP-complete) problems a natural chemical computing approach for solving them is exponentially slow. In this chapter, we show that the corresponding computations can become significantly faster if we use very-high-concentration chemical reactions, concentrations at which the usual equations of chemical kinetics no longer apply. We also show that the resulting method is related to numerical optimization, neural computing, reasoning under uncertainty, and freedom of choice.
机译:化学计算-使用化学反应执行计算-是解决计算密集型问题的有前途的方法。化学计算是有前途的,因为它有可能使用多达10 ^ {23}个分子作为并行工作的处理器-因此,具有巨大的加速潜力。不幸的是,对于难以解决的问题(NP完全问题),自然的化学计算方法以指数级的速度解决。在本章中,我们表明,如果我们使用非常高浓度的化学反应,则相应的计算会变得更快,而在这种浓度下,不再适用常规的化学动力学方程式。我们还表明,所得方法与数值优化,神经计算,不确定性下的推理和选择自由有关。

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