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用拉马努金机生成基本常数的猜想。

Generating conjectures on fundamental constants with the Ramanujan Machine.

机构信息

Technion-Israel Institute of Technology, Haifa, Israel.

The Technion Harry and Lou Stern Family Science and Technology Youth Center, Pre-University Education, Haifa, Israel.

出版信息

Nature. 2021 Feb;590(7844):67-73. doi: 10.1038/s41586-021-03229-4. Epub 2021 Feb 3.

Abstract

Fundamental mathematical constants such as e and π are ubiquitous in diverse fields of science, from abstract mathematics and geometry to physics, biology and chemistry. Nevertheless, for centuries new mathematical formulas relating fundamental constants have been scarce and usually discovered sporadically. Such discoveries are often considered an act of mathematical ingenuity or profound intuition by great mathematicians such as Gauss and Ramanujan. Here we propose a systematic approach that leverages algorithms to discover mathematical formulas for fundamental constants and helps to reveal the underlying structure of the constants. We call this approach 'the Ramanujan Machine'. Our algorithms find dozens of well known formulas as well as previously unknown ones, such as continued fraction representations of π, e, Catalan's constant, and values of the Riemann zeta function. Several conjectures found by our algorithms were (in retrospect) simple to prove, whereas others remain as yet unproved. We present two algorithms that proved useful in finding conjectures: a variant of the meet-in-the-middle algorithm and a gradient descent optimization algorithm tailored to the recurrent structure of continued fractions. Both algorithms are based on matching numerical values; consequently, they conjecture formulas without providing proofs or requiring prior knowledge of the underlying mathematical structure, making this methodology complementary to automated theorem proving. Our approach is especially attractive when applied to discover formulas for fundamental constants for which no mathematical structure is known, because it reverses the conventional usage of sequential logic in formal proofs. Instead, our work supports a different conceptual framework for research: computer algorithms use numerical data to unveil mathematical structures, thus trying to replace the mathematical intuition of great mathematicians and providing leads to further mathematical research.

摘要

基本数学常数,如 e 和 π,广泛存在于从抽象数学和几何到物理、生物和化学等各个科学领域。然而,几个世纪以来,新的与基本常数相关的数学公式一直很少见,通常是零星发现的。这些发现通常被认为是高斯和拉马努金等伟大数学家的数学智慧或深刻直觉的体现。在这里,我们提出了一种系统的方法,利用算法来发现基本常数的数学公式,并有助于揭示常数的潜在结构。我们称这种方法为“拉马努金机”。我们的算法发现了几十个著名的公式,以及以前未知的公式,如π、e、Catalan 常数和 Riemann ζ 函数的值的连分数表示。我们的算法发现的几个猜想在回顾时很容易证明,而其他的仍然没有证明。我们提出了两种在寻找猜想时很有用的算法:一种是“中间相遇”算法的变体,另一种是针对连分数递归结构的梯度下降优化算法。这两种算法都是基于数值匹配的;因此,它们在没有提供证明或不需要先验的基本数学结构知识的情况下提出公式,使这种方法与自动化定理证明互补。当应用于发现未知数学结构的基本常数公式时,我们的方法特别有吸引力,因为它颠覆了形式证明中顺序逻辑的传统用法。相反,我们的工作支持了一种不同的研究概念框架:计算机算法使用数值数据来揭示数学结构,从而试图取代伟大数学家的数学直觉,并为进一步的数学研究提供线索。

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