数学不止于严谨与证明

Terence Tao 2007-05-06

数学不止于严谨与证明

每个主要银河文明的历史都倾向于经历三个截然不同且可识别的阶段:生存阶段、探究阶段和精致阶段,也就是所谓的”如何”、“为何”和”何处”阶段。例如,第一阶段以”我们如何吃饭?“为特征,第二阶段以”我们为何吃饭?“为特征,第三阶段以”我们在哪里吃午餐?“为特征。

— 道格拉斯·亚当斯,《银河系漫游指南》

我们可以大致将数学教育分为三个阶段:

“前严谨”阶段

在这个阶段,数学以非正式、直观的方式教授,基于例子、模糊概念和粗略说明。(例如,微积分通常首先通过斜率、面积、变化率等概念引入。)重点更多在于计算而非理论。这个阶段通常持续到本科早期。

“严谨”阶段

在这个阶段,人们被教导要”正确”地做数学,需要以更加精确和形式化的方式工作和思考(例如,到处使用ε和δ重新学习微积分)。重点现在主要在理论上;人们期望能够舒适地操作抽象的数学对象,而不过多关注这些对象实际上”意味着”什么。这个阶段通常占据本科后期和研究生早期。

“后严谨”阶段

在这个阶段,人们已经对自己所选领域的所有严谨基础感到舒适,现在准备重新审视和完善自己在该主题上的前严谨直觉,但这次直觉得到了严谨理论的坚实支撑。(例如,在这个阶段,人们能够通过使用与标量微积分的类比,或者非正式和半严谨地使用无穷小、大O符号等,快速准确地执行向量微积分中的计算,并能够在需要时将所有这些计算转换为严谨的论证。)重点现在在于应用、直觉和”大局观”。这个阶段通常占据研究生后期及以后。

从第一阶段到第二阶段的转变众所周知是相当痛苦的,可怕的”证明类问题”是许多数学本科生的祸根。(另见”数学不止于成绩、考试和方法”。)但从第二阶段到第三阶段的转变同样重要,不应被遗忘。

当然,知道如何严谨思考至关重要,因为这给了你避免许多常见错误和消除许多误解的纪律。不幸的是,这有一个意想不到的后果,即”更模糊”或”直观”的思考(如启发式推理、从例子中明智地推断,或与其他背景如物理学的类比)被贬低为”不严谨”。很多时候,人们最终丢弃了最初的直觉,只能以形式化水平处理数学,从而在数学教育的第二阶段停滞不前。(除此之外,这会影响阅读数学论文的能力;当遇到论文中即使是一个打字错误或歧义时,过于字面的思维模式可能导致”编译错误”。)

严谨的目的不是摧毁所有直觉;相反,它应该用来摧毁坏的直觉,同时澄清和提升好的直觉。只有结合严谨的形式主义和良好的直觉,才能处理复杂的数学问题;需要前者来正确处理细节,需要后者来正确处理大局。缺少其中任何一个,你都会在黑暗中摸索很长时间(这可能具有教育意义,但效率极低)。所以一旦你完全适应了严谨的数学思维,你应该重新审视自己在该主题上的直觉,并使用新的思维技能来测试和完善这些直觉,而不是丢弃它们。一种方法是问自己愚蠢的问题;另一种是重新学习你的领域

要达到的理想状态是,每个启发式论证自然暗示其严谨对应物,反之亦然。然后你将能够同时使用大脑的两个半球来处理数学问题——也就是说,就像你处理”现实生活”中问题的方式一样。

另见:


后来补充: 或许值得注意的是,处于上述数学发展所有三个阶段的数学家仍然可能在他们的数学写作中犯形式错误。然而,这些错误的性质往往相当不同,取决于所处的阶段:

  • 处于前严谨发展阶段的数学家经常犯形式错误,因为他们无法理解严谨的数学形式主义实际上如何工作,而是盲目应用形式规则或启发式方法。即使这些错误被明确指出来,这样的数学家通常也很难欣赏和纠正这些错误。

  • 处于严谨发展阶段的数学家仍然可能犯形式错误,因为他们尚未完善自己的形式理解,或者无法执行足够的”合理性检查”来对抗直觉或其他经验法则,以捕捉例如符号错误,或未能正确验证工具中的关键假设。然而,一旦这些错误被指出来,通常可以检测到(并且经常修复)。

  • 处于后严谨发展阶段的数学家并非不会犯错,仍然可能在他们的写作中犯形式错误。但这通常是因为他们不再需要形式主义来进行高水平的数学推理,实际上主要通过直觉进行,然后(可能错误地)翻译成形式数学语言。

这三种错误之间的区别可能导致这样的现象(对于处于数学发展早期阶段的读者来说常常相当令人困惑):后严谨数学家的数学论证在局部包含许多打字错误和其他形式错误,但在全局上相当合理,局部错误传播一段时间后被其他局部错误抵消。(相比之下,当没有坚实直觉检查时,一旦前严谨或严谨数学家在论证中引入错误,错误可能失控传播,直到论证结束时留下完全无意义的内容。)关于此类错误的进一步讨论以及如何阅读论文来弥补它们,请参见这篇文章

我在这个与布雷迪·“数字狂”·哈兰的视频中进一步讨论了这个话题。

There’s more to mathematics than rigour and proofs

The history of every major galactic civilization tends to pass through three distinct and recognizable phases, those of Survival, Inquiry and Sophistication, otherwise known as the How, Why, and Where phases. For instance, the first phase is characterized by the question ‘How can we eat?’, the second by the question ‘Why do we eat?’ and the third by the question, ‘Where shall we have lunch?’

— Douglas Adams, “The Hitchhiker’s Guide to the Galaxy”

One can roughly divide mathematical education into three stages:

The “pre-rigorous” stage

In which mathematics is taught in an informal, intuitive manner, based on examples, fuzzy notions, and hand-waving. (For instance, calculus is usually first introduced in terms of slopes, areas, rates of change, and so forth.) The emphasis is more on computation than on theory. This stage generally lasts until the early undergraduate years.

The “rigorous” stage

In which one is now taught that in order to do maths “properly”, one needs to work and think in a much more precise and formal manner (e.g. re-doing calculus by using epsilons and deltas all over the place). The emphasis is now primarily on theory; and one is expected to be able to comfortably manipulate abstract mathematical objects without focusing too much on what such objects actually “mean”. This stage usually occupies the later undergraduate and early graduate years.

The “post-rigorous” stage

In which one has grown comfortable with all the rigorous foundations of one’s chosen field, and is now ready to revisit and refine one’s pre-rigorous intuition on the subject, but this time with the intuition solidly buttressed by rigorous theory. (For instance, in this stage one would be able to quickly and accurately perform computations in vector calculus by using analogies with scalar calculus, or informal and semi-rigorous use of infinitesimals, big-O notation, and so forth, and be able to convert all such calculations into a rigorous argument whenever required.) The emphasis is now on applications, intuition, and the “big picture”. This stage usually occupies the late graduate years and beyond.

The transition from the first stage to the second is well known to be rather traumatic, with the dreaded “proof-type questions” being the bane of many a maths undergraduate. (See also “There’s more to maths than grades and exams and methods”.) But the transition from the second to the third is equally important, and should not be forgotten.

It is of course vitally important that you know how to think rigorously, as this gives you the discipline to avoid many common errors and purge many misconceptions. Unfortunately, this has the unintended consequence that “fuzzier” or “intuitive” thinking (such as heuristic reasoning, judicious extrapolation from examples, or analogies with other contexts such as physics) gets deprecated as “non-rigorous”. All too often, one ends up discarding one’s initial intuition and is only able to process mathematics at a formal level, thus getting stalled at the second stage of one’s mathematical education. (Among other things, this can impact one’s ability to read mathematical papers; an overly literal mindset can lead to “compilation errors” when one encounters even a single typo or ambiguity in such a paper.)

The point of rigour is not to destroy all intuition; instead, it should be used to destroy bad intuition while clarifying and elevating good intuition. It is only with a combination of both rigorous formalism and good intuition that one can tackle complex mathematical problems; one needs the former to correctly deal with the fine details, and the latter to correctly deal with the big picture. Without one or the other, you will spend a lot of time blundering around in the dark (which can be instructive, but is highly inefficient). So once you are fully comfortable with rigorous mathematical thinking, you should revisit your intuitions on the subject and use your new thinking skills to test and refine these intuitions rather than discard them. One way to do this is to ask yourself dumb questions; another is to relearn your field.

The ideal state to reach is when every heuristic argument naturally suggests its rigorous counterpart, and vice versa. Then you will be able to tackle maths problems by using both halves of your brain at once – i.e., the same way you already tackle problems in “real life”.

See also:


Added later: It is perhaps worth noting that mathematicians at all three of the above stages of mathematical development can still make formal mistakes in their mathematical writing. However, the nature of these mistakes tends to be rather different, depending on what stage one is at:

  • Mathematicians at the pre-rigorous stage of development often make formal errors because they are unable to understand how the rigorous mathematical formalism actually works, and are instead applying formal rules or heuristics blindly. It can often be quite difficult for such mathematicians to appreciate and correct these errors even when those errors are explicitly pointed out to them.

  • Mathematicians at the rigorous stage of development can still make formal errors because they have not yet perfected their formal understanding, or are unable to perform enough “sanity checks” against intuition or other rules of thumb to catch, say, a sign error, or a failure to correctly verify a crucial hypothesis in a tool. However, such errors can usually be detected (and often repaired) once they are pointed out to them.

  • Mathematicians at the post-rigorous stage of development are not infallible, and are still capable of making formal errors in their writing. But this is often because they no longer need the formalism in order to perform high-level mathematical reasoning, and are actually proceeding largely through intuition, which is then translated (possibly incorrectly) into formal mathematical language.

The distinction between the three types of errors can lead to the phenomenon (which can often be quite puzzling to readers at earlier stages of mathematical development) of a mathematical argument by a post-rigorous mathematician which locally contains a number of typos and other formal errors, but is globally quite sound, with the local errors propagating for a while before being cancelled out by other local errors. (In contrast, when unchecked by a solid intuition, once an error is introduced in an argument by a pre-rigorous or rigorous mathematician, it is possible for the error to propagate out of control until one is left with complete nonsense at the end of the argument.) See this post for some further discussion of such errors, and how to read papers to compensate for them.

I discuss this topic further in this video with Brady “Numberphile” Haran.