Whats so sexy about math Cdric Villani

What is it that French people
do better than all the others?

If you would take polls,

the top three answers might be:

love, wine and whining.

(Laughter)

Maybe.

But let me suggest a fourth one:

mathematics.

Did you know that Paris
has more mathematicians

than any other city in the world?

And more streets
with mathematicians' names, too.

And if you look at the statistics
of the Fields Medal,

often called the Nobel Prize
for mathematics,

and always awarded to mathematicians
below the age of 40,

you will find that France has more
Fields medalists per inhabitant

than any other country.

What is it that we find so sexy in math?

After all, it seems to be
dull and abstract,

just numbers and computations
and rules to apply.

Mathematics may be abstract,

but it’s not dull

and it’s not about computing.

It is about reasoning

and proving our core activity.

It is about imagination,

the talent which we most praise.

It is about finding the truth.

There’s nothing like the feeling
which invades you

when after months of hard thinking,

you finally understand the right
reasoning to solve your problem.

The great mathematician
André Weil likened this –

no kidding –

to sexual pleasure.

But noted that this feeling
can last for hours, or even days.

The reward may be big.

Hidden mathematical truths
permeate our whole physical world.

They are inaccessible to our senses

but can be seen
through mathematical lenses.

Close your eyes for moment

and think of what is occurring
right now around you.

Invisible particles from the air
around are bumping on you

by the billions and billions
at each second,

all in complete chaos.

And still,

their statistics can be accurately
predicted by mathematical physics.

And open your eyes now

to the statistics of the velocities
of these particles.

The famous bell-shaped Gauss Curve,

or the Law of Errors –

of deviations with respect
to the mean behavior.

This curve tells about the statistics
of velocities of particles

in the same way as a demographic curve

would tell about the statistics
of ages of individuals.

It’s one of the most
important curves ever.

It keeps on occurring again and again,

from many theories and many experiments,

as a great example of the universality

which is so dear to us mathematicians.

Of this curve,

the famous scientist Francis Galton said,

“It would have been deified by the Greeks
if they had known it.

It is the supreme law of unreason.”

And there’s no better way to materialize
that supreme goddess than Galton’s Board.

Inside this board are narrow tunnels

through which tiny balls
will fall down randomly,

going right or left, or left, etc.

All in complete randomness and chaos.

Let’s see what happens when we look
at all these random trajectories together.

(Board shaking)

This is a bit of a sport,

because we need to resolve
some traffic jams in there.

Aha.

We think that randomness
is going to play me a trick on stage.

There it is.

Our supreme goddess of unreason.

the Gauss Curve,

trapped here inside this transparent box
as Dream in “The Sandman” comics.

For you I have shown it,

but to my students I explain why
it could not be any other curve.

And this is touching
the mystery of that goddess,

replacing a beautiful coincidence
by a beautiful explanation.

All of science is like this.

And beautiful mathematical explanations
are not only for our pleasure.

They also change our vision of the world.

For instance,

Einstein,

Perrin,

Smoluchowski,

they used the mathematical analysis
of random trajectories

and the Gauss Curve

to explain and prove that our
world is made of atoms.

It was not the first time

that mathematics was revolutionizing
our view of the world.

More than 2,000 years ago,

at the time of the ancient Greeks,

it already occurred.

In those days,

only a small fraction of the world
had been explored,

and the Earth might have seemed infinite.

But clever Eratosthenes,

using mathematics,

was able to measure the Earth
with an amazing accuracy of two percent.

Here’s another example.

In 1673, Jean Richer noticed

that a pendulum swings slightly
slower in Cayenne than in Paris.

From this observation alone,
and clever mathematics,

Newton rightly deduced

that the Earth is a wee bit
flattened at the poles,

like 0.3 percent –

so tiny that you wouldn’t even
notice it on the real view of the Earth.

These stories show that mathematics

is able to make us go out of our intuition

measure the Earth which seems infinite,

see atoms which are invisible

or detect an imperceptible
variation of shape.

And if there is just one thing that you
should take home from this talk,

it is this:

mathematics allows us
to go beyond the intuition

and explore territories
which do not fit within our grasp.

Here’s a modern example
you will all relate to:

searching the Internet.

The World Wide Web,

more than one billion web pages –

do you want to go through them all?

Computing power helps,

but it would be useless without
the mathematical modeling

to find the information
hidden in the data.

Let’s work out a baby problem.

Imagine that you’re a detective
working on a crime case,

and there are many people
who have their version of the facts.

Who do you want to interview first?

Sensible answer:

prime witnesses.

You see,

suppose that there is person number seven,

tells you a story,

but when you ask where he got if from,

he points to person
number three as a source.

And maybe person number three, in turn,

points at person number one
as the primary source.

Now number one is a prime witness,

so I definitely want
to interview him – priority.

And from the graph

we also see that person
number four is a prime witness.

And maybe I even want
to interview him first,

because there are more
people who refer to him.

OK, that was easy,

but now what about if you have
a big bunch of people who will testify?

And this graph,

I may think of it as all people
who testify in a complicated crime case,

but it may just as well be web pages
pointing to each other,

referring to each other for contents.

Which ones are the most authoritative?

Not so clear.

Enter PageRank,

one of the early cornerstones of Google.

This algorithm uses the laws
of mathematical randomness

to determine automatically
the most relevant web pages,

in the same way as we used randomness
in the Galton Board experiment.

So let’s send into this graph

a bunch of tiny, digital marbles

and let them go randomly
through the graph.

Each time they arrive at some site,

they will go out through some link
chosen at random to the next one.

And again, and again, and again.

And with small, growing piles,

we’ll keep the record of how many
times each site has been visited

by these digital marbles.

Here we go.

Randomness, randomness.

And from time to time,

also let’s make jumps completely
randomly to increase the fun.

And look at this:

from the chaos will emerge the solution.

The highest piles
correspond to those sites

which somehow are better
connected than the others,

more pointed at than the others.

And here we see clearly

which are the web pages
we want to first try.

Once again,

the solution emerges from the randomness.

Of course, since that time,

Google has come up with much more
sophisticated algorithms,

but already this was beautiful.

And still,

just one problem in a million.

With the advent of digital area,

more and more problems lend
themselves to mathematical analysis,

making the job of mathematician
a more and more useful one,

to the extent that a few years ago,

it was ranked number one
among hundreds of jobs

in a study about the best and worst jobs

published by the Wall Street
Journal in 2009.

Mathematician –

best job in the world.

That’s because of the applications:

communication theory,

information theory,

game theory,

compressed sensing,

machine learning,

graph analysis,

harmonic analysis.

And why not stochastic processes,

linear programming,

or fluid simulation?

Each of these fields have
monster industrial applications.

And through them,

there is big money in mathematics.

And let me concede

that when it comes to making
money from the math,

the Americans are by a long shot
the world champions,

with clever, emblematic billionaires
and amazing, giant companies,

all resting, ultimately,
on good algorithm.

Now with all this beauty,
usefulness and wealth,

mathematics does look more sexy.

But don’t you think

that the life a mathematical
researcher is an easy one.

It is filled with perplexity,

frustration,

a desperate fight for understanding.

Let me evoke for you

one of the most striking days
in my mathematician’s life.

Or should I say,

one of the most striking nights.

At that time,

I was staying at the Institute
for Advanced Studies in Princeton –

for many years, the home
of Albert Einstein

and arguably the most holy place
for mathematical research in the world.

And that night I was working
and working on an elusive proof,

which was incomplete.

It was all about understanding

the paradoxical stability
property of plasmas,

which are a crowd of electrons.

In the perfect world of plasma,

there are no collisions

and no friction to provide
the stability like we are used to.

But still,

if you slightly perturb
a plasma equilibrium,

you will find that the
resulting electric field

spontaneously vanishes,

or damps out,

as if by some mysterious friction force.

This paradoxical effect,

called the Landau damping,

is one of the most important
in plasma physics,

and it was discovered
through mathematical ideas.

But still,

a full mathematical understanding
of this phenomenon was missing.

And together with my former student
and main collaborator Clément Mouhot,

in Paris at the time,

we had been working for months
and months on such a proof.

Actually,

I had already announced by mistake
that we could solve it.

But the truth is,

the proof was just not working.

In spite of more than 100 pages
of complicated, mathematical arguments,

and a bunch discoveries,

and huge calculation,

it was not working.

And that night in Princeton,

a certain gap in the chain of arguments
was driving me crazy.

I was putting in there all my energy
and experience and tricks,

and still nothing was working.

1 a.m., 2 a.m., 3 a.m.,

not working.

Around 4 a.m., I go to bed in low spirits.

Then a few hours later,

waking up and go,

“Ah, it’s time to get
the kids to school –”

What is this?

There was this voice in my head, I swear.

“Take the second term to the other side,

Fourier transform and invert in L2.”

(Laughter)

Damn it,

that was the start of the solution!

You see,

I thought I had taken some rest,

but really my brain had
continued to work on it.

In those moments,

you don’t think of your career
or your colleagues,

it’s just a complete battle
between the problem and you.

That being said,

it does not harm when you do get
a promotion in reward for your hard work.

And after we completed our huge
analysis of the Landau damping,

I was lucky enough

to get the most coveted Fields Medal

from the hands of the President of India,

in Hyderabad on 19 August, 2010 –

an honor that mathematicians
never dare to dream,

a day that I will remember until I live.

What do you think,

on such an occasion?

Pride, yes?

And gratitude to the many collaborators
who made this possible.

And because it was a collective adventure,

you need to share it,
not just with your collaborators.

I believe that everybody can appreciate
the thrill of mathematical research,

and share the passionate stories
of humans and ideas behind it.

And I’ve been working with my staff
at Institut Henri Poincaré,

together with partners and artists
of mathematical communication worldwide,

so that we can found our own,
very special museum of mathematics there.

So in a few years,

when you come to Paris,

after tasting the great, crispy
baguette and macaroon,

please come and visit us
at Institut Henri Poincaré,

and share the mathematical dream with us.

Thank you.

(Applause)

法国人
比其他人做得更好的是什么?

如果您进行民意调查

,前三个答案可能是:

爱、美酒和抱怨。

(笑声)

也许吧。

但让我建议第四个:

数学。

你知道
巴黎的数学家

比世界上任何其他城市都多吗?

还有更多
带有数学家名字的街道。

如果您查看菲尔兹奖的统计数据

该奖通常被称为
诺贝尔数学奖,

并且总是
授予 40 岁以下的数学家,

您会发现法国
人均菲尔兹奖得主

比其他任何国家都多。

是什么让我们觉得数学如此性感?

毕竟,它似乎是
枯燥而抽象的,

只是应用数字、计算
和规则。

数学可能是抽象的,

但它并不枯燥

,也与计算无关。

它是关于推理

和证明我们的核心活动。

这是关于想象力

,我们最赞美的天赋。

这是关于寻找真相。

在经过数月的艰苦思考之后,

您终于明白
了解决问题的正确理由,没有什么比这种感觉更能侵入您了。

伟大的数学家
安德烈·威尔把这——

不开玩笑——比

作性快感。

但请注意,这种感觉
可以持续数小时,甚至数天。

回报可能很大。

隐藏的数学真理
渗透到我们的整个物理世界。

我们的感官无法接近它们,

但可以
通过数学镜头看到它们。

暂时闭上眼睛

,想想
你周围正在发生的事情。 周围

空气中的无形粒子以每秒

数十亿的
速度撞击你,

一切都处于完全混乱的状态。

而且,

它们的统计数据仍然可以
通过数学物理学准确预测。

现在睁开眼睛

看看这些粒子的速度统计数据

著名的钟形高斯曲线

或误差定律——

关于平均行为的偏差。

这条曲线讲述
了粒子速度的统计数据

,就像人口统计

曲线讲述
了个人年龄的统计数据一样。

这是有史以来最
重要的曲线之一。

它不断地

从许多理论和许多实验中一次又一次地出现,

作为我们数学家如此珍视的普遍性的一个很好的例子

对于这条曲线

,著名科学家弗朗西斯·高尔顿说:

“如果他们知道的话,希腊人早就把它神化了

这是非理性的最高法则。”

没有比高尔顿董事会更好的方式来实现
这位至高无上的女神了。

在这个板子里面是狭窄的

隧道,小球
会随机落下

,向右或向左或向左等。

所有这些都是完全随机和混乱的。

让我们看看当我们一起查看
所有这些随机轨迹时会发生什么。

(董事会摇晃)

这有点像运动,

因为我们需要解决
那里的一些交通拥堵。

啊哈。

我们认为
随机性会在舞台上给我耍花招。

它在那里。

我们无理的至高女神。

高斯曲线,

被困在这个透明盒子里,
就像“睡魔”漫画中的梦一样。

我已经为你展示了它,

但我向我的学生解释了为什么
它不能是任何其他曲线。

而这触动
了那位女神的奥秘,

用美丽的解释代替了美丽的巧合

所有的科学都是这样的。

美丽的数学
解释不仅是为了我们的乐趣。

它们也改变了我们对世界的看法。

例如,

爱因斯坦、

佩林、

斯莫鲁霍夫斯基,

他们用
随机轨迹

和高斯曲线的数学分析

来解释和证明我们的
世界是由原子构成的。

这不是

数学第一次彻底改变
我们的世界观。

2000多年前,

在古希腊人的时代,

它就已经发生了。

在那些日子里,

只探索了世界的一小部分

,地球可能看起来是无限的。

但聪明的埃拉托色尼利

用数学

,能够
以惊人的 2% 准确度测量地球。

这是另一个例子。

1673 年,Jean Richer

注意到卡宴的钟摆摆动
比巴黎稍慢。

仅从这个观察
和聪明的数学,

牛顿正确地

推断出地球在两极有点
扁平,

比如 0.3%

——太小了,你甚至不会
在地球的真实视图中注意到它。

这些故事表明,

数学能够让我们超越我们的直觉,

测量看似无限的地球,

看到不可见的原子

或检测到难以察觉
的形状变化。

如果你
应该从这次演讲中带回家一件事,

那就是:

数学让
我们超越直觉

,探索
我们无法掌握的领域。

这是一个现代的例子,
你们都会涉及到:

搜索互联网。

万维网,

超过 10 亿个网页——

你想浏览一遍吗?

计算能力有所帮助,

但如果
没有数学建模

来找到
隐藏在数据中的信息,它将毫无用处。

让我们解决一个婴儿问题。

想象一下,您是一名侦探,
正在处理一起犯罪案件,

并且有很多
人对事实有自己的看法。

你想先采访谁?

明智的答案:

主要证人。

你看,

假设有 7 号人,

给你讲了一个故事,

但是当你问他从哪里得到的,

他指出了
3 号人作为来源。

反过来,也许第三个人

指出第一个人
是主要来源。

现在第一是主要证人,

所以我肯定
想采访他——优先。

从图中

我们还可以看到,
第四个人是主要证人。

也许我什
至想先采访他,

因为有更多的
人提到他。

好的,这很容易,

但现在如果你有
一大群人要作证怎么办?

而这张图,

我可能认为它是所有
在一个复杂的犯罪案件中作证的人,

但它也可能是
相互指向的网页,

相互引用的内容。

哪些是最权威的?

不是很清楚。

进入 PageRank,

这是 Google 的早期基石之一。

该算法使用
数学随机性定律

来自动确定
最相关的网页

,就像我们
在高尔顿板实验中使用随机性一样。

因此,让我们将

一堆微小的数字弹珠发送到该图中,

并让它们随机
通过该图。

每次他们到达某个站点时,

他们都会通过
随机选择的某个链接到达下一个站点。

一次又一次,一次又一次。

随着越来越多的小堆,

我们将记录这些数字弹珠
访问每个站点的次数

开始了。

随机性,随机性。

并且不时地

,让我们完全
随机地跳跃以增加乐趣。

看看这个:

从混乱中会出现解决方案。

最高的桩
对应于那些

以某种方式比其他站点连接得更好,

比其他站点更指向的站点。

在这里我们可以清楚地看到

哪些是
我们首先要尝试的网页。

再一次

,解决方案从随机性中出现。

当然,从那时起,

谷歌就提出了更
复杂的算法,

但这已经很漂亮了。

仍然

,百万分之一的问题。

随着数字领域的出现,

越来越多的问题借给
了数学分析,

使得数学家的工作
变得越来越有用

,以至于在几年前,

它在一项研究中被
列为数百个工作

中的第一名 关于华尔街日报 2009 年发表的最佳和最差工作

数学家——

世界上最好的工作。

这是因为应用:

通信理论、

信息论、

博弈论、

压缩感知、

机器学习、

图形分析、

谐波分析。

为什么不采用随机过程、

线性规划

或流体模拟呢?

这些领域中的每一个都有
巨大的工业应用。

通过他们,

数学有了大笔资金。

让我承认

,当谈到
从数学中赚钱时

,美国人很可能
是世界冠军,

拥有聪明的、标志性的亿万富翁
和令人惊叹的大公司

,最终都
依赖于好的算法。

现在有了这些美丽、
有用和财富,

数学看起来确实更性感了。

但是你不

认为数学研究员的生活
是轻松的吗?

它充满了困惑、

沮丧

和为理解而拼命的斗争。

让我为你唤起

我的数学家一生中最引人注目的日子之一。

或者我应该说,

最引人注目的夜晚之一。

那时,

我住
在普林斯顿高等研究院——

多年来,这里
是爱因斯坦

的故乡,可以说
是世界上数学研究最神圣的地方。

那天晚上,我
正在研究一个难以捉摸的证明,

它是不完整的。

这一切都是为了理解等离子体

的矛盾
稳定性,

等离子体是一群电子。

在等离子的完美世界中,

没有碰撞

和摩擦,可以
像我们习惯的那样提供稳定性。

但是,

如果你稍微
扰乱等离子体平衡,

你会发现
产生的电场会

自发地消失

或衰减,

就好像受到某种神秘的摩擦力一样。

这种

称为朗道阻尼的矛盾效应

是等离子体物理学中最重要的效应之一

,它是
通过数学思想发现的。

但是,

仍然缺少对这种现象的完整数学理解。 当时在巴黎

,我和我以前的学生
和主要合作者克莱门特·穆奥特(Clément Mouhot)一起,


这样的证明工作了好几个月。

实际上,

我已经错误地
宣布我们可以解决它。

但事实是

,证明是行不通的。

尽管有 100 多
页复杂的数学论证

、一堆发现

和巨大的计算,

但它还是没有用。

在普林斯顿的那个晚上

,争论链中的某个间隙
让我发疯了。

我把所有的精力、经验和技巧都投入其中,但

仍然没有任何效果。

凌晨 1 点,凌晨 2 点,凌晨 3 点,

不工作。

凌晨四点左右,我情绪低落地上床睡觉。

然后几个小时后,

醒来然后走,

“啊,是时候
送孩子们上学了——”

这是什么?

我发誓,我的脑海里有这个声音。

“将第二项带到另一边,

傅里叶变换并在 L2 中反转。”

(笑声)

该死,

这就是解决方案的开始!

你看,

我以为我已经休息了,

但实际上我的大脑
仍在继续工作。

在那些时刻,

你不会想到你的事业
或你的同事,

这只是
问题和你之间的一场彻底的战斗。

话虽如此,


您因辛勤工作而获得晋升奖励时,这并没有什么坏处。

在我们完成了
对朗道阻尼的大量分析之后,

我很幸运

于 2010 年 8 月 19 日在海得拉巴从印度总统手中获得了最令人梦寐以求的菲尔兹奖——

这是数学家
做梦都不敢想的荣誉,

我会记得直到我活着的一天。

在这样的场合,你怎么看?

骄傲,是吗?

感谢许多
使这成为可能的合作者。

因为这是一次集体冒险,

你需要分享它,
而不仅仅是与你的合作者分享。

我相信每个人都能体会
到数学研究的快感

,分享人类的激情
故事和背后的想法。

我一直在与
亨利庞加莱研究所的员工

以及
全球数学交流的合作伙伴和艺术家一起工作,

以便我们可以在那里建立我们自己的、
非常特别的数学博物馆。

所以几年后,

当你来到巴黎

,品尝了香脆的
法式长棍面包和马卡龙之后,

请来
Institut Henri Poincaré 拜访我们,

与我们分享数学梦想。

谢谢你。

(掌声)