TED2016
Cédric Villani: What's so sexy about math?
Cédric Villani: 數學的哪些方面這麼迷人？
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隱藏的真相在我們的世界蔓延；我們的感官難以見到它們，但是數學允許我們超越我們的直覺來揭開它們的神秘面紗。在這個數學重大突破的調查中，菲爾茲獎獲得者Cédric Villani談論了發現新事物的興奮，並且詳細描述了有時複雜的數學家的生活。“完美的數學解釋不僅讓我們愉快，”他說，“它們改變了我們對世界的看法。“
Cédric Villani - Mathematician
Cédric Villani tackles perplexing problems in mathematical physics, analysis and geometry with rigor, wit and a signature personal style. Full bio
Cédric Villani tackles perplexing problems in mathematical physics, analysis and geometry with rigor, wit and a signature personal style. Full bio
Double-click the English transcript below to play the video.
00:12
What is it that French people
do better than all the others?
do better than all the others?
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法國人比其他國家的人都擅長的是什麼？
00:18
If you would take polls,
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如果你進行民意調查的話，
00:20
the top three answers might be:
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排在前三位的答案可能是：
00:22
love, wine and whining.
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愛情，葡萄酒和抱怨。
00:26
(Laughter)
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（笑聲）
00:27
Maybe.
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也許是這樣。
00:29
But let me suggest a fourth one:
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但是讓我再加一項：
00:31
mathematics.
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數學。
00:33
Did you know that Paris
has more mathematicians
has more mathematicians
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你知道巴黎的數學家
00:36
than any other city in the world?
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比世界上其他任何一座城市的都多嗎？
00:38
And more streets
with mathematicians' names, too.
with mathematicians' names, too.
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而且也有更多的帶有數學家名字的街道。
00:42
And if you look at the statistics
of the Fields Medal,
of the Fields Medal,
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如果你看看菲爾茲獎的數據，
00:45
often called the Nobel Prize
for mathematics,
for mathematics,
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它通常被稱作數學領域的諾貝爾獎，
00:48
and always awarded to mathematicians
below the age of 40,
below the age of 40,
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並且總是頒發給40歲以下的數學家，
00:52
you will find that France has more
Fields medalists per inhabitant
Fields medalists per inhabitant
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你會發現法國人均菲爾茲獎得主數量
00:56
than any other country.
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多過其他任何一個國家。
00:58
What is it that we find so sexy in math?
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我們認為數學很迷人的地方是什麼？
01:02
After all, it seems to be
dull and abstract,
dull and abstract,
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畢竟，它看起來枯燥又抽象，
01:05
just numbers and computations
and rules to apply.
and rules to apply.
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僅僅是數字，計算和運算規則。
01:10
Mathematics may be abstract,
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數學可能是抽象的，
01:12
but it's not dull
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但是它不是枯燥的
01:13
and it's not about computing.
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而且它不是關於計算。
01:16
It is about reasoning
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它是關於推理
01:17
and proving our core activity.
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以及證明你的核心任務。
01:20
It is about imagination,
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它是關於想像力，
01:22
the talent which we most praise.
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我們最讚賞的一種能力。
01:24
It is about finding the truth.
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它是關於發現真相。
01:27
There's nothing like the feeling
which invades you
which invades you
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沒有任何事情可以和
01:30
when after months of hard thinking,
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經過幾個月苦思終於得出能解決問題的正確推理時
01:32
you finally understand the right
reasoning to solve your problem.
reasoning to solve your problem.
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充盈你的那種感受相比
01:37
The great mathematician
André Weil likened this --
André Weil likened this --
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偉大的數學家安德雷·韋伊把這種感覺比作 －
01:40
no kidding --
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不是開玩笑的 －
性愉悅。
01:41
to sexual pleasure.
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01:44
But noted that this feeling
can last for hours, or even days.
can last for hours, or even days.
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但是請注意這種感覺能持續幾個小時，甚至幾天，
01:50
The reward may be big.
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隨之而來的獎賞也可能很豐厚。
01:53
Hidden mathematical truths
permeate our whole physical world.
permeate our whole physical world.
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我們的現實世界中充滿了未被發現的數學真相。
01:57
They are inaccessible to our senses
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我們的感官無法感知到它們，
02:00
but can be seen
through mathematical lenses.
through mathematical lenses.
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但我們可以用數學的眼光看見它們。
02:04
Close your eyes for moment
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請把你們的眼睛閉上一會兒
02:05
and think of what is occurring
right now around you.
right now around you.
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然後想一想現在你們身邊正發生著什麼。
02:10
Invisible particles from the air
around are bumping on you
around are bumping on you
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空氣中一片混亂，
02:13
by the billions and billions
at each second,
at each second,
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每秒都有上億不可見的微粒
02:16
all in complete chaos.
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撞在你的身上。
02:19
And still,
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然而，
02:20
their statistics can be accurately
predicted by mathematical physics.
predicted by mathematical physics.
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它們的數據可以被數學物理準確地預測。
02:25
And open your eyes now
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現在請睜開你們的眼睛
02:28
to the statistics of the velocities
of these particles.
of these particles.
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來看看這些顆粒移動速率的數據。
02:32
The famous bell-shaped Gauss Curve,
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這個著名的鍾型高斯曲線，
02:35
or the Law of Errors --
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或者是誤差定律 －
02:37
of deviations with respect
to the mean behavior.
to the mean behavior.
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相對於平均數的絕對偏差。
02:41
This curve tells about the statistics
of velocities of particles
of velocities of particles
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這條線描述了顆粒移動速率
02:45
in the same way as a demographic curve
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就如同
02:48
would tell about the statistics
of ages of individuals.
of ages of individuals.
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人口曲線描述個體年齡。
02:52
It's one of the most
important curves ever.
important curves ever.
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它是迄今為止最重要的曲線之一。
02:56
It keeps on occurring again and again,
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在眾多理論與實驗中，
02:59
from many theories and many experiments,
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它作為對我們的數學家們十分寶貴的普遍性的
03:01
as a great example of the universality
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一個重要例證
03:05
which is so dear to us mathematicians.
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一次又一次地出現。
03:09
Of this curve,
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關於這條曲線，
03:10
the famous scientist Francis Galton said,
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著名的科學家弗朗西斯·高爾頓說過，
03:14
"It would have been deified by the Greeks
if they had known it.
if they had known it.
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“如果希臘人知道這條曲線的話，它一定會被他們神化的。
03:19
It is the supreme law of unreason."
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它是無理性的終極法則。”
03:23
And there's no better way to materialize
that supreme goddess than Galton's Board.
that supreme goddess than Galton's Board.
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沒有比加爾頓實驗板更好的方式來展現這位至尊女神。
03:31
Inside this board are narrow tunnels
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在這個實驗板裡面是狹窄的通道
03:34
through which tiny balls
will fall down randomly,
will fall down randomly,
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小球會通過這些通道隨機落下，
03:40
going right or left, or left, etc.
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向右或者向左，或者向左，等等。
03:46
All in complete randomness and chaos.
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一切都是完全隨機和任意的。
03:50
Let's see what happens when we look
at all these random trajectories together.
at all these random trajectories together.
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我們來看看把這些隨機的路徑放在一起觀察將會如何。
03:56
(Board shaking)
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（搖晃實驗板）
04:01
This is a bit of a sport,
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這有點像一種運動，
04:04
because we need to resolve
some traffic jams in there.
some traffic jams in there.
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因為我們需要解決一些在那裡的交通擁堵。
04:11
Aha.
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啊哈。
04:13
We think that randomness
is going to play me a trick on stage.
is going to play me a trick on stage.
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我們認為隨機性將會在這個台上展現一些極妙。
04:19
There it is.
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就是這樣。
04:22
Our supreme goddess of unreason.
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我們無理性的至尊女神。
04:24
the Gauss Curve,
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高斯曲線，
04:26
trapped here inside this transparent box
as Dream in "The Sandman" comics.
as Dream in "The Sandman" comics.
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被困在了這個透明的實驗板裡，就像《睡魔》中的夢一樣。
04:34
For you I have shown it,
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我已經給你們展示了這條曲線，
04:37
but to my students I explain why
it could not be any other curve.
it could not be any other curve.
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但是在我的學生面，我要解釋為什麼不會是其它的曲線。
04:43
And this is touching
the mystery of that goddess,
the mystery of that goddess,
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這就涉及到這位至尊女神的神祕性，
04:46
replacing a beautiful coincidence
by a beautiful explanation.
by a beautiful explanation.
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用一個完美的解釋代替一個美麗的巧合。
04:51
All of science is like this.
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所有的科學都如此。
04:54
And beautiful mathematical explanations
are not only for our pleasure.
are not only for our pleasure.
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完美的數學解釋不僅僅讓我們愉快。
04:59
They also change our vision of the world.
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它們也會改變我們對世界的看法。
05:03
For instance,
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比如，
05:04
Einstein,
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愛因斯坦，
05:05
Perrin,
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佩蘭，
05:06
Smoluchowski,
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斯莫魯霍夫斯基，
05:07
they used the mathematical analysis
of random trajectories
of random trajectories
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他們用隨機路徑的數學分析
05:11
and the Gauss Curve
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和高斯曲線
05:13
to explain and prove that our
world is made of atoms.
world is made of atoms.
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來解釋並且證明我們的世界是由原子組成的。
05:19
It was not the first time
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這不是第一次
05:21
that mathematics was revolutionizing
our view of the world.
our view of the world.
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數學革新了我們對世界的看法。
05:25
More than 2,000 years ago,
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2000多年前，
05:27
at the time of the ancient Greeks,
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在古希臘的時候，
05:31
it already occurred.
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這就發生了。
05:33
In those days,
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在那個時候，
05:35
only a small fraction of the world
had been explored,
had been explored,
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只有一小部分的世界已經被探索，
05:38
and the Earth might have seemed infinite.
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而且地球似乎是無窮大的。
05:42
But clever Eratosthenes,
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但是聰明的艾拉托瑟尼，
05:43
using mathematics,
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用數學，
05:45
was able to measure the Earth
with an amazing accuracy of two percent.
with an amazing accuracy of two percent.
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成功地以2%的驚人精確度測量了地球。
05:51
Here's another example.
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還有另一個例子。
05:54
In 1673, Jean Richer noticed
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在1673年，簡·裡歇爾發現
05:58
that a pendulum swings slightly
slower in Cayenne than in Paris.
slower in Cayenne than in Paris.
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鐘擺在卡宴比在巴黎擺動得略微慢一些。
06:06
From this observation alone,
and clever mathematics,
and clever mathematics,
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僅僅是通過這個發現和巧妙的數學，
06:10
Newton rightly deduced
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牛頓正確地推斷出
06:13
that the Earth is a wee bit
flattened at the poles,
flattened at the poles,
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地球的兩極有細微的扁平，
06:18
like 0.3 percent --
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像是0.3%那麼多 －
06:20
so tiny that you wouldn't even
notice it on the real view of the Earth.
notice it on the real view of the Earth.
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太小了以至於你甚至無法在地球的真實圖像上注意到。
06:26
These stories show that mathematics
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這些故事說明了數學
06:30
is able to make us go out of our intuition
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可以讓我們走出直覺、
06:35
measure the Earth which seems infinite,
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測量似乎是無窮大的地球、
06:39
see atoms which are invisible
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看到肉眼不可見的原子
06:41
or detect an imperceptible
variation of shape.
variation of shape.
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或者是發現難以察覺的形狀差異。
06:44
And if there is just one thing that you
should take home from this talk,
should take home from this talk,
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這個演講中你最應當領悟到的
06:48
it is this:
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應該是：
06:49
mathematics allows us
to go beyond the intuition
to go beyond the intuition
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數學讓我們超越直覺
06:54
and explore territories
which do not fit within our grasp.
which do not fit within our grasp.
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並且探索不在我們掌控範圍內的領域。
06:59
Here's a modern example
you will all relate to:
you will all relate to:
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這是一個和你們都相關的現代案例：
07:03
searching the Internet.
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上網。
07:06
The World Wide Web,
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互聯網，
07:07
more than one billion web pages --
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超過十億的網頁 －
07:09
do you want to go through them all?
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你們想要瀏覽完所有的網頁嗎？
07:11
Computing power helps,
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計算機的能力可以提供幫助，
07:13
but it would be useless without
the mathematical modeling
the mathematical modeling
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但是它是無用的，如果沒有數學模型
07:16
to find the information
hidden in the data.
hidden in the data.
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來幫助找到隱藏在數據中的信息。
07:20
Let's work out a baby problem.
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讓我們解決一個和嬰兒有關的問題。
07:23
Imagine that you're a detective
working on a crime case,
working on a crime case,
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想像一下你是一名偵探，在偵查一個犯罪案，
07:27
and there are many people
who have their version of the facts.
who have their version of the facts.
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然後很多人都有各自版本的事實。
07:32
Who do you want to interview first?
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你想要先詢問誰？
07:34
Sensible answer:
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合理的答案：
07:36
prime witnesses.
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首要證人。
07:38
You see,
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要知道，
07:40
suppose that there is person number seven,
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假設七號人物
07:44
tells you a story,
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告訴了你一件事，
07:45
but when you ask where he got if from,
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但是你問他，他是怎麼知道的，
07:47
he points to person
number three as a source.
number three as a source.
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他說消息來在三號人物。
07:50
And maybe person number three, in turn,
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然後可能三號人物
07:52
points at person number one
as the primary source.
as the primary source.
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又說消息來自一號人物。
07:56
Now number one is a prime witness,
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現在一號人物就是首要證人。
07:58
so I definitely want
to interview him -- priority
to interview him -- priority
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所以我肯定想要詢問他 －首要任務
08:02
And from the graph
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從圖表中
08:03
we also see that person
number four is a prime witness.
number four is a prime witness.
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我們也可以看出四號人物也是首要證人。
08:06
And maybe I even want
to interview him first,
to interview him first,
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也許我想要先詢問他，
08:09
because there are more
people who refer to him.
people who refer to him.
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因為有更多人的提到了他。
08:12
OK, that was easy,
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好的，那很容易，
08:15
but now what about if you have
a big bunch of people who will testify?
a big bunch of people who will testify?
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但是現在如果你有一大群人需要詢問該怎麼辦呢？
08:20
And this graph,
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這幅圖表，
08:22
I may think of it as all people
who testify in a complicated crime case,
who testify in a complicated crime case,
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我可以把它看作是要在一個複雜的犯罪案中作證詞的所有人，
08:27
but it may just as well be web pages
pointing to each other,
pointing to each other,
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但是它也可以是彼此聯繫的網頁，
08:31
referring to each other for contents.
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通過彼此參考來獲取信息。
08:34
Which ones are the most authoritative?
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最具權威的是哪些呢？
08:37
Not so clear.
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不是很清楚。
08:40
Enter PageRank,
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輸入網頁排序，
08:42
one of the early cornerstones of Google.
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一個谷歌早期的奠基石。
08:45
This algorithm uses the laws
of mathematical randomness
of mathematical randomness
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這個算法使用數學隨機法則
08:49
to determine automatically
the most relevant web pages,
the most relevant web pages,
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來自動確定最相關的網頁，
08:53
in the same way as we used randomness
in the Galton Board experiment.
in the Galton Board experiment.
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和我們在高爾頓實驗板實驗中所使用的隨機性方法一樣。
08:59
So let's send into this graph
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讓我們把
09:01
a bunch of tiny, digital marbles
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一束極小的電子彈珠輸送到這個圖表中
09:04
and let them go randomly
through the graph.
through the graph.
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然後讓它們在圖表中隨機移動。
09:08
Each time they arrive at some site,
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每一次它們都會到達某個地方，
09:10
they will go out through some link
chosen at random to the next one.
chosen at random to the next one.
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它們會通過隨機選擇的、通往下一個地方的通道出去。
09:14
And again, and again, and again.
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一次，一次， 又一次。
09:16
And with small, growing piles,
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根據這些小的，不斷變大的堆積，
09:18
we'll keep the record of how many
times each site has been visited
times each site has been visited
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我們會記錄每一個地方被
09:21
by these digital marbles.
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這些電子彈珠到訪的次數。
09:24
Here we go.
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我們開始吧。
09:25
Randomness, randomness.
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隨機，隨機。
09:27
And from time to time,
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不時地，
09:29
also let's make jumps completely
randomly to increase the fun.
randomly to increase the fun.
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讓我們也完全隨機地跳躍來增加趣味性。
09:34
And look at this:
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看看這個：
09:36
from the chaos will emerge the solution.
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答案會從混亂中顯現出來。
09:39
The highest piles
correspond to those sites
correspond to those sites
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最高的堆積對應那些地點
09:41
which somehow are better
connected than the others,
connected than the others,
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那些出於某種原因比其它地點有更多連接的地點，
09:45
more pointed at than the others.
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比其它地點受到更多指示的地點。
09:47
And here we see clearly
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在這裡我們可以清楚地看見
09:49
which are the web pages
we want to first try.
we want to first try.
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哪些是我們想要先看的網頁。
09:53
Once again,
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再一次，
09:54
the solution emerges from the randomness.
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答案從隨機性中顯現。
09:57
Of course, since that time,
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當然，從那時以後，
10:00
Google has come up with much more
sophisticated algorithms,
sophisticated algorithms,
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谷歌設計出了更複雜的算法，
10:03
but already this was beautiful.
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但是這個已經足夠好了。
10:06
And still,
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但是，
10:08
just one problem in a million.
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有一個萬里挑一的問題。
10:10
With the advent of digital area,
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隨著數碼時代的到來，
10:13
more and more problems lend
themselves to mathematical analysis,
themselves to mathematical analysis,
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越來越多的問題需要數學分析來解釋，
10:18
making the job of mathematician
a more and more useful one,
a more and more useful one,
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讓數學家的工作越來越有用，
10:23
to the extent that a few years ago,
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以至於達到了這樣的程度，幾年前，
10:25
it was ranked number one
among hundreds of jobs
among hundreds of jobs
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它排在幾百個工作之首
10:29
in a study about the best and worst jobs
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在一份關於最佳工作和最差工作的研究中
10:33
published by the Wall Street
Journal in 2009.
Journal in 2009.
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2975
2009年由華爾街日報出版。
10:37
Mathematician --
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1852
數學家 －
10:39
best job in the world.
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世界上最好的工作。
10:41
That's because of the applications:
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那是因為各種應用：
10:44
communication theory,
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通信原理，
10:46
information theory,
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信息原理，
10:48
game theory,
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博弈論，
10:50
compressed sensing,
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壓縮傳感，
10:51
machine learning,
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機器學習，
10:53
graph analysis,
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圖表分析，
10:54
harmonic analysis.
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1742
和聲分析。
10:56
And why not stochastic processes,
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應該還有隨機過程，
10:59
linear programming,
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線性編程，
11:00
or fluid simulation?
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或者是流體仿真吧？
11:03
Each of these fields have
monster industrial applications.
monster industrial applications.
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這些領域中的每一個都有龐大的工業應用。
11:07
And through them,
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通過它們，
11:08
there is big money in mathematics.
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656386
1999
數學可以帶來豐厚的收入。
11:11
And let me concede
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659400
2040
請允許我承認
11:13
that when it comes to making
money from the math,
money from the math,
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當涉及到通過數學賺錢，
11:15
the Americans are by a long shot
the world champions,
the world champions,
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美國人是遙遙領先的世界冠軍，
11:19
with clever, emblematic billionaires
and amazing, giant companies,
and amazing, giant companies,
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有著機敏的、象徵億萬富翁的、令人驚異的大公司，
11:24
all resting, ultimately,
on good algorithm.
on good algorithm.
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所有的這些公司最終都依靠好的算法。
11:29
Now with all this beauty,
usefulness and wealth,
usefulness and wealth,
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3972
現在，有了這種美麗，實用性和財富，
11:33
mathematics does look more sexy.
215
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2284
數學的確看起來更迷人了。
11:36
But don't you think
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684399
1617
但是不要認為
11:38
that the life a mathematical
researcher is an easy one.
researcher is an easy one.
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4120
數學研究員的生活很容易。
11:42
It is filled with perplexity,
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690959
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它充滿了複雜性，
11:46
frustration,
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694347
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沮喪，
11:48
a desperate fight for understanding.
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為了解釋而進行的絕望的鬥爭。
11:51
Let me evoke for you
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請讓我為你回憶一下
11:54
one of the most striking days
in my mathematician's life.
in my mathematician's life.
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一位數學家一生中最震撼的一天之一。
11:58
Or should I say,
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1151
或許我應該說，
11:59
one of the most striking nights.
224
707698
1737
最震撼的夜晚之一。
12:02
At that time,
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710713
1151
那個時候，
12:03
I was staying at the Institute
for Advanced Studies in Princeton --
for Advanced Studies in Princeton --
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3151
我在普林斯頓的高級研究所工作 －
12:07
for many years, the home
of Albert Einstein
of Albert Einstein
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很多年來都是阿爾伯特·愛因斯坦的住所
12:09
and arguably the most holy place
for mathematical research in the world.
for mathematical research in the world.
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717226
4428
而且可以說是世界上最神聖的數學研究的地方。
12:14
And that night I was working
and working on an elusive proof,
and working on an elusive proof,
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722878
3844
那個晚上，我在推理一個很難的證明，
12:18
which was incomplete.
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1378
一個那時尚未完成的證明。
12:21
It was all about understanding
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729304
2208
它完全是關於理解
12:23
the paradoxical stability
property of plasmas,
property of plasmas,
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等離子體的矛盾的穩定特性，
12:27
which are a crowd of electrons.
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735383
1958
等離子體是一團電子。
12:30
In the perfect world of plasma,
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2736
在理想的等離子體世界中，
12:33
there are no collisions
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1778
是沒有碰撞
12:34
and no friction to provide
the stability like we are used to.
the stability like we are used to.
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也沒有摩擦力來提供我們所習慣的穩定性的。
12:39
But still,
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1151
但是，
12:40
if you slightly perturb
a plasma equilibrium,
a plasma equilibrium,
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3033
如果你稍微破壞了等離子體的平衡狀態，
12:43
you will find that the
resulting electric shield
resulting electric shield
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你會發現隨之而來的靜電屏蔽
12:46
spontaneously vanishes,
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自然消失了，
12:48
or damps out,
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756699
1975
或者減弱了，
12:50
as if by some mysterious friction force.
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就像是由一些神秘的摩擦力造成的一樣。
12:54
This paradoxical effect,
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這種矛盾的效應，
12:56
called the Landau damping,
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被稱作朗道阻尼，
12:58
is one of the most important
in plasma physics,
in plasma physics,
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是等離子體物理學中最重要的效應之一，
13:01
and it was discovered
through mathematical ideas.
through mathematical ideas.
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769101
3002
它是通過數學概念發現的。
13:04
But still,
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1151
但是，
13:06
a full mathematical understanding
of this phenomenon was missing.
of this phenomenon was missing.
248
774145
4230
一套對於這個現象完整的數學理解那時並不存在。
13:10
And together with my former student
and main collaborator Clément Mouhot,
and main collaborator Clément Mouhot,
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4786
和我以前的學生，也是我主要的合作者克萊蒙·穆奧，
13:15
in Paris at the time,
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783209
1492
那時在巴黎，
13:16
we had been working for months
and months on such a proof.
and months on such a proof.
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4086
我們為了這樣的一個證明一起努力了很多個月。
13:21
Actually,
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實際上，
13:23
I had already announced by mistake
that we could solve it.
that we could solve it.
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我那時錯誤地宣布了我們可以解決它。
13:27
But the truth is,
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1725
但事實是，
13:29
the proof was just not working.
255
797710
2147
那個證明是無效的。
13:32
In spite of more than 100 pages
of complicated, mathematical arguments,
of complicated, mathematical arguments,
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800196
4349
儘管用了超過100頁的複雜的數學論證，
13:36
and a bunch discoveries,
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804569
1690
有了一些發現，
13:38
and huge calculation,
258
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1267
和完成了龐大的計算量，
13:39
it was not working.
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1169
那個證明還是無效。
13:41
And that night in Princeton,
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809290
1681
在普林斯頓的那晚，
13:42
a certain gap in the chain of arguments
was driving me crazy.
was driving me crazy.
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810995
4301
一系列論證中的某個欠缺幾乎讓我發瘋。
13:47
I was putting in there all my energy
and experience and tricks,
and experience and tricks,
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4593
我把我所有的精力、經驗和技巧都用在那裡了，
13:52
and still nothing was working.
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1742
但是還是沒有任何結果。
13:54
1 a.m., 2 a.m., 3 a.m.,
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3882
凌晨一點，兩點，三點，
13:58
not working.
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1308
什麼結果都沒有。
14:00
Around 4 a.m., I go to bed in low spirits.
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大概凌晨四點的時候，我情緒低落地去睡覺了。
14:05
Then a few hours later,
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2460
然後幾個小時以後，
14:08
waking up and go,
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1151
我醒來，繼續工作，
14:09
"Ah, it's time to get
the kids to school --"
the kids to school --"
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3357
“啊，孩子們上學的時間到了 －”
14:12
What is this?
270
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這是什麼？
14:14
There was this voice in my head, I swear.
271
842130
2142
我發誓，在我腦中有這樣一個聲音。
14:16
"Take the second term to the other side,
272
844894
1913
“把第二項移到另一側，
14:18
Fourier transform and invert in L2."
273
846831
1919
傅立葉變換，然後把L2倒置。”
14:21
(Laughter)
274
849257
1151
（笑聲）
14:22
Damn it,
275
850432
1702
見鬼了，
14:24
that was the start of the solution!
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852158
2113
那就是答案的開始！
14:27
You see,
277
855519
1151
要知道，
14:28
I thought I had taken some rest,
278
856694
2283
我認為我休息了一下，
14:31
but really my brain had
continued to work on it.
continued to work on it.
279
859001
3388
但是事實上我的大腦繼續思考著那個問題。
14:35
In those moments,
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1597
在那些時刻，
14:36
you don't think of your career
or your colleagues,
or your colleagues,
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2601
你不會想到你的職業或者是你的同事，
14:39
it's just a complete battle
between the problem and you.
between the problem and you.
282
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3690
那只是那個問題和你之間的一場鬥爭。
14:44
That being said,
283
872098
1328
儘管如此，
14:45
it does not harm when you do get
a promotion in reward for your hard work.
a promotion in reward for your hard work.
284
873450
3949
當你因為你的努力而得到升職，也沒什麼不好。
14:49
And after we completed our huge
analysis of the Landau damping,
analysis of the Landau damping,
285
877808
5160
我們完成了龐大的朗道阻尼分析之後，
14:54
I was lucky enough
286
882992
1615
我很幸運
14:56
to get the most coveted Fields Medal
287
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3030
得到了夢寐以求的菲爾茲獎
14:59
from the hands of the President of India,
288
887685
2867
由印度主席授予，
15:02
in Hyderabad on 19 August, 2010 --
289
890576
3920
2010年8月19日在海得拉巴 －
15:07
an honor that mathematicians
never dare to dream,
never dare to dream,
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895453
3251
一個數學家們從不敢奢求的榮譽，
15:10
a day that I will remember until I live.
291
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2399
我永遠都會記得的一天。
15:14
What do you think,
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1447
你會有什麼想法，
15:15
on such an occasion?
293
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2141
在這樣的一個場合？
15:18
Pride, yes?
294
906002
1150
自豪，對嗎？
15:19
And gratitude to the man collaborators
who made this possible.
who made this possible.
295
907791
3640
還有感激，對那些讓這個成為可能的人。
15:24
And because it was a collective adventure,
296
912304
2212
因為這是一個集體的經歷，
15:26
you need to share it,
not just with your collaborators.
not just with your collaborators.
297
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4142
你需要分享它，不僅僅是和你的合作者。
15:31
I believe that everybody can appreciate
the thrill of mathematical research,
the thrill of mathematical research,
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919548
5692
我相信每一個人都可以感受數學研究的刺激，
15:37
and share the passionate stories
of humans and ideas behind it.
of humans and ideas behind it.
299
925264
4318
並且分享在這背後的充滿激情的人和事。
15:42
And I've been working with my staff
at Institut Henri Poincaré,
at Institut Henri Poincaré,
300
930494
4774
我和我的職員在Henri Poincaré學院已經工作一段時間了，
15:47
together with partners and artists
of mathematical communication worldwide,
of mathematical communication worldwide,
301
935292
5181
還有世界各地的數學通訊夥伴和藝術家，
15:52
so that we can found our own,
very special museum of mathematics there.
very special museum of mathematics there.
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4587
以至於我們可以在那裡建立我們自己的非常特別的數學博物館。
15:58
So in a few years,
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946537
1777
所以幾年後，
16:00
when you come to Paris,
304
948885
1577
當你來到巴黎的時候，
16:02
after tasting the great, crispy
baguette and macaroon,
baguette and macaroon,
305
950486
5658
品嚐完美味酥脆的法國長棍麵包和馬卡龍之後，
16:08
please come and visit us
at Institut Henri Poincaré,
at Institut Henri Poincaré,
306
956168
3663
請來Henri Poincaré學院拜訪我們，
16:11
and share the mathematical dream with us.
307
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2515
並且和我們分享數學夢想。
16:14
Thank you.
308
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1151
謝謝。
16:15
(Applause)
309
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7000
（掌聲）
ABOUT THE SPEAKER
Cédric Villani - MathematicianCédric Villani tackles perplexing problems in mathematical physics, analysis and geometry with rigor, wit and a signature personal style.
Why you should listen
His Byronesque hair, colorful ascots and spider brooches have earned Cédric Villani the nickname “the Lady Gaga of Mathematics.” But this moniker has not obscured Villani’s deeper, serious mission: inspiring students to delve into the mysteries of mathematics.
Villani’s fame is based on his work resolving difficult problems of kinetic theory, for which he received the Fields Medal in 2010. His book Birth of a Theorem is an exhilarating journey into the nocturnal dilemmas of mathematicians hot on the trail of discovery.
Villani was elected to the French National Assembly in June 2017.
Cédric Villani | Speaker | TED.com