諾獎得主Wilczek：“精確”：大自然的饋贈_風聞
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撰文 | Frank Wilczek
翻譯 | 胡風、梁丁當
中文版
“精確”是一個強大的工具，但它常常很難實現。關於“精確”的主題一直是科學、生命和現代技術的主旋律。而今，在量子計算的前沿，這個旋律再次響起。
在生物界中，複雜機體把它們的基本操作系統——即如何構建細胞並使之運行的指令——存儲在長串的DNA分子中。這些基本指令被讀取、翻譯成相應的化學反應。如果翻譯出了錯，其後果可能是災難性的，會產生有缺陷、功能紊亂的蛋白質，甚至致癌。因此，生物界演化出了一套精準的修復與勘誤機制，能使錯誤率維持在十億分之一左右。在這個校正過程中，有一系列複雜的分子機器監控着翻譯的進程並進行糾錯。這種分子機器的產生是生物演化過程中最偉大的成就之一。
計算機的許多應用也要求精確。（比如，在銀行交易中，準確的密碼是非常重要的！）當可靠的微型固態晶體管出現時，現代計算機技術便應運而生了。在晶體管中，電子被儲存在一個“容器”裏。這個容器的兩個不同位置編碼了“0”與“1”。如果容器裏的電子足夠多，那麼少數幾個電子的位置錯誤並不會破壞信息的準確性。
但在計算過程中，計算機必須移動這些容器。容器越小，就越容易移動。事實上，計算機運行速度的不斷刷新，很大程度上是因為製造單個比特的電子數在不斷減少。目前的前沿技術已達到10個電子甚至更少的水平。可與此同時，大量“冗餘”電子所帶來的抗誤差能力也隨之消失。要繼續維持幾乎完美、精確的操作，就需要新的技巧。
基礎物理還帶來了另一個問題。當接近單電子的層面時，量子力學的影響變得更加突出。對我們來説，這既是挑戰，也可能是福音。
量子力學告訴我們，電子的位置不是確定的，而是以一定的幾率分佈。這種量子性進一步模糊了關鍵的0與1的區別。但禍兮福所倚，這也帶來了潛在的好處，即我們可以嘗試利用量子物質的複雜性來達成目標。這就是量子計算的願景。目前，世界各地都在積極開展相關研究，旨在為量子計算創建可用的平台。
量子計算最大的挑戰是如何獲得足夠高的計算精度。目前人們試圖通過兩種策略來實現這一目標。
第一種策略是類似於生物的方法，即允許錯誤的發生，但同時也在努力地糾錯。不幸的是，有效的糾錯需要大量“冗餘”和複雜的糾錯機制，因此通過這種途徑來實現“精確”會比較痛苦。
另一種策略則是所謂的“拓撲量子計算”。這是一種很前沿的技術，它的前提是製造出所謂的“任意子” (anyon) ，這種粒子可以被看作一團團有記憶的能量。人們希望製造出使用任意子而不是電子的新型晶體管。但直到最近，物理學家才成功地製造出了任意子，而它們的實際應用前景還尚待觀察。
我們能否繼續應對精確性的挑戰？自然界本身讓我們堅定了信心——畢竟，大自然已經完美地“製造”了大量可交換的部件（比如電子），並以完美的精確度“計算”出了它們的行為。
英文版
Modern computing has sought to mimic the error-correction success of the natural world, and quantum weirdness may now provide new solutions.
Precision is a powerful tool, but it can be hard to come by. That theme, with variations, is a leitmotif of science, organic life and modern technology. It is sounding again today, at the frontier of quantum computing.
Consider biology. Complex organisms store their essential operating systems—instructions for how to build cells and keep them going—within long DNA molecules. Those basic programs must be read out and translated into chemical events. Errors in translation can be catastrophic, resulting in defective, dysfunctional proteins or even in cancers. So biology has evolved an elaborate machinery of repair and proofreading to keep error rates low—around one per billion operations. A series of complicated molecular machines examine the progress and correct mistakes, in a process aptly called proof-reading. The creation of this machinery is one of evolution’s greatest achievements.
Many applications of computers also need precision. (For instance, in bank transactions it’s important to get passwords and transfers exactly right!) Modern computer technology came into its own when small, reliable solid-state transistors became available. Here, the basic distinction between “0” and “1” gets encoded in two alternative locations for buckets of electrons. When there are many electrons per bucket, errors in the position of one or a few don’t spoil the message.
But in doing computations the computer must move the buckets around. Making those buckets of electrons smaller makes the job of moving them around easier. Indeed, the computer industry’s spectacular record of ever-faster speed is largely the story of lowering the number of electrons used to make a bit; nowadays we’re approaching ten or fewer. Unfortunately, at this frontier the near error-immunity that stems from having many “redundant” electrons is less automatic. To maintain nearly error-free, precise operation, new tricks will be necessary.
Fundamental physics brings in another issue. As you approach the level of single electrons, the effects of quantum mechanics become more prominent. This is both a challenge and, potentially, a blessing.
In quantum mechanics, we learn that electrons do not have definite positions but rather distributions of probability. This further blurs the crucial 0-1 distinction. The potential blessing is the flip side of that coin. We can try to exploit the complexity of matter that quantum theory reveals for useful purposes. This is the vision of so-called quantum computing. Vigorous research efforts aimed at providing useful platforms for quantum computing are in progress around the world.
The great challenge is to reach high precision. People are pursuing two kinds of strategies, broadly parallel to those in biology and classical computing.
The first, quasi-biological approach is to let some errors happen but to work hard to correct them. Unfortunately, good error correction requires redundancy and lots of complex machinery, so this path to precision is painful.
The second, called topological quantum computing, is an avant-garde technology. It is premised on making buckets of energy that have a kind of memory—so-called “anyons.” People hope to construct new kinds of transistors that use anyonics rather than electronics. But only very recently have physicists succeeded in producing anyons at all, and it remains to be seen if they can be put to practical use.
Can we continue to meet the challenge of precision? Nature herself inspires faith, for Nature “manufactures” perfectly interchangeable parts (e.g., electrons) in vast quantities and “calculates” their behavior—with perfect accuracy.
Frank Wilczek：弗蘭克·維爾切克是麻省理工學院物理學教授、量子色動力學的奠基人之一。因發現了量子色動力學的漸近自由現象，他在2004年獲得了諾貝爾物理學獎。
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