被英国《自然》吹成“量子之父”的潘建伟为何在美国《科学》不受待见？ 展望2018年量子计算机进展竟然不见中国科学家身影
特别声明
本平台推出文稿均出于非商业性的教育和科研目的，旨在传播学术研究信息、净化大学教育与科研生态环境。但声明该文仅代表原作者的个人观点并不意味着本公众号赞同其观点或证实其内容的真实性。如有异议或侵权，本平台将在第一时间处理。期望读者关注点赞《蝌蚪士》公益事业： 为苦逼科民发声、并贡献正义的智力；且为平民大众免费科普，使之走进科学、传承科学、壮大科学——人人都能成为真才实学的蝌蚪士 (主编| 赛德夫).
2017年底，中国的潘建伟被英国《自然》吹成“量子之父”，而他主导研制的量子计算机还被作为重大科学进展收入中国元首的元旦献词。
但是，这个“量子之父”到底是否靠谱？真正的世界强国到底看不看得起中国的“世界第一”的量子计算机？读下美国《科学》的最新报道或许可以明白一点真相。
最近美国《科学》杂志对2018年的科学进展做了一个展望，其中提到了量子计算。
测试量子计算机
数十年来，物理学家一直努力寻求构建一个量子计算机，取得了一些重要成果。与现有计算机不同的是，量子计算机将依靠于更微妙的物理现象来进行运算，如量子波干涉。谷歌与其他实验室正在争分夺秒地研究。但一切似乎还为时尚早。
在这个简短的展望里，提到了美国的谷歌，但对于量子计算机的整体评价是：“一切似乎还为时尚早”。
而在最近一期《科学》杂志发表的文章中，中国科学家的量子计算机工作也没有任何提及。
IN DEPTHCOMPUTATION
DOE pushes for useful quantum computing
Adrian Cho
See all authors and affiliations
Science 12 Jan 2018:
Vol. 359, Issue 6372, pp. 141-142
DOI: 10.1126/science.359.6372.141
Summary
The U.S. Department of Energy (DOE) is joining the quest to develop quantum computers, devices that would exploit quantum mechanics to crack problems that overwhelm conventional computers. The initiative comes as Google and other companies race to build a quantum computer that can demonstrate "quantum supremacy" by beating classical computers on a test problem. But reaching that milestone will not mean practical uses are at hand, and the new $40 million DOE effort is intended to spur the development of useful quantum computing algorithms for its work in chemistry, materials science, nuclear physics, and particle physics. With the resources at its 17 national laboratories, DOE could play a key role in developing the machines, researchers say, although finding problems with which quantum computers can help isn't so easy.
The U.S. Department of Energy (DOE) is joining the quest to develop quantum computers, devices that would exploit quantum mechanics to crack problems that overwhelm conventional computers. The initiative comes as Google and other companies race to build a quantum computer that can demonstrate “quantum supremacy” by beating classical computers on a test problem. But reaching that milestone will not mean practical uses are at hand, and the new $40 million DOE effort is intended to spur the development of useful quantum computing algorithms for its work in chemistry, materials science, nuclear physics, and particle physics.
“We are looking for algorithms that can advance the science,” says Stephen Binkley, acting director of DOE's $5.4 billion Office of Science in Washington, D.C., who in a 29 November 2017 open letter urged researchers to submit proposals for such work.
The U.S. government already spends about $250 million per year on quantum computing, mostly through the Army Research Office, says Christopher Monroe, a physicist at the University of Maryland in College Park and co-founder of the quantum computing startup IonQ. But the DOE money will go mostly to its national laboratories. Monroe says researchers there can play a leading role in developing the machines. “Industry can't do it because they don't have the people, and academics can't do it because they don't build things.”
Whereas a conventional computer manipulates bits that can be set to either 0 or 1, a quantum computer employs quantum bits or qubits that, bizarrely, can be set to 0 and 1 at the same time. A qubit can be a patch of superconducting metal that can be electrically charged to encode 1, uncharged to encode 0, or both charged and uncharged at the same time. Trapped ions, which can spin in opposite directions or both ways at once, can also serve as qubits. With their two-ways-at-once capability, just 300 qubits could simultaneously encode more numbers than there are atoms in the observable universe.
However, it is the way quantum computers solve problems that accounts for their power—and their limitations. Problems can be encoded so that potential solutions correspond to different quantum waves sloshing through the qubits. Set things up so the waves interfere the right way, and the wrong solutions will cancel one another while the right solution pops out. That's how a quantum computer could quickly factor large numbers, potentially enabling it to crack current internet encryption protocols. But the approach cannot aid every computation.
A quantum computing to-do list
Researchers have several general ideas for scientific applications of quantum computers.
For instance, quantum computers won't help analyze the billions of records of individual particle collisions produced by atom smashers such as the Large Hadron Collider in Switzerland, says James Amundson, a computational physicist at Fermi National Accelerator Laboratory in Batavia, Illinois. Each of the records is easy to analyze, so they need only to be fed through an army of ordinary computers working in parallel, Amundson says. A quantum computer can't speed up the process.
Still, the machines hold great promise for some problems, researchers say, such as those that involve modeling or simulating inherently quantum mechanical processes. In chemistry, for example, enzymes called nitrogenases catalyze the reactions that enable nitrogen-fixing bacteria to turn nitrogen from the air into a form that plants can use. No conventional computer can calculate exactly how the process works, but a quantum computer could, says Wibe de Jong, a computational chemist at Lawrence Berkeley National Laboratory in Berkeley, California. “There are lots of catalytic processes that are still very hard to model because of the computational complexity,” he says.
Quantum computers might also aid in the design of materials from their atomic constituents on up. And they could help predict how the superdense matter in neutron stars behaves or how a proton breaks up during a particle collision. Such applications all involve the interplay of the quantum waves that describe subatomic particles. Tracking the oscillating waves swamps a conventional computer, but a quantum computer handles that aspect of a calculation automatically, explains Martin Savage, a nuclear theorist at the University of Washington in Seattle.
Researchers have only begun to figure out how to map such problems onto a quantum computer's qubits. To speed the process, DOE in September 2017 launched two testbeds to enable designers and scientists to work together on approaches to quantum computation. At the Berkeley lab, physicist Irfan Siddiqi and colleagues aim to build their own 64-qubit quantum computer using superconducting qubits. Feedback from users will influence their designs, such has how the qubits are arranged and connected with one another on a chip, Siddiqi says.
In contrast, a testbed at Oak Ridge National Laboratory in Tennessee will provide remote access to existing machines at IBM and IonQ. That approach should spark the same sort of “co-design” without requiring Oak Ridge researchers to build a machine from scratch, says Raphael Pooser, a quantum information scientist at Oak Ridge. It also more closely resembles the way DOE develops its supercomputers in partnership with industry, he says.
In the meantime, commercial machines are getting more powerful. This week, researchers at Google's laboratory in Santa Barbara, California, began testing a 50-qubit chip they think will achieve quantum supremacy, although the experiment could still take months. Yet some researchers worry that such a demonstration may mislead the public into thinking that scientists have reached the end of the road in developing a useful quantum computer. “It's not even the beginning of the road,” Siddiqi says.
John Martinis, the physicist who leads Google's effort, says the company “understands that quantum supremacy is a great milestone and that it will take longer, perhaps much longer, to make something practical.” DOE clearly agrees.
笔者上世纪九十年代中期曾在美国能源部管辖的橡树岭国家实验室做过一些科学研究工作，一个成果还发表在美国《科学》杂志。
因此，对于美国能源部，其中还提到橡树岭国家实验室，在量子计算机领域在做些什么也表示一下关心。
笔者将该文中应当注意的字句套红加粗。
Summary
The U.S. Department of Energy (DOE) is joining the quest to develop quantum computers, devices that would exploit quantum mechanics to crack problems that overwhelm conventional computers. The initiative comes as Google and other companies race to build a quantum computer that can demonstrate "quantum supremacy" by beating classical computers on a test problem. But reaching that milestone will not mean practical uses are at hand, and the new $40 million DOE effort is intended to spur the development of useful quantum computing algorithms for its work in chemistry, materials science, nuclear physics, and particle physics. With the resources at its 17 national laboratories, DOE could play a key role in developing the machines, researchers say, although finding problems with which quantum computers can help isn't so easy.
The U.S. Department of Energy (DOE) is joining the quest to develop quantum computers, devices that would exploit quantum mechanics to crack problems that overwhelm conventional computers. The initiative comes as Google and other companies race to build a quantum computer that can demonstrate “quantum supremacy” by beating classical computers on a test problem. But reaching that milestone will not mean practical uses are at hand, and the new $40 million DOE effort is intended to spur the development of useful quantum computing algorithms for its work in chemistry, materials science, nuclear physics, and particle physics.
“We are looking for algorithms that can advance the science,” says Stephen Binkley, acting director of DOE's $5.4 billion Office of Science in Washington, D.C., who in a 29 November 2017 open letter urged researchers to submit proposals for such work.
The U.S. government already spends about $250 million per year on quantum computing, mostly through the Army Research Office, says Christopher Monroe, a physicist at the University of Maryland in College Park and co-founder of the quantum computing startup IonQ. But the DOE money will go mostly to its national laboratories. Monroe says researchers there can play a leading role in developing the machines. “Industry can't do it because they don't have the people, and academics can't do it because they don't build things.”
Whereas a conventional computer manipulates bits that can be set to either 0 or 1, a quantum computer employs quantum bits or qubits that, bizarrely, can be set to 0 and 1 at the same time. A qubit can be a patch of superconducting metal that can be electrically charged to encode 1, uncharged to encode 0, or both charged and uncharged at the same time. Trapped ions, which can spin in opposite directions or both ways at once, can also serve as qubits. With their two-ways-at-once capability, just 300 qubits could simultaneously encode more numbers than there are atoms in the observable universe.
However, it is the way quantum computers solve problems that accounts for their power—and their limitations. Problems can be encoded so that potential solutions correspond to different quantum waves sloshing through the qubits. Set things up so the waves interfere the right way, and the wrong solutions will cancel one another while the right solution pops out. That's how a quantum computer could quickly factor large numbers, potentially enabling it to crack current internet encryption protocols. But the approach cannot aid every computation.
A quantum computing to-do list
Researchers have several general ideas for scientific applications of quantum computers.
For instance, quantum computers won't help analyze the billions of records of individual particle collisions produced by atom smashers such as the Large Hadron Collider in Switzerland, says James Amundson, a computational physicist at Fermi National Accelerator Laboratory in Batavia, Illinois. Each of the records is easy to analyze, so they need only to be fed through an army of ordinary computers working in parallel, Amundson says. A quantum computer can't speed up the process.
Still, the machines hold great promise for some problems, researchers say, such as those that involve modeling or simulating inherently quantum mechanical processes. In chemistry, for example, enzymes called nitrogenases catalyze the reactions that enable nitrogen-fixing bacteria to turn nitrogen from the air into a form that plants can use. No conventional computer can calculate exactly how the process works, but a quantum computer could, says Wibe de Jong, a computational chemist at Lawrence Berkeley National Laboratory in Berkeley, California. “There are lots of catalytic processes that are still very hard to model because of the computational complexity,” he says.
Quantum computers might also aid in the design of materials from their atomic constituents on up. And they could help predict how the superdense matter in neutron stars behaves or how a proton breaks up during a particle collision. Such applications all involve the interplay of the quantum waves that describe subatomic particles. Tracking the oscillating waves swamps a conventional computer, but a quantum computer handles that aspect of a calculation automatically, explains Martin Savage, a nuclear theorist at the University of Washington in Seattle.
Researchers have only begun to figure out how to map such problems onto a quantum computer's qubits. To speed the process, DOE in September 2017 launched two testbeds to enable designers and scientists to work together on approaches to quantum computation. At the Berkeley lab, physicist Irfan Siddiqi and colleagues aim to build their own 64-qubit quantum computer using superconducting qubits. Feedback from users will influence their designs, such has how the qubits are arranged and connected with one another on a chip, Siddiqi says.
In contrast, a testbed at Oak Ridge National Laboratory in Tennessee will provide remote access to existing machines at IBM and IonQ. That approach should spark the same sort of “co-design” without requiring Oak Ridge researchers to build a machine from scratch, says Raphael Pooser, a quantum information scientist at Oak Ridge. It also more closely resembles the way DOE develops its supercomputers in partnership with industry, he says.
In the meantime, commercial machines are getting more powerful. This week, researchers at Google's laboratory in Santa Barbara, California, began testing a 50-qubit chip they think will achieve quantum supremacy, although the experiment could still take months. Yet some researchers worry that such a demonstration may mislead the public into thinking that scientists have reached the end of the road in developing a useful quantum computer. “It's not even the beginning of the road,” Siddiqi says.
John Martinis, the physicist who leads Google's effort, says the company “understands that quantum supremacy is a great milestone and that it will take longer, perhaps much longer, to make something practical.” DOE clearly agrees.
从头看到尾，感觉美国的研究机构对量子计算的研究重点还不是在“造机器”上，而是在寻找能发挥量子特性的算法上，而且还在评价这些算法到底在哪些方面有使价值。美国能源部花在量子计算研究上的钱似乎也是要把好钢用在刀刃上，不闭门造车、而是利用别人的台子唱自己的戏。
从这篇文章，笔者看到了谷歌的50量子的模板。但该文也只是称或许可能实现“量子霸权”，但那也许还要数月。
那么，中国的一个10量子的“量子计算机”，为什么就被看成了领先世界了呢？