This article is produced by NetEase Smart Studio (public number smartman 163). Focus on AI and read the next big era! [Netease smart news August 9 news] salesman Tom will soon be on the road for a one-month journey, visit customers and sales prospects, he will travel to the United States 50 places. Tom needs to optimize this trip with three priorities. First, he must maximize the time for each customer. Second, he must complete the trip in the shortest distance possible. Finally, he must minimize the cost of doing this. This classic "travel salesman problem" has lasted for decades, and the quantum computer can solve it in a few seconds. Path optimization is a bright spot for quantum computers, but it also models chemical compounds, discovers patterns in DNA sequences, optimizes financial combinations, and predicts weather. The use of quantum computers will also be more secure and effective than traditional self-driving cars, and this technology may also completely change the insurance industry's risk analysis. In short, the more complex the problem, the more variables involved, the better the quantum computation will be. This is why the scientists have been pursuing this field for more than 35 years in this field. More and more evidence shows that quantum computing is approaching reality. Investment capital is flowing into the market, and some quantum computer developers are discussing the prototype of a supercomputer-class system as soon as next year. Quantum startup company IonQ said that last month the company had completed a financing of 22 million US dollars, the goal is to create a universal quantum processor within 12 months. This is the second time this year's startup companies have obtained large sums of money this year. In March of this year, Rigetti Computer Company stated that it had raised US$64 million. It is expected that a machine will be displayed next year, and in some missions it will surpass the world’s largest supercomputer. In March of this year, IBM installed a quantum processor on its public cloud and invited researchers to experiment with it. Previously, D-Wave Systems announced that it would sell a huge quantum computer to an unnamed customer for $15 million. In July of this year, a report said that Google also plans to provide researchers with new quantum computing technology through cloud services. Just three years ago, experts were still debating whether quantum computers could be built. The consensus now is that this is only a matter of time, not just a matter of time. "For the coherent and capable system, the major obstacles have been solved," said Andrew Bestwick, Rigetti Engineering Director. "The main challenge now is how to use the demonstration on a small system and realize it in a highly scalable form. it." This may also open up a lucrative new market. At present, its scale is small, but its growth rate is very fast. Market research firm expects that by 2022 the annual sales of quantum computers will increase by 24% to nearly 2.5 billion U.S. dollars. Market research media companies are more optimistic and expect to have annual sales of 5 billion U.S. dollars in 2020. Great timing Moore's Law has driven the development of the computer industry for more than 50 years, but it seems to have finally lost momentum. Quantum computers can open a new era of computing power. This is what we urgently need. The Internet of Things is expected to make the network more complex. As a result, we need a new approach to network management. This is a task that is very suitable for quantum technology. In addition, the explosive growth of Internet of Things data requires new analytical methods to analyze all of this. And organizations that are looking for new efficiencies and revenues to seek digital transformation will find that quantum technology opens up tremendous new opportunities. Does this mean that it is time to hang a "sale" sign on these Intel servers? not yet. People in the front lines of quantum computers say that users are expected to see tangible benefits in the next few years, but those boasting machines capable of cracking 256-bit encryption codes in a matter of seconds will still take 10 years or more to be realized. D-Wave is currently the only company that transports commercial quantum computers. Experts question whether its technology is really a "real" quantum computer. Large companies such as IBM, Google, and Microsoft have all established their own plans, but the market is fragmented and has no leader. There are still many arguments about architectural details. But it is too early to think about the problems that quantum technology can solve, such as the task of optimizing traffic routes, mapping molecular interactions, optimizing stock market portfolios, and forecasting the complexity of the index. This requires understanding the difference between the median and qubits of quantum computing. Bits and qubits The principle of quantum mechanics is still very confusing to most people, so experts tend to use traditional calculation methods to describe computing technology. The mainstream digital computer is based on binary arithmetic, where the numbers are represented as a combination of 1 and 0. Using these binary numbers or binary numbers for the calculations is very slow, but it has the advantage that the transistors can be used very well whether they are on or off. When you throw enough transistors on a problem, they can complete binary operations at a dazzling speed. This is how binary digital computers work. Traditional computer technology excels at quickly calculating large amounts of data, but they do not adapt well to the problems of multiple interdependent variables, such as travel salesman problems. This also brings a place for quantum computers. Qubits are bits of a quantum, but they are much more complex. One bit is 0 or 1, and the qubit can be 0, 1 or other. Other things can be 1/2, 9/16, 123/128, or other points on multi-dimensional axes. If there is a horizontal line, then a qubit is a sphere that contains the x, y, and z axes, and the ability to represent data anywhere in the sphere. This concept is usually expressed as an inflated sphere (pictured). This "superpositioning" feature allows qubits to represent complex sets of problems that binary computers can't do. Another important difference in quantum computers is what is called "entanglement" or the ability of qubits to relate to each other, so everyone can recognize the state of all other things. This means that quantum computers grow exponentially with the increase of qubits. Therefore, theoretically, the power of a 200 qubit system is 200 times the square of the 100 qubit system. In contrast, traditional digital computers have grown linearly. Experts generally believe that quantum computers with 30 qubits or smaller can still be surpassed by traditional digital computers, but when the density exceeds 30 qubits, the situation will change. You need a fairly large IBM Power system to simulate a 30-qubit device. When it comes to 40 or 45 qubits, you need the world's largest supercomputer. "Scott Crowder, vice president and chief technology officer of IBM's quantum computing technology strategy and transformation. Extremely complex challenges But qubits also bring some major challenges, the most important of which is reliability. Computers always make mistakes, including hardware failures, environmental factors, and power changes. These errors are easily corrected in digital computers using simple verification techniques such as checksums. Qubits are much more complex and are therefore more fragile than bits. In some quantum models, qubits tend to change state rapidly, leading to frequent errors. Over the years, how to solve this so-called "consistency" problem has plagued developers. "If you have a second calculation and your consistency disappears within 100 microseconds, then you will not have the power of quantum computing," said Eric O'Connell CEO. "Then the results will be wrong." Making the problem more complicated is the interdependence of qubits, which makes it more difficult to measure and isolate errors. In fact, the process of measuring a qubit causes it to go into an error state, IBM's Claude said. In the second half of 2015, IBM announced a major breakthrough in resolving qubit error corrections and scalability problems. It has successfully used qubits to solve each other's mistakes, but the solution is not perfect because it requires 1000 or more qubits to monitor individual errors. This problem not only inhibits performance issues but also limits scalability. Another issue developers are solving is the control of heat. Most lattice-based methods require supercooling, which limits the data center environment. For example, D-Wave's 700-cubic foot process engine (left) is a cryogenic refrigeration unit that cools the quantum processor to temperatures 180 times lower than interstellar space. IBM and Rigetti are also pursuing superconductor systems that require extremely low temperatures. IonQ Corporation has a different method called "trap ion", which uses a laser to cool and separate individual ions. This makes the qubits easier to control and therefore more predictable. The company expects that trapped-ion technology will allow its computers to run at room temperature, although prototypes have not yet been manufactured. A misunderstanding A common misconception about quantum computers is that they will replace digital computers. In fact, these two architectures are suitable for different types of problems. For most common data processing tasks involving basic algorithms, digital computers will always be good solutions for many years to come. Quantum computers are more suited to the problem of increasing the complexity as an index of the number of variables. IonQ's Moehring will use fertilizer production as a quantum computer to solve the problems that traditional computers cannot solve. The answer given by quantum computers is that about 2% of the world's energy is used for fertilizer production. This is an expensive process, and the natural processing is more clever. Understanding how to replicate natural processes requires molecular modeling, an issue that grows exponentially with potential interactions. "Even if it is a moderate-sized molecule, the world's most powerful classic computer cannot simulate its interaction," he said. "And they will never, because traditional computers can't reach a sufficient scale." Another misconception is that there is only one kind of quantum computer. In fact, there are several types. Most commercial activities are concentrated on three architectures. The quantum gate model was developed in different ways by Rigetti, IonQ, and IBM (pictured). It is flexible enough to be programmed to adapt to different usage scenarios. Error correction is one of the biggest drawbacks of the quantum gate model. IonQ is using trapped ion technology to solve this problem, while Rigetti and IBM are pursuing superconducting qubits. The quantum annealing model used by D-Wave has a stability advantage but is considered more flexible than the quantum gate model. The topological quantum model proposed by Microsoft Corporation is considered to have the highest technological content among the three. It combines flexibility with low error rates, but at this point, its shortcomings are only theoretical: no one has ever been built. The market is so new that there is almost no consensus. Which method is best, and participants are still discussing fiercely the definition and advantages of "pure" quantum computing. The company that is currently shipping the commercial quantum processor D-Wave has adopted the quantized method, which has caused considerable controversy. "The weakness of D-Wave is that you need to map the problem to a fixed function," said IBM's Crowder. "I don't know if it will have advantages over traditional computers, but as long as they show commercial value, the others are not important." Ricketti's Bestwick agrees. He said: "It's like a special-purpose ASIC (application-specific integrated circuit) that can only do one thing and one thing." D-Wave's Brownell refuted this criticism because competitors ignored the fact that they had no products in order to divert people's attention. He said that D-Wave's method is as scalable and flexible as other solutions. D-Wave pointed out his 140 U.S. patents and more than 90 peer-reviewed papers as evidence. He said: "Other people are trying to do a more mathematical or theoretically purer quantum calculations, but they will take years to solve some of these simple problems." "We are the only people with real customers." As evidence of the feasibility of the D-Wave method, he mentioned the company's continued scalability. The first machine launched in 2011 contained 128 qubits. The new 2000Q qubit is 2000, an increase of 15 times. He cited Google's 2015 discovery that in a Monte Carlo simulation, a D-Wave machine was 100 million times faster than a single-core computer. He said: “The machines we ship today are stronger than our first-time machines. Hundreds of thousands of times." The next five years In the next three to five years, quantum computing is unlikely to be used in applications outside the core science. But then, 50 quantum gate processors should begin to enter the market. IBM said it will develop commercial hardware in the next few years. "It won't take a long time," he said. "We are at the cusp of the storm." IonQ's Moehring believes that the systems his company will build in 2022 "are unlikely to solve very large molecular dynamics or optimization problems, but they will create a road map for us to find these applications." Rigetti's Bestwick said, His company's first commercial system is likely to be a hybrid car, "using classical computers for some applications of classical computers, and using quantum computing to solve unsolvable parts." In the field of information technology, currently focused on abstracting all possible hardware functions into software, the quantum computer industry is still firmly rooted in metal hardware. There is no standard, no equivalent processor platform, no reference architecture. Each supplier is launching its own solution and supporting software. Does this mean that a company will dominate the field of quantum computing like IBM in the 1980s? But IBM's chief representative did not think so. He said: "Companies like IBM provide complete services, but we also need third parties. They have a very intuitive understanding of the areas of corporate customers." "We have made a lot of efforts for the development of the system." Crowder said that system software-level programming will require expertise, but he expects that application developers will be able to switch to quantum more easily. He said: "You don't need to be a quantum expert to write code for quantum computers." "You can download Python notes from GitHub to accomplish this task." Until these platform issues are resolved, the application will mainly be written by hand. Andrew Schon, head of the venture capital firm New Business Association, said it is too early to bet on packaged software. "It was like investing in Amazon before Fairchild was founded," he said. But as a major investor in IonQ, NEA is putting money into his mouth. "The role of venture capital is to invest in people and companies that have the opportunity to dramatically improve the future," he said. "Quantum computing fits perfectly in this framework." If the current trend continues, it will also increasingly meet the mainstream enterprise's processing framework. In 37 years after the quantum mechanics model was first published, salesman Tom may soon begin his ultimate journey. (Selected from: Silicon Angle Author: PAUL GILLIN compile: NetEase see foreign intelligence platform compiler revision: Towers) Pay attention to NetEase smart public number (smartman163), get the latest report of artificial intelligence industry.