Jian-Wei Pan: ‘The next quantum breakthrough will happen in five years’

Any leap in quantum computing multiplies the potential of a technology capable of performing calculations and simulations that are beyond the scope of current computers while facilitating the study of phenomena that have been only theoretical to date.

Last year, a group of researchers put forward the idea in the journal Nature that an alternative to quantum theory based on real numbers can be experimentally falsified. The original proposal was a challenge that has been taken up by the leading scientist in the field, Jian-Wei Pan, with the participation of physicist Adán Cabello, from the University of Seville. Their combined research has demonstrated “the indispensable role of complex numbers [square root of minus one, for example] in standard quantum mechanics.” The results allow progress to be made in the development of computers that use this technology and, according to Cabello, “to test quantum physics in regions that have previously been inaccessible.”

Jian-Wei Pan, 51, a 1987 graduate of the Science and Technology University of China (USTC) and a PhD graduate of Vienna University, leads one of the largest and most successful quantum research teams in the world, and has been described by physics Nobel laureate Frank Wilczek as “a force of nature.” Jian-Wei Pan’s thesis supervisor at the University of Vienna, physicist Anton Zeilinger, added: “I cannot imagine the emergence of quantum technology without Jian-Wei Pan.”

Pan’s leadership in the research has been fundamental. “The experiment can be seen as a game between two players: real-valued quantum mechanics versus complex-valued quantum mechanics,” he explains. “The game is played on a quantum computer platform with four superconducting circuits. By sending in random measurement bases and measuring the outcome, the game score is obtained which is a mathematical combination of the measurement bases and outcome. The rule of the game is that the real-valued quantum mechanics is ruled out if the game score exceeds 7.66, which is the case in our work.”

Covered by the scientific journal Physical Review Letters, the experiment was developed by a team from USTC and the University of Seville to answer a fundamental question: Are complex numbers really necessary for the quantum mechanical description of nature? The results exclude an alternative to standard quantum physics that uses only real numbers.

According to Jian-Wei Pan: “Physicists use mathematics to describe nature. In classical physics, a real number appears complete to describe the physical reality in all classical phenomenon, whereas a complex number is only sometimes employed as a convenient mathematical tool. However, whether the complex number is necessary to represent the theory of quantum mechanics is still an open question. Our results disprove the real-number description of nature and establish the indispensable role of a complex number in quantum mechanics.”

“It’s not only of interest regarding excluding a specific alternative,” Cabello adds, “the importance of the experiment is that it shows how a system of superconducting qubits [those used in quantum computers] allows us to test predictions of quantum physics that are impossible to test with the experiments we have been carrying out until now. This opens up a very interesting range of possibilities, because there are dozens of fascinating predictions that we have never been able to test, since they require firm control over several qubits. Now we will be able to test them.”

According to Chao-Yang Lu, of USTC and co-author of the experiment: “The most promising near-term application of quantum computers is the testing of quantum mechanics itself and the study of many-body systems.”

Thus, the discovery provides not only a way forward in the development of quantum computers, but also a new way of approaching nature to understand the behavior and interactions of particles at the atomic and subatomic level.

But, like any breakthrough, the opening of a new way forward generates uncertainties. However, Jian-Wei Pan prefers to focus on the positive: “Building a practically useful fault-tolerant quantum computer is one of the great challenges for human beings,” he says. “I am more concerned about how and when we will build one. The most formidable challenge for building a large-scale universal quantum computer is the presence of noise and imperfections. We need to use quantum error correction and fault-tolerant operations to overcome the noise and scale up the system. A logical qubit with higher fidelity than a physical qubit will be the next breakthrough in quantum computing and will occur in about five years. In homes, quantum computers would, if realized, be available first through cloud services.”

Applications

According to Cabello, “when quantum computers are sufficiently large and have thousands or millions of qubits, they will make it possible to understand complex chemical reactions that will help to design new drugs and better batteries; perform simulations that lead to the development of new materials and calculations that make it possible to optimize artificial intelligence and machine learning algorithms used in logistics, cybersecurity and finance, or to decipher the codes on which the security of current communications is based.”

“Quantum computers,” he adds, “use the properties of quantum physics to perform calculations. Unlike the computers we use, in which the basic unit of information is the bit [which can take two values], in a quantum computer, the basic unit is the quantum bit, or qubit, which has an infinite number of states.”

Cabello goes on to say that “the quantum computers built by companies such as Google, IBM or Rigetti take advantage of the fact that objects the size of a micron and produced using standard semiconductor-manufacturing techniques can behave like qubits.”

The goal of having computers with millions of qubits is still a long way off, since most current quantum computers, according to Cabello, “only have a few qubits and not all of them are good enough.” However, the results of the Chinese and Spanish team’s research make it possible to expand the uses of existing computers and to understand physical phenomena that have puzzled scientists for years.

Time crystal

For example, Google Quantum AI has published the observation of a time crystal through the Sycamore quantum processor for the first time in the Nature journal. A quantum time crystal is similar to a grain of salt composed of sodium and chlorine atoms. However, while the layers of atoms in that grain of salt form a physical structure based on repeating patterns in space, in the time crystal the structure is configured from an oscillating pattern. The Google processor has been able to observe these oscillatory wave patterns of stable time crystals.

This finding, according to Pedram Roushan and Kostyantyn Kechedzhi, shows “how quantum processors can be used to study new physical phenomena. Moving from theory to actual observation is a critical leap and is the basis of any scientific discovery. Research like this opens the door to many more experiments, not only in physics, but hopefully inspires future quantum applications in many other fields.”

In Spain, a consortium of seven companies – Amatech, BBVA bank, DAS Photonics, GMV, Multiverse computing, Qilimanjaro Quantum Tech and Repsol – and five research centers – Barcelona Supercomputing Center (BSC), Spanish National Research Council (CSIC), Donostia International Physics Center (DIPC), The Institute of Photonic Sciences (ICFO), Tecnalia and the Polytechnic University of Valencia (UPV) – have launched a new project called CUCO to apply quantum computing to Spanish strategic industries: energy, finance, space, defense and logistics.

Subsidized by the Center for the Development of Industrial Technology (CDTI) and with the support of the Ministry of Science and Innovation, the CUCO project, is the first major quantum computing initiative in Spain in the business field and aims to “advance the scientific and technological knowledge of quantum computing algorithms through public-private collaboration between companies, research centers and universities.” The goal is for this technology to be implemented in the medium-term future.