IBM has discovered a breakthrough in quantum computing: solving a complex problem that supercomputing approximation methods could not handle. This discovery can lead to being able to use quantum systems to solve intractable problems in artificial intelligence and subjects such as chemistry.
A quantum is a small, discrete unit of phenomenon. For example, an electron is a quantum of electricity. Quantum computing specifically is a new technology that uses quantum mechanics to solve problems that classical computers are not capable of. It uses subatomic particles to perform calculations instead of using electrical signals. Furthermore, quantum computing uses quantum bits, or qubits, as opposed to binary bits. Binary bits are used in most classical daily-use computers, and they store a single unit of information that has a value of zero or one. Qubits are different as they are a two-state system, meaning they can hold a value of zero, one, or a superposition of both. Quantum computers are necessary to calculate complex problems. Some examples include identifying subtle patterns of fraud in financial transactions and new physics in a supercollider. However, quantum computers always require some form of quantum error correction, as it yields an error margin of 0.00005.
In this new cutting-edge field of quantum computing, IBM wanted to test a 127-qubit Eagle quantum computer. To do this, they had to obtain accurate results from an error-prone quantum computer and confirm that the answer given was correct. IBM wanted to simulate the Ising model, which represents the moments of atomic spins. Precisely, IBM wanted to calculate the magnetization of this system. This study was essential to understanding ferromagnetism, liquid-gas phase transitions, and protein folding. Regarding the Ising model, IBM stated, “Although such a problem is well-suited for quantum computing due to its variable dynamics and a tremendous range of potential scenarios, it has previously remained out of reach of quantum computation due to the error-prone and noisy state of today’s quantum computers.”
To correct the large margin of error from quantum computers, IBM used Zero Noise Extrapolation to reduce bias. The noise was increased between 20 and 60% and then extrapolated back to the expected value at zero noise. Dr. Abhinav Kandala, Research Manager of Quantum Capabilities and Demonstrations at IBM, said, “We were only able to do this because we’ve now built a quantum system of unprecedented scale and quality and developed the ability to manipulate noise on a quantum system at this scale.” IBM also hired experts in classical computation methods at the University of California Berkeley. The experts ran the same problem on classical supercomputers at the Lawrence Berkeley National Laboratory. They used brute-force simulations due to the lower level of complexity. The result they produced matched the answer found by the quantum computer at IBM.
This experiment proved that increasingly difficult computations could not be performed using classical methods. The performance of the quantum methods was confirmed by classical approximations, which showed that quantum computers were giving more accurate answers. While IBM cannot verify results at high levels of complexity, matching results at lower complexity gives hope for the future. IBM has also issued a statement that: “this does not prove quantum computers are now better than classical systems.” The current state has been deemed “quantum utility,” which means quantum computing can be used to solve real-world problems.
With this breakthrough in quantum computing, IBM scientists remain hopeful for future innovation. IBM plans to have a quantum system with over 100,000 qubits within the next ten years. This will lead to significant advancements in all aspects of life, and the possibilities for knowledge will expand tenfold.
