Quantum computers are currently small in scope compared to traditional digital computers. However, their ability to consider multiple possibilities simultaneously makes them valuable for solving complex computational problems. On Wednesday, IBM researchers announced a method to manage the unreliability of quantum computers, leading to more reliable and useful answers. This advancement is seen as a crucial step towards serious quantum algorithmic design.
While Google claimed to have achieved “quantum supremacy” in 2019, IBM’s researchers say their achievement is new and more useful. They believe we are entering a phase of quantum computing called “utility” where quantum computers can solve big, complex problems in fields like chemistry and materials science that are currently out of reach.
Quantum computers differ from traditional digital computers in that they perform calculations on qubits which can be in a superposition of states, representing both 1 and 0 simultaneously. This allows quantum computers to perform multiple calculations at once, while digital computers perform calculations separately. By accelerating computation, quantum computers have the potential to revolutionize fields like chemistry and materials science. However, they also pose a threat to privacy through algorithms that can break encrypted communications.
IBM’s research team used a quantum processor with 127 qubits to simulate the behavior of atom-scale bar magnets in a magnetic field. This simulation, known as the Ising model, is used to study magnetism and is too complex for traditional computers to solve precisely. The quantum computer completed the calculation in less than a thousandth of a second, despite the inherent unreliability of quantum calculations due to quantum noise. The researchers were able to mitigate the effects of this noise and obtain an accurate answer by running the calculation multiple times and extrapolating the result in the absence of noise.
To evaluate the accuracy of their quantum calculations, the IBM team compared them to classical algorithms used by physicists at the University of California, Berkeley. In cases where both the quantum and classical algorithms produced different answers, the quantum one proved to be correct. However, it is still unclear if quantum computing is definitively superior to classical techniques for the Ising model.
While error correction is expected to be the ultimate solution for quantum computing, it is still years away. In the meantime, error mitigation provides a useful interim solution for solving increasingly complex problems beyond the Ising model. IBM’s researchers are now focused on generalizing their approach and applying it to more interesting natural science problems, such as studying exotic materials, accelerating drug discovery, and modeling fusion reactions.
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