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A quantum computer has overtaken a supercomputer in the calculation of a physical problem

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A quantum computer has overtaken a supercomputer in the calculation of a physical problem

Researchers have shown that a quantum computer can solve some physical problems better than a classical supercomputer, even if it makes noise and makes mistakes.

Scientists at IBM Quantum in New York and colleagues at the University of California at Berkeley and Lawrence Berkeley National Laboratory have shown that a quantum computer can produce more accurate results for some types of calculations than a modern “classical” supercomputer. They reported this in the journal Nature.

The researchers compared the performance of the IBM Eagle quantum computer, which contains 127 qubits, and the Summit supercomputer, one of the most powerful in the world. They were solving a problem from the field of quantum mechanics related to determining the energy of the ground state of a system of particles. This problem often arises when studying the quantum properties of superconductors and new electronic materials.

The quantum computer used an algorithm called QAOA (Quantum Approximate Optimization Algorithm), which allows finding approximate solutions to complex optimization problems. The supercomputer used a classic algorithm called QMC (Quantum Monte Carlo), which simulates a quantum system using random numbers.

It turned out that as the complexity of the task increased, the quantum computer continued to give correct answers, while the supercomputer began to make mistakes. This suggests that quantum computers may have an advantage over classical ones for some types of calculations, even though they are prone to noise and errors.

The scientists also applied a technique called error mitigation to reduce the impact of noise on quantum computer results. They showed that this method significantly improves the accuracy of the quantum algorithm and makes it more competitive than the classical one.

“We are entering a mode where a quantum computer can do things that current algorithms on classical computers cannot do,” said study co-author Sajant Anand, a graduate student at the University of California at Berkeley.

“We can start thinking about quantum computers as a tool for studying problems that we wouldn’t be able to study otherwise,” added Sarah Sheldon, senior manager of quantum theory and capabilities at IBM Quantum.



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