The researchers first used a quantum algorithm to solve a complex mathematical problem, which was considered unequal even for the most powerful supercomputers. We are talking about the factorization of the representations of groups – a fundamental operation used in the physics of elementary particles, material science, and data transfer.
The work was performed by scientists of the Los -Alamos National Laboratory by Martin Laroja and the IBM researcher Voyah Khavalichek. The results are published in the journal PHYSICAL ReView letters. Shore showed the possibility of factorization of integers on a quantum computer. Now it is proved that similar methods are applicable to symmetry. In fact, we are talking about the decomposition of complex structures on their “indecent representations” – basic building blocks.
For classical computers, such a task becomes exorbitantly difficult when working with complex systems. The definition of these blocks and the calculation of their number (the so -called “multiplier numbers”) requires colossal computing resources.
The new algorithm is based on quantum converting Fourier – a family of quantum schemes that allow effectively perform transformations that are used in classical mathematics to analyze signals. More about this is stated in a press release from the Los Alamos Laboratory. “Quantum advantage” is the moment when the quantum computer copes with the task that is unattainable for traditional machines. According to them, it is precisely such examples that determine the practical value of quantum technologies.
The article notes that researchers managed to highlight the classes of tasks in the theory of representations that allow effective quantum algorithms. At the same time, a parametric mode is described, where a real increase in performance is possible.
The practical significance of the work is wide. In physics of elementary particles, the method can be used in the calibration of detectors. In the field of data science – when creating reliable codes for correction of errors for storing and transmitting information. In the material science, he helps to understand the properties of substances more and design new materials.
Thus, the work of Larockey and Havlichek expands the list of tasks in which quantum calculations really open new horizons.
As the authors note, the main challenge for science is now simple: it is necessary to determine exactly where quantum computers can bring real benefits and