IMPROVEMENT OF COMPUTATIONAL ALGORITHMS IN BIOSYSTEMS USING QUANTUM COMPUTERS

Unlocking the gene potential of both humans and plants is an unsolvable task for existing computers, so many problems are solved in a roundabout way. The problems of high-speed processing of large data sets, studying the structure of proteins and the human genome, or modeling complex physical systems are still relevant due to the slowness of classical computers. The potential of quantum computers was investigated in the work using a theoretical experiment to assemble the human genome. A classical computer with an AMD A10 4600M processor with 4 cores and a quantum computer with a Bristlecone processor with 72 qubits act as comparison elements. It was found that the quantum device was 3.69 1014 times faster than the classical one, and conclusions were made about the potential application of this technology. An approach to improving computational algorithms in biosystems on quantum computers using the example of one qubit by creating an ideal quantum computer with a constant coherent state was proposed, i.e. in such a computer there is no influence of the external environment leading to decoherence. Thus, external signals that set the calculation parameters will carry out precise control of the calculation. The state of the ideal quantum computer changes under the action of some computational transformation according to the formed algorithm at each moment of time. From a formal point of view, such transformations have the form U ⊗ I, where U is the matrix acting on the selected qubits or qubit, I is the identity matrix acting on the remaining qubits. The resulting quantum algorithm implies the sequential application of such transformations from one qubit to another.