Three principles of quantum computing

TL;DR

This paper outlines three fundamental principles of quantum computing, emphasizing modeling approaches, limitations on qubit systems, and the quantum nature of reality, to advance understanding and development of quantum technologies.

Contribution

It introduces three core principles that guide the modeling, limitations, and fundamental quantum properties essential for advancing quantum computing.

Findings

Finite-dimensional models are central to quantum modeling.

Decoherence is treated as a classical memory limitation.

Quantum nonlocality underpins the advantages of quantum devices.

Abstract

The point of building a quantum computer is that it allows to model living things with predictive power and gives the opportunity to control life. Its scaling means not just the improvement of the instrument part, but also, mainly, mathematical and software tools, and our understanding of the QC problem. The first principle of quantum modeling is the reduction of reality to finite-dimensional models similar to QED in optical cavities. The second principle is a strict limitation of the so-called Feynman principle, the number of qubits in the standard formulation of the QC. This means treating decoherence exclusively as a limitation of the memory of a classical modeling computer, and introducing corresponding progressive restrictions on the working area of the Hilbert space of quantum states as the model expands. The third principle is similarity in processes of different nature. The quantum nature of reality is manifested in this principle; its nature is quantum nonlocality, which is the main property that ensures the prospects of quantum physical devices and their radical advantage over classical ones.