## Publication Date

3-2018

## Abstract

It is known that some algorithms are feasible, and some take too long to be practical/ For example, if the running time of an algorithm is 2^{n}, where n = len(x) is the bit size of the input x, then already for n = 500, the computation time exceeds the lifetime of the Universe. In computer science, it is usually assumed that an algorithm A is feasible if and only if it is *polynomial-time*, i.e., if its number of computational steps t_{A}(x) on any input x is bounded by a polynomial P(n) of the input length n = len}(x).

An interesting *encubation* phenomenon is that once we succeed in finding a polynomial-time algorithm for solving a problem, eventually it turns out to be possible to further decrease its computation time until we either reach the cubic time t_{A}(x) ~ n^{3} or reach some even faster time n^{α} for α < 3.

In this paper, we provide a possible physics-based explanation for the encubation phenomenon.

## Comments

Technical Report: UTEP-CS-18-29

Published in

International Journal of Computing and Optimization, 2018, Vol. 5, No. 1, pp. 5-8.