Combinatorial optimization through variational quantum power method

Combinatorial Optimization through Multiresolution Analysis

Recently, multiresolution analysis and wavelets have had a great impact on computer algorithm design, chieey in the areas of signal processing and compression, computer graphics, and numeric optimization algorithms. Of the algorithms that have beneetted, Meyers mul-tiresolution polygon tiling algorithm is unique in that it solves a combinatorial optimization problem. This paper suggests a gener...

Quantum adiabatic optimization and combinatorial landscapes.

In this paper we analyze the performance of the Quantum Adiabatic Evolution algorithm on a variant of the satisfiability problem for an ensemble of random graphs parametrized by the ratio of clauses to variables, gamma=M/N . We introduce a set of macroscopic parameters (landscapes) and put forward an ansatz of universality for random bit flips. We then formulate the problem of finding the small...

Variational Methods in Combinatorial Optimization and Phylogeny Reconstruction

Considering Stochastic and Combinatorial Optimization

Here, issues connected with characteristic stochastic practices are considered. In the first part, the plausibility of covering the arrangements of an improvement issue on subjective subgraphs is studied. The impulse for this strategy is a state where an advancement issue must be settled as often as possible for discretionary illustrations. Then, a preprocessing stage is considered that would q...

Combinatorial Optimization through Statistical Instance-Based Learning

Different successful heuristic approaches have been proposed for solving combinatorial optimization problems. Commonly, each of them is specialized to serve a different purpose or address specific difficulties. However, most combinatorial problems that model real world applications have a priori well known measurable properties. Embedded machine learning methods may aid towards the recognition ...