The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic research in the design, development, analysis, and scalability of randomized algorithms for ...

Combinatorial optimisation algorithms are central to addressing problems in which the goal is to select an optimal solution from a finite set of alternatives. These algorithms have evolved ...

Cambridge, UK, July 22, 2021 – In a development the company said “is likely to set a new industry standard,” scientists at Cambridge Quantum (CQ) have developed a new algorithm for solving ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.

Analysis shows combinatorial approach is more effective than single-gene testing at predicting sertraline metabolism in patients with major depressive disorder SALT LAKE CITY, Feb. 23, 2022 (GLOBE ...

In this graduate-level course, we will be covering advanced topics in combinatorial optimization. We will start with matchings and cover many results, extending the fundamental results of matchings, ...

BERKELEY, Calif., Oct. 03, 2023 (GLOBE NEWSWIRE) -- Rigetti Computing, Inc. (Nasdaq: RGTI) (“Rigetti” or the “Company”), a pioneer in full-stack quantum-classical computing, today announced that it ...

In a new development that is most likely to establish a new industry standard, scientists at Cambridge Quantum (CQ) have created a new algorithm for solving combinatorial optimization problems that ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

The proposed algorithm combines variational scheduling with post-processing to achieve near-optimal solutions to combinatorial optimization problems with constraints within the operation time of ...