Although computers are overwhelmingly digital today, there’s a good point to be made that analog computers are the more efficient approach for specific applications. The authors behind a recent paper ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

Abstract: Recently, neural combinatorial optimization (NCO) methods have been prevailing for solving multiobjective combinatorial optimization problems (MOCOPs). Most NCO methods are based on the ...

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...

Abstract: Programmable quantum systems utilizing Rydberg atoms have recently been shown to efficiently encode combinatorial optimization problems. The relationships among the variables in these ...

The objective of the 3D-SCALO problem is to assign the given components to optimal mounting surfaces and position them at the best locations, while satisfying the requirements for (1) heat dissipation ...

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

Researchers from the Department of Electrical Engineering at Tokyo University of Science in Japan have developed what “a novel approach” to combinatorial optimisation problems (COPs). COPs are ...