Abstract: Ising machines are next-generation computers expected to efficiently sample near-optimal solutions of combinatorial optimization problems. Combinatorial optimization problems are modeled as ...

Cheng, R. , Liu, J. , Hao, L. and Wu, D. (2026) On the Application of the Infinitesimal Method to Two Categories of Problems in College Physics. Open Journal of Social Sciences, 14, 378-389. doi: ...

NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. In October 2024, news broke that Facebook parent company Meta had cracked an "impossible" problem ...

Abstract: Several real-world applications introduce derivativefree optimization problems, called variable dimension problems, where the problem's dimension is not known in advance. Despite their ...

Defect lead Emanuel Palalic thinks leaning into this mindset from early development will leave the game optimized as well as pretty. When you purchase through links on our site, we may earn an ...

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 ...

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 ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

In the late 19th century, Karl Weierstrass invented a fractal-like function that was decried as nothing less than a “deplorable evil.” In time, it would transform the foundations of mathematics.

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...