We study the problem of estimating the size of a maximum matching in sublinear time. The problem has been studied extensively in the literature and various algorithms and lower bounds are known for it ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

A new wave of “reasoning” systems from companies like OpenAI is producing incorrect information more often. Even the companies don’t know why. Credit...Erik Carter Supported by By Cade Metz and Karen ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates rule-based optimization with preference-based optimization for LLM reasoning tasks 🤖🧠. As a ...

Abstract: Finding the shortest vector in a lattice is a NP-hard problem. The best known approximation algorithm for this problem is LLL algorithm with the approximation factor of αn-1\2, α≥4\3, which ...

1 Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, RJ, Brazil 2 Petróleo Brasileiro S.A., Centro de Pesquisas Leopoldo Miguez de Mello, Rio de Janeiro, Brazil Recent advancements in quantum ...

An international research team has developed a particle swarm optimization (PSO) algorithm based on quantum computing for real-time maximum power point tracking (MPPT) implementation in PV systems.

Computer scientists have written a network flow algorithm that computes almost as fast as is mathematically possible. This algorithm computes the maximum traffic flow with minimum transport costs for ...