This year has left mathematicians reeling as AI models are increasingly solving seemingly intractable maths problems. Terence ...

A million-dollar math mystery may someday be resolved in a physics lab. A new study brings this vision one step closer.

LLMs and classical optimization have been treated as separate tools. The teams pulling ahead use them together.

D-Wave quantum supremacy challenged: Flatiron Institute physicists showed that a classical algorithm using 3D tensor networks and a revived 1982 belief propagation method can match spin glass dynamics ...

Timely reconstruction of epidemic dynamics is essential for public health, and structured coalescent models constitute an essential tool for this purpose. However, statistical and computational ...

NP-complete for general graphs APX-hard: difficult to approximate within a constant factor Generalizes well-known problems such as maximum clique and subgraph isomorphism ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and solve the long-standing polaron problem, unlocking deeper understanding of ...

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 ...

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 ...

Combinatorial optimisation problems arise in many fields, from logistics and network design to machine learning and bioinformatics. Most classical formulations are NP-hard, rendering exact ...

Abstract: In applied and numerical algebraic geometry, many problems are reduced to computing an approximation to a real algebraic curve. In order to elevate the results of such a computation to the ...