Algorithmic complexity, a cornerstone of theoretical computer science, examines the intrinsic resource requirements of computational problems and the limits of what can be efficiently computed. Within ...

Complexity theory is a fundamental branch of theoretical computer science that categorises computational problems according to their inherent difficulty and the resources required to solve them. At ...

In computational complexity theory, P and NP are two classes of problems. P is the class of decision problems that a deterministic Turing machine can solve in polynomial time. In useful terms, any ...

WEST LAFAYETTE, Ind. — In 2019, Google claimed it was the first to demonstrate a quantum computer performing a calculation beyond the abilities of today’s most powerful supercomputers. But most of the ...

Promising results and future work The impact of the research goes well beyond the technical breakthrough itself. The algorithm's efficient polynomial complexity allows it to scale with system size, ...

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape. How fundamentally difficult is a problem?

SAS/INSIGHT software provides nonparametric curve-fitting estimates from smoothing spline, kernel, loess, and fixed bandwidth local polynomial estimators that are alternatives to fitting polynomials.

Rice quantum computing researchers have introduced a novel algorithm that earned the team a place in the global XPRIZE Quantum Applications competition.

The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...