A concept developed for computer science could have a key role in fundamental physics — and point the way to a new understanding of space and time. When physicist Leonard Susskind gives talks these ...

The computational complexity of voting systems examines the algorithmic effort required to determine outcomes, resist strategic interventions and safeguard democratic processes. Central to this field ...

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 ...

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 ...

A major advance reveals deep connections between the classes of problems that computers can — and can’t — possibly do. At first glance, the big news coming out of this summer’s conference on the ...

Our research area encompasses the study of computation, computational models, computational complexity, algorithm design, algorithm verification, combinatorial optimization, computational biology and ...

Computational neuroscientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the complexity of single brain cells. Our mushy brains seem ...

Nobel laureate economist Richard Thaler famously quipped: People aren’t dumb, the world is hard. Indeed, we routinely encounter problems in our everyday lives that feel complex – from choosing the ...

Marco Nicotra joined the CU Boulder faculty in 2018. He completed a double degree program in 2012, receiving an MS in mechanical engineering from Politecnico di Milano and an MS in electromechanical ...

MIP * = RE is not a typo. It is a groundbreaking discovery and the catchy title of a recent paper in the field of quantum complexity theory. Complexity theory is a zoo of “complexity classes” – ...