Iontronics is a newly emerging interdisciplinary concept which bridges electronics and
ionics, covering electrochemistry, solid‐state physics, electronic engineering, and biological …

We provide Ising formulations for many NP-complete and NP-hard problems, including all of
Karp's 21 NP-complete problems. This collects and extends mappings to the Ising model …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …

This survey describes probabilistic algorithms for linear algebraic computations, such as
factorizing matrices and solving linear systems. It focuses on techniques that have a proven …

Supervised machine learning is the classification of new data based on already classified
training examples. In this work, we show that the support vector machine, an optimized …

The usual way to reveal properties of an unknown quantum state, given many copies of a
system in that state, is to perform measurements of different observables and to analyse the …

A number of problems in probability and statistics can be addressed using the multivariate
normal (Gaussian) distribution. In the one-dimensional case, computing the probability for a …

Algorithms have never been more important. As the recipes of computer programs,
algorithms rule our lives. Although they can be forces for both good and evil, this is not a …

Low-rank matrix approximations, such as the truncated singular value decomposition and
the rank-revealing QR decomposition, play a central role in data analysis and scientific …

Randomized algorithms for very large matrix problems have received a great deal of
attention in recent years. Much of this work was motivated by problems in large-scale data …