Abstract: Iterative gradient-based optimization algorithms are widely used to solve difficult or large-scale optimization problems. There are many algorithms to choose from, such as gradient descent ...

Abstract: Many applications, from logistics to social networks, rely on quickly navigating the shortest pathways inside large-scale graphs. For shortest route finding in huge data settings, this study ...

In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum ...