2 citations · 7 across the 7 of their papers we have counts for
7 papers · 1 filter
Improved quantum lower and upper bounds for matrix scaling
Sander Gribling, Harold Nieuwboer
Matrix scaling is a simple to state, yet widely applicable linear-algebraic problem: the goal is to scale the rows and columns of a given non-negative matrix such that the rescaled…
Improving quantum linear system solvers via a gradient descent perspective
Sander Gribling, Iordanis Kerenidis, Dániel Szilágyi
Solving systems of linear equations is one of the most important primitives in quantum computing that has the potential to provide a practical quantum advantage in many different a…
Quantum algorithms for matrix scaling and matrix balancing
Joran van Apeldoorn, Sander Gribling, Yinan Li +3
Matrix scaling and matrix balancing are two basic linear-algebraic problems with a wide variety of applications, such as approximating the permanent, and pre-conditioning linear sy…
The Haemers bound of noncommutative graphs
Sander Gribling, Yinan Li
We continue the study of the quantum channel version of Shannon's zero-error capacity problem. We generalize the celebrated Haemers bound to noncommutative graphs (obtained from qu…
Semidefinite programming formulations for the completely bounded norm of a tensor
Sander Gribling, Monique Laurent
We show that a certain tensor norm, the completely bounded norm, can be expressed by a semidefinite program. This tensor norm recently attracted attention in the field of quantum c…
Simon's problem for linear functions
Joran van Apeldoorn, Sander Gribling
Simon's problem asks the following: determine if a function is one-to-one or if there exists a unique such that $f(x) = f(x \…