5 papers
Approximate Sparse State Preparation with the Grover-Rudolph Algorithm
Debora Ramacciotti, Martin Steinbach, Bence Temesi +2
Sparse quantum state preparation is a common subroutine in quantum algorithms, where classical data with few nonzero entries must be loaded into a quantum state. In this work, we c…
Use case study: benchmarking quantum breadth-first search for maximum flow problems
Andreea-Iulia Lefterovici, Lara Lelakowski, Michael Perk
The maximum flow problem asks to find the largest possible flow from a source to a sink in a capacitated network. It arises frequently in scheduling, project selection, and as a co…
A quantum search method for quadratic and multidimensional knapsack problems
Sören Wilkening, Andreea-Iulia Lefterovici, Lennart Binkowski +5
Solving combinatorial optimization problems is a promising application area for quantum algorithms in real-world scenarios. In this work, we extend the "Quantum Tree Generator" (QT…
Beyond asymptotic scaling: Comparing functional quantum linear solvers
Andreea-Iulia Lefterovici, Michael Perk, Debora Ramacciotti +3
Solving systems of linear equations is a key subroutine in many quantum algorithms. In the last 15 years, many quantum linear solvers (QLS) have been developed, competing to achiev…
A quantum algorithm for solving 0-1 Knapsack problems
Sören Wilkening, Andreea-Iulia Lefterovici, Lennart Binkowski +3
Here we present two novel contributions for achieving quantum advantage in solving difficult optimisation problems, both in theory and foreseeable practice. (1) We introduce the "Q…