collaborators

5 papers

quant-ph2026

Constraint Preserving XY-Mixers under Trotterized Adiabatic Evolution

Abhishek Awasthi, Maximilian Hess, Salome Lomadze +2

Constraint handling is a central challenge for quantum algorithms applied to combinatorial optimization. Standard penalty-based approaches increase problem size, distort energy lan…

quant-ph2026

A Nested Amplitude Amplification Protocol for the Binary Knapsack Problem

Laurin Demmler, Maximilian Hess

Amplitude Amplification offers a provable speedup for search problems, which is leveraged in combinatorial optimization by Grover Adaptive Search (GAS). The protocol demands deep c…

quant-ph2026

Benchmarking Techniques for Decoded Quantum Interferometry

Leon Bollmann, Maximilian Hess

We develop a new benchmarking scheme for the Decoded Quantum Interferometry (DQI) algorithm quantifying the number of quantum gates required to obtain an optimal solution to a prob…

quant-ph2026

Grover Adaptive Search with Problem-Specific State Preparation

Maximilian Hess, Lilly Palackal, Abhishek Awasthi +5

Grover's search algorithm is one of the basic building block in the world of quantum algorithms. Successfully applying it to combinatorial optimization problems is a subtle challen…

quant-ph2025

Constraint-oriented biased quantum search for linear constrained combinatorial optimization problems

Sören Wilkening, Timo Ziegler, Maximilian Hess

In this paper, we extend a previously presented Grover-based heuristic to tackle general combinatorial optimization problems with linear constraints. We further describe the introd…