1 citations · 1 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
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…
Effective Embedding of Integer Linear Inequalities for Variational Quantum Algorithms
Maximilian Hess, Lilly Palackal, Abhishek Awasthi +1
In variational quantum algorithms, constraints are usually added to the problem objective via penalty terms. For linear inequality constraints, this procedure requires additional s…
Realistic Runtime Analysis for Quantum Simplex Computation
Sabrina Ammann, Maximilian Hess, Debora Ramacciotti +10
In recent years, strong expectations have been raised for the possible power of quantum computing for solving difficult optimization problems, based on theoretical, asymptotic wors…
Graph-controlled Permutation Mixers in QAOA for the Flexible Job-Shop Problem
Lilly Palackal, Leonhard Richter, Maximilian Hess
One of the most promising attempts towards solving optimization problems with quantum computers in the noisy intermediate scale era of quantum computing are variational quantum alg…