28 citations · 63 across the 9 of their papers we have counts for
9 papers
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…
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…
Improving Quantum and Classical Decomposition Methods for Vehicle Routing
Laura S. Herzog, Friedrich Wagner, Christian Ufrecht +4
Quantum computing is a promising technology to address combinatorial optimization problems, for example via the quantum approximate optimization algorithm (QAOA). Its potential, ho…
Quantum and classical correlations in shrinking algorithms for optimization
Victor Fischer, Maximilian Passek, Friedrich Wagner +3
Understanding the benefits of quantum computing for solving combinatorial optimization problems (COPs) remains an open research question. In this work, we extend and analyze algori…
Efficient Encodings of the Travelling Salesperson Problem for Variational Quantum Algorithms
Manuel Schnaus, Lilly Palackal, Benedikt Poggel +4
Routing problems are a common optimization problem in industrial applications, which occur on a large scale in supply chain planning. Due to classical limitations for solving NP-ha…
Efficient learning of Sparse Pauli Lindblad models for fully connected qubit topology
Jose Este Jaloveckas, Minh Tham Pham Nguyen, Lilly Palackal +2
The challenge to achieve practical quantum computing considering current hardware size and gate fidelity is the sensitivity to errors and noise. Recent work has shown that by learn…
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…
Quantum-Assisted Solution Paths for the Capacitated Vehicle Routing Problem
Lilly Palackal, Benedikt Poggel, Matthias Wulff +3
Many relevant problems in industrial settings result in NP-hard optimization problems, such as the Capacitated Vehicle Routing Problem (CVRP) or its reduced variant, the Travelling…
Quantum Computing Techniques for Multi-Knapsack Problems
Abhishek Awasthi, Francesco Bär, Joseph Doetsch +16
Optimization problems are ubiquitous in various industrial settings, and multi-knapsack optimization is one recurrent task faced daily by several industries. The advent of quantum…