activity
20242026
collaborators

5 papers

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…

cs.LG2025

Generative-enhanced optimization for knapsack problems: an industry-relevant study

Yelyzaveta Vodovozova, Abhishek Awasthi, Caitlin Jones +4

Optimization is a crucial task in various industries such as logistics, aviation, manufacturing, chemical, pharmaceutical, and insurance, where finding the best solution to a probl…

quant-ph2024

Polynomial Reduction Methods and their Impact on QAOA Circuits

Lukas Schmidbauer, Karen Wintersperger, Elisabeth Lobe +1

Abstraction layers are of paramount importance in software architecture, as they shield the higher-level formulation of payload computations from lower-level details. Since quantum…

quant-ph2024

Ion-Based Quantum Computing Hardware: Performance and End-User Perspective

Thomas Strohm, Karen Wintersperger, Florian Dommert +6

This is the second paper in a series of papers providing an overview of different quantum computing hardware platforms from an industrial end-user perspective. It follows our first…

quant-ph2024

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…