collaborators

6 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

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-ph2026

Quantum Computing -- Strategic Recommendations for the Industry

Marvin Erdmann, Lukas Karch, Abhishek Awasthi +9

This whitepaper surveys the current landscape and short- to mid-term prospects for quantum-enabled optimization and machine learning use cases in industrial settings. Grounded in t…

quant-ph2025

Solving a real-world modular logistic scheduling problem with a quantum-classical metaheuristics

Florian Krellner, Abhishek Awasthi, Nico Kraus +3

This study evaluates the performance of a quantum-classical metaheuristic and a traditional classical mathematical programming solver, applied to two mathematical optimization mode…

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-ph2025

Digitized Counterdiabatic Quantum Algorithms for Logistics Scheduling

Archismita Dalal, Iraitz Montalban, Narendra N. Hegade +7

We study a job shop scheduling problem for an automatized robot in a high-throughput laboratory and a travelling salesperson problem with recently proposed digitized counterdiabati…