6 papers
Comparing Qubit and Qudit Encodings for EV Charging and Trip Assignment Problems
Linus Ekstrøm, Hao Wang, Sebastian Schmitt
Variational quantum algorithms have attracted attention for their potential to solve combinatorial optimization problems. We study how the choice of encoding affects the resource r…
Enabling Low-Latency Machine learning on Radiation-Hard FPGAs with hls4ml
Katya Govorkova, Julian Garcia Pardinas, Vladimir Loncar +5
This paper presents an end-to-end demonstration of a viable, ultra-fast, radiation-hard machine learning (ML) application on FPGAs, which could be used in future high-energy physic…
Improving Quantum Multi-Objective Optimization with Archiving and Substitution
Linus Ekstrøm, Takafumi Hosogi, Xavier Bonet-Monroig +3
Finding optimal solutions of conflicting objectives is a daily matter in many industrial applications, with multi-objective optimization trying to find the best solutions to them.…
Machine learning with minimal use of quantum computers: Provable advantages in Learning Under Quantum Privileged Information (LUQPI)
Vasily Bokov, Lisa Kohl, Sebastian Schmitt +1
Quantum machine learning (QML) is often listed as a promising candidate for useful applications of quantum computers, in part due to numerous proofs of possible quantum advantages.…
Variational Quantum Multi-Objective Optimization
Linus Ekstrom, Hao Wang, Sebastian Schmitt
Solving combinatorial optimization problems on near-term quantum devices has gained a lot of attraction in recent years. Currently, most works have focused on single-objective prob…
Inequality constraints in variational quantum circuits with qudits
Alberto Bottarelli, Sebastian Schmitt, Philipp Hauke
Quantum optimization is emerging as a prominent candidate for exploiting the capabilities of near-term quantum devices. Many application-relevant optimization tasks require the inc…