Open Research
Explore the future with our open research – Discover insights, innovate with us, and shape the world of tomorrow.
Discover our open research
EnerQuant
Fundamental modeling in energy economics with quantum algorithms.
Within this project we develop solutions for models in energy markets that consist of complex optimization problems including stochastic components. Solutions are prototyped and tested on various quantum hardware. The project is funded by the Federal Ministry of Economics and Technology (BMWK).
QuSAA
Quantum computing for strategic asset allocation.
The project investigates application of quantum algorithms to achieve lower fluctuations of investment portfolios to contribute to the stabilization of companies and thus of the financial system. The project is funded by the Federal Ministry of Education and Research (BMBF)
ATIQ
Financial risk modelling with ion trap quantum computers.
The goal of the joint project is to build a reliable demonstrators of Ion trap quantum computers. Our part is to develop algorithms for credit risk modelling and evaluation using Quantum Monte Carlo methods and gain insights for requirements towards quantum advantage. The project is funded by the Federal Ministry of Education and Research (BMBF)
Learn quantum algorithms
We at JoS have been building quantum algorithms since 2018 (and much earlier in our university lifes ;). Our different algorithms show ways to use quantum systems, present or future, in different applications. Click below on the tutorial that appeals to you most to get started and dive into the world of quantum algorithm design.
Merit Order - mixed- integer optimization
Sensitivity Analysis of Business Risk Models
Solving the SUCP with QUBO's
Parallel Quantum Amplitude Estimation
Example of Outlier Detection using QML
Circuit Constructions and Optimizations
Energy Load Forecasting with QML
Quantum Asset Allocation
Explore Our Research
We aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.
QKD as a Quantum Machine Learning task
Quantum amplitude estimation with error mitigation for time-evolving probabilistic networks
Towards optimization under uncertainty for fundamental models in energy markets using quantum computers
Error Resilient Quantum Amplitude Estimation from Parallel Quantum Phase Estimation.
