××× The tender is closed ×××
We are looking for industrial partners for the QCI project QCoKaIn: Hybrid quantum high-performance computing based on causal inference
The QCoKaIn project has two goals: On the one hand, it creates an infrastructure for hybrid quantum high-performance computing on the software side. On the other hand, it develops, uses and evaluates hybrid algorithms for anomaly detection based on causal inference. For full details of the call, visit TED: 118480-2023. The submission deadline is March 22, 2023, 2 p.m. local time.
QCoKaIn is managed by the DLR Institute for Data Science, which focuses on finding solutions for the new challenges of the digitization era. The research focuses on the areas of data management, data analysis and data acquisition. These research activities complement established research areas at other DLR institutes and expand the core competencies of DLR.
At the heart of QCoKaIn is the industrial use case for hybrid computing in the automated detection of anomalies in telemetry data from satellites and spacecraft. Building on a classic computing infrastructure for data analysis, the project team is investigating how hybrid computing can be used in terms of computing speed and the accuracy or reliability of the predictions.
Hybrid Quantum High-Performance Computing using Causal Inference
The software-side construction of an infrastructure for hybrid quantum high-performance computing and the development, use and evaluation of hybrid algorithms for anomaly detection based on causal inference.
Cookie Consent with Real Cookie Banner