15. February 2023

SQuAp: Spin Qubit Analysis platform for hardware based on colour centres

Objective We are developing a qualification system to analyse the functionality and properties of solid-state spin qubits. Quantum computers can be built using a variety of physical systems, including flaws in the crystal lattice of solids, where a…
10. February 2023

AQuRA: Development of an analogue quantum computing machine

Objective We are designing a novel analogue quantum computing machine (AQuRA) based on continuous quantum variables. For this purpose, we are creating quantum algorithms and developing software to simulate AQuRA and the associated algorithms on classical computing systems….
7. February 2023

QCoKaIn: Hybrid Quantum High-Performance Computing using Causal Inference

Objective We are building a software infrastructure for hybrid Quantum High-Performance Computing (Q-HPC) and developing, using and evaluating hybrid algorithms for anomaly detection based on causal inference. Our topic is Q-HPC, which combines elements of classical HPC with…
7. February 2023

KLIM-QML: Improving climate models using quantum machine learning

Objective We are improving climate models using quantum machine learning for robust technology assessment and mitigation recommendations. To this end, we are exploiting the potential of quantum computing for the improvement of climate models. We will also make…
7. February 2023

QLearning – Quantum processors for reinforcement learning

Objective We are investigating the suitability of quantum processors from the DLR Quantum Computing Initiative (QCI) for the implementation of quantum algorithms for reinforcement learning. Machine learning, and in particular reinforcement learning, is becoming increasingly important in the…
7. February 2023

QuantiCoM: Quantum Computing for Materials Science and Engineering

Objective We are exploring tools for the rapid discovery and development of new materials, their transfer to industrial partners for application, and the identification of simulation approaches that promise quantum advantage. The aim of QuantiCoM is to develop…
7. February 2023

R-QIP: Reliable Quantum Information Processing

Objective We are improving the reliability of quantum information processing using methods such as error models, simulators for quantum error correction algorithms and new decoders for quantum error correction. Quantum computers of the noisy intermediate-scale quantum computer (NISQ)…
7. February 2023

Quant²AI: Quantifying the benefits of quantum AI systems

Objective We are making the complete end-to-end pipeline of quantum artificial intelligence (AI) systems comparable, quantifying any quantum advantages over classical methods, developing a demonstrator, and thus initiating the process of standardisation in the field of quantum AI…
1. February 2023

QUA-SAR: Quantum computing for radar remote sensing

Objective We use quantum computing for processing and optimization tasks in radar remote sensing. Quantum computing is used for processing and optimisation tasks in radar remote sensing. With the QUA-SAR project, we are combining the classical research field…
1. February 2023

ALQU: Algorithms for quantum computer development in hardware-software codesign

Objective We are developing customised compilation strategies for the DLR QCI’s quantum computers and customised quantum algorithms for difficult, industry-relevant computational problems. Through our research and development work, we support the quantum computing ecosystem in the development of…
23. September 2022

Computing with light

Contract awarded as part of the DLR Quantum Computing Initiative Turning light particles into arithmetic building blocks offers great potential for building quantum computers. However, quantum processors based on light particles (photons) are less mature than other platforms….