Theory

As part of the theoretical research within MQV, the THEQUCO consortium will develop hardware-independent theoretical foundations of quantum computing, construct new quantum algorithms, build new methods and protocols to certify quantum computers and establish new control and error mitigation methods. The HAT consortium, on the other hand, provides application-oriented theory support for the different experimental quantum computing platforms within MQV to enable the optimal execution of quantum algorithms.


Related projects and activities

Efficient Quantum Algorithms for the Hubbard Model (EQUAHUMO)

The Hubbard model plays an important role in the description of quantum materials. Solving the mathematical equations for the Hubbard model with classical computers is very difficult because the resources required grow exponentially with system size. However, quantum computers could overcome this hurdle and provide solutions in much shorter time. The goal of the project is to develop efficient quantum algorithms for Hubbard models at finite temperatures.

Hardware Adapted Theory (HAT)

The Hardware Adapted Theory (HAT) consortium provides theory support for the experimental groups within MQV. This includes the numerical modeling of hardware to help in the development of novel hardware generations. Furthermore, the HAT consortium will help to explore suitable applications of each generation of quantum-computing hardware.

Theoretical Quantum Computing (THEQUCO)

The THEQUCO consortium contributes to the development of the quantum information theory behind Noisy Intermediate-Scale Quantum (NISQ) and analog devices. It constructs new quantum algorithms both for present and planned scalable generations of devices. It also builds new methods and protocols to certify quantum computers and their capability of demonstrating a quantum advantage. Finally, it investigates the improvement of current quantum computers by establishing new control and error mitigation methods, and helps scaling them up by devising and improving error correction techniques.