We develop algorithms that enable complex calculations for industry and research. This allows for greater precision in a range of simulations, from battery storage to weather and climate simulations. The aerospace, energy and financial sectors all benefit from this.

With HAPEQS, we are improving widely used methods in science and industry by developing techniques for solving partial differential equations. Battery research andresearch into fluid dynamics andatmospheric physics, amongst others, benefit from these calculations carried out on neutral-atom quantum computers. Using these methods, HAPEQS can optimise simulations for batteries as mobile and stationary storage systems, with potential users in the energy and mobility sectors; the aerospace industry benefits fromimproved simulations of weather and climate.

Motivation

Using HAPEQS, we are investigating the solution of non-linear partial differential equations on real quantum hardware. The applications under consideration range from the microscopic modelling of energy storage systems, through aerodynamics, to atmospheric simulations. The project encompasses a wide range of quantum algorithms, from machine learning and Hamiltonian simulation to tensor networks, which facilitates the transfer of applications and approaches.

Partial differential equations (PDEs) are ubiquitous in nature and technology, which is why a wide range of research and development fields, as well as economic sectors such as the energy sector,aerospace and the financial sector, benefit from the algorithms developed in HAPEQS. Non-linear PDEs pose a particular challenge for quantum computers, which are fundamentally based on linear operations.

Close cooperation betweenvarious applications within the DLR and the hardware development team is creating synergies in the field ofhardware-software code design, which benefit all users within the DLR QCI.Through this integrated andcoordinated developmentapproach, we can gradually improve both the scale and accuracy of the simulations as we refine the neutral-atom quantum computers.

Challenge

There is a gap between the scalability of algorithms on the one hand and their execution on real hardware on the other, which hinders the development of practical quantum algorithms. In the HAPEQS project, we are pooling our existing expertise and bringing together both software and hardware developers to bridge this gap and enable the solution of partial differential equations on quantum computers.

Impact

With HAPEQS, we are integrating the development of algorithms andquantum computing hardware even more closely than before. Both the DLR and external partners benefit from this close collaboration, as it brings together user requirements with the capabilities of theplatforms. Our DLR QCI ecosystem thus provides an environment for hardware-software co-design thatwill significantlyaccelerate the efficient solution of PDEs on quantum computers.

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