Fraunhofer Institute for Mechanics of Materials IWMQUBE develops quantum algorithms for materials research to simulate high-performance functional materials more efficiently. Highly correlated materials, such as perovskites in solid-oxide fuel cells, benefit from more precise calculations that outperform classical methods.
Quantum Algorithm Development, Benchmarking and Resource Estimation for Materials Simulation with User Benefits on Noisy Intermediate-Scale Quantum (NISQ) Quantum Computers
Ongoing research project
Project description
The development of new energy storage and conversion devices requires a deep understanding of the electronic properties of the functional materials used. Many of these materials, particularly transition-metal oxides with a perovskite structure (e.g., ternary ferrates and cobaltates), exhibit strongly correlated electronic states, and the quantitative simulation of these states presents opportunities for developing methods beyond established classical approaches such as density functional theory (DFT). Even advanced embedding methods such as Dynamical Mean Field Theory (DMFT) require significant approximations and immense computational effort on classical high-performance computers, which limits the accuracy of predictions and thus the speed of materials development.
This is where the QUBE joint research project comes in. The goal is to develop hybrid quantum-classical simulation methods that shift the most numerically demanding part of DMFT- for the first time - the calculation of the Green'schen function of the correlated subproblem - to a quantum computer, thereby achieving a quantum advantage for materials simulation. The project thus addresses, on the one hand, the energy and materials industries’ need for more precise, faster simulation tools for the development of functional materials for the energy transition (fuel cells, batteries, catalysts) and, on the other hand, the growing need for concrete, industrially relevant use cases for quantum computers.
Fraunhofer IWM’s work packages within the QUBE consortium:
Fraunhofer IWM performs ab initio density functional theory (DFT) simulations for a systematic class of perovskite ferrates and cobaltates, constructs and parameterizes model Hamiltonian operators from these (using Wannier transformation and the coherent renormalization perturbation approach (cRPA)) and calculates classical reference results using progressively more complex methods (DFT+U, DFT+DMFT). Fraunhofer IWM provides these reference data and Hamiltonians to the consortium partners (IQM, TUHH, Bosch) as a starting point for their work. In this way, Fraunhofer IWM establishes the materials science foundation.
In addition, Fraunhofer IWM is developing two complementary quantum algorithms for calculating the Green'schen function within the framework of DMFT. The Krylov approach uses a continued fraction representation with good resource scalability; the time-evolution approach calculates the Green'schen function via the quantum dynamics of the system. Both methods are integrated into the established DMFT software stack (TRIQS) and are being tested step by step on emulated and real IQM quantum hardware. The key innovation is the embedding of these quantum solvers into the self-consistent DMFT cycle - a seamless hybrid HPC/QC workflow from the DFT calculation to the converged electronic structure.
Based on this project work, Fraunhofer IWM can offer industrial companies the following new R&D services:
- Hybrid high-performance computing (HPC) and quantum computing (QC) materials simulation for strongly correlated electronic systems
For functional materials with complex electronic properties (e.g., electrodes for fuel cells and batteries, catalyst materials, superconductors), Fraunhofer IWM designs simulation workflows that integrate quantum computer-assisted solution methods into established density functional theory and dynamical mean-field theory (DFT+DMFT) calculations. - Consulting and Feasibility Studies on the Use of Quantum Computing in Materials Development
Fraunhofer IWM develops decision-making frameworks for investments in quantum computing infrastructure and expertise. - Simulation and screening of perovskite and transition metal oxide materials using advanced methods
The modular software stack developed in the project enables systematic screening of other technologically relevant materials systems, e.g., for thermoelectrics, sensor technology and electrocatalysis, with greater accuracy, in addition to the ferrates and cobaltates considered in the project.
