Competence Center Quantum Computing Rhineland-Palatinate

Quantum Computing at the Fraunhofer ITWM in Kaiserslautern

In contrast to classical computers, quantum computers work on the basis of quantum mechanical states such as superposition and entanglement. This different mode of operation leads to a paradigm shift in programming and far-reaching changes in algorithms in terms of complexity and computability. In comparison to classical computing, quantum computing promises both an up to exponential acceleration of certain algorithms and the possibility to treat extremely complex problems.

In the current phase, it is important to estimate under which conditions practical problems can be solved on quantum computers that cannot be computed on classical computers or can only be computed with a significantly longer runtime. Once quantum superiority has been achieved, the effects will be shown in various branches of industry.

Our institute director, Prof. Dr. Anita Schöbel, together with Prof. Manfred Hauswirth (institute director at Fraunhofer FOKUS) is responsible for quantum computing at Fraunhofer.

Aim of the Competence Center

In cooperation with IBM Germany, the Fraunhofer-Gesellschaft is establishing a national competence network in the research field of quantum computing. The aim is to develop quantum-based computing strategies for the next generation of high-performance computers. With the participation of currently eleven Fraunhofer Institutes, specialist expertise is being pooled in regional competence centers. The Center for Quantum HPC (High Performance Computing) has been established at Fraunhofer ITWM.

The overall goal of the activities is to further develop quantum-based computing strategies for industrial applications, such as quantum simulations of chemical systems and quantum algorithms in financial mathematics.

Organizational Structure of the Competence Network
© Fraunhofer-Gesellschaft
Organizational structure of the competence network with currently seven competence centers in the participating federal states.
IBM Q System One
© IBM Research
In 2019, IBM introduced the first commercially - i.e. outside of laboratory environments - usable quantum computer, the IBM Q System One. It will be managed by Fraunhofer in Germany from 2021.

Cracking Complex Application Problems With Quantum Computing

The Competence Center Quantum Computing at Fraunhofer ITWM harbors great opportunities and potential for the entire region. Through the cooperation of Fraunhofer with IBM, Fraunhofer has cloud access to IBM quantum computers in the USA and an IBM quantum computer will be located in Germany in 2021, operating under German law. Access to quantum computers enables research into technology, application scenarios and algorithms. The early development of specialist competencies in Germany represents a competitive advantage that should not be underestimated, allowing the location to participate in the value creation in the field of quantum computing at an early stage.

Germany's high-tech landscape offers many opportunities for the application-oriented use of quantum computing. The Fraunhofer ITWM is closely linked to the scientific institutions (TU, university, Fraunhofer IESE, IVW, DKFI) at the location and to researching companies through the performance center for simulation and software-based innovation. We are also closely networked with the performance center with regard to quantum computing and cooperate especially in the transfer of know-how.


Our Services and Offers

The Fraunhofer experts will offer training courses for industry and science in the field of »quantum computing«, thus also ensuring the transfer of knowledge to the region. Interested regional university and non-university institutions and companies will also be involved in the competence center within the framework of joint projects, through contract research or through memberships.

Within the scope of contract research projects with Fraunhofer ITWM, interested users can access the IBM quantum computer. From 2021 on, in addition to the cloud access to the quantum computers located in the USA, you can access the quantum computer at location Ehningen near Stuttgart. The quantum computer at location Ehningen is operated under German law. The access is subject to a license agreement and export control. We work with the ticket model where you have one calendar month access to the quantum computer per ticket purchased. An individual ticket currently costs 11,621 Euro per month for external customers.

Main Fields of Application

The following topics were initially defined as focal points, as they offer great potential for transfer to the region and the necessary expertise for implementation already exists at Fraunhofer ITWM:

Quantum Chemistry on Quantum Computers

Quantum chemistry on quantum computers
© iStockphoto
Particular breakthroughs are expected in quantum chemistry.

Quantum chemistry on quantum computers is considered to be one of the first realistic use cases in which an advantage of quantum computers is demonstrated. Especially in the simulation of metals strong electron-electron correlations occur, which are efficiently solved by the entanglement of quantum computers in contrast to conventional methods.

Algorithms such as the Variational Quantum Eigensolver (VQE) and mixed approaches, so-called »shallow-depth circuits« algorithms, which are state of the art, show promising potential on quantum computers. Currently, we are in the intermediate NISQ (Noisy Intermediate Scale Quantum) development stage of hardware technology, with significant progress in the number of available qubits and error rates in recent years. Nevertheless, not all known quantum algorithms can yet be successfully implemented due to the limitations of error rates and decoherence effects. When developing new quantum computing workflows, science often combines robust classical approaches with algorithms on the quantum computer.

Examples of such hybrid quantum/classical approaches are variational algorithms like the VQE for quantum chemistry simulation. Variational algorithms are suitable methods for current hardware with respect to the required gate depth and the error tolerance of the algorithm. The parts that are computationally intensive for classical high-performance computers are solved on the quantum computer, while the other parts of the workflow are calculated on conventional computers.

However, the scaling of these hybrid methods compared to purely classical methods on high performance computers remains the subject of research. We are tackling this exciting topic at the Fraunhofer ITWM.

Quantum Algorithms for Finance and Energy

Quantum algorithms for finance and energy industry
© iStockphoto
Quantum computers certainly have the potential to extremely shorten central computer applications. These include processes in financial mathematics.

The current issues of stochastic capital and energy market simulations as well as asset management pose great challenges to computing power, which even conventional high-performance computing techniques can only fulfill to a limited extent. The new technology of quantum computing opens up the perspective of solving previously incalculable problems in the near future or creating new simulation approaches.

We develop algorithms for the valuation of financial derivatives, the modelling of energy markets with stochastic variables and for the solution of mixed-integer optimisation problems in the financial and energy industry. The research also includes the investigation of various infrastructures such as gate-based quantum computers, quantum simulators and digital annealers for the high-performance implementation of the developed methods. Digital Annealers use a procedure inspired by quantum annealing. Here a global minimum of a given target function is found by a process that uses quantum fluctuations.

Direct applications can be found in the strategic allocation of assets, energy park management and risk analysis of portfolios on an industrial scale.

Quantum Algorithms in Material Simulation

Digital Twins in the Quantum Age
© Fraunhofer ITWM
Digital twins in materials research in the quantum age: Application example long-term use and safety analyses of reservoir rocks.

In recent years, the improved quality of computed tomography (CT) images has led to a digitalization of the material characterization process for composite materials. Today, commercially available CT devices have a maximum resolution of less than one micron and produce 3D images with up to (4096x4096x4096) voxels. New algorithms based on Fourier transformations are needed for analysis. These Fourier transforms are the most time consuming algorithms in simulation.

Quantum Fourier transformations accelerate the simulation for realistic geometries by a factor of 100 to 1000. This is our starting point. We want to use acceleration and look at the accuracy and errors of quantum Fourier transformations and their applicability to real problems.

Quantum Fourier Transform in Image Processing

Nowadays, image analysis is often slower than data acquisition or can not exploit the data completely. The amount of image data grows faster than the speed of the analysis methods. This is due to:

  • new acquisition methods
  • higher resolutions
  • higher dimensionality
  • wider availability of new camera systems

One example is the computed tomography device Gulliver provided to the Civil Engineering of TU Kaiserslautern by the DFG (Deutsche Forschungsgemeinschaft). This globally unique experimental facility will image concrete beams during bending tests. One experiment will generate approximately 2TB image data. Thus quantum computing promising faster processing of larger data sets is very attractive for image processing.

Typical image analysis solutions consist of numerous, multiply linked image transformations. Many filtering and analysis algorithms are either based on or sped up considerably using the discrete Fourier transform.

Replacing it by its quantum counterpart bears therefore particularly high potential for efficiently processing huge image data as provided eg by Gulliver.  Exploiting this potential requires however representing images including discrete connectivities accordingly.

Volume Rendering: 3D visualization of cracks
© Fraunhofer ITWM
Volume rendering: 3D visualization of cracks in steel fibre concrete specimen, which was examined with computer tomography.
Schematic Drawing of the Computed Tomography Device Gulliver
© TU Kaiserslautern
Schematic Drawing of the Computed Tomography Device Gulliver

Quantum Computing Revolutionizes Artificial Intelligence and Machine Learning

Quantum Machine Learning (QML) is an emerging interdisciplinary research area at the interface of quantum physics and artificial intelligence. The underlying idea is to adapt classical learning algorithms for use on quantum computers in order to combine the advantages of quantum technology with the statistical framework of machine learning. Since quantum physics itself is characterized by an inherently statistical behavior, this synthesis offers the potential to achieve a technological breakthrough also on near-term quantum computers.

We develop QML algorithms in an application-based context and evaluate the practicability and performance of quantum approaches in comparison with classical approaches. For this purpose, we consider regression, classification and data encoding problems motivated by real-world applications, for example in the field of image processing and process engineering. By identifying interesting use cases and making them run on IBM quantum computers, we use QML to advance on the road to quantum readiness.

Cross sectional view of the reconstructed tomographic image of packed gravel.
© Fraunhofer ITWM
Cross sectional view of the reconstructed tomographic image of packed gravel.
Same slice with separated particles. Colors indicate the image object labels.
© Fraunhofer ITWM
Same slice with separated particles. Colors indicate the image object labels.

News and Press Releases About Quantum Computing

Short News / 7.7.2021

Kickoff for the BMBF Project QuSAA

On June 1, the QuSAA project was launched. The abbreviation stands for Quantum Algorithms for Strategic Asset Allocation. In the project, we are developing quantum algorithms for the optimization of investment decisions together with JoS QUANTUM and R + V Lebensversicherung.

For complex optimization problems, quantum computers promise completely new possibilities in the future. QuSAA investigates the extent to which quantum computers can help to better manage the complexity of the problem.


Press Release / 15.6.2021

Fraunhofer and IBM to unveil Quantum Computer

The quantum computer has been unveiled and the launch of the quantum computing research platform operated by Fraunhofer and IBM has begun. Read more in the press release and in the SWR report.

Event / 8.7.2021

Fraunhofer Solution Days 2021

Trusted and quantum computing: On the second theme day of the Fraunhofer Solution Days 2021, participants will gain insights into challenges and solutions for engineering reliable AI systems and quantum computing topics. This includes, among other things, transfers from theory to practice. Fraunhofer experts will provide insights into the labs, demonstrate the immense potential of future technology and present the range of products and services related to the IBM Q System One quantum computer.


Quantum Technology at Fraunhofer

The Fraunhofer-Gesellschaft wants to promote and decisively advance research in the field of quantum computing in Germany. The aim is to drive the competences and strategies surrounding the topic for industry and application-oriented processes.

Definitions, explanations, news, interviews and project examples on the overarching topic of quantum technology and quantum computing can be found on the Fraunhofer-Gesellschaft website.

Video: The Quantum World

When quantum technologies come into use, the possibilities are still hardly foreseeable, but the potential is enormous.