Competence Center Quantum Computing Rhineland-Palatinate

Quantum Computing at the Fraunhofer ITWM in Kaiserslautern with focus on High Performance Computing.

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.

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

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.

Here on the website of the Competence Center HPC we present

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.

Standorte und Forschungsthemen des Fraunhofer-Kompetenznetzwerks Quantencomputing
© Fraunhofer
Standorte und Forschungsthemen des Fraunhofer-Kompetenznetzwerks Quantencomputing
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.

Quantum Computing Projects at the Fraunhofer ITWM



In the project »QuSAA« (Quantum Algorithms for Strategic Asset Allocation) we are working on new ways of asset allocation using quantum computing (QC).


Quantum Technology Professional

In the Project we are developing a modular and expandable education program with the topics »Quantum Computing« and »Quantum Technology«.



In the project »AnQuC-3« we focus on the topics »Quantum Fourier Transformation«, »Quantum Machine Learning« and »Algorithms«.


Quanten-Initiative Rheinland-Pfalz (QUIP)

In the project »QUIP«, we support young researchers together with our project partners on the topic of quantum computing (QC) and quantum technologies (QT).



The purpose of »QCStack« is to create a cross-technology middleware that provides standardized functions for the development and compilation of gate-based quantum computers.



In the BMWi-funded project, we develop algorithms for qubit-based quantum computers and quantum simulators for solving an energy fundamental model with stochastic influence variables.


Rymax One

In the BMBF project, we and our partners are developing a quantum computer based on Rydberg atoms – the »Rymax One«. 



In the project »EniQmA« (Enabling Hybrid Quantum Applications) we work on systematizing hybrid approaches in the field of quantum computing (QC) in a targeted way.

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 (HPC) 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
© RPTU 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 / 03.04.2024

Staking Out the Quantum Frontiers: Results of the »Applied Quantum Computing« Project

The project »Applied Quantum Computing« (AnQuC) will come to an end. The Fraunhofer ITWM's Quantum Computing working group has met with the industrial advisory board, which accompanied the project for two years, for a final summary.


Annual Report 2022/2023 has been Published

The Chapter »Quantum Computing« in the Current Annual Report for Download as PDF is Available here: [German only]


Kaiserslautern / Winterschool / 19.02. – 23.02.2024

QUIP Winterschool 2024

The QUIP Winter School brings together students, leading researchers and industry to discuss the latest developments, challenges and applications in the field of Quantum Machine Learning. The program includes intensive courses, lectures and workshops on the topic, with experts from our institute as speakers.


Taipei, Taiwan / Conference / 13.01. – 19.01.2024

Quantum Information Processing 2024 (QIP 2024)

Experts from our department »Image Processing« will be attending one of the largest conferences on »Quantum Physics« and will be presenting two exciting posters on our work with a focus on »Quantum Computing«.


Kaiserslautern, Workshop / 22. November 2023

EnerQuant – Quantum Computing in the Energy Sector

In the joint project »EnerQuant: Energy Fundamental Modeling with Quantum Algorithms«, experts are researching the application of quantum computing to optimization problems in the energy industry and the development of a quantum simulator. This event has been postponed from 19.10.2023.


Press Release / 17.3.2023

Minister Clemens Hoch hands over funding decisions for »QUIP« and »MaTBiZ«

Science Minister Clemens Hoch brought two funding decisions to Kaiserslautern to support Quantum Initiative Rhineland-Palatinate (QUIP) and the project MaTBiZ.

Video: German Online Course Quantum Computing

Quantum Computing for Managers and Decision Makers in Insurance Companies (Recorded February 17, 2022)

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With this german online course, which took place in cooperation with the Versicherungsforen Leipzig, the participants got an insight into the principles of quantum computing and learned which basic questions are suitable for quantum computing. Potential applications from industry and especially the insurance industry were outlined. The presentation was given by Prof. Dr. Daniel Loebenberger (Fraunhofer AISEC), Dr. Stefan Mai (Fraunhofer ITWM), and Dr. Roman Horsky (Fraunhofer ITWM).