Quantum computing at Fraunhofer

Overview of ongoing quantum computing projects

SEQUENCE: An EU project aiming to make quantum computing technology scalable

As part of the European research project SEQUENCE, nine partners including Fraunhofer IAF are employing new methods to develop electronics for cryogenic applications. This has resulted in the creation of innovative cryogenic 3D nanoelectronics that will contribute to improving key technologies for quantum computers as well as satellite-based and terrestrial communication systems. Fraunhofer IAF is contributing to the project with its many years of experience in technological development, circuit design and cryogenic measurement technology for ultra-low-noise, high-frequency electronic systems.

PlanQK: Platform and ecosystem for quantum-assisted artificial intelligence

PlanQK is a platform and ecosystem for quantum-assisted artificial intelligence. PlanQK is aimed at enabling users to access a quantum app store, developers to use quantum platforms in a simple manner and specialists to provide plans for making quantum computing easily accessible.

The QFC-4-1QID project: Bringing quantum bits to the fiber-optic network

Fiber-optics with the capacity to transmit quantum information over long distances would put the quantum Internet within easy reach. With this goal in mind, the Dutch research institution QuTech and the Fraunhofer Institute for Laser Technology ILT launched the ICON project QFC-4-1QID on September 1, 2019. In this long-term, strategic partnership between the research institutions, scientists are developing quantum frequency converters for linking quantum processors with fiber-optic networks. This new technology will be deployed in the world’s first quantum Internet demonstrator in 2022.

EnerQuant: Quantum computing for the energy sector

As part of this BMWi-funded project, we are developing algorithms for qubit-based quantum computers and quantum simulators to create a fundamental model for the energy sector with stochastic variables. The basis of the project involves defining a simple fundamental model that we can translate into a quantum-mechanical problem, which can then be solved efficiently by a quantum simulator.

IQuAn: Ion quantum processor with HPC connection

Trapped ions possess a number of advantages in comparison to other physical realizations. In particular, the long coherence time of trapped ions provides a basis for a correspondingly long operation time when executing quantum algorithms. The IQuAn Group (which includes Fraunhofer IOF) is pursuing a new, scalable approach with high qubit connectivity. By moving and regrouping the ions, the individual optical addressing of small registers is combined with the coupling and the dynamic configuration of multiple registers.

AQTION: Fraunhofer IOF provides a laser optics system for the German quantum computer

The »Advanced quantum computing with trapped ions« (AQTION for short) group was set up in 2018, with the objective of driving applied research on quantum computing in the European Union. The initiative forms part of the EU’s Quantum Technologies Flagship program. The object of the project is to realize a scalable ion-based quantum computer. Fraunhofer IOF researchers have developed innovative optics and laser technology for the 19-inch quantum computer.

SEQUOIA: Software engineering for industrial, hybrid quantum applications and algorithms

Fraunhofer IAO is developing new methods, tools and algorithms based on use cases and user requirements. These include quantum algorithms as well as technologies for everything from the development process to the execution of quantum circuits. Another focus relates to developing procedures for mitigating errors and standardized interfaces. This technology is deployed in hybrid solutions that combine quantum algorithms with conventional solutions.

QUASAR: Semiconductor quantum processor with shuttling-based scalable architecture

The project aims to develop architecture for quantum computers without geometric scaling limits, using semiconductor technology that is commercially available in Germany. Fraunhofer IPMS is participating by using processes adapted from CMOS fabrication. Through multiple iteration steps and by taking into account the possibilities offered by fabrication technology, the project aims to provide optimized component structures with the highest possible level of homogeneity on the substrate level.

QLSI: Quantum Large-Scale Integration with Silicon

The QLSI project has set itself the goal of developing scalable technology for silicon qubits for quantum computers. Silicon qubits can be controlled and read at high speed and due to their small size, high value and compatibility with industrial production processes, they are ideally suited for quantum computing. Silicon qubits have already been successfully demonstrated many times; this project focuses on developing scalable technology for later industrial implementation and for demonstrating a 16-qubit chip.

HalQ — Semiconductor-based quantum computing

The HAlQ project is developing an overarching platform for evaluating and integrating qubit concepts into an overall system that will enable the participating Fraunhofer institutes to implement the German federal government road map for developing a quantum computer “Made in Germany.” The project will pay special attention to the advantages of microelectronics for realizing highly scalable quantum computers and to the further development of the necessary technologies.

MATQu: Materials for Quantum Computing

With the goal of creating a complete European value chain for the fabrication of superconducting Josephson junctions as promising qubit candidates for quantum computing, the Materials for Quantum Computing (MATQu) project was launched in June. In the areas of substrate technology, process technology and tools, the MATQu project brings together key European players in the field, including four major RTOs. The FMD office, together with Fraunhofer IAF, is leading the project, which is funded by the EU Horizon 2020 framework program.


AutoQML: Developer suite for automated machine learning with QC

Quantum computing enables an acceleration of machine learning (ML) approaches and the development of new solution approaches. However, the implementation of such quantum algorithms is use case specific and therefore requires characteristic development by interdisciplinary quantum software engineers. The AutoQML project aims to simplify these processes. The goal is to extend approaches for the automation of machine learning by quantum computing, in order to be able to, among others, solve problems in the production and automotive area more easily and faster.

Q.E.D. Quantum Ecosystem Germany

»Quantum Ecosystem Deutschland (Q.E.D.)«  aims to provide scientific support for the establishment of sovereign innovation and value chains in the quantum computing ecosystem in Germany. The project, which is divided into two modules, is intended to help develop actionable knowledge and strategies for the medium- to long-term establishment of a technologically sovereign and internationally competitive quantum computing ecosystem. New technology and knowledge markets are to be opened up and the quantum computing ecosystem in Germany strengthened. For this purpose, new methods and instruments of ecosystem analysis will be developed and new accompanying and networking formats will be piloted.

QuaST: Quantum-enabling services and tools for industrial applications

The aim of the QuaST project is to provide low-threshold access to quantum computers for companies of all sizes. Industrial end users will only need to have minimal knowledge of QC hardware and software to automatically receive easily accessible and reliable QC-supported solutions for their application problems. The project members are focusing on researching different development tools and application libraries so that users can formulate problems in the programming language that they are used to. This is modeled on the success of artificial intelligence, which can be largely attributed to the easy, widespread availability enabled by software libraries and development tools.

QuSAA: Quantum Algorithms for Strategic Asset Allocation

The aim of the project is to support strategic asset allocation and, in particular, to incorporate Solvency II capital requirements into this investment decision. For this purpose, it will be investigated to what extent the use of quantum computers can contribute to a better control of the complexity of the problem and to deliver more stable results. In doing so, the optimization problem is formulated step by step at different levels of complexity. The solvency ratio and stochastic optimization will be investigated in the further course and the model formulated in the beginning will be extended.

SPINNING: Diamond spin-photon-based quantum computer

The joint project SPINNING (diamond spin-photon-based quantum computer) aims to develop the demonstrator of a quantum processor “made in Germany” as well as the peripherals needed to connect the processor to classical computer systems. The quantum processor is based on so-called spin qubits in synthetic diamond. Compared to today’s quantum computers, the planned hardware features longer operation times and smaller error rates as well as low cooling requirements. The quantum processor will initially be able to compute with 10, and subsequently with 100 qubits and more, and would thus be able to predict the products of complex quantum chemical reactions.

QC-4-BW: Diamond-based spintronic quantum register for a scalable quantum processor

Within the Competence Center Quantum Computing Baden-Württemberg a miniaturized and scalable quantum processor will be developed. It will be evaluated and compared to the superconducting quantum processors of the IBM quantum computer »Quantum System One«, which has a quantum volume of 30. The targeted quantum processor is based on optically coupled quantum registers, where each quantum register is formed by 10 nuclear spin-based qubits and one electron spin.

QORA: Quantum optimization using resilient algorithms

Companies are increasingly confronted with the need to manage large and complex portfolios that already require massive use of information technology. The ability to make optimal decisions quickly is increasingly becoming a decisive competitive advantage. Quantum computers offer the prospect of outperforming conventional computers in the relevant optimization processes and could decisively accelerate portfolio-related decisions. In the QORA project, such optimization methods are developed based on the Quantum Approximate Optimization Algorithm (QAOA) and tested on the quantum computer IBM Quantum System One, which is operated by the Fraunhofer-Gesellschaft.  

AnQuC-3: Application-Oriented Quantum Computing

The first project, AnQuC, focused on applications on the IBM Quantum System One, with an eye toward broad exploitation of quantum computing. Runtime measurements were used to study hybrid algorithms that have both classical and quantum components, and the effects of characteristic quantities such as the coherence time and error rate of 2-qubit circuits on specific algorithms were investigated. In the AnQuC-3 project, the focus is on the topics "Quantum Fourier Transformation", "Quantum Machine Learning", and variational algorithms. The Fraunhofer ITWM concentrates on the first two areas.

EniQmA: Hybrid Quantum Computing meets use cases

Industrially relevant applications in QC are almost always hybrid. Variational algorithms play a central role in the NISQ era to achieve quantum advantages. In the project "EniQmA", Fraunhofer ITWM is working with partners from research and industry to systematize these hybrid approaches in a targeted way and supports the structured development of hybrid quantum applications with software, methods, and tools. The EniQmA team is creating a set of tools for the entire life cycle of hybrid quantum applications.

NeQST: NExt level Quantum information processing for Science and Technology

NeQST's vision is to leverage recent advances in the control of d-level quantum systems, Qudits, to achieve breakthroughs across the quantum computing value chain. These include an experimentally tested Qudit platform based on trapped ions, validated automatic design tools, tailored certification methods, and demonstrated feasibility of practical applications. The use cases »quantum simulation of lattice gauge theories« and »quantum optimization in the energy domain« are in focus.

DEGRAD-EL3-Q: Hybrid QC methods for modeling the degradation of alkaline electrolysers

As part of »DEGRAD-EL3-Q«, Fraunhofer IPA is investigating the use of quantum computing methods for lifetime analysis of electrolyzers. The project is part of the lead project H2Giga with the aim of advancing the industrial manufacturing process of electrolyzers. The project investigates different methods of quantum machine learning and explores how quantum computing can be used to simulate chemical processes in the context of electrolyzer degradation.


AQUAS: Application of quantum simulations in hydrogen research

»AQUAS« aims to take hydrogen research and production to a new level by quantum simulation. Accurate simulation of electrolysis materials will enable the desired increase in process efficiency. This will be achieved by validating and implementing innovative software tools using hybrid classical-quantum algorithms. The focus will be on preparing algorithms that are ready for use on existing and future fault-aware hardware.