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Which computers does the QAR-Lab work with?

Evaluation and use of QC technologies

Two types of quantum computers

In addition to theoretical preparatory work, such as use case analysis and knowledge transfer, prototypes and algorithms developed in the QAR-Lab can already be evaluated on a variety of quantum computing hardware. We currently use two different quantum computing hardware technologies.

Quantum Annealer

Quantum annealers are designed specifically for solving optimization problems. All the issues, whether costs, distances, or other variables, are modeled in the form of a mathematical description – the so-called QUBO problem – on a grid of qubits and solved by the hardware.

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Universal Gate Quantum Computer

The universal quantum gate model is another quantum computing approach that is based on the use of quantum gates. Like classical computers, quantum logic gates are assembled in sequences to perform certain algorithms and solve problems.

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We are currently working on the following quantum computers

We develop and test quantum computing algorithms and their practical execution on the following hardware platforms, among others:

D-Wave Systems Advantage

Quantum Annealer

Canadian hardware manufacturer D-Wave Systems Inc. was the first and only commercial supplier for quantum annealing. The D-Wave Advantage is particularly well-suited for solving optimization problems. The QAR-Lab has already tackled numerous such problems, from pure logic problems such as 3SAT and the Game of Life to practical applications such as airport gate assignment or capacitated vehicle routing, especially in hybrid execution using D-Wave’s ocean library.

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© D-Wave Systems Inc.

Fujitsu DAU

Digital Annealing

Fujitsu’s Digital Annealer uses a digital circuit design inspired by quantum phenomena. It is used to solve complex combinatorial optimization problems rapidly. The QAR-Lab has already been able to perform numerous calculations via the Digital Annealer.

© Fujitsu Limited

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Rigetti Aspen-8

Quantum Gate Computer

Rigetti quantum processors are universal gate-model computers based on superconducting qubits. With its Forest SDK, Rigetti uses a development tool optimized for NISQ computers to perform hybrid quantum-classical algorithms. The QAR-Lab has already implemented various variational algorithms, such as the QAOA and VQE approach, on the Rigetti Aspen-8 processor with 32 qubits.

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IBM Q System One

Quantum Gate Computer

IBM Q System One includes the company’s own series of universal gate-model computers whose quantum processors are based on supra-conducting qubits. Algorithms are executed using the open-source Qiskit SDK. The QAR-Lab has already executed some prototypical variational algorithms on the freely available IBM simulator with 32 qubits. Starting in June 2021, LMU Munich has signed a contract to use the first IBM quantum computer available in Europe in Ehningen.

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Furthermore, the QAR-Lab is in talks to use the following additional hardware platforms

Quantum Inspire by QuTech

Quantum Gate Computer

Quantum Inspire is a platform designed, built and driven by QuTech, an advanced research center for quantum computing and quantum internet that was founded by Delft University of Technology and TNO. In particular, it provides a graphical user interface to program quantum algorithms in language QASM and to visualize those operations via circuit diagrams. There are two quantum processors available (Spin-2, Starmon-5) as well as two simulators (QX-26, QX-31). There are several code examples, for example to perform quantum classification or Grover’s algorithm.

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© Cheesework for QuTech

Quantum Brilliance

Quantum Gate Computer

The Australian hardware manufacturer Quantum Brilliance builds and sells room-temperature quantum computers powered by synthetic diamond, enabling applications in edge quantum computing and hybrid quantum-classical computing. The goal of Quantum Brilliance is a future for ubiquitous quantum computing.

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QAR-Lab – Quantum Applications and Research Laboratory
Ludwig-Maximilians-Universität München
Oettingenstraße 67
80538 Munich
Phone: +49 89 2180-9153
E-mail: qar-lab@mobile.ifi.lmu.de

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