05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Rigorous compilation for near-term quantum computers(2024) Brandhofer, Sebastian; Polian, Ilia (Prof.)Quantum computing promises an exponential speedup for computational problems in material sciences, cryptography and drug design that are infeasible to resolve by traditional classical systems. As quantum computing technology matures, larger and more complex quantum states can be prepared on a quantum computer, enabling the resolution of larger problem instances, e.g. breaking larger cryptographic keys or modelling larger molecules accurately for the exploration of novel drugs. Near-term quantum computers, however, are characterized by large error rates, a relatively low number of qubits and a low connectivity between qubits. These characteristics impose strict requirements on the structure of quantum computations that must be incorporated by compilation methods targeting near-term quantum computers in order to ensure compatibility and yield highly accurate results. Rigorous compilation methods have been explored for addressing these requirements as they exactly explore the solution space and thus yield a quantum computation that is optimal with respect to the incorporated requirements. However, previous rigorous compilation methods demonstrate limited applicability and typically focus on one aspect of the imposed requirements, i.e. reducing the duration or the number of swap gates in a quantum computation. In this work, opportunities for improving near-term quantum computations through compilation are explored first. These compilation opportunities are included in rigorous compilation methods to investigate each aspect of the imposed requirements, i.e. the number of qubits, connectivity of qubits, duration and incurred errors. The developed rigorous compilation methods are then evaluated with respect to their ability to enable quantum computations that are otherwise not accessible with near-term quantum technology. Experimental results demonstrate the ability of the developed rigorous compilation methods to extend the computational reach of near-term quantum computers by generating quantum computations with a reduced requirement on the number and connectivity of qubits as well as reducing the duration and incurred errors of performed quantum computations. Furthermore, the developed rigorous compilation methods extend their applicability to quantum circuit partitioning, qubit reuse and the translation between quantum computations generated for distinct quantum technologies. Specifically, a developed rigorous compilation method exploiting the structure of a quantum computation to reuse qubits at runtime yielded a reduction in the required number of qubits of up to 5x and result error by up to 33%. The developed quantum circuit partitioning method optimally distributes a quantum computation to distinct separate partitions, reducing the required number of qubits by 40% and the cost of partitioning by 41% on average. Furthermore, a rigorous compilation method was developed for quantum computers based on neutral atoms that combines swap gate insertions and topology changes to reduce the impact of limited qubit connectivity on the quantum computation duration by up to 58% and on the result fidelity by up to 29%. Finally, the developed quantum circuit adaptation method enables to translate between distinct quantum technologies while considering heterogeneous computational primitives with distinct characteristics to reduce the idle time of qubits by up to 87% and the result fidelity by up to 40%.Item Open Access Benchmarking the performance of portfolio optimization with QAOA(2022) Brandhofer, Sebastian; Braun, Daniel; Dehn, Vanessa; Hellstern, Gerhard; Hüls, Matthias; Ji, Yanjun; Polian, Ilia; Bhatia, Amandeep Singh; Wellens, ThomasWe present a detailed study of portfolio optimization using different versions of the quantum approximate optimization algorithm (QAOA). For a given list of assets, the portfolio optimization problem is formulated as quadratic binary optimization constrained on the number of assets contained in the portfolio. QAOA has been suggested as a possible candidate for solving this problem (and similar combinatorial optimization problems) more efficiently than classical computers in the case of a sufficiently large number of assets. However, the practical implementation of this algorithm requires a careful consideration of several technical issues, not all of which are discussed in the present literature. The present article intends to fill this gap and thereby provides the reader with a useful guide for applying QAOA to the portfolio optimization problem (and similar problems). In particular, we will discuss several possible choices of the variational form and of different classical algorithms for finding the corresponding optimized parameters. Viewing at the application of QAOA on error-prone NISQ hardware, we also analyse the influence of statistical sampling errors (due to a finite number of shots) and gate and readout errors (due to imperfect quantum hardware). Finally, we define a criterion for distinguishing between ‘easy’ and ‘hard’ instances of the portfolio optimization problem.Item Open Access Adaptierung an Zeitverhalten-Variationen in rekonfigurierbaren Hardwarestrukturen(2015) Brandhofer, SebastianDas Zeitverhalten von Komponenten in rekonfigurierbaren Hardwarestrukturen kann durch Alterungseffekte und zufällige Defekte variieren. Wenn ein System nicht an diese Abweichungen vom nominellen Zeitverhalten adaptiert werden kann, entstehen Verzögerungsfehler während des Betriebs, die zu falschen Ergebnissen oder Systemausfällen führen können. Insbesondere in sicherheitskritischen Anwendungen von rekonfigurierbaren Hardwarestrukturen kann dies zu Gefährdung von Personen führen. Diese Arbeit stellt einen Algorithmus zur Adaptierung an Zeitverhalten-Variationen in rekonfigurierbaren Hardwarestrukturen vor, der Alterung von Komponenten sowie zufällige Defekte berücksichtigt und Verzögerungsfehler durch eine dem Zeitverhalten angepasste Nutzung der rekonfigurierbaren Hardwarestrukturen vermeidet. Der entworfene Algorithmus wird mit Hilfe von verschiedenen Verzögerungsverteilungen hinsichtlich der Adaptionsfähigkeit, Speicheranforderungen und Laufzeit untersucht.Item Open Access Cryogenic embedded system to support quantum computing : from 5-nm FinFET to full processor(2023) Genssler, Paul R.; Klemme, Florian; Parihar, Shivendra Singh; Brandhofer, Sebastian; Pahwa, Girish; Polian, Ilia; Chauhan, Yogesh Singh; Amrouch, Hussam