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Auflistung nach Schlagwort "Quantum Computing"

1 - 10 von 10
  • Eingeladene Vorträge
    20x INFOS - 40 Jahre Informatikunterricht
    (INFOS 2023 - Informatikunterricht zwischen Aktualität und Zeitlosigkeit, 2023) Hartmann, Werner
    Seit der Durchführung der ersten Tagung in Berlin 1984 waren Diskussionen zur Einführung eines Fachs Informatik, zu Lehrplänen und Bildungsstandards und zur Abgrenzung Informatik versus Medienbildung wiederkehrende Themen an den INFOS-Tagungen. Die Fachdidaktik Informatik bewegte sich dabei im Spannungsfeld zwischen den Ansprüchen an Forschung und Entwicklung seitens der Hochschulen, der Realität in der Schulpraxis und der raschen Entwicklung der Informatik selbst. Basierend auf den Erfahrungen der letzten 40 Jahre werden im Beitrag Überlegungen zur Zukunft des Informatikunterrichts vorgestellt verbunden mit einem Plädoyer für eine weniger fachsystematische, mehr auf die Menschen in einer digitalen Welt ausgerichtete Sicht.
  • Konferenzbeitrag
    Connecting the Hamiltonian structure to the QAOA performance and energy landscape
    (INFORMATIK 2024, 2024) Müssig, Daniel; Wappler, Markus; Lenk, Steve; Lässig, Jörg
    Quantum computing holds promise for outperforming classical computing in specialized applications such as optimization. With current Noisy Intermediate Scale Quantum (NISQ) devices, only variational quantum algorithms like the Quantum Alternating Operator Ansatz (QAOA) can be practically run. QAOA is effective for solving Quadratic Unconstrained Binary Optimization (QUBO) problems by approximating Quantum Annealing via Trotterization. Successful implementation on NISQ devices requires shallow circuits, influenced by the number of variables and the sparsity of the augmented interaction matrix. This paper investigates the necessary sparsity levels for augmented interaction matrices to ensure solvability with QAOA. By analyzing the Max-Cut problem with varying sparsity, we provide insights into how the Hamiltonian density affects the QAOA performance. Our findings highlight that, while denser matrices complicate the energy landscape, the performance of QAOA remains largely unaffected by sparsity variations. This study emphasizes the algorithm’s robustness and potential for optimization tasks on near-term quantum devices, suggesting avenues for future research in enhancing QAOA for practical applications.
  • Konferenzbeitrag
    Constrained Grover Adaptive Search for Optimization of the Bidirectional EV Charging Problem
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Federer, Marika; Lenk, Steve; Müssig, Daniel; Wappler, Markus; Lässig, Jörg
    The optimization problem of bidirectional electrical vehicle charging (Vehicle-to-Home) becomes more and more important with rising energy prices and the required reduction of 𝐶𝑂2 emissions. We maximize the usage of local solar power generation, while minimizing the power grid usage. This is constrained by the energy demand of the household and the required state of charge at departure as well as the idle times of the car at home. The problem is formulated as a Constrained Polynomial Binary Optimization (CPBO) problem, which is convenient for Grover Adaptive Search by representing the objective function and the constraints as a Quantum Dictionary.
  • Textdokument
    Extraktion und Analyse von Schlüsselwörtern in einer Literaturrecherche zu Quantum Computing
    (INFORMATIK 2022, 2022) Copurkuyu,Mazlum; Barton,Thomas
    Durch die große Menge an wissenschaftlichen Publikationen, die meist als unstrukturierte Daten vorliegt, nehmen Komplexität und Arbeitsaufwand eines Literature-Review Prozesses stetig zu. Auch im Forschungsgebiet Quantum Computing hat sich die Anzahl wissenschaftlicher Veröffentlichungen in den letzten Jahren stark erhöht. Dieser Beitrag gibt einen Überblick, wie man Text-Mining-Methoden zur Informationsextraktion bei der Literaturrecherche zu Quantum Computing einsetzen kann. Das zentrale Forschungsziel besteht in der Anwendung von Text-Mining zur automatischen Extraktion und Visualisierung von Schlüsselwörtern auf Basis der Abstracts von wissenschaftlichen Publikationen. Dieser Ansatz verwendet zum einen die TF-IDF-Methode und auf der anderen Seite den Word2Vec-Algorithmus, um die automatische Erfassung sowie die Verarbeitung relevanter Literatur zu ermöglichen. Anschließend wird eine visuelle Darstellung der Ergebnisse wie z.B. dynamische Word-Clouds durchgeführt. Aus der Analyse werden Erkenntnisse für den Forschungsbereich Quantum Computing abgeleitet.
  • Textdokument
    High-Performance and Quantum Computing for Students
    (INFORMATIK 2022, 2022) Faber,Peter; Liebelt,Helena
    Many technical advances have been applied in the area High-Performance Computing for the first time, and this also seems to hold for Quantum Computing. Traditionally, however, experts in these fields come from a diverse educational background. Recently, Technische Hochschule Deggendorf (Deggendorf Institute of Technology, DIT) introduced a new master's program "`High-Performance Computing / Quantum Computing"' to offer students a direct way into the application specific aspects of these field of expertise. To our knowledge, this is the first course of studies of its kind. This work describes this new program of studies and tentatively identifies some of the first lessons learned so far.
  • Konferenzbeitrag
    A Proposal for Physics-Informed Quantum Graph Neural Networks for Simulating Laser Cutting Processes
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Mehrin Ruhi, Zurana; Stein, Hannah; Maaß, Wolfgang
    Simulations are crucial for production monitoring and planning in manufacturing. Still, the performance of simulations based on mathematical modeling and machine learning methods is limited and opaque to widespread application. Quantum computing offers the potential for exponential acceleration of these tools, while physically informed neural networks (PINN) improve learning and reduce ambiguity. Objective of this paper is to explore the concept of developing a tool for laser cutting simulation based on a quantum neural network that can be trained on thermal physics principles.
  • Textdokument
    Quantum Computer and Quantum Algorithm Benchmarking
    (INFORMATIK 2022, 2022) Müssig,Daniel; Lässig,Jörg
    Quantum computing is an exciting field, which brought out many competitors, both on the hardware and algorithmic side. Although users are not expecting to outperform classical machines yet, they are still interested in quantum computers, which can demonstrate advantages of their algorithms best. However, for users, especially in the industry, it is not easy to find a quantum device, which fits their needs. This problem arises from an unmanageable amount of meta information about qubits and connections between them such as fidelity, error rates and timings. In this paper we propose a web tool, which helps the user to find quantum computers best suited for their problem or quantum algorithm. Further, it will generate necessary graphs and reports for benchmark studies, which can be directly included in papers of scientists.
  • Konferenzbeitrag
    quark: QUantum Application Reformulation Kernel
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Lobe, Elisabeth
    Quantum annealers solve Ising problems heuristically. Several standard methods have been established to transform more complex problems into the Ising problem format, which are commonly still applied by hand. In this work, we present our software package quark, automating the full transformation process from an arbitrary discrete optimization problem to the corresponding Ising problem. Based on a parameterized formulation of the original problem, a series of easily reproducible experiments can thus be set up. This allows users to evaluate the suitability of the annealing machines in solving their specific problem without a deeper knowledge about the Ising problem specifics.
  • Textdokument
    Real-world application benchmark for QAOA algorithm for an electromobility use case
    (INFORMATIK 2022, 2022) Federer,Marika; Müssig,Daniel; Lenk,Steve; Lässig,Jörg
    To reduce $CO_2$ emissions in the mobility sector, battery electric service vehicles might play an important role in the future. Here, an optimal charging scheduling use case will be presented which includes local solar power generation for minimizing the power grid usage for electric service vehicles. Different formulations of the use case are given to illustrate the differences for classical and quantum-based optimization using a mixed integer linear program and a quadratic unconstrained binary optimization program, respectively. Addtionally, we study the complexity of our benchmark experiments by characterizing the respective QUBO matrices and the optimization landscapes. It is shown how the setting of the parameters of a certain experiment and its penalty function influences the complexity for a quantum-based optimizer. Additionally, we present a comparison of the computing times and summarize the current state of gate-based quantum computing for electromobility.
  • Konferenzbeitrag
    Towards View-based Development of Quantum Software
    (INFORMATIK 2024, 2024) Ammermann, Joshua; Mauerer, Wolfgang; Schaefer, Ina
    Quantum computing is an interdisciplinary field that relies on the expertise of many different stakeholders. The views of various stakeholders on the subject of quantum computing may differ, thereby complicating communication. To address this, we propose a view-based quantum development approach based on a Single Underlying Model (SUM) and a supporting quantum Integrated Development Environment (IDE). We highlight emerging challenges for future research.