Thesis supervisor: Gábor Vattay
Location of studies (in Hungarian): Institute of Physics and Astronomy at Eötvös Loránd University Abbreviation of location of studies: ELTE
Description of the research topic:
"Quantum Reservoir Computing (QRC) is a novel framework for quantum machine learning that leverages the complex and rich dynamics of quantum systems as temporal information processors. QRC aims to overcome the limitations of near-term quantum devices, such as noise, decoherence, and limited connectivity, by using a fixed and untrained quantum system as a reservoir that encodes the input signals into a high-dimensional quantum state. A simple readout layer, which can be classical or quantum, is then trained to map the reservoir state to the desired output. QRC has been shown to be effective and feasible for various tasks, such as time-series prediction, chaotic system modeling, and natural language processing, on different quantum platforms, such as superconducting qubits and photonic circuits.
The main goal of this PhD project is to explore the theoretical and experimental aspects of QRC, and to develop new methods and applications for quantum machine learning. The specific objectives are:
- To investigate the optimal design and performance of QRC systems, such as the choice of reservoir size, topology, dynamics, and readout scheme, and to compare them with classical reservoir computing and other quantum machine learning models.
- To develop new algorithms and techniques for QRC, such as quantum error correction, and to analyze their advantages and limitations.
- To demonstrate QRC on various quantum hardware platforms and to benchmark their scalability, robustness, and speed against classical counterparts.
- To apply QRC to solve challenging and relevant problems in physics and to explore the potential of QRC for interdisciplinary domains, such as biology, chemistry, and finance.
"
Required language skills: English Further requirements: MSc in Physics or Electrical Engineering and knowledge of Python programming language
Number of students who can be accepted: 2
Deadline for application: 2024-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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