@misc{BartkiewiczHE,
title = {Quantum Excellence Centre for Quantum-Enhanced Applications (QEC4QEA)},
author = {Karol Bartkiewicz},
url = {https://eurohpc-ju.europa.eu/european-quantum-excellence-centres-qecs-applications-science-and-industry_en},
year = {2029},
date = {2029-01-01},
urldate = {2024-11-25},
abstract = {Quantum computing has the potential to revolutionize science and technology, offering breakthroughs in optimization, cryptography, machine learning, materials science, and drug discovery. However, challenges including the lack of standardized tools, specialized training, infrastructure access, and limited industrial collaboration hinder its impactful progress or adoption. The QEC4QEA project seeks to overcome these obstacles by building a unified platform to accelerate the development and integration of quantum-enhanced applications across various scientific and industrial fields. QEC4QEA will provide a suite of resources, including a hardware-agnostic application library, benchmarking tools, compilers, APIs, and curated access to high-performance computing and quantum computing infrastructures. The project will refine its capabilities through agile development while promoting cross-disciplinary collaboration. A training program and help desk will support scientists and developers, enabling them to build and integrate quantum-enhanced solutions. By focusing on applications such as complex multi-objective optimization, advanced cryptography, quantum-enhanced machine learning, accelerated materials discovery, financial crash prediction, image analysis, graph classification and routing, QEC4QEA aims to demonstrate quantum computing's practical potential. Leveraging the collective expertise of its consortium and engaging industries like finance, pharmaceuticals, and supply chain management, QEC4QEA will deliver impactful solutions for real-world needs. This outreach strategy will foster collaboration between academia and industry, translating scientific breakthroughs into commercial applications. QEC4QEA will eliminate the barriers to adoption and catalyse a rapid shift from theoretical potential to practical deployment. These deployments might then enable new pathways for quantum computing applications with accelerated societal and economic benefits.},
howpublished = {2025},
note = {European Quantum Excellence Centres (QECs) in applications for science and industry (HORIZON-EUROHPC-JU-2023-QEC-05), budget: 462 250€ [AMU]},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}

@misc{Bartkiewicz2021,
title = {Kernel based quantum machine learning in optical circuits},
author = {Karol Bartkiewicz},
year = {2021},
date = {2021-12-01},
abstract = {This project focuses on theoretical and experimental research on kernel-based quantum machine learning (QML) using linear optics and individual photons as information carriers. QML is crucial for future development of quantum artificial neural networks and other quantum-enhanced technologies. QML can exponentially improve machine learning (ML) vastly applied in many industries. Here, we focus on three research objectives.First task is to design quantum optical circuits and implementing assorted kernels for QML. We plan on implementing these kernels to verify the benefits of this approach to QML over other solutions described in the literature.Second part of the project is to apply QML to classification or clustering, i.e., typical supervised and unsupervised ML problems. We plan to apply QML to learning properties of a quantum system. We will be developing a fremework for explaining parameters of QML system in terms directly relevant to the investigated problem. In the third stage we plan on applying QML to generative models (creating new data based on the training data). Three research objectives will be investigated both theoretically and experimentally: (i) quantum optical circuits for QML kernel implementation, (ii) applications and explainability of QML with kernels for supervised and unsupervised learning problems, (iii) quantum generative models.},
howpublished = {2019},
note = {Czech Science Foundation (at Palacy University in Olomouc), budget: 4 875 000 CZK (~ 850 000 PLN)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}