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Ryszard Kukulski (IT4Innovations National Supercomputing Center)06/11/2026, 09:30Computational Sciences & Informatics (e.g. AI, HPC, Data Science)User's talk
In this presentation, we propose a quantum certification method whose main goal is to verify if a quantum provider is honest about the capabilities of their quantum machine. To do this, we use machine learning methods to carefully create a quantum circuit to be executed by the provider. By investigating the outputs of the computation, we are able to certify the validity of the quantum machine...
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Zaira Carboni (Università degli studi di Cagliari)06/11/2026, 09:50Computational Sciences & Informatics (e.g. AI, HPC, Data Science)User's talk
Graphyne and graphdiyne represent two-dimensional carbon allotropes structurally related to graphene. Unlike graphene, which is composed exclusively of sp²-hybridized carbon atoms arranged in a honeycomb lattice, graphyne and graphdiyne incorporate sp-hybridized carbon atoms through acetylenic linkages. In graphyne, aromatic rings are connected by single –C≡C– units, while in graphdiyne they...
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Mr Michal Kubicek (Silesian University in Opava, School of Business Administration in Karvina)06/11/2026, 10:10Computational Sciences & Informatics (e.g. AI, HPC, Data Science)User's talk
How much exposure does a language model need before it reliably learns a new entity, and how can this process be measured experimentally on large-scale HPC infrastructure? We present the computational design of a dissertation experiment focused on entity learnability in large language models, using fictitious brands and their attributes as a controlled case. The experiment uses continued...
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