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 Discovering nonlinear resonances through physics-informed machine learning

G. D. Barmparis and G. P. Tsironis, use physics-informed machine learning (PIML) techniques to find the parameters for the efficient transfer of an electron (or photon) to a targeted state in a nonlinear dimer.

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Detection of abnormal left ventricular geometry in patients without cardiovascular disease through machine learning: An ECG‐based approach.

E. Angelaki, M. E. Marketou, G. D. Barmparis, A. Patrianakos, P. E. Vardas, F. Parthenakis, and G. P. Tsironis apply Machine Learning techniques to basic clinical parameters and electrocardiographic features in order to detect abnormal left ventricular geometry even before the onset of left ventricular hypertrophy, in a population without established CVD.

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Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach

G.D. Barmparis and G.P. Tsironis estimate the infection horizon of COVID-19 in eight countries and predict successfully both the expected number of daily infections per country and the duration of the epidemic in each country.

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Holographic Competition of Phases and Superconductivity

QCN members E. Kiritsis and Li Li, has used holographic techniques to model and study the competition of four phases.

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Chimeras in SQUID Metamaterials

In recent a article of QCN researchers in Physical Review B, the mythological beast chimera appears on the title of the paper.

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Generic ferroelectric ground state in underdoped La-214 cuprates

QCN researchers have performed extensive measurements of the electric polarization on Sr and Li doped La2CuO4 single crystals. It is shown that La1.999Sr0.001CuO4 exhibits distinct ferroelectric behavior along different crystallographic directions.

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Ultrafast observation of critical nematic fluctuations and giant magnetoelastic coupling in iron pnictides

CCQCN member Prof. I. Perakis in collaboration with a group of researchers, published a significant article in Nature Communications, entitled "Ultrafast observation of critical nematic fluctuations and giant magnetoelastic coupling in iron pnictides"

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