Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Barmparis, G. D."'
Autor:
Angelaki, E., Lazarides, N., Barmparis, G. D., Kourakis, I., Marketou, M. E., Tsironis, G. P.
Publikováno v:
Chaos 34, 043140 (2024)
The heart beats due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large bo
Externí odkaz:
http://arxiv.org/abs/2311.08173
We investigate the use of Quantum Neural Networks for discovering and implementing quantum error-correcting codes. Our research showcases the efficacy of Quantum Neural Networks through the successful implementation of the Bit-Flip quantum error-corr
Externí odkaz:
http://arxiv.org/abs/2304.06681
Artificial intelligence in the form of deep learning is now very popular and directly implemented in many areas of science and technology. In the present work we study time evolution of Discrete Breathers in one-dimensional nonlinear chains using the
Externí odkaz:
http://arxiv.org/abs/2212.02211
In quantum targeted energy transfer, bosons are transferred from a certain crystal site to an alternative one, utilizing a nonlinear resonance configuration similar to the classical targeted energy transfer. We use a novel computational method based
Externí odkaz:
http://arxiv.org/abs/2212.00556
We focus on chaotic dynamical systems and analyze their time series with the use of autoencoders, i.e., configurations of neural networks that map identical output to input. This analysis results in the determination of the latent space dimension of
Externí odkaz:
http://arxiv.org/abs/2109.13078
The nonlinear dimer obtained through the nonlinear Schr{\"o}dinger equation has been a workhorse for the discovery the role nonlinearity plays in strongly interacting systems. While the analysis of the stationary states demonstrates the onset of a sy
Externí odkaz:
http://arxiv.org/abs/2109.15057
Autor:
Barmparis, G. D., Tsironis, G. P.
For an ensemble of nonlinear systems that model, for instance, molecules or photonic systems, we propose a method that finds efficiently the configuration that has prescribed transfer properties. Specifically, we use physics-informed machine-learning
Externí odkaz:
http://arxiv.org/abs/2104.13471
Autor:
Barmparis, G. D., Tsironis, G. P.
The spread of COVID-19 during the initial phase of the first half of 2020 was curtailed to a larger or lesser extent through measures of social distancing imposed by most countries. In this work, we link directly, through machine learning techniques,
Externí odkaz:
http://arxiv.org/abs/2008.08162
Autor:
Barmparis, G. D., Tsironis, G. P.
The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial, and educational organization. The strict disciplinary measures implemented by Chi
Externí odkaz:
http://arxiv.org/abs/2003.14334
Autor:
Neofotistos, G., Mattheakis, M., Barmparis, G. D., Hizanidis, J., Tsironis, G. P., Kaxiras, E.
Chimeras and branching are two archetypical complex phenomena that appear in many physical systems; because of their different intrinsic dynamics, they delineate opposite non-trivial limits in the complexity of wave motion and present severe challeng
Externí odkaz:
http://arxiv.org/abs/1807.10758