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pro vyhledávání: '"Kourtis A"'
With the emergence of Foundational Machine Learning Interatomic Potential (FMLIP) models trained on extensive datasets, transferring data between different ML architectures has become increasingly important. In this work, we examine the extent to whi
Externí odkaz:
http://arxiv.org/abs/2409.05590
We show that unconventional relaxation dynamics of special initial states in one-dimensional arrays of Rydberg atoms produce non-generic decay of the initial-state survival probability at early times. Using the PXP hamiltonian as a minimal model of t
Externí odkaz:
http://arxiv.org/abs/2406.12968
Autor:
Osaba, Eneko, Petrič, Matic, Oregi, Izaskun, Seidel, Raphael, Ruiz, Alejandra, Bock, Sebastian, Kourtis, Michail-Alexandros
This paper focuses on the presentation and evaluation of the high-level quantum programming language Eclipse Qrisp. The presented framework, used for developing and compiling quantum algorithms, is measured in terms of efficiency for its implementati
Externí odkaz:
http://arxiv.org/abs/2405.20173
Publikováno v:
Front. Phys. 12, 1431810 (2024)
We introduce a tensor network algorithm for the solution of $p$-spin models. We show that bond compression through rank-revealing decompositions performed during the tensor network contraction resolves logical redundancies in the system exactly and i
Externí odkaz:
http://arxiv.org/abs/2405.08106
We introduce fermionic machine learning (FermiML), a machine learning framework based on fermionic quantum computation. FermiML models are expressed in terms of parameterized matchgate circuits, a restricted class of quantum circuits that map exactly
Externí odkaz:
http://arxiv.org/abs/2404.19032
Publikováno v:
Phys. Rev. Research 6, 023294 (2024)
We introduce a quantum-inspired approximation algorithm for MaxCut based on low-depth Clifford circuits. We start by showing that the solution unitaries found by the adaptive quantum approximation optimization algorithm (ADAPT-QAOA) for the MaxCut pr
Externí odkaz:
http://arxiv.org/abs/2310.15022
Autor:
Lorena Espinar, Marta Garcia-Cao, Alisa Schmidt, Savvas Kourtis, Antoni Gañez Zapater, Carla Aranda-Vallejo, Ritobrata Ghose, Laura Garcia-Lopez, Ilir Sheraj, Natalia Pardo-Lorente, Marina Bantulà, Laura Pascual-Reguant, Evangelia Darai, Maria Guirola, Joan Montero, Sara Sdelci
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract Nuclear metabolism and DNA damage response are intertwined processes, but the precise molecular links remain elusive. Here, we explore this crosstalk using triple-negative breast cancer (TNBC) as a model, a subtype often prone to DNA damage
Externí odkaz:
https://doaj.org/article/0fd2c3a7be624c68af7c1b6ba8b07ae7
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-3-2024, Pp 507-512 (2024)
Floods are among the most prevalent and devastating natural disasters, affecting over 2 billion people worldwide. The increasing frequency and intensity of extreme precipitation events, driven by climate change, increase the vulnerability of communit
Externí odkaz:
https://doaj.org/article/97e7844ed7784e3081f1a8d36a37d904
Autor:
Shen, Yao, Chandrasekaran, Anirudh, Sears, Jennifer, Zhang, Tiantian, Han, Xin, Shi, Youguo, Li, Jiemin, Pelliciari, Jonathan, Bisogni, Valentina, Dean, Mark P. M., Kourtis, Stefanos
The energy spectrum of topological semimetals contains protected degeneracies in reciprocal space that correspond to Weyl, Dirac, or multifold fermionic states. To exploit the unconventional properties of these states, one has to access the electroni
Externí odkaz:
http://arxiv.org/abs/2301.02677
Autor:
Bozis, Emmanouil-Zafeirios G., Sagias, Nikos C., Batistatos, Michael C., Kourtis, Michail-Alexandros, Xilouris, George K., Kourtis, Anastasios
Publikováno v:
In AEUE - International Journal of Electronics and Communications December 2024 187