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pro vyhledávání: '"Paletta, P."'
Autor:
Paletta, Chiara, Prosen, Tomaž
In this paper, we address the problem of Yang-Baxter integrability of doubled quantum circuit of qubits (spins 1/2) with open boundary conditions where the two circuit replicas are only coupled at the left or right boundary. We investigate the cases
Externí odkaz:
http://arxiv.org/abs/2406.12695
Autor:
Paletta, Chiara
This work is based on the author's PhD thesis. The main result of the thesis is the use of the boost operator to develop a systematic method to construct new integrable spin chains with nearest-neighbour interaction and characterized by an R-matrix o
Externí odkaz:
http://arxiv.org/abs/2312.00064
Publikováno v:
Quantum 8, 1337 (2024)
Between NISQ (noisy intermediate scale quantum) approaches without any proof of robust quantum advantage and fully fault-tolerant quantum computation, we propose a scheme to achieve a provable superpolynomial quantum advantage (under some widely acce
Externí odkaz:
http://arxiv.org/abs/2307.10729
In recent years, deep learning-based solar forecasting using all-sky images has emerged as a promising approach for alleviating uncertainty in PV power generation. However, the stochastic nature of cloud movement remains a major challenge for accurat
Externí odkaz:
http://arxiv.org/abs/2306.11682
We consider spin-1/2 chains with external driving that breaks the continuous symmetries of the Hamiltonian. We introduce a family of models described by the Lindblad equation with local jump operators. The models have hidden strong symmetries in the
Externí odkaz:
http://arxiv.org/abs/2305.01922
Publikováno v:
SciPost Phys. 15, 071 (2023)
In this paper we present a new integrable deformation of the Hubbard model. Our deformation gives rise to a range 3 interaction term in the Hamiltonian which does not preserve spin or particle number. This is the first non-trivial medium range deform
Externí odkaz:
http://arxiv.org/abs/2301.01612
Sky-image-based solar forecasting using deep learning has been recognized as a promising approach in reducing the uncertainty in solar power generation. However, one of the biggest challenges is the lack of massive and diversified sky image samples.
Externí odkaz:
http://arxiv.org/abs/2211.14709
Autor:
Nie, Yuhao, Paletta, Quentin, Scott, Andea, Pomares, Luis Martin, Arbod, Guillaume, Sgouridis, Sgouris, Lasenby, Joan, Brandt, Adam
Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep learning-b
Externí odkaz:
http://arxiv.org/abs/2211.02108
Autor:
Ricardo Augusto Paletta Guedes, Vanessa Maria Paletta Guedes, Daniela Marcelo Gravina, Daniel Augusto Guedes Moraes, Alfredo Chaoubah
Publikováno v:
Revista Brasileira de Oftalmologia, Vol 83 (2024)
RESUMO Objetivo Avaliar os resultados preliminares em médio prazo (até 6 meses) do uso isolado ou em combinação com a cirurgia de catarata do dispositivo XEN® Gel Stent na população brasileira. Métodos Realizou-se um estudo longitudinal retro
Externí odkaz:
https://doaj.org/article/f315736e49234f21ababec2289bf11db
Publikováno v:
Methane, Vol 3, Iss 1, Pp 160-171 (2024)
The collection and use of Sargassum spp. as feedstock for the production of valuable products such as biomethane by anaerobic digestion (AD) would mitigate the negative impact of the blooms and the costs related to waste management in the Dominican R
Externí odkaz:
https://doaj.org/article/2f67c7b6827a4588b6a67e96f2615cd4