Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Mandarino, Antonio"'
A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems
Quantum many-body systems are of great interest for many research areas, including physics, biology and chemistry. However, their simulation is extremely challenging, due to the exponential growth of the Hilbert space with the system size, making it
Externí odkaz:
http://arxiv.org/abs/2407.20669
The use of deep learning in physical sciences has recently boosted the ability of researchers to tackle physical systems where little or no analytical insight is available. Recently, the Physics-Informed Neural Networks (PINNs) have been introduced a
Externí odkaz:
http://arxiv.org/abs/2405.13442
Autor:
Mironowicz, Piotr, H., Akshata Shenoy, Mandarino, Antonio, Yilmaz, A. Ege, Ankenbrand, Thomas
Machine learning and quantum machine learning (QML) have gained significant importance, as they offer powerful tools for tackling complex computational problems across various domains. This work gives an extensive overview of QML uses in quantitative
Externí odkaz:
http://arxiv.org/abs/2405.10119
Publikováno v:
Phys. Rev. E 109, 064146 (2024)
Navigating the intricacies of thermal management at the quantum scale is a challenge in the pursuit of advanced nanoscale technologies. To this extent, theoretical frameworks introducing minimal models mirroring the functionality of electronic curren
Externí odkaz:
http://arxiv.org/abs/2402.16721
State preparation plays a pivotal role in numerous quantum algorithms, including quantum phase estimation. This paper extends and benchmarks counterdiabatic driving protocols across three one-dimensional spin systems characterized by phase transition
Externí odkaz:
http://arxiv.org/abs/2311.04282
Autor:
Mandarino, Antonio, Scala, Giovanni
Publikováno v:
Entropy 2023, 25(1), 94
The theorem developed by John Bell constituted the starting point of a revolution that translated a philosophical question about the nature of reality into the broad and intense field of research of the quantum information technologies. We focus on a
Externí odkaz:
http://arxiv.org/abs/2310.09231
Autor:
Scala, Giovanni, Mandarino, Antonio
Publikováno v:
Int J Theor Phys 63, 17 (2024)
We explore the relationship between Kochen-Specker quantum contextuality and Bell-nonclassicality for ensembles of two-qubit pure states. We present a comparative analysis showing that the violation of a noncontextuality inequality on a given quantum
Externí odkaz:
http://arxiv.org/abs/2310.09047
We frame entanglement detection as a problem of random variable inference to introduce a quantitative method to measure and understand whether entanglement witnesses lead to an efficient procedure for that task. Hence we quantify how many bits of inf
Externí odkaz:
http://arxiv.org/abs/2308.07744
Autor:
Incudini, Massimiliano, Grossi, Michele, Ceschini, Andrea, Mandarino, Antonio, Panella, Massimo, Vallecorsa, Sofia, Windridge, David
Publikováno v:
Quantum Machine Intelligence, vol. 5, no. 2, pp. 1-24, ISSN: 2524-4906, Springer Nature, Germany, December 2023
Quantum neural networks hold significant promise for numerous applications, particularly as they can be executed on the current generation of quantum hardware. However, due to limited qubits or hardware noise, conducting large-scale experiments often
Externí odkaz:
http://arxiv.org/abs/2303.11283
The Bell inequalities stand at the cornerstone of the developments of quantum theory on both the foundational and applied side. The discussion started as a way to test whether the quantum description of reality is complete or not, but it developed in
Externí odkaz:
http://arxiv.org/abs/2302.06320