Simone Severini mostly deals with Discrete mathematics, Combinatorics, Quantum, Quantum algorithm and Graph theory. Her Discrete mathematics research includes themes of Quantum information, Quantum information science, Classical capacity and Hamiltonian. Her Quantum study is associated with Quantum mechanics.
The Quantum algorithm study combines topics in areas such as Quantum computer and Theoretical computer science. Her Theoretical computer science study combines topics from a wide range of disciplines, such as Test data generation, Quantum machine learning and Reinforcement learning. The concepts of her Graph theory study are interwoven with issues in Modular decomposition, 1-planar graph, Laplacian matrix, Symmetric group and Gauge theory.
Simone Severini mainly focuses on Combinatorics, Discrete mathematics, Quantum, Quantum entanglement and Quantum computer. Her Combinatorics study integrates concerns from other disciplines, such as Upper and lower bounds and Unitary matrix. Her Discrete mathematics study combines topics in areas such as Quantum walk and Graph theory.
Simone Severini is interested in Quantum state, which is a field of Quantum. Her Quantum computer research incorporates elements of Quantum algorithm, Theoretical computer science and Artificial intelligence. Her work deals with themes such as Quantum mechanics and Qubit, which intersect with Statistical physics.
Quantum, Quantum state, Quantum computer, Discrete mathematics and Artificial neural network are her primary areas of study. Her study explores the link between Quantum and topics such as Algorithm that cross with problems in Quantum process and Master equation. Her Quantum state research includes elements of State, Quantum information, Reconstruction conjecture, Graph theory and Statistical physics.
Her Quantum computer research is multidisciplinary, relying on both Hamiltonian mechanics, Theoretical computer science, Applied mathematics, Artificial intelligence and MNIST database. Simone Severini works mostly in the field of Theoretical computer science, limiting it down to topics relating to Computation and, in certain cases, Boltzmann machine and Computational complexity theory. Her studies deal with areas such as Multipartite and Network science, Complex network as well as Discrete mathematics.
Simone Severini spends much of her time researching Quantum, Quantum computer, Quantum state, Theoretical computer science and Quantum machine learning. Her Quantum research incorporates themes from Artificial neural network and Algorithm. Her study ties her expertise on Quantum algorithm together with the subject of Quantum computer.
Her Quantum state study incorporates themes from Quantum information, Scaling and Qubit. Her Quantum machine learning research integrates issues from Test data generation and Reinforcement learning. Her research investigates the connection between Quantum entanglement and topics such as Hermitian matrix that intersect with issues in Tensor product.
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Graph-theoretic approach to quantum correlations.
Adán Cabello;Simone Severini;Andreas Winter.
Physical Review Letters (2014)
Quantum graphity: A model of emergent locality
Tomasz Konopka;Fotini Markopoulou;Fotini Markopoulou;Simone Severini.
Physical Review D (2008)
Differential network entropy reveals cancer system hallmarks
James West;Ginestra Bianconi;Simone Severini;Andrew E. Teschendorff.
Scientific Reports (2012)
The Laplacian of a Graph as a Density Matrix: A Basic Combinatorial Approach to Separability of Mixed States
Samuel L. Braunstein;Sibasish Ghosh;Simone Severini.
Annals of Combinatorics (2006)
Zero-error communication via quantum channels, non-commutative graphs and a quantum Lovasz theta function
Runyao Duan;Simone Severini;Andreas J. Winter.
arXiv: Quantum Physics (2010)
On dynamic network entropy in cancer
James West;Ginestra Bianconi;Simone Severini;Andrew Teschendorff.
arXiv: Molecular Networks (2012)
Zero-Error Communication via Quantum Channels, Noncommutative Graphs, and a Quantum Lovász Number
Runyao Duan;S. Severini;A. Winter.
IEEE Transactions on Information Theory (2013)
Quantum machine learning: a classical perspective.
Carlo Ciliberto;Mark Herbster;Alessandro Davide Ialongo;Alessandro Davide Ialongo;Massimiliano Pontil;Massimiliano Pontil.
Proceedings of The Royal Society A: Mathematical, Physical and Engineering Sciences (2018)
On the quantum chromatic number of a graph
Peter J. Cameron;Ashley Montanaro;Michael W. Newman;Simone Severini.
Electronic Journal of Combinatorics (2007)
Shannon and von Neumann entropy of random networks with heterogeneous expected degree
Kartik Anand;Ginestra Bianconi;Simone Severini.
Physical Review E (2011)
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