Follow
Mattia Fiorentini
Mattia Fiorentini
Rigetti Computing
Verified email at rigetti.com
Title
Cited by
Cited by
Year
Parameterized quantum circuits as machine learning models
M Benedetti, E Lloyd, S Sack, M Fiorentini
Quantum Science and Technology 4 (4), 043001, 2019
8672019
Hardware-efficient variational quantum algorithms for time evolution
M Benedetti, M Fiorentini, M Lubasch
Physical Review Research 3 (3), 033083, 2021
1422021
Filtering variational quantum algorithms for combinatorial optimization
D Amaro, C Modica, M Rosenkranz, M Fiorentini, M Benedetti, M Lubasch
Quantum Science and Technology 7 (1), 015021, 2022
1122022
Thermoelectric coefficients of n -doped silicon from first principles via the solution of the Boltzmann transport equation
M Fiorentini, N Bonini
Physical Review B 94 (8), 085204, 2016
992016
A case study of variational quantum algorithms for a job shop scheduling problem
D Amaro, M Rosenkranz, N Fitzpatrick, K Hirano, M Fiorentini
EPJ Quantum Technology 9 (1), 5, 2022
632022
Variational quantum amplitude estimation
K Plekhanov, M Rosenkranz, M Fiorentini, M Lubasch
Quantum 6, 670, 2022
462022
Variational inference with a quantum computer
M Benedetti, B Coyle, M Fiorentini, M Lubasch, M Rosenkranz
Physical Review Applied 16 (4), 044057, 2021
442021
Erratum: Parameterized quantum circuits as machine learning models (2019 Quant. Sci. Tech. 4 043001)
M Benedetti, E Lloyd, S Sack, M Fiorentini
Quantu m Science and Technology 5 (1), 019601, 2019
122019
Parameterized quantum circuits as machine learning models. Quantum Science and Technology 4 (4), 043001 (2019)
M Benedetti, E Lloyd, S Sack, M Fiorentini
5
Circuitos cuánticos parametrizados como modelos de aprendizaje automático
M Benedetti, E Lloyd, S Sack, M Fiorentini
Ciencia y tecnología cuánticas 4 (4), 043001, 2019
32019
Computer system and method for utilizing variational inference
M Benedetti, BJ Coyle, M Fiorentini, M Lubasch, M Rosenkranz
US Patent App. 17/654,225, 2022
22022
Parametrerade kvantkretsar som maskininlärningsmodeller
M Benedetti, E Lloyd, S Sack, M Fiorentini
Quantum Science and Technology 4 (4), 043001, 2019
22019
Parameterized quantum circuits as machine learning models. Quantum Science and Technology 4 (4): 043001, DOI: 10.1088/2058-9565/ab4eb5
M Benedetti, E Lloyd, S Sack, M Fiorentini
arXiv preprint arXiv:1906.07682, 2019
22019
Hardware-efficient variational quantum algorithms for time evolution (2020)
M Benedetti, M Fiorentini, M Lubasch
arXiv preprint arXiv:2009.12361, 0
2
Method for reducing quantum circuit depth for amplitude estimation
M Rosenkranz, M Lubasch, M Fiorentini, K Plekhanov
US Patent App. 17/930,339, 2023
12023
Parameterized quantum circuits as machine learning models (vol 4, 043001, 2019)
M Benedetti, E Lloyd, S Sack, M Fiorentini
QUANTUM SCIENCE AND TECHNOLOGY 5 (1), 2020
12020
Apparatus And Method For Optimizing, Monitoring And Controlling A Real Physical System
L Coopmans, Y Kikuchi, M Benedetti, M Fiorentini
US Patent App. 18/201,410, 2023
2023
Quantum computer system and method for combinatorial optimization
D Amaro, C Modica, M Benedetti, M Fiorentini, M Lubasch, ...
US Patent App. 17/825,908, 2022
2022
Stefan Sack en Mattia Fiorentini,"
M Benedetti, E Lloyd
Geparametriseerde kwantumcircuits als modellen voor machine learning …, 2019
2019
downloaded from the King’s Research Portal at https://kclpure. kcl. ac. uk/portal
C Piacentini
2015
The system can't perform the operation now. Try again later.
Articles 1–20