Quantum computing is a growing field where the information is processed by two-levels quantum states known as qubits. Current physical realizations of qubits require a careful calibration, composed by different experiments, due to noise and decoherence phenomena. Among the different characterization experiments, a crucial step is to develop a model to classify the measured state by discriminating the ground state from the excited state. In this proceedings we benchmark multiple classification techniques applied to real quantum devices.
Benchmarking machine learning models for quantum state classification / E. Pedicillo, A. Pasquale, S. Carrazza. - (2023 Sep 14). (Intervento presentato al 26. convegno International Conference on Computing in High Energy & Nuclear Physics tenutosi a Norfolk : 8-12 May nel 2023) [10.48550/arXiv.2309.07679].
Benchmarking machine learning models for quantum state classification
E. PedicilloPrimo
;A. PasqualeSecondo
;S. CarrazzaUltimo
2023
Abstract
Quantum computing is a growing field where the information is processed by two-levels quantum states known as qubits. Current physical realizations of qubits require a careful calibration, composed by different experiments, due to noise and decoherence phenomena. Among the different characterization experiments, a crucial step is to develop a model to classify the measured state by discriminating the ground state from the excited state. In this proceedings we benchmark multiple classification techniques applied to real quantum devices.File | Dimensione | Formato | |
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