Topology identification comprises reconstructing the Hamiltonian, and thus the corresponding interaction terms, by properly processing measurements of its density operator within a fixed time interval. It finds application in several quantum technology contexts, ranging from quantum communication to quantum computing or sensing. In this paper we provide analytical conditions for the solvability of the topology identification problem for autonomous quantum dynamical networks (i.e., as in our case, not explicitly depending on time via the use of an external drive). The solvability condition is then converted in an algorithm for quantum network reconstruction that is easily implementable on standard computer facilities. The obtained algorithm is tested for Hamiltonian reconstruction on numerical examples based on the quantum walks formalism.
Topology identification of autonomous quantum dynamical networks
Gherardini S
;
2022
Abstract
Topology identification comprises reconstructing the Hamiltonian, and thus the corresponding interaction terms, by properly processing measurements of its density operator within a fixed time interval. It finds application in several quantum technology contexts, ranging from quantum communication to quantum computing or sensing. In this paper we provide analytical conditions for the solvability of the topology identification problem for autonomous quantum dynamical networks (i.e., as in our case, not explicitly depending on time via the use of an external drive). The solvability condition is then converted in an algorithm for quantum network reconstruction that is easily implementable on standard computer facilities. The obtained algorithm is tested for Hamiltonian reconstruction on numerical examples based on the quantum walks formalism.File | Dimensione | Formato | |
---|---|---|---|
Topology_identification_autonomous_quantum_dynamical_networks_PRA_106_052426_2022.pdf
solo utenti autorizzati
Tipologia:
Versione Editoriale (PDF)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
485.33 kB
Formato
Adobe PDF
|
485.33 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.