Parameter Shift Rule for Variational Photonic Quantum Circuit

In recent years, variational quantum algorithms (VQA) have been receiving a great deal of attention, demonstrating their applicability in a wide range of tasks and implementable even in the noisy quantum processors currently available [1]. A VQA is a hybrid quantum-classical algorithm where a proble...

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Vydáno v:Conference on Lasers & Electro-Optics Europe & International Quantum Electronics Conference (Online) s. 1
Hlavní autoři: Hoch, Francesco, Rodari, Giovanni, Giordani, Taira, Perret, Paul, Spagnolo, Nicolo, Carvacho, Gonzalo, Pentangelo, Ciro, Piacentini, Simone, Crespi, Andrea, Ceccarelli, Francesco, Osellame, Roberto, Sciarrino, Fabio
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 23.06.2025
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ISSN:2833-1052
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Shrnutí:In recent years, variational quantum algorithms (VQA) have been receiving a great deal of attention, demonstrating their applicability in a wide range of tasks and implementable even in the noisy quantum processors currently available [1]. A VQA is a hybrid quantum-classical algorithm where a problem is encoded in a cost function that can be efficiently evaluated on a parametric quantum device and the minimum represents the desired solution. A classical optimizer can then be used to tune the parameters of the quantum device in order to minimize the loss function and find the optimal solution (Fig. 1). In the field of quantum computing, one of the main promising platforms is based on the use of single photons and integrated photonic circuits since photons are a natural choice for transferring information and have different degree of freedom that can be to encode the information. Moreover the use of integrated photonic allow the realization of compact and table complex interferometers with a high number of control parameters. Even if there are few applications [2], [3], VQA with photonic platforms remains a relatively unexplored subject. One of the main problems is the application of the classical optimizer to the photonic platform since most of the algorithms are based on the estimation of the gradient of the cost function with the finite difference method but that can not be applied to a noisy apparatus.
ISSN:2833-1052
DOI:10.1109/CLEO/Europe-EQEC65582.2025.11109568