Retrieving space-dependent polarization transformations via near-optimal quantum process tomography
Year: 2023
Type: article
Abstract: An optical waveplate rotating light polarization can be modeled as a single-qubit unitary operator. This analogy can be exploited to experimentally retrieve a polarization transformation within the paradigm of quantum process tomography. Standard approaches to tomographic problems rely on the maximum-likelihood estimation, providing the most likely transformation to yield the same outcomes as a set of experimental projective measurements. The performances of this method strongly depend on the number of input measurements and the numerical minimization routine that is adopted. Here we investigate the application of genetic and machine learning approaches to this problem, finding that both allow for accurate reconstructions and fast operations when processing a set of projective measurements very close to the minimal one. We apply these techniques to the case of space-dependent polarization transformations, providing an experimental characterization of the optical action of spin-orbit metasurfaces having patterned birefringence. Our efforts thus expand the toolbox of methodologies for optical process tomography. In particular, we find that the neural network-based scheme provides a significant speed-up, that may be critical in applications requiring a characterization in real-time. We expect these results to lay the groundwork for the optimization of tomographic approaches in more general quantum processes, including non-unitary gates and operations in higher-dimensional Hilbert spaces.
Source: Optics Express
DOI: 10.1364/oe.491518
Authors: Francesco Di Colandrea, Lorenzo Amato, Roberto Schiattarella, Alexandre Dauphin, Filippo Cardano
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,270
Funders: National Science Foundation, “la Caixa” Foundation, Centres de Recerca de Catalunya, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Generalitat de Catalunya, Narodowe Centrum Nauki, Narodowym Centrum Nauki, Barcelona Supercomputing Center, QuantERA, Ministero dell'Università e della Ricerca, European Research Council, Agència de Gestió d'Ajuts Universitaris i de Recerca, European Regional Development Fund, European Social Fund, NextGenerationEU
Awards: G1188902550, G1255325603, G148743912, G162601807, G1648780019, Junior Leader la Caixa Postdoctoral Fellowship Programme: Shaping the new generation of leaders in research, G1888088267, G19065579, G1908469581, G1909050264, G1953887145, G2064873908, G2163055958, G2185723689, G2341542479, G2357050330, G2478333882, G2601397997, G2654780445, G2673512141, G2724632752, G2744780120, G288263039, G3005324705, G3048907528, G3176176206, G3203908756, G3257784381, G3261693824, G3288897321, G3323999484, G3375376170, G3522231704, G3529102120, G356394092, G3639969887, G3674674691, G3681454997, G3729210810, G3803561910, G3886156397, G4042783231, G410571670, G4160207744, G434337789, G4353981422, G451917667, G4571205363, G4630312626, G4727238542, G4993383890, G5395125964, G5426121769, G5440125773, G5443090575, G5505639174, G5554424168, G5784736367, G5852091828, G5893741411, G5955501538, G5967599077, G598773271, G6079324567, G6145842628, Structured electric-dipole-based chirality, G6342290315, G6482940084, G6501668260, G654413331, G6573142848, G6631906350, G6656126374, G6662880077, G6727213032, G6731467812, G6740521169, G6790183914, G6924429424, G7194998952, G7222869497, G7226647862, G7271754958, G7385800239, G7407602803, G7425137858, G7731791180, Regulation of vomeronasal receptor genes in the mouse, G777498305, G7898799392, G8023785571, G8041829832, G8191894158, G8306300202, G853839195, G860593315, Optical Topologic Logic, G8665153912, G8676624529, G885552189
OpenAlex ID: W4383500422