@article{Getman2021,

title = {Broadband vectorial ultrathin optics with experimental efficiency up to 99% in the visible region via universal approximators},

author = {F Getman and M Makarenko and A Burguete-Lopez and A Fratalocchi},

url = {https://doi.org/10.1038/s41377-021-00489-7},

doi = {10.1038/s41377-021-00489-7},

issn = {2047-7538},

year  = {2021},

date = {2021-03-04},

journal = {Light: Science & Applications},

volume = {10},

number = {1},

pages = {47},

abstract = {Integrating conventional optics into compact nanostructured surfaces is the goal of flat optics. Despite the enormous progress in this technology, there are still critical challenges for real-world applications due to the limited operational efficiency in the visible region, on average lower than 60%, which originates from absorption losses in wavelength-thick (≈ 500thinspacenm) structures. Another issue is the realization of on-demand optical components for controlling vectorial light at visible frequencies simultaneously in both reflection and transmission and with a predetermined wavefront shape. In this work, we developed an inverse design approach that allows the realization of highly efficient (up to 99%) ultrathin (down to 50thinspacenm thick) optics for vectorial light control with broadband input--output responses in the visible and near-IR regions with a desired wavefront shape. The approach leverages suitably engineered semiconductor nanostructures, which behave as a neural network that can approximate a user-defined input--output function. Near-unity performance results from the ultrathin nature of these surfaces, which reduces absorption losses to near-negligible values. Experimentally, we discuss polarizing beam splitters, comparing their performance with the best results obtained from both direct and inverse design techniques, and new flat-optics components represented by dichroic mirrors and the basic unit of a flat-optics display that creates full colours by using only two subpixels, overcoming the limitations of conventional LCD/OLED technologies that require three subpixels for each composite colour. Our devices can be manufactured with a complementary metal-oxide-semiconductor (CMOS)-compatible process, making them scalable for mass production at low cost.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1002/aisy.202100105,

title = {Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks},

author = {Maksim Makarenko and Qizhou Wang and Arturo Burguete-Lopez and Fedor Getman and Andrea Fratalocchi},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/aisy.202100105},

doi = {https://doi.org/10.1002/aisy.202100105},

year  = {2021},

date = {2021-01-01},

journal = {Advanced Intelligent Systems},

volume = {n/a},

number = {n/a},

pages = {2100105},

abstract = {In the past 20 years, flat-optics has emerged as a promising light manipulation technology, surpassing bulk optics in performance, versatility, and miniaturization capabilities. As of today, however, this technology is yet to find widespread commercial applications. One of the challenges is obtaining scalable and highly efficient designs that can withstand the fabrication errors associated with nanoscale manufacturing techniques. This problem becomes more severe in flexible structures, in which deformations appear naturally when flat-optics structures are conformally applied to, for example, biocompatible substrates. Herein, an inverse design platform that enables the fast design of flexible flat-optics that maintain high performance under deformations of their original geometry is presented. The platform leverages on suitably designed evolutionary large-scale optimizers, equipped with fast-trained neural network predictors based on encoder decoder architectures. This approach supports the implementation of flexible flat-optics robust to both fabrication errors or user-defined perturbation stress. This method is validated by a series of experiments in which broadband flexible light polarizers, which maintain an average polarization efficiency of 80% over 200 nm bandwidths when measured under large mechanical deformations, are realized. These results could be helpful for the realization of a robust class of flexible flat-optics for biosensing, imaging, and biomedical devices.},

keywords = {flexible flat optics, inverse design, neural networks, robust design},

pubstate = {published},

tppubtype = {article}

}

@article{Makarenko2020,

title = {Generalized Maxwell projections for multi-mode network Photonics},

author = {M Makarenko and A Burguete-Lopez and F Getman and A Fratalocchi},

url = {https://doi.org/10.1038/s41598-020-65293-6},

doi = {10.1038/s41598-020-65293-6},

issn = {2045-2322},

year  = {2020},

date = {2020-06-03},

journal = {Scientific Reports},

volume = {10},

number = {1},

pages = {9038},

abstract = {The design of optical resonant systems for controlling light at the nanoscale is an exciting field of research in nanophotonics. While describing the dynamics of few resonances is a relatively well understood problem, controlling the behavior of systems with many overlapping states is considerably more difficult. In this work, we use the theory of generalized operators to formulate an exact form of spatio-temporal coupled mode theory, which retains the simplicity of traditional coupled mode theory developed for optical waveguides. We developed a fast computational method that extracts all the characteristics of optical resonators, including the full density of states, the modes quality factors, and the mode resonances and linewidths, by employing a single first principle simulation. This approach can facilitate the analytical and numerical study of complex dynamics arising from the interactions of many overlapping resonances, defined in ensembles of resonators of any geometrical shape and in materials with arbitrary responses.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}