no code implementations • 17 Jul 2023 • Mustafa Yıldırım, Niyazi Ulas Dinc, Ilker Oguz, Demetri Psaltis, Christophe Moser
In this study, we present a novel framework that uses multiple scattering that is capable of synthesizing programmable linear and nonlinear transformations concurrently at low optical power by leveraging the nonlinear relationship between the scattering potential, represented by data, and the scattered field.
no code implementations • 30 May 2023 • Ilker Oguz, Junjie Ke, Qifei Wang, Feng Yang, Mustafa Yıldırım, Niyazi Ulas Dinc, Jih-Liang Hsieh, Christophe Moser, Demetri Psaltis
Neural networks (NN) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations.
no code implementations • 19 Aug 2022 • Mustafa Yıldırım, Ilker Oguz, Fabian Kaufmann, Marc Reig Escale, Rachel Grange, Demetri Psaltis, Christophe Moser
A dataset is encoded digitally on the spectrum of a femtosecond pulse which is then launched in the waveguide.
no code implementations • 25 Oct 2021 • Babak Rahmani, Demetri Psaltis, Christophe Moser
To characterize a physical system to behave as desired, either its underlying governing rules must be known a priori or the system itself be accurately measured.
1 code implementation • 22 Dec 2020 • Uğur Teğin, Mustafa Yıldırım, İlker Oğuz, Christophe Moser, Demetri Psaltis
Today's heavy machine learning tasks are fueled by large datasets.
1 code implementation • 29 Jun 2019 • Babak Rahmani, Damien Loterie, Eirini Kakkava, Navid Borhani, Uğur Teğin, Demetri Psaltis, Christophe Moser
The output of physical systems is often accessible by measurements such as the 3D position of a robotic arm actuated by many actuators or the speckle patterns formed by shining the spot of a laser pointer on a wall.