Publications de Carlo Gigli | EPFL Graph Search

Subwavelength imaging using a solid-immersion diffractive optical processor

Demetri Psaltis, Carlo Gigli, Niyazi Ulas Dinç

Phase imaging is widely used in biomedical imaging, sensing, and material characterization, among other fields. However, direct imaging of phase objects with subwavelength resolution remains a challenge. Here, we demonstrate subwavelength imaging of phase ...

Springernature2024

Wave optical model for tomographic volumetric additive manufacturing

Christophe Moser, Carlo Gigli, Jorge Andres Madrid Wolff, Felix Wechsler

Tomographic Volumetric Additive Manufacturing (TVAM) allows printing of mesoscopic objects within seconds or minutes. In TVAM, tomographic patterns are illuminated onto a rotating glass vial which contains a photosensitive resin. Current pattern optimizati ...

2024

Programming nonlinear propagation for efficient optical learning machines

Demetri Psaltis, Christophe Moser, Carlo Gigli, Niyazi Ulas Dinç, Ugur Tegin

The ever-increasing demand for training and inferring with larger machine-learning models requires more efficient hardware solutions due to limitations such as power dissipation and scalability. Optics is a promising contender for providing lower power com ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

SwissVAMyKnife.jl: an open-source package for tomographic volumetric additive manufacturing

Christophe Moser, Carlo Gigli, Jorge Andres Madrid Wolff, Felix Wechsler

We introduce an optimization framework for ray and wave optical tomographic volumetric additive manufacturing (TVAM). In TVAM, tomographic patterns are projected with a light modulator onto a photocurable resin from different angular directions. Once an en ...

EDP Sciences2024

Programming the scalable optical learning operator with spatial-spectral optimization

Demetri Psaltis, Christophe Moser, Carlo Gigli, Niyazi Ulas Dinç, Yi Zhou Ju

Electronic computers have evolved drastically over the past years with an ever-growing demand for improved performance. However, the transfer of information from memory and high energy consumption have emerged as issues that require solutions. Optical tech ...

2024

Predicting nonlinear optical scattering with physics-driven neural networks

Demetri Psaltis, Ahmed Ayoub, Carlo Gigli

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

AIP Publishing2023

From 3D to 2D and back again

Demetri Psaltis, Christophe Moser, Carlo Gigli, Niyazi Ulas Dinç, Amirhossein Saba Shirvan, Jorge Andres Madrid Wolff, Antoine Vincent Boniface

The prospect of massive parallelism of optics enabling fast and low energy cost operations is attracting interest for novel photonic circuits where 3-dimensional (3D) implementations have a high potential for scalability. Since the technology for data inpu ...

WALTER DE GRUYTER GMBH2023

Physics-informed neural networks for diffraction tomography

Demetri Psaltis, Ahmed Ayoub, Carlo Gigli, Amirhossein Saba Shirvan

We propose a physics-informed neural network (PINN) as the forward model for tomographic reconstructions of biological samples. We demonstrate that by training this network with the Helmholtz equation as a physical loss, we can predict the scattered field ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2022

Xeno Nucleic Acid Nanosensors for Enhanced Stability Against Ion-Induced Perturbations

Ardemis Anoush Boghossian, Justyna Kupis-Rozmyslowicz, Alice Judith Gillen, Carlo Gigli

The omnipresence of salts in biofluids creates a pervasive challenge in designing sensors suitable for in vivo applications. Fluctuations in ion concentrations have been shown to affect the sensitivity and selectivity of optical sensors based on single-wal ...

2018