184 citations · 695 across the 31 of their papers we have counts for
32 papers
Super-resolution enhancement in bi-photon spatial mode demultiplexin
Florence Grenapin, Dilip Paneru, Alessio D'Errico +3
Imaging systems measuring intensity in the far field succumb to Rayleigh's curse, a resolution limitation dictated by the finite aperture of the optical system. Many proof-of-princ…
Ultrafast Transverse Modulation of Free Electrons by Interaction with Shaped Optical Fields
I. Madan, V. Leccese, A. Mazur +11
Spatio-temporal shaping of electron beams is a bold frontier in electron microscopy, enabling new routes toward spatial-resolution enhancement, selective probing, low-dose imaging…
Near-real-time diagnosis of electron optical phase aberrations in scanning transmission electron microscopy using an artificial neural network
Giovanni Bertoni, Enzo Rotunno, Daan Marsmans +4
The key to optimizing spatial resolution in a state-of-the-art scanning transmission electron microscope is the ability to precisely measure and correct for electron optical aberra…
Single-Pixel Imaging in Space and Time with Optically-Modulated Free Electrons
Andrea Konečná, Enzo Rotunno, Vincenzo Grillo +2
Single-pixel imaging, originally developed in light optics, facilitates fast three-dimensional sample reconstruction, as well as probing with light wavelengths undetectable by conv…
Generation of electron vortex beams with over 1000 orbital angular momentum quanta using a tuneable electrostatic spiral phase plate
A. H. Tavabi, P. Rosi, A. Roncaglia +9
We report the use of an electrostatic MEMS-based device to produce high quality electron vortex beams with more than 1000 quanta of orbital angular momentum (OAM). Diffraction and…
Automatic alignment of an orbital angular momentum sorter in a transmission electron microscope using a convolution neural network
P. Rosi, A. Clausen, D. Weber +6
We report on the automatic alignment of a transmission electron microscope equipped with an orbital angular momentum sorter using a convolutional neural network. The neural network…