Alignment of electron optical beam shaping elements using a convolutional neural network
Enzo Rotunno, Amir H. Tavabi, Paolo Rosi, Stefano Frabboni, Peter Tiemeijer, Rafal E. Dunin–Borkowski, Vincenzo Grillo
Abstract
A convolutional neural network is used to align an orbital angular momentum sorter in a transmission electron microscope. The method is demonstrated using simulations and experiments. As a result of its accuracy and speed, it offers the possibility of real-time tuning of other electron optical devices and electron beam shaping configurations.
Topics & Concepts
Convolutional neural networkTransmission (telecommunications)OpticsCathode rayTransmission electron microscopyElectronElectron microscopeAngular momentumBeam (structure)PhysicsComputer scienceArtificial intelligenceTelecommunicationsQuantum mechanicsAdvanced Electron Microscopy Techniques and ApplicationsNear-Field Optical MicroscopyAdvanced Fluorescence Microscopy Techniques