Related papers: NELM: Modern Open-Source Software for Multipurpose…
The LCLS-II Free Electron Laser (FEL) will generate X-ray pulses for beamline experiments at rates of up to 1~MHz, with detectors producing data throughputs exceeding 1 TB/s. Managing such massive data streams presents significant…
The NEID spectrograph on the WIYN 3.5-m telescope at Kitt Peak has completed its first full year of science operations and is reliably delivering sub-m/s precision radial velocity measurements. The NEID instrument control system uses the…
Stack autoencoder (SAE), as a representative deep network, has unique and excellent performance in feature learning, and has received extensive attention from researchers. However, existing deep SAEs focus on original samples without…
This study introduces a novel methodology for fault detection and cause identification within the Tennessee Eastman Process (TEP) by integrating a Bidirectional Long Short-Term Memory (BiLSTM) neural network with an Integrated Attention…
The robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on the ensemble learning and iterative training (ELIT) of deep convolutional neural networks, is implemented on an…
Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission…
The needle bio-potential sensors for measuring muscle and brain activity need invasive surgical targeted muscle reinnervation (TMR) and a demanding process to maintain, but surface bio-potential sensors lack clear bio-signal reading…
The Institute for Solid State Physics (ISSP) at The University of Tokyo has been carrying out a software development project named ``the Project for Advancement of Software Usability in Materials Science (PASUMS)". Since the launch of…
One of the pillars of any machine learning model is its concepts. Using software engineering, we can engineer these concepts and then develop and expand them. In this article, we present a SELM framework for Software Engineering of machine…
Low-energy electron microscopy (LEEM) is a surface science method that works primarily in the UHV environment. It provides information complementary to the other established techniques: it extends the limited view of scanning probe…
As the demand for efficient data processing escalates, reconfigurable analog hardware which implements novel analog compute paradigms, is promising for energy-efficient computing at the sensing and actuation boundaries. These analog…
Photonic neural networks offer a promising alternative to traditional electronic systems for machine learning accelerators due to their low latency and energy efficiency. However, the challenge of implementing the backpropagation algorithm…
Scanning Transmission Electron Microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In…
Recent studies on large language models (LLMs) and large multimodal models (LMMs) have demonstrated promising skills in various domains including science and mathematics. However, their capability in more challenging and real-world related…
Surface integral equation (SIE) methods are of great interest for the efficient electromagnetic modeling of various devices, from integrated circuits to antenna arrays. Existing acceleration algorithms for SIEs, such as the adaptive…
Two-dimensional electronic spectroscopy (2DES) has enabled significant discoveries in both biological and synthetic energy-transducing systems. Although deriving chemical information from 2DES is a complex task, machine learning (ML) offers…
AI tools to support real world decision making must be able to build simulation models that inform their recommendations and render them interpretable. Tools that can automate aspects of modeling practice must complement human expertise,…
Fine structure analysis of core electron excitation spectra is a cornerstone characterization technique across the physical sciences. Spectra are most commonly measured with synchrotron radiation and X-ray spot sizes on the {\mu}m to mm…
Electromagnetic (EM) simulation plays a crucial role in analyzing and designing devices with sub-wavelength scale structures such as solar cells, semiconductor devices, image sensors, future displays and integrated photonic devices.…
Electron energy-loss spectroscopy (EELS) can measure similar information to X-ray, UV-Vis, and IR spectroscopies but with atomic resolution and increased scattering cross sections. Recent advances in electron monochromators have expanded…