Related papers: Full Automation for Rapid Modulator Characterizati…
Mutation analysis is an effective technique to evaluate a test suite adequacy in terms of revealing unforeseen bugs in software. Traditional source- or IR-level mutation analysis is not applicable to the software only available in binary…
Three-dimensional rigid-body transforms, i.e. rotations and translations, are central to modern differentiable machine learning pipelines in robotics, vision, and simulation. However, numerically robust and mathematically correct…
Solid-state modulators for pulsed power applications have been a goal since the first fast high-power semiconductor devices became available. Recent improvements in both the speed and peak power capabilities of semiconductor devices…
Machine Learning (ML) is a fundamental part of modern perception systems. In the last decade, the performance of computer vision using trained deep neural networks has outperformed previous approaches based on careful feature engineering.…
The light yield, the time resolution and the efficiency of different types of scintillating tiles with direct Silicon Photomultiplier readout and instrumented with a customised front-end electronics have been measured at the Beam Test…
This work introduces MICSim, an open-source, pre-circuit simulator designed for early-stage evaluation of chip-level software performance and hardware overhead of mixed-signal compute-in-memory (CIM) accelerators. MICSim features a modular…
A Python program has been developed which fits a published detector-response model to SiPM charge spectra to characterise SiPMs. Spectra for SiPMs illuminated by low intensity pulsed light with Poisson-distributed number of photons and a…
We report on several versions of the calibration and monitoring system dedicated to scintillator tile calorimeters built within the CALICE collaboration and intended for future linear collider experiments. Whereas the first, a 1 m3 analogue…
Silicon Photomultipliers (SiPM) represent a promising alternative to classical photomultipliers, for instance, for the detection of photons in high energy physics and medical physics. In the present work, electrical characterizations of…
Simulation-based falsification is a practical testing method to increase confidence that the system will meet safety requirements. Because full-fidelity simulations can be computationally demanding, we investigate the use of simulators with…
We present a Python module for simulating Silicon Photo-Multipliers, Avalanche Photo-Diodes, and Multi-Pixel Photon Counters. This module allows users to perform noise analyses: Dark Count Rate, crosstalk, and afterpulsing. Furthermore, the…
Reconfigurable photonic devices capable of routing the flow of light enable flexible integrated-optic circuits that are not hard-wired but can be externally controlled. Analogous to free-space spatial light modulators, we demonstrate…
This paper is an overview of Image Processing and Analysis using Scilab, a free prototyping environment for numerical calculations similar to Matlab. We demonstrate the capabilities of SIP -- the Scilab Image Processing Toolbox -- which…
Simulation is a useful tool in situations where training data for machine learning models is costly to annotate or even hard to acquire. In this work, we propose a reinforcement learning-based method for automatically adjusting the…
The ability to shape photon emission facilitates strong photon-mediated interactions between disparate physical systems, thereby enabling applications in quantum information processing, simulation and communication. Spectral control in…
Automatic modulation classification enables intelligent communications and it is of crucial importance in today's and future wireless communication networks. Although many automatic modulation classification schemes have been proposed, they…
The use of several open source scientific packages in the Schr\"odinger Materials Science Suite will be discussed. A typical workflow for materials discovery will be described, discussing how open source packages have been incorporated at…
modAL is a modular active learning framework for Python, aimed to make active learning research and practice simpler. Its distinguishing features are (i) clear and modular object oriented design (ii) full compatibility with scikit-learn…
Modern combustion engines incorporate a number of actuators and sensors that can be used to control and optimize the performance and emissions. We describe a semi-automatic method to simultaneously measure and calibrate the actuator…
Precision experiments, such as the search for electric dipole moments of charged particles using storage rings, demand for an understanding of the spin dynamics with unprecedented accuracy. The ultimate aim is to measure the electric dipole…