Related papers: Development of data processing and analysis pipeli…
In cryo-electron microscopy, accurate particle localization and classification are imperative. Recent deep learning solutions, though successful, require extensive training data sets. The protracted generation time of physics-based models,…
Even though novel imaging techniques have been successful in studying brain structure and function, the measured biological signals are often contaminated by multiple sources of noise, arising due to e.g. head movements of the individual…
We present a data reduction pipeline (DRP) for Keck/NIRSPEC built as an addition to the PypeIt Python package. The DRP is capable of reducing multi-order echelle data taken both before and after the detector upgrade in 2018. As part of…
Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and process or device technologies are increasingly important to…
Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we…
The potential to use neutrinos for nuclear non-proliferation has been heavily debated due to the tension between production abundance and low interaction rate. A newly detected neutrino interaction channel, coherent elastic neutrino-nucleus…
We present a fully modular and scalable software pipeline for processing electron microscope (EM) images of brain slices into 3D visualization of individual neurons and demonstrate an end-to-end segmentation of a large EM volume using a…
We demonstrate that several techniques based on cross correlation are able to significantly reduce the detection threshold of seismic sources worldwide and to improve the reliability of IDC arrivals by a more accurate estimation of their…
Recently, the IceCube Neutrino Observatory has reported a deviation from the single power law in the extragalactic diffuse neutrino flux. A neural network-based event selection of contained and uncontained cascade events from IceCube, in…
The planned IceCube-Gen2 radio neutrino detector at the South Pole will enhance the detection of cosmic ultra-high-energy neutrinos. It is crucial to utilize the available time until construction to optimize the detector design. A fully…
We present a convenient, all-in-one framework for the scientific analysis of fully reduced, (integral-field) spectroscopic data. The GIST pipeline (Galaxy IFU Spectroscopy Tool) is entirely written in Python3 and conducts all steps from the…
The detection and cross-section measurement of Coherent Elastic Neutrino-Nucleus Scattering (CE{\nu}NS) are vital for particle physics, astrophysics, and nuclear physics. Therefore, a new CE{\nu}NS detection experiment is proposed in China.…
This paper introduces Sparklen, a statistical learning toolkit for Hawkes processes in Python, designed to bring together efficiency and ease of use. The purpose of this package is to provide the Python community with a complete suite of…
Detailed modeling of processors and high performance cycle-accurate simulators are essential for today's hardware and software design. These problems are challenging enough by themselves and have seen many previous research efforts.…
Coming high-cadence wide-field optical telescopes will image hundreds of thousands of sources per minute. Besides inspecting the near real-time data streams for transient and variability events, the accumulated data archive is a wealthy…
We developed a pulsar search pipeline based on PRESTO (PulsaR Exploration and Search Toolkit). This pipeline simply runs dedispersion, FFT (Fast Fourier Transformation), and acceleration search in process-level parallel to shorten the…
The IceCube Neutrino Observatory at the South Pole has measured the diffuse astrophysical neutrino flux up to ~PeV energies and is starting to identify first point source candidates. The next generation facility, IceCube-Gen2, aims at…
The European Spallation Source (ESS), presently well on its way to completion, will soon provide the most intense neutron beams for multi-disciplinary science. Fortuitously, it will also generate the largest pulsed neutrino flux suitable…
Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos is challenging due to experimental uncertainty. This work bridges abstract notions of…
The ENUBET project recently concluded the R&D for a site independent design of a monitored neutrino beam for high precision cross section measurements, in which the neutrino flux is inferred from the measurement of charged leptons in an…