Related papers: Measuring the Evolution of the NuSTAR Detector Gai…

Experiments deploying large arrays of transition-edge sensors (TESs) often require a robust method to monitor gain variations with minimal loss of observing time. We propose a sensitive and non-intrusive method for monitoring variations in…

We present a routinized and reliable method to obtain source catalogs from the $\textit{Nuclear Spectroscopic Telescope Array}$ ($\textit{NuSTAR}$) extragalactic surveys of the Extended $\textit{Chandra}$ Deep Field-South (E-CDF-S) and…

New technology, the ultrastable low-noise current amplifier and the electron pump, provide new methods for making traceable measurements of small DC electric currents. We review four traceability routes for small current measurements and…

Motivated by an example from remote sensing of gas emission sources, we derive two novel change point procedures for multivariate time series where, in contrast to classical change point literature, the changes are not required to be…

We investigate a method to assess the validity of gravitational-wave detector calibration through the use of gamma-ray bursts as standard sirens. Such signals, as measured via gravitational-wave observations, provide an estimated luminosity…

Existing deep neural network (DNN) based wireless localization approaches typically do not capture uncertainty inherent in their estimates. In this work, we propose and evaluate variational and scalable DNN approaches to measure the…

Neutrinos from STORed Muons (nuSTORM; formerly VLENF) is a proposed experiment to use 3.8 GeV/c muon decay to produce a well-understood beam of electron and muon neutrinos that can be used for short baseline physics. A magnetized far…

Albeit revealing impressive predictive performance for several computer vision tasks, deep neural networks (DNNs) are prone to making overconfident predictions. This limits the adoption and wider utilization of DNNs in many safety-critical…

Simultaneously monitoring changes in both the mean and variance is a fundamental problem in Statistical Process Control, and numerous methods have been developed to address it. However, many existing approaches face notable limitations:…

Data mining techniques, including clustering and classification tasks, for the automatic information extraction from large datasets are increasingly demanded in several scientific fields. In particular, in the astrophysical field, large…

We present a novel method for generating sequential parameter estimates and quantifying epistemic uncertainty in dynamical systems within a data-consistent (DC) framework. The DC framework differs from traditional Bayesian approaches due to…

Tumer et al. 2022, ATel #15171, have recently reported the discovery of an X-ray source, NuSTAR J053449+2126.0, during a calibration observation which took place on 25 April 2020. We scan the Zwicky Transient Facility (ZTF) alerts and…

Electricity theft detection issue has drawn lots of attention during last decades. Timely identification of the electricity theft in the power system is crucial for the safety and availability of the system. Although sustainable efforts…

Accurate forecasting of long-term time series has important applications for decision making and planning. However, it remains challenging to capture the long-term dependencies in time series data. To better extract long-term dependencies,…

This study presents the development of an integrated device for measuring magnetoelastic resonance, utilizing a gain/phase detector and the Arduino platform. The device stands out for its simplicity, low cost, and efficiency. It employs the…

Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from…

We present a method for precise monitoring of the loop gain of transition edge sensors (TES) under electrothermal feedback. The measurement is implemented on the ICE DfMux electronics and operates simultaneously with Digital Active Nulling…

Detecting fast radio bursts (FRBs) with frequency-dependent intensity remains a challenge, as existing search algorithms do not account for the spectral shape, potentially leading to non-detections. We propose a novel detection statistic,…

Remote sensing change detection is crucial for understanding the dynamics of our planet's surface, facilitating the monitoring of environmental changes, evaluating human impact, predicting future trends, and supporting decision-making. In…

We report on the results of active galactic nuclei (AGNs) detection by NuSTAR performed in three extragalactic survey fields (COSMOS, UDS, ECDFS) in three hard bands, namely H1 (8-16 keV), H2 (16-24 keV) and VH (35-55 keV). The aggregated…