Related papers: The SpECTRE Cauchy-characteristic evolution system…
Anomaly detection aims to distinguish observations that are rare and different from the majority. While most existing algorithms assume that instances are i.i.d., in many practical scenarios, links describing instance-to-instance…
SCTE intends to provide a simple, yet powerful, framework for building data acquisition and equipment control systems for experimental Physics, and correlated areas. Via its SCTE::Instrument module, RS-232, USB, and LAN buses are supported,…
This paper proposes an efficient potential and viscous flow decomposition method for wave-structure interaction simulation with single-phase potential flow wave models and two-phase Computational Fluid Dynamics (CFD) solvers. The potential…
Time Series Anomaly Detection metrics serve as crucial tools for model evaluation. However, existing metrics suffer from several limitations: insufficient discriminative power, strong hyperparameter dependency, sensitivity to perturbations,…
Image restoration tasks traditionally rely on convolutional neural networks. However, given the local nature of the convolutional operator, they struggle to capture global information. The promise of attention mechanisms in Transformers is…
We present the Swift Analysis Pipeline for Lightcurve Extraction (SAPLE), a semi-automated pipeline to extract the Swift-UVOT and Swift-XRT data products and spectral information (magnitudes, photon indices, and fluxes) for a set of…
Valuable insights into galaxy evolution can be gleaned from studies of resolved stellar populations in the local Universe. Deep photometric surveys have provided tracers of the star-formation histories in galaxies from 0.8-16 Mpc, but…
This article investigates the problem of estimating stellar atmospheric parameters from spectra. Feature extraction is a key procedure in estimating stellar parameters automatically. We propose a scheme for spectral feature extraction and…
Long-standing challenges in cluster expansion (CE) construction include choosing how to truncate the expansion and which crystal structures to use for training. Compressive sensing (CS), which is emerging as a powerful tool for model…
In the literature, channel estimation and synchronization (CE/SY) algorithms are classified as blind, and hence spectrally efficient, if they do not require pilot symbols. However, we show in this letter that such classification is not…
Autoencoders have been widely used as a nonlinear tool for data dimensionality reduction. While autoencoders don't utilize the label information, Centroid-Encoders (CE)\cite{ghosh2022supervised} use the class label in their learning…
Citizen science is a powerful analysis tool, capable of processing large amounts of data in a very short time. To bridge the gap between classification data products from web-based citizen science platforms to statistically robust signal…
Within the ESPRESSO project a new flexible data reduction library is being built. ESPRESSO, the Echelle SPectrograph for Rocky Exoplanets and Stable Spectral Observations is a fiber-fed, high-resolution, cross-dispersed echelle…
The Habitable Worlds Observatory requires active speckle suppression to directly image Earth-like exoplanets. Focal plane wavefront sensing and control allows us to detect, and subsequently remove, time-varying speckles through measurements…
We present Causal Posterior Estimation (CPE), a novel method for Bayesian inference in simulator models, i.e., models where the evaluation of the likelihood function is intractable or too computationally expensive, but where one can…
Spectral evolution models are a widely used tool for determining the stellar content of galaxies. I provide a review of the latest developments in stellar atmosphere and evolution models, with an emphasis on massive stars. In contrast to…
To achieve reliable mining results for massive vessel trajectories, one of the most important challenges is how to efficiently compute the similarities between different vessel trajectories. The computation of vessel trajectory similarity…
Recently, a number of works have studied clustering strategies that combine classical clustering algorithms and deep learning methods. These approaches follow either a sequential way, where a deep representation is learned using a deep…
Network alignment consists of finding a structure-preserving correspondence between the nodes of two correlated, but not necessarily identical, networks. This problem finds applications in a wide variety of fields, from the alignment of…
Spectangular is a GUI based software package written in C++ designed for spectral disentangling on the wavelength scale. The code disentangles spectra of SB1 and SB2 systems and can now also be used also for spectra showing variability. In…