Blog
Development of the Beam Monitor Detectors for the Low-E Beamline at the CERN SPS H2 Line
A series of beam tests were conducted at the KEK AR test beamline in ordet to investigate the performance of a prototype detector for instrumentation in the low-E beamline at the CERN H2 line. For the silicon strip detector, the simultaneous readout...
Cooperative-Memory Photonic Reservoir using Modulation Nonlinearity: Circumventing the Speed Constraints of Nonlinear Silicon Microring Resonators
Complex dynamics of silicon microring resonators loaded by delayed feedback elements enable high-speed photonic reservoir computing. Implementing feedback is especially challenging when the required delay should match the time scales of silicon’s nonlinearities. To increase the computation speed and preclude any need...
Spectral stability of periodic traveling waves in Caudrey-Dodd-Gibbon-Sawada-Kotera Equation
We study the spectral stability of the one-dimensional small-amplitude periodic traveling wave solutions of the (1+1)-dimensional Caudrey-Dodd-Gibbon-Sawada-Kotera equation. We show that these waves are spectrally stable with respect to co-periodic as well as square integrable perturbations. Este artículo explora los viajes en...
Energy Rates Due to Weak Decay Rates of Vanadium Isotopes in Stellar Environment
The neutrino cooling and gamma heating rates are considered as an important input needed to study the final phases of the evolution of high-mass stars. The weak-interaction mediated processes, namely the $\beta$-decay and electron capture, significantly change the lepton to baryon ratio...
iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network
As time evolves, data within specific domains exhibit predictability that motivates time series forecasting to predict future trends from historical data. However, current deep forecasting methods can achieve promising performance but generally lack interpretability, hindering trustworthiness and practical deployment in safety-critical applications...
Towards a fast and robust deep hedging approach
We present a robust Deep Hedging framework for the pricing and hedging of option portfolios that significantly improves training efficiency and model robustness. In particular, we propose a neural model for training model embeddings which utilizes the paths of several advanced equity...
Goodness-of-fit for amplitude analysis with anomaly detection
Amplitude analysis serves as a pivotal tool in hadron spectroscopy, fundamentally involving a series of likelihood fits to multi-dimensional experimental distributions. While numerous robust goodness-of-fit tests are available for low-dimensional scenarios, evaluating goodness-of-fit in amplitude analysis poses significant challenges. In this work,...
SoCov: Semi-Orthogonal Parametric Pooling of Covariance Matrix for Speaker Recognition
In conventional deep speaker embedding frameworks, the pooling layer aggregates all frame-level features over time and computes their mean and standard deviation statistics as inputs to subsequent segment-level layers. Such statistics pooling strategy produces fixed-length representations from variable-length speech segments. However, this...
Nonlinear contagion dynamics on dynamical networks: exact solutions ranging from consensus times to evolutionary trajectories
Understanding nonlinear social contagion dynamics on dynamical networks, such as opinion formation, is crucial for gaining new insights into consensus and polarization. Similar to threshold-dependent complex contagions, the nonlinearity in adoption rates poses challenges for mean-field approximations. To address this theoretical gap,...
Marginalized Generalized IoU (MGIoU): A Unified Objective Function for Optimizing Any Convex Parametric Shapes
Optimizing the similarity between parametric shapes is crucial for numerous computer vision tasks, where Intersection over Union (IoU) stands as the canonical measure. However, existing optimization methods exhibit significant shortcomings: regression-based losses like L1/L2 lack correlation with IoU, IoU-based losses are unstable...