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The incorporation of systematic uncertainties into confidence interval calculations has been addressed recently in a paper by Conrad et al. (Physical Review D 67 (2003) 012002). In their work, systematic uncertainities in detector…
Physics at a multi-TeV muon collider needs a change of perspective for the detector design due to the large amount of background induced by muon beam decays. Preliminary studies, based on simulated data, on the composition and the…
Daya Bay Neutrino Experiment is dedicated to measuring the last unobserved neutrino mixing angle theta_13. The predicted precision on sin^2(2theta_13) is 0.01 at 90% confidence level. This document briefly reviews the measurement method and…
This study presents a new concept of segmented antineutrino detector based on hexagonal plastic scintillator bars for detecting antineutrinos from a nuclear reactor core. The choice of hexagonal scintillator bars is original and provides…
In high-energy astrophysics, it is common practice to account for the background overlaid with the counts from the source of interest with the help of auxiliary measurements carried on by pointing off-source. In this "on/off" measurement,…
We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis…
We study decoherence effects and phase corrections in heavy neutrino-antineutrino oscillations (NNOs), based on quantum field theory with external wave packets. Decoherence damps the oscillation pattern, making it harder to resolve…
The problem of optimizing affine feedback laws that explicitly steer the mean and covariance of an uncertain system state in the presence of a Gaussian random field is considered. Spatially-dependent disturbances are successively…
Accelerator-based neutrino oscillation experiments have the potential to revolutionise our understanding of fundamental physics, offering an opportunity to characterise charge-parity violation in the lepton section, to determine the…
Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) models assists…
Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper…
We present a neutrino oscillation analysis of two particular data sets from the Daya Bay and RENO reactor neutrino experiments aiming to study the increase in precision in the oscillation parameters $\sin^2{2\theta}_{13}$ and the effective…
Recurrent neural network based solutions are increasingly being used in the analysis of longitudinal Electronic Health Record data. However, most works focus on prediction accuracy and neglect prediction uncertainty. We propose Deep Kernel…
This article reports an improved independent measurement of neutrino mixing angle $\theta_{13}$ at the Daya Bay Reactor Neutrino Experiment. Electron antineutrinos were identified by inverse $\beta$-decays with the emitted neutron captured…
Fast-turn around methods to predict airfoil trailing-edge noise are crucial for incorporating noise limitations into design optimization loops of several applications. Among these aeroacoustic predictive models, Amiet's theory offers the…
We study theoretically the effects of dissipation on the performances of a variational quantum algorithm used to approximately solve a combinatorial optimization problem, the Maximum Independent Set, on a platform of neutral atoms. We take…
In this work, we emphasize that it is necessary to take into account one-loop corrections of $2.0\%$ to the neutrino matter potential in the precision measurements of neutrino oscillation parameters and in the experimental searches for new…
The estimation of directed couplings between the nodes of a network from indirect measurements is a central methodological challenge in scientific fields such as neuroscience, systems biology and economics. Unfortunately, the problem is…
We introduce an analytical approach that allows predictions and mechanistic insights into the dynamics of nonlinear oscillator networks with heterogeneous time delays. We demonstrate that time delays shape the spectrum of a matrix…
A PhD student is locked inside a box, imitating a quantum system by mimicking the measurement statistics of any viable observable nominated by external observers. Inside a second box lies a genuine quantum system. Either box can be used to…