相关论文: Efficiently Exploring Multi-Dimensional Parameter …
In the framework of uncertainty quantification, we consider a quantity of interest which depends non-smoothly on the high-dimensional parameter representing the uncertainty. We show that, in this situation, the multilevel Monte Carlo…
High-dimensional tests are applied to find relevant sets of variables and relevant models. If variables are selected by analyzing the sums of products matrices and a corresponding mean-value test is performed, there is the danger that the…
We propose to use the branching ratio of channels of free-space hadron-nucleon interaction as a test in the construction and verification of the models of complicated processes in the nuclei. The particle self-energy and amplitudes of…
In this paper, we study the problem of learning multi-dimensional Gaussian Mixture Models (GMMs), with a specific focus on model order selection and efficient mixing distribution estimation. We first establish an information-theoretic lower…
The problem of Majorana neutrino mass generated in Arkani-Hamed--Dimopoulos-Dvali model with n extra spatial dimensions is discussed. Taking into account constraints on neutrino masses coming from cosmological observations, it is possible…
A range of experimental results point to the existence of a massive neutrino. The recent high precision measurements of the cosmic microwave background and the large scale surveys of galaxies can be used to place an upper bound on this…
Experiments searching for Heavy Neutral Leptons (HNLs) typically interpret their results within simplified models consisting of a single HNL coupled to a single lepton flavor. However, any model which aims to describe neutrino oscillations…
Models involving large extra spatial dimension(s) have interesting predictions on lepton flavor violating processes. We consider some 5D models which are related to neutrino mass generation or address the fermion masses hierarchy problem.…
Nonparametric two sample testing deals with the question of consistently deciding if two distributions are different, given samples from both, without making any parametric assumptions about the form of the distributions. The current…
Long-lived particles are contained in a variety of beyond Standard Model theories, including supersymmetric models, universal extra dimensions, or technicolor theories. If the lifetime of such a particle is long enough, the particle can…
Assuming that neutrinos are Majorana particles, we explore what information can be inferred from future strong limits (i.e. non-observation) for neutrinoless double beta decay. Specifically we consider the case where the mass hierarchy is…
We discuss how much we can probe the effective number of neutrino species N_nu with cosmic microwave background alone. Using the data of WMAP, ACBAR, CBI and BOOMERANG experiments, we obtain a constraint on the effective number of neutrino…
Dimensionality reduction is an effective method for learning high-dimensional data, which can provide better understanding of decision boundaries in human-readable low-dimensional subspace. Linear methods, such as principal component…
We propose a neural network based approach for extracting models from dynamic data using ordinary and partial differential equations. In particular, given a time-series or spatio-temporal dataset, we seek to identify an accurate governing…
Neutrinos are some of the most elusive particles in the standard model, being incredibly common throughout the universe, but interacting with detectors incredibly rarely. Certain properties of neutrinos remain difficult to measure,…
Machine-Learned Likelihoods (MLL) combines machine-learning classification techniques with likelihood-based inference tests to estimate the experimental sensitivity of high-dimensional data sets. We extend the MLL method by including Kernel…
Atomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales accessible to brute-force simulations. This…
Searches for New Physics focus either on the direct production of new particles at colliders or at deviations from known observables at low energies. In order to discover New Physics in precision measurements, both experimental and…
We study the lifetimes of TeV-scale heavy neutral leptons (Majorana neutrinos) that appear in a model suggested by Okamura et al. [2]. We develop a convenient way to parametrize the neutrino mass texture of the model, and illustrate our…
The existence of bulk sterile neutrinos in theories with large extra dimensions can naturally explain small 4-dimensional Dirac masses for the active neutrinos. We study a model with 3 bulk neutrinos and derive various constraints on the…