Likelihood-free inference of experimental Neutrino Oscillations using Neural Spline Flows
In machine learning, likelihood-free inference refers to the task of performing an analysis driven by data instead of an analytical expression. We discuss the application of Neural Spline Flows, a neural density estimation algorithm, to the likelihood-free inference problem of the measurement of neutrino oscillation parameters in Long Baseline neutrino experiments. A method adapted to physics parameter inference is developed and applied to the case of the disappearance muon neutrino analysis at the T2K experiment.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningDensity EstimationSimilar Papers 제목 키워드 기반
Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning
Precise modeling of detector energy response is crucial for next-generation neutrino experiments which present computational challenges due to lack of analytical likelihoods. We propose a solution using neural likelihood…
Neutrino Oscillation Parameter Estimation Using Structured Hierarchical Transformers
Neutrino oscillations encode fundamental information about neutrino masses and mixing parameters, offering a unique window into physics beyond the Standard Model. Estimating these parameters from oscillation probability …
What do we (not) know theoretically about solar neutrino fluxes?
Solar model predictions of 8B and p-p neutrinos agree with the experimentally-determined fluxes (including oscillations): phi(pp)_{measured} = (1.02 +- 0.02 +- 0.01)phi(pp)_{theory}, and phi(8B)_{measured} =(0.88 +- .04 …
Recent neutrino oscillation result with the IceCube experiment
The IceCube South Pole Neutrino Observatory is a Cherenkov detector instrumented in a cubic kilometer of ice at the South Pole. IceCube's primary scientific goal is the detection of TeV neutrino emissions from astrophysi…
Solar Models: current epoch and time dependences, neutrinos, and helioseismological properties
We calculate accurate solar models and report the detailed time dependences of important solar quantities. We use helioseismology to constrain the luminosity evolution of the sun and report the discovery of semi-convecti…