scholarly journals Efficient neutrino oscillation parameter inference using Gaussian processes

2020 ◽  
Vol 101 (1) ◽  
Author(s):  
Lingge Li ◽  
Nitish Nayak ◽  
Jianming Bian ◽  
Pierre Baldi
Keyword(s):  
Neutrino Oscillation ◽  
Gaussian Processes ◽  
Oscillation Parameter ◽  
Parameter Inference ◽  
Neutrino Oscillation Parameter

scholarly journals Efficient Neutrino Oscillation Parameter Inference with Gaussian Process

2019 ◽  
Vol 33 ◽  
pp. 9967-9968
Author(s):  
Lingge Li ◽  
Nitish Nayak ◽  
Jianming Bian ◽  
Pierre Baldi
Keyword(s):  
Gaussian Process ◽  
Neutrino Oscillation ◽  
Oscillation Parameter ◽  
Unified Approach ◽  
Parameter Inference ◽  
Computation Cost ◽  
Computationally Expensive ◽  
Set Up ◽  
The Universe ◽  
Neutrino Oscillation Parameter

Many experiments have been set-up to measure the parameters governing the neutrino oscillation probabilities accurately, with implications for the fundamental structure of the universe. Very often, this involves inferences from tiny samples of data which have complicated dependencies on multiple oscillation parameters simultaneously. This is typically carried out using the unified approach of Feldman and Cousins which is very computationally expensive, on the order of tens of millions of CPU hours. In this work, we propose an iterative method using Gaussian Process to efficiently find a confidence contour for the oscillation parameters and show that it produces the same results at a fraction of the computation cost.

scholarly journals Neutrino oscillation parameter sampling with MonteCUBES

2010 ◽  
Vol 181 (1) ◽  
pp. 227-231 ◽  
Author(s):  
Mattias Blennow ◽  
Enrique Fernandez-Martinez
Keyword(s):  
Neutrino Oscillation ◽  
Oscillation Parameter ◽  
Neutrino Oscillation Parameter

CONSTRAINTS ON NEUTRINO OSCILLATION PARAMETERS FROM TIME/ENERGY DEPENDENCE OF SOLAR 8B NEUTRINO FLUX

2001 ◽  
Vol 16 (supp01b) ◽  
pp. 718-720
Author(s):  
◽  
MICHAEL B SMY
Keyword(s):  
Energy Dependence ◽  
Neutrino Oscillation ◽  
Parameter Space ◽  
Time Variation ◽  
Solar Neutrino ◽  
Neutrino Flux ◽  
Oscillation Parameter ◽  
Solar Neutrino Flux ◽  
Time Variations ◽  
Neutrino Oscillation Parameter

A search for neutrino oscillation is presented using time variations and energy dependence of the observed reduction of the solar neutrino flux. No significant time variation or energy dependence has been found in 1117 days of solar neutrino data taken with the Super-Kamiokande experiment. This constrains the two-neutrino oscillation parameter space independently of the model dependence of the solar neutrino flux. The combination of Super-Kamiokande's data of the day-night variation, energy dependence and flux results in two allowed regions at 95% C.L.

scholarly journals Parameter inference for weak lensing using Gaussian Processes and MOPED

2020 ◽  
Vol 497 (2) ◽  
pp. 2213-2226
Author(s):  
Arrykrishna Mootoovaloo ◽  
Alan F Heavens ◽  
Andrew H Jaffe ◽  
Florent Leclercq
Keyword(s):  
Gaussian Process ◽  
Gaussian Processes ◽  
Cosmological Parameter ◽  
Weak Lensing ◽  
Summary Statistics ◽  
Parameter Inference ◽  
Leibler Divergence ◽  
Future Data ◽  
Summary Data ◽  
Fast Mechanism

ABSTRACT In this paper, we propose a Gaussian Process (GP) emulator for the calculation both of tomographic weak lensing band powers, and of coefficients of summary data massively compressed with the MOPED algorithm. In the former case cosmological parameter inference is accelerated by a factor of ∼10–30 compared with Boltzmann solver class applied to KiDS-450 weak lensing data. Much larger gains of order 103 will come with future data, and MOPED with GPs will be fast enough to permit the Limber approximation to be dropped, with acceleration in this case of ∼105. A potential advantage of GPs is that an error on the emulated function can be computed and this uncertainty incorporated into the likelihood. However, it is known that the GP error can be unreliable when applied to deterministic functions, and we find, using the Kullback–Leibler divergence between the emulator and class likelihoods, and from the uncertainties on the parameters, that agreement is better when the GP uncertainty is not used. In future, weak lensing surveys such as Euclid, and the Legacy Survey of Space and Time, will have up to ∼104 summary statistics, and inference will be correspondingly more challenging. However, since the speed of MOPED is determined not the number of summary data, but by the number of parameters, MOPED analysis scales almost perfectly, provided that a fast way to compute the theoretical MOPED coefficients is available. The GP provides such a fast mechanism.

The status of the Double Chooz experiment

2014 ◽  
Vol 31 ◽  
pp. 1460299
Author(s):  
Guang Yang ◽  
Keyword(s):  
Neutrino Oscillation ◽  
Nuclear Power ◽  
Mixing Angle ◽  
Electron Neutrinos ◽  
Long Baseline ◽  
Neutrino Oscillation Experiment ◽  
Double Chooz ◽  
The Status ◽  
Neutrino Oscillation Parameter ◽  
Oscillation Experiment

Double Chooz is a long baseline neutrino oscillation experiment at Chooz, France. The purpose of this experiment is to measure the non-zero neutrino oscillation parameter θ13, a parameter for changing electron neutrinos into other neutrinos. This experiment uses reactors of the Chooz Nuclear Power Plant as a neutrino source. Double Chooz has published two papers with results showing the measurement of the mixing angle, and 3rd publication is processing.

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