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This paper describes the performance and sensitivity to neutrino mixing parameters of a Magnetised Iron Neutrino Detector (MIND) at a Neutrino Factory with a neutrino beam created from the decay of 10 GeV muons. Specifically, it is…
KM3NeT has recently reported the detection of a very high-energy neutrino event, while IceCube has previously set upper limits on the differential neutrino flux above 100 PeV but has yet to observe a neutrino event with an energy comparable…
The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity…
We demonstrate the prompt-delayed signals induced by knockout neutrons from the quasi-elastic scattering in neutrino experiments provides a new avenue for detecting light dark matter. As an illustration, we consider the detection of…
As dark matter (DM) direct detection experiments continue to improve their sensitivity they will inevitably encounter an irreducible background arising from coherent neutrino scattering. This so-called "neutrino floor" may significantly…
A 20-kiloton liquid scintillator detector is designed in the Jiangmen Underground Neutrino Observatory (JUNO) for multiple physics purposes, including the determination of the neutrino mass ordering through reactor neutrinos, as well as…
The problem of classifying turbulent environments from partial observation is key for some theoretical and applied fields, from engineering to earth observation and astrophysics, e.g. to precondition searching of optimal control policies in…
Machine learning promises to deliver powerful new approaches to neutron scattering from magnetic materials. Large scale simulations provide the means to realise this with approaches including spin-wave, Landau Lifshitz, and Monte Carlo…
Machine learning (ML) tools such as encoder-decoder convolutional neural networks (CNN) can represent incredibly complex nonlinear functions which map between combinations of images and scalars. For example, CNNs can be used to map…
The JUNO observatory, a 20 kt liquid scintillator detector to be completed in 2022 in China, belongs to the next-generation of neutrino detectors, which share the common features of having a multi-ton scale and an energy resolution at…
The calculation of reactive properties is a challenging task in chemical reaction discovery. Machine learning (ML) methods play an important role in accelerating electronic structure predictions of activation energies and reaction…
Nonlinearity of the liquid scintillator energy response is a key to measuring the neutrino energy spectrum in reactor neutrino experiments such as Daya Bay and JUNO. We measured in laboratory the nonlinearity of the Linear Alkyl Benzene…
Recent developments in machine learning (ML) techniques present a promising new analysis method for high-speed imaging in astroparticle physics experiments, for example with imaging atmospheric Cherenkov telescopes (IACTs). In particular,…
The leptonic mixing matrix is examined within bi-large mixing patterns and confronted with the latest results announced by the Jiangmen Underground Neutrino Observatory (JUNO). We analyze the viability of bi large mixing schemes and assess…
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment currently under construction in China. It is located 52.5km away from two nuclear power plants in a newly constructed 700-m-deep underground…
Atmospheric neutrino experiments can show the "oscillation dip" feature in data, due to their sensitivity over a large $L/E$ range. In experiments that can distinguish between neutrinos and antineutrinos, like INO, oscillation dips can be…
We compare different neural network architectures for Machine Learning (ML) algorithms designed to identify the neutrino interaction vertex position in the MINERvA detector. The architectures developed and optimized by hand are compared…
Jiangmen Underground Neutrino Observatory (JUNO) is the next generation neutrino experiment which aims at neutrino mass hierarchy problem along with many other cutting-edge studies concerning neutrinos. Located 700m underground in Jiangmen…
In the effort to obtain a precise measurement of leptonic CP-violation with the ESS$\nu$SB experiment, accurate and fast reconstruction of detector events plays a pivotal role. In this work, we examine the possibility of replacing the…
Neural networks as well as other methods of machine learning (ML) are known to be highly efficient in different classification tasks, including classification of images and videos. Mini- EUSO is a wide-field-of-view imaging telescope that…