Borehole image techniques applied to identification of chert and dolomite layers in lacustrine sediments

Geophysical logging tools, particularly ultrasonic acoustic borehole image techniques, are applied on two different wells (CP1 and CP2) to identify and characterize the lacustrine interval (40m) of the Camp dels Ninots maardiatreme infill (Pliocene, Catalan Coastal Ranges). The CP1 well was cored and also geophysical logs and oriented borehole images were acquired. CP2 hole was partially cored but logging (geophysics and borehole images) was fully undertaken. Continuous core recovery in CP1 is compared with oriented images and is further used to identify and characterize highly reflective signals in a section of CP2 borehole that was not cored. These signals are related to silicified zones and belong to discontinuous centimetric chert nodules, while indurated massive carbonates are characterized as intervals of continuous reflectance. Despite opal nodules (chert) can be relatively small, they have a distinctive response in the ultrasonic borehole images.Peer Reviewe

Snowmass 2021 White Paper: Cosmogenic Dark Matter and Exotic Particle Searches in Neutrino Experiments

The signals from outer space and their detection have been playing animportant role in particle physics, especially in discoveries of and searchesfor physics beyond the Standard Model (BSM); beyond the evidence of dark matter(DM), for example, the neutrinos produced from the dark matter annihilation isimportant for the indirect DM searches. Moreover, a wide range of new,well-motivated physics models and dark-sector scenarios have been proposed inthe last decade, predicting cosmogenic signals complementary to those in theconventional direct detection of particle-like dark matter. Most notably,various mechanisms to produce (semi-)relativistic DM particles in the presentuniverse (e.g. boosted dark matter) have been put forward, while beingconsistent with current observational and experimental constraints on DM. Theresulting signals often have less intense and more energetic fluxes, to whichunderground, kiloton-scale neutrino detectors can be readily sensitive. Inaddition, the scattering of slow-moving DM can give rise to a sizable energydeposit if the underlying dark-sector model allows for a large mass differencebetween the initial and final state particles, and the neutrino experimentswith large volume detectors are well suited for exploring these opportunities. This White Paper is devoted to discussing the scientific importance of thecosmogenic dark matter and exotic particle searches, not only overviewing therecent efforts in both the theory and the experiment communities but alsoproviding future perspectives and directions on this research branch. Alandscape of technologies used in neutrino detectors and their complementarityis discussed, and the current and developing analysis strategies are outlined.<br

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

The present and future status of heavy neutral leptons

The existence of nonzero neutrino masses points to the likely existence of multiple Standard Model neutral fermions. When such states are heavy enough that they cannot be produced in oscillations, they are referred to as heavy neutral leptons (HNLs). In this white paper, we discuss the present experimental status of HNLs including colliders, beta decay, accelerators, as well as astrophysical and cosmological impacts. We discuss the importance of continuing to search for HNLs, and its potential impact on our understanding of key fundamental questions, and additionally we outline the future prospects for next-generation future experiments or upcoming accelerator run scenarios

Measurement of nuclear effects in neutrino-argon interactions using generalized kinematic imbalance variables with the MicroBooNE detector

We present a set of new generalized kinematic imbalance variables that can be measured in neutrino scattering. These variables extend previous measurements of kinematic imbalance on the transverse plane and are more sensitive to modeling of nuclear effects. We demonstrate the enhanced power of these variables using simulation and then use the MicroBooNE detector to measure them for the first time. We report flux-integrated single- and double-differential measurements of charged-current muon neutrino scattering on argon using a topology with one muon and one proton in the final state as a function of these novel kinematic imbalance variables. These measurements allow us to demonstrate that the treatment of charged current quasielastic interactions in genie version 2 is inadequate to describe data. Further, they reveal tensions with more modern generator predictions particularly in regions of phase space where final state interactions are important