Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

A fossiliferous spherule-rich bed at the Cretaceous-Paleogene (K-Pg) boundary in Mississippi, USA: implications for the K-Pg mass extinction event in the MS Embayment and Eastern Gulf Coastal Plain

We describe an outcrop of the Cretaceous–Paleogene (K–Pg) boundary exposed due to construction near New Albany, Union County, Mississippi. It consists of the Owl Creek Formation and overlying Clayton Formation. The Owl Creek Formation is rich in the ammonites Discoscaphites iris and Eubaculites carinatus, which, along with biostratigraphically important dinoflagellate cysts and calcareous nannofossils, indicate deposition occurred within the last 1 million years, most likely last 500 kyrs, of the Cretaceous. The base of the overlying Clayton Formation marks the K–Pg boundary, and consists of a 15-30 cm thick muddy, poorly sorted quartz sand containing abundant spherules representing ejecta derived from the Chicxulub impact event. Impact spherules range in size from 0.5 mm to 1 mm in diameter and are hollow and well preserved, with details such as smaller vesicular spherules enclosed within. The spherules are altered to clay minerals such as smectite and are typical of those found at K–Pg boundary sites in the Gulf of Mexico and beyond. Spherules are scattered throughout the bed, and surface counts suggest an average of 4 spherules per cm2. Macrofossils within the spherule bed represent a rich fauna of ammonites, benthic molluscs (bivalves and gastropods), echinoids, as well as crabs and sharks. Macrofossil preservation ranges from whole to fragmentary, with most fossils preserved as internal moulds. The infill of the fossils is lithologically identical to the matrix of the spherule bed, including impact ejecta preserved within phragmocones and body chambers of ammonites, and differs from the underlying Owl Creek Formation. This suggests that the animals were either alive or loosely scattered on the sea floor at the time of deposition. Grain size changes indicate multiple events were responsible for deposition, and together with taphonomic evidence are consistent with dynamic high energy post-impact processes. Later sea level change during the Paleocene is responsible for a sharp contact at the top of the spherule bed. Geochemical evidence from the Owl Creek and Clayton Formations at this locality indicate numerous local paleoenvironmental changes affected the Mississippi Embayment at the time of the K–Pg boundary and mass extinction event

KM3NeT front-end and readout electronics system: hardware, firmware, and software

he KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-in. photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module, and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven Watts. We present an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1-ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 years

Architecture and performance of the KM3NeT front-end firmware

The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine

KM3NeT front-end and readout electronics system: hardware, firmware, and software

The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-in. photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module, and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven Watts. We present an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1-ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 year