Scintillation and charge extraction from the tracks of energetic electrons in superfluid helium-4

An energetic electron passing through liquid helium causes ionization along its track. The ionized electrons quickly recombine with the resulting positive ions, which leads to the production of prompt scintillation light. By applying appropriate electric fields, some of the ionized electrons can be separated from their parent ions. The fraction of the ionized electrons extracted in a given applied field depends on the separation distance between the electrons and the ions. We report the determination of the mean electron-ion separation distance for charge pairs produced along the tracks of beta particles in superfluid helium at 1.5 K by studying the quenching of the scintillation light under applied electric fields. Knowledge of this mean separation parameter will aid in the design of particle detectors that use superfluid helium as a target material.Comment: 10 pages, 8 figure

The MIGDAL experiment : Measuring a rare atomic process to aid the search for dark matter

We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking experimental confirmation. Our goal is to detect the predicted atomic electron emission which is thought to accompany nuclear scattering with low, but calculable, probability, by deploying an Optical Time Projection Chamber filled with a low-pressure gas based on CF. Initially, pure CF will be used, and then in mixtures containing other elements employed by leading dark matter search technologies — including noble species, plus Si and Ge. High resolution track images generated by a Gas Electron Multiplier stack, together with timing information from scintillation and ionisation readout, will be used for 3D reconstruction of the characteristic event topology expected for this process — an arrangement of two tracks sharing a common vertex, with one belonging to a Migdal electron and the other to a nuclear recoil. Different energy-loss rate distributions along both tracks will be used as a powerful discrimination tool against background events. In this article we present the design of the experiment, informed by extensive particle and track simulations and detailed estimations of signal and background rates. In pure CF we expect to observe 8.9 (29.3) Migdal events per calendar day of exposure to an intense D–D (D–T) neutron generator beam at the NILE facility located at the Rutherford Appleton Laboratory (UK). With our nominal assumptions, 5 median discovery significance can be achieved in under one day with either generator.Peer reviewe

Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection

Deep learning-based object detection algorithms enable the simultaneous classification and localization of any number of objects in image data. Many of these algorithms are capable of operating in real-time on high resolution images, attributing to their widespread usage across many fields. We present an end-to-end object detection pipeline designed for real-time rare event searches for the Migdal effect, using high-resolution image data from a state-of-the-art scientific CMOS camera in the MIGDAL experiment. The Migdal effect in nuclear scattering, crucial for sub-GeV dark matter searches, has yet to be experimentally confirmed, making its detection a primary goal of the MIGDAL experiment. Our pipeline employs the YOLOv8 object detection algorithm and is trained on real data to enhance the detection efficiency of nuclear and electronic recoils, particularly those exhibiting overlapping tracks that are indicative of the Migdal effect. When deployed online on the MIGDAL readout PC, we demonstrate our pipeline to process and perform the rare event search on 2D image data faster than the peak 120 frame per second acquisition rate of the CMOS camera. Applying these same steps offline, we demonstrate that we can reduce a sample of 20 million camera frames to around 1000 frames while maintaining nearly all signal that YOLOv8 is able to detect, thereby transforming a rare search into a much more manageable search. Our studies highlight the potential of pipelines similar to ours significantly improving the detection capabilities of experiments requiring rapid and precise object identification in high-throughput data environments

Fungal Planet description sheets: 1436–1477

Novel species of fungi described in this study include those from various countries as follows: Argentina, Colletotrichum araujiae on leaves, stems and fruits of Araujia hortorum. Australia, Agaricus pateritonsus on soil, Curvularia fraserae on dying leaf of Bothriochloa insculpta, Curvularia millisiae from yellowing leaf tips of Cyperus aromaticus, Marasmius brunneolorobustus on well-rotted wood, Nigrospora cooperae from necrotic leaf of Heteropogon contortus, Penicillium tealii from the body of a dead spider, Pseudocercospora robertsiorum from leaf spots of Senna tora, Talaromyces atkinsoniae from gills of Marasmius crinis-equi and Zasmidium pearceae from leaf spots of Smilax glyciphylla. Brazil, Preussia bezerrensis fromair. Chile, Paraconiothyrium kelleni from the rhizosphere of Fragaria chiloensis subsp. chiloensis f. chiloensis. Finland, Inocybe udicola onsoilinmixedforest with Betula pendula, Populus tremula, Picea abies and Alnus incana. France, Myrmecridium normannianum on dead culm of unidentified Poaceae. Germany, Vexillomyces fraxinicola from symptomless stem wood of Fraxinus excelsior. India, Diaporthe limoniae on infected fruit of Limonia acidissima, Didymella naikii on leaves of Cajanus cajan, and Fulvifomes mangroviensis on basal trunk of Aegiceras corniculatum. Indonesia, Penicillium ezekielii from Zea mays kernels. Namibia, Neocamarosporium calicoremae and Neocladosporium calicoremae on stems of Calicorema capitata, and Pleiochaeta adenolobi on symptomatic leaves of Adenolobus pechuelii. Netherlands, Chalara pteridii on stems of Pteridium aquilinum, Neomackenziella juncicola (incl. Neomackenziella gen. nov.)and Sporidesmiella junci from dead culms of Juncus effusus. Pakistan, Inocybe longistipitata on soil in a Quercus forest. Poland, Phytophthora viadrina from rhizosphere soil of Quercus robur, and Septoria krystynae on leaf spots of Viscum album. Portugal (Azores), Acrogenospora stellata on dead wood or bark. South Africa, Phyllactinia greyiae on leaves of Greyia sutherlandii and Punctelia anae on bark of Vachellia karroo. Spain, Anteaglonium lusitanicum on decaying wood of Prunus lusitanica subsp. lusitanica, Hawksworthiomyces riparius from fluvial sediments, Lophiostoma carabassense endophytic in roots of Limbarda crithmoides, and Tuber mohedanoi from calcareussoils. Spain (Canary Islands), Mycena laurisilvae on stumps and woody debris. Sweden, Elaphomyces geminus from soil under Quercus robur. Thailand, Lactifluus chiangraiensis on soil under Pinus merkusii, Lactifluus nakhonphanomensis and Xerocomus sisongkhramensis on soil under Dipterocarpus trees. Ukraine, Valsonectria robiniae on dead twigs of Robinia hispida. USA, Spiralomyces americanus (incl. Spiralomyces gen. nov.) from office air. Morphological and culture characteristics are supported by DNA barcodes.Fungal Planet description sheets: 1436–1477publishedVersio