Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

Here we publish three years of data from the UCNr experiment performed at the Los Alamos Ultracold Neutron Facility at the Los Alamos Neutron Science Center. These data are in addition to our previously published data. Our goals in this paper are to better understand and quantify systematic uncertainties and to improve the lifetime statistical precision. We previously reported a value from our 2017-2018 data for the neutron lifetime of 877.75 +/- 0.28 (statistical) +0.22-0.16 (systematic) s. We have collected an additional three years of data reported here for the first time. When all the data from UCNr are averaged for 2017, 2018, 2020, 2021, and 2022, we report an updated value for the lifetime of 877.83 +/- 0.22 (statistical)+0.20-0.17 (systematic) s. We utilized improved monitor detectors, reduced our correction due to UCN upscattering on residual gas, and employed four different UCN detector geometries both to reduce the correction required for rate dependence and to explore potential contributions due to phase space evolution.

The upcoming UCNProBe experiment at Los Alamos National Laboratory will measure the β-decay rate of free neutrons with different systematic uncertainties than previous beam-based neutron lifetime experiments. We have developed a new ^10B-coated YAP:Ce scintillator whose properties are presented. The advantage of the YAP:Ce scintillator is its high Fermi potential, which reduces the probability for upscattering of ultracold neutrons, and its short decay time, which is important at high counting rates. Birks' coefficient of YAP:Ce was measured to be (5.56^+0.05_-0.30)× 10^-4 cm/MeV and light losses due to 120 nm of ^10B-coating to be about 60 polystyrene scintillator was about 50 that are captured on the ^10B coating is (86.82 ± 2.61) with ultracold neutrons showed that YAP:Ce crystal counted 8 compared to ZnS screen. This may be due to an uneven coating of ^10B on the rough surface.

The past two decades have yielded several new measurements and reanalysis of older measurements of the neutron lifetime. These have led to a 4.4 standard deviation discrepancy between the most precise measurements of the neutron decay rate producing protons in cold neutron beams and the most precise lifetime measured in neutron storage experiments. Here we publish an analysis of the recently published UCN aimed a searching for an explanation of this difference using the model proposed by Koch and Hummel.

A study of the dead layer thickness and quenching factor of a plastic scintillator for use in ultracold neutron (UCN) experiments is described. Alpha spectroscopy was used to determine the thickness of a thin surface dead layer to be 630 ± 110 nm. The relative light outputs from the decay of 241Am and Compton scattering of electrons were used to extract Birks' law coefficient, yielding a kB value of 0.087 ± 0.003 mm/MeV, consistent with some previous reports for other polystyrene-based scintillators. The results from these measurements are incorporated into the simulation to show that an energy threshold of (∼9 keV) can be achieved for the UCNProBe experiment. This low threshold enables high beta particle detection efficiency and the indirect measurement of UCN. The ability to make the scintillator deuterated, accompanied by its relatively thin dead layer, gives rise to unique applications in a wide range of UCN experiments, where it can be used to trap UCN and detect charged particles in situ.

We have developed a two-dimensional neutron imager based on a semiconductor pixelated sensor, especially designed for experiments measuring of a spatial and a temporal behavior of quantum bound states of ultra-cold neutrons. Through these measurements, we expect to measure the ratio between the inertial and gravitational masses of neutrons and to test the equivalence principle in the quantum regime. As one of the principal neutron imagers, we fabricated a sensor with a sandwich configuration, named 10B-INTPIX4-sw, and tested its response to ultra-cold neutrons at the Los Alamos Neutron Science Center (LANSCE). We observed simultaneous events on both sandwiching sensors without significant loss of detection efficiency. The efficiency was evaluated to be about 16%, relative to the 10B/ZnS reference detector. The coincidence condition reduces its efficiency by a factor of about 3.

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

High spatial resolution of ultracold neutron (UCN) measurements of 1 µm or less is highly desired for many UCN experiments. Optical neural networks are potential radiation-hard hardware platforms for real-time, energy-efficient analysis of UCN hits.(LA-UR-23-33103)

The upcoming UCNProBe experiment at Los Alamos National Laboratory will measure the beta decay rate of free neutrons with different systematic uncertainties than previous beam-based neutron lifetime experiments. We have tested a new B-10-coated Yttrium Aluminum Perovskite (YAP:Ce) scintillator and present its properties. The advantages of the YAP:Ce scintillator include its high Fermi potential, which reduces the probability for upscattering of ultracold neutrons (UCN), and its short decay time, which increases sensitivity at high counting rates. Birks' coefficient of YAP:Ce was measured to be (5.56(-0.30)(+0.05))x10-4 cm/MeV. The loss of light due to the 120 nm B-10-coating was measured to be about 60%, and the loss of light from YAP:Ce due to transmission through a deuterated polystyrene scintillator was about 50%. The efficiency for neutron capture on the B-10 coating was (86.8 +/- 2.6)%, and a measurement using UCN showed that the YAP:Ce crystal counted 8%-28% more UCN compared to a ZnS:Ag screen. The difference may be due to the uneven coating of B-10 on the rough surface of ZnS:Ag. (c) 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0International (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).

Magnetic Johnson noise is an important consideration for many applications involving precision magnetometry, and its significance will only increase in the future with improvements in measurement sensitivity. The fluctuation-dissipation theorem can be utilized to derive analytic expressions for magnetic Johnson noise in certain situations. But when used in conjunction with finite element analysis tools, the combined approach is particularly powerful as it provides a practical means to calculate the magnetic Johnson noise arising from conductors of arbitrary geometry and permeability. In this paper, we demonstrate this method to be one of the most comprehensive approaches presently available to calculate thermal magnetic noise. In particular, its applicability is shown to not be limited to cases where the noise is evaluated at a point in space but also can be expanded to include cases where the magnetic field detector has a more general shape, such as a finite size loop, a gradiometer, or a detector that consists of a polarized atomic species trapped in a volume. Furthermore, some physics insights gained through studies made using this method are discussed.

The neutron electric dipole moment (nEDM) experiment that is currently being developed at Los Alamos National Laboratory (LANL) will use ultracold neutrons (UCN) and Ramsey's method of separated oscillatory fields to search for a nEDM. In this paper, we present measurements of UCN storage and UCN transport performed during the commissioning of a new beamline at the LANL UCN source and demonstrate a sufficient number of stored polarized UCN to achieve a statistical uncertainty of odn = 2x 10-27 e cm in 5 calendar years of running. We also present an analytical model describing data that provides a simple parameterization of the input UCN energy spectrum on the new beamline.

Fundamental neutron physics, combining precision measurements and theory, probes particle physics at short range with reach well beyond the highest energies probed by the LHC. Significant US efforts are underway that will probe BSM CP violation with orders of magnitude more sensitivity, provide new data on the Cabibbo anomaly, more precisely measure the neutron lifetime and decay, and explore hadronic parity violation. World-leading results from the US Fundamental Neutron Physics community since the last Long Range Plan, include the world's most precise measurement of the neutron lifetime from UCN$\tau$, the final results on the beta-asymmetry from UCNA and new results on hadronic parity violation from the NPDGamma and n-${^3}$He runs at the FNPB (Fundamental Neutron Physics Beamline), precision measurement of the radiative neutron decay mode and n-${}^4$He at NIST. US leadership and discovery potential are ensured by the development of new high-impact experiments including BL3, Nab, LANL nEDM and nEDM@SNS. On the theory side, the last few years have seen results for the neutron EDM from the QCD $\theta$ term, a factor of two reduction in the uncertainty for inner radiative corrections in beta-decay which impacts CKM unitarity, and progress on {\it ab initio} calculations of nuclear structure for medium-mass and heavy nuclei which can eventually improve the connection between nuclear and nucleon EDMs. In order to maintain this exciting program and capitalize on past investments while also pursuing new ideas and building US leadership in new areas, the Fundamental Neutron Physics community has identified a number of priorities and opportunities for our sub-field covering the time-frame of the last Long Range Plan (LRP) under development. This white paper elaborates on these priorities.

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.

This whitepaper presents the research priorities decided on by attendees of the 2022 Town Meeting for Fundamental Symmetries, Neutrons and Neutrinos, which took place December 13-15, 2022 in Chapel Hill, NC, as part of the Nuclear Science Advisory Committee (NSAC) 2023 Long Range Planning process. A total of 275 scientists registered for the meeting. The whitepaper makes a number of explicit recommendations and justifies them in detail.

High spatial resolution of ultracold neutron (UCN) measurement is of growing interest to UCN experiments such as UCN spectrometers, UCN polarimeters, quantum physics of UCNs, and quantum gravity. Here we utilize physics-informed deep learning to enhance the experimental position resolution and to demonstrate sub-micron spatial resolutions for UCN position measurements obtained using a room-temperature CMOS sensor, extending our previous work [1, 2] that demonstrated a position uncertainty of 1.5 microns. We explore the use of the open-source software Allpix Squared to generate experiment-like synthetic hit images with ground-truth position labels. We use physics-informed deep learning by training a fully-connected neural network (FCNN) to learn a mapping from input hit images to output hit position. The automated analysis for sub-micron position resolution in UCN detection combined with the fast data rates of current and next generation UCN sources will enable improved precision for future UCN research and applications.

The past two decades have yielded several new measurements and reanalyses of older measurements of the neutron lifetime. These have led to a 4.4 standard deviation discrepancy between the most precise measurements of the neutron decay rate producing protons in cold neutron beams and the lifetime measured in neutron storage experiments. Measurements using different techniques are important for investigating whether there are unidentified systematic effects in any of the measurements. In this paper we report a new measurement using the Los Alamos asymmetric magneto-gravitational trap where the surviving neutrons are counted external to the trap using the fill and dump method. The new measurement gives a free neutron lifetime of . Although this measurement is not as precise, it is in statistical agreement with previous results using in situ counting in the same apparatus.

In this paper, we report studies of the Fermi potential and loss per bounce of ultracold neutrons (UCNs) on a deuterated scintillator (Eljen-299-02D). These UCN properties of the scintillator enable its use in a wide variety of applications in fundamental neutron research.

We report an improved measurement of the free neutron lifetime τ_{n} using the UCNτ apparatus at the Los Alamos Neutron Science Center. We count a total of approximately 38×10^{6} surviving ultracold neutrons (UCNs) after storing in UCNτ's magnetogravitational trap over two data acquisition campaigns in 2017 and 2018. We extract τ_{n} from three blinded, independent analyses by both pairing long and short storage time runs to find a set of replicate τ_{n} measurements and by performing a global likelihood fit to all data while self-consistently incorporating the β-decay lifetime. Both techniques achieve consistent results and find a value τ_{n}=877.75±0.28_{stat}+0.22/-0.16_{syst}  s. With this sensitivity, neutron lifetime experiments now directly address the impact of recent refinements in our understanding of the standard model for neutron decay.

We report results from a study on electrical breakdown in liquid helium using near-uniform-field stainless steel electrodes with a stressed area of ∼0.7cm2. The distribution of the breakdown field is obtained for temperatures between 1.7 K and 4.0 K, pressures between the saturated vapor pressure and 626 Torr, and with electrodes of different surface polishes. A data-based approach for determining the electrode-surface-area scaling of the breakdown field is presented. The dependence of the breakdown probability on the field strength as extracted from the breakdown field distribution data is used to show that breakdown is a surface phenomenon closely correlated with Fowler–Nordheim field emission from asperities on the cathode. We show that the results from this analysis provide an explanation for the supposed electrode gap-size effect and also allow for a determination of the breakdown-field distribution for arbitrary shaped electrodes. Most importantly, the analysis method presented in this work can be extended to other noble liquids to explore the dependencies for electrical breakdown in those media.