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At least 145 records · Page 8

Evidence for ground-state electron capture of K 40

Potassium-40 is a widespread, naturally occurring isotope whose radioactivity impacts estimated geological ages spanning billions of years, nuclear structure theory, and subatomic rare-event searches—including those for dark matter and neutrinoless double-beta decay. The decays of this long-lived isotope must be precisely known for its use as a geochronometer, and to account for its presence in low-background experiments. There are several known decay modes for potassium-40, but a predicted electron-capture decay directly to the ground state of argon-40 has never been observed. The existence of this decay mode impacts several fields, while theoretical predictions span an order of magnitude. Here we report on the first, successful observation of this rare decay mode, obtained by the KDK (potassium decay) Collaboration using a novel combination of a low-threshold x-ray detector surrounded by a tonne-scale, high-efficiency γ -ray tagger at Oak Ridge National Laboratory. A blinded analysis reveals a distinctly nonzero ratio of intensities of ground-state electron-captures ( I EC 0 ) over excited-state ones ( I EC * ) of I EC 0 / I EC * = 0.0095 ± stat 0.0022 ± sys 0.0010 (68% CL), with the null hypothesis rejected at 4 σ [Stukel et al. , Phys. Rev. Lett. 131 , 052503 (2023) ]. In terms of branching ratio, this unambiguous signal yields I EC 0 = 0.098 % ± stat 0.023 % ± sys 0.010 % , roughly half of the commonly used prediction. This first observation of a third-forbidden unique electron capture improves our understanding of low-energy backgrounds in dark-matter searches and has implications for nuclear-structure calculations. For example, a shell-model based theoretical estimate for the neutrinoless double-beta decay half-life of calcium-48 is increased by a factor of 7 - 2 + 3 . Our nonzero measurement shifts geochronological ages by up to a percent; implications are illustrated for Earth and solar system chronologies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NOvA as a Supernova Observatory

Extra-solar system neutrino astronomy was born in February 1987 when a supernova in a nearby satellite galaxy deposited a couple dozen neutrino events across three solar neutrino and nucleon decay experiments. This marked the first-ever observation of supernova neutrinos, as well as the first supernova in our galactic neighborhood visible to the naked eye in nearly 400 years. There is still much we do not know about the dynamics of these powerful explosions, but one thing is certain: neutrinos play a central role in driving a supernova. They also provide a unique opportunity for probing the interior conditions of a collapsing stellar core. Since 1987, the number of neutrino detectors around the world has grown. When the next supernova occurs, detectors must be ready to seize the moment and record data from this rare event that only happens a couple times per century. The NOvA experiment has been prepared for this for some time, but it has been unclear how well NOvA will be ab le to se parate supernova-like events from the large cosmogenic backgrounds and extract meaningful physical insight. In this thesis, I show that the cosmic-induced backgrounds in the NOvA detectors---especially the far detector---can be reduced to an acceptable level for core-collapse supernovae within $\sim$15 kpc and that a determination of the neutrino mass ordering can be made for nearby supernovae under certain conditions. This thesis paves the way for future sensitivity studies and eventual analyses of real supernova data, and shows that NOvA's liquid scintillator neutrino detectors are a capable supernova observatory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NOvA as a Supernova Observatory

Extra-solar system neutrino astronomy was born in February 1987 when a supernova in a nearby satellite galaxy deposited a couple dozen neutrino events across three solar neutrino and nucleon decay experiments. This marked the first-ever observation of supernova neutrinos, as well as the first supernova in our galactic neighborhood visible to the naked eye in nearly 400 years. There is still much we do not know about the dynamics of these powerful explosions, but one thing is certain: neutrinos play a central role in driving a supernova. They also provide a unique opportunity for probing the interior conditions of a collapsing stellar core. Since 1987, the number of neutrino detectors around the world has grown. When the next supernova occurs, detectors must be ready to seize the moment and record data from this rare event that only happens a couple times per century. The NOvA experiment has been prepared for this for some time, but it has been unclear how well NOvA will be ab le to se parate supernova-like events from the large cosmogenic backgrounds and extract meaningful physical insight. In this thesis, I show that the cosmic-induced backgrounds in the NOvA detectors---especially the far detector---can be reduced to an acceptable level for core-collapse supernovae within $\sim$15 kpc and that a determination of the neutrino mass ordering can be made for nearby supernovae under certain conditions. This thesis paves the way for future sensitivity studies and eventual analyses of real supernova data, and shows that NOvA's liquid scintillator neutrino detectors are a capable supernova observatory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ProtoDUNE-VD for Beyond the Standard Model Searches: Initial Studies and Future Prospects

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino program designed to address fundamental questions in neutrino and astroparticle physics. ProtoDUNE, operating at the CERN Neutrino Platform, serves as a full-scale prototype for the DUNE Far Detector. In particular, the ProtoDUNE Vertical Drift (ProtoDUNE-VD) detector provides a powerful testbed for validating reconstruction and event selection techniques for future DUNE operations. In addition to detector R&D, ProtoDUNE enables a novel parasitic beam-dump search for beyond-the-Standard-Model (BSM) particles. However, it faces several challenges. Most notably, the ProtoDUNE-VD modules operate on the surface and are consequently exposed to an intense flux of cosmic rays, which requires a dedicated trigger. In addition, standard neutrinos are also produced in the T2 target area from the decay of unstable mesons, constituting a relevant background, which needs to be well understood and characterized a priori. We present the first studies based on 2025 data taken with a trigger designed to identify neutrino candidates at ProtoDUNE-VD. ProtoDUNE-VD’s high-resolution LArTPC imaging allows detailed reconstruction of decay and scattering signatures. This work demonstrates the complementarity of traditional tools such as Pandora and modern machine-learning approaches, providing key input for atmospheric neutrino and rare-event searches in the DUNE Vertical Drift program.

Bagdu, Halit [U. Iowa, Iowa City]↗

Harnessing the Quantum Zeno Effect in superconducting qubits for particle detection

Superconducting qubits, originally developed for quantum computing, are emerging as a potentially powerful tool for detecting low-energy particle interactions, such as dark matter and neutrinos. These devices can register energy deposits as small as a few meV, dramatically lowering the detection threshold compared to conventional sensors. However, their deployment in rare-event searches is hampered by a critical and unresolved background: Two-Level Systems (TLSes). TLSes are material defects that can scramble qubit frequencies and coherence times in a way that resembles particle energy deposits. Such false signals can critically limit the sensitivity and extend experimental runtimes for qubit-based sensors by years. This talk introduces a novel method to eliminate TLSes as a background source in superconducting qubit-based detectors. By harnessing the Quantum Zeno Effect (QZE), a well-established quantum phenomenon where frequent observation inhibits system evolution, I will discuss the possibility of “freezing” these TLS defects in place. This effectively suppresses their interference, stabilizes qubit behavior, and opens the door to using TLSes themselves as auxiliary sensors. I have already identified target TLSes and observed early signs of QZE-like dynamics in Fermilab-fabricated devices. The method builds on my existing collaborations at Fermilab’s Quantum Information Testbed (QUIET), with access to low muon flux cryogenic facilities 100 meters underground, control electronics, and expert mentors across multiple institutions. By removing a key bottleneck to superconducting sensor deployment, this research targets advancing the development of a general-purpose technique to enhance sensitivity, reduce false positives, and accelerate discovery in searches for dark matter, neutrinos, and other rare phenomena.

Seidel, Olivia [Texas U., Arlington]↗

Quantum Information Science in High Energy Physics at the Large Hadron Collider (Final Report-QuantISED)

We pursue scientific research at the interface of High Energy Physics and Quantum Information Science. This includes studies of thermal radiation and quantum entanglement in high-energy collisions at the Large Hadron Collider (LHC), with special emphasis on entanglement entropy and the Higgs boson. This project has also been extended to include quantum entanglement and charged current weak interactions using Fermilab results. And most recently, we have begun tests of the temporal entanglement using LHC data. Collider experiments such as proton-proton collisions at the LHC yield hadrons that exhibit an exponential behavior at low transverse momenta. This surprising behavior is seen in data from both the ATLAS and CMS collaborations. We attribute this phenomenon to quantum entanglement between the regions in the nucleon wave function. The exponential component to the transverse momentum distribution is a result of thermal radiation that is akin to Hawking or Unruh radiation that should exist at the event horizon of astrophysical black holes and neutron stars. The Principal Investigator, in collaboration with a theoretical physicist at Stony Brook University and Brookhaven National Laboratory, and with Yale University students, has shown evidence for this thermal radiation in several production and decay processes in the ATLAS and CMS data, and its connection to entanglement entropy (O.K. Baker and D.E Kharzeev, Phys. Rev. D 98, 054007 (2018)), including even the Higgs boson sector. Interestingly, this thermal behavior is also seen in momentum distributions of charged current weak interactions according to our studies. These findings suggest a deep connection between quantum entanglement (entanglement entropy) and thermalization in both hadron collisions at the energy frontier and neutrino scattering at the intensity frontier. We have confirmed the proposed relation between the effective temperature and the hard-scattering scale at lower energies using the most recent LHC data for the following systems: Higgs bosons, top quarks, and charged hadrons. Additionally, we have results for hadron production in neutrino scattering from nuclei using Fermilab weak interaction data. This study is carried out using data from the MINERvA collaboration. In those cases where entanglement is expected, there is an exponential component to the momentum distribution, while this component is absent in those processes where no entanglement is expected. This research thus tests the hypothesis about a link between quantum entanglement and thermalization in strong and weak interactions. See Phys Lett B 811, 135948 (2020). We also initiated research applying a quantum search algorithm (Grover's Algorithm) to LHC data. This quantum algorithm was used to show how rare events in LHC data can be searched for in large, unsorted databases, with quadratic speedup compared to classical search algorithms on classical computers. See "Application of a Quantum Search Algorithm to High- Energy Physics Data at the Large Hadron Collider", arXiv:2010.00649 [quant-ph].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Soft Decision Analyzer

The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the receiver under test is subjected to conditions where its performance degrades to high error rates (30 percent or beyond). The design incorporates a number of features, such as watchdog triggers that permit the SDA system to recover from large receiver upsets automatically and continue accumulating performance analysis unaided by operator intervention. This accommodates tests that can last in the order of days in order to gain statistical confidence in results and is also useful for capturing snapshots of rare events.

Steele, Glen↗

A review of artificial intelligence applications in manufacturing operations

Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

Plathottam, Siby Jose↗

Search for solar axions produced through the axion-electron coupling gae using a new GridPix detector at CAST

We present a search for solar axions produced through the axion-electron coupling (g ae ) using data from a novel 7-GridPix detector installed at the CERN Axion Solar Telescope (CAST). The detector, featuring ultra-thin silicon nitride windows and multiple veto systems, collected approximately 160 hours of solar tracking data between 2017–2018. Using machine learning techniques and the veto systems, we achieved a background rate of 1.06 × 10 −5 keV −1 cm −2 s −1 at a signal efficiency of about 80% in the 0.2 to 8 keV range. Analysis of the data yielded no significant excess above background, allowing us to set a new upper limit on the product of the axion-electron and axion-photon couplings of g ae · g aγ < 7.35 × 10 −23 GeV −1 at 95% confidence level for axion masses below 10 meV. This result improves upon the previous best helioscope limit and demonstrates the potential of GridPix technology for rare event searches. Additionally, we derived a limit on the axion-photon coupling of g aγ < 9.0 × 10 −11 GeV −1 at 95% CL, which, while not surpassing CAST’s best limit, provides complementary constraints on axion models.

Beyond Standard Model↗

The CUORE Detector and Results

The cryogenic underground observatory for rare events (CUORE) is a cryogenic experiment searching for neutrinoless double beta decay (0νββ) of 130 Te. The detector consists of an array of 988TeO 2 crystals arranged in a compact cylindrical structure of 19 towers. We report the CUORE initial operations and optimization campaigns. We then present the CUORE results on 0νββ and 2νββ decay of 130 Te obtained from the analysis of the physics data acquired in 2017.

0vββ↗

Latest Results from the CUORE Experiment

Abstract The Cryogenic Underground Observatory for Rare Events (CUORE) is the first cryogenic experiment searching for $$0\nu \beta \beta $$ 0 ν β β decay that has been able to reach the one-tonne mass scale. The detector, located at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy, consists of an array of 988 $${\mathrm{TeO}}_{2}$$ TeO 2 crystals arranged in a compact cylindrical structure of 19 towers. CUORE began its first physics data run in 2017 at a base temperature of about 10 mK and in April 2021 released its $$3{\mathrm{rd}}$$ 3 rd result of the search for $$0\nu \beta \beta $$ 0 ν β β , corresponding to a tonne-year of $$\mathrm{TeO}_{2}$$ TeO 2 exposure. This is the largest amount of data ever acquired with a solid state detector and the most sensitive measurement of $$0\nu \beta \beta $$ 0 ν β β decay in $${}^{130}\mathrm{Te}$$ 130 Te ever conducted . We present the current status of CUORE search for $$0\nu \beta \beta $$ 0 ν β β with the updated statistics of one tonne-yr. We finally give an update of the CUORE background model and the measurement of the $${}^{130}\mathrm{Te}$$ 130 Te $$2\nu \beta \beta $$ 2 ν β β decay half-life and decay to excited states of $${}^{130}\mathrm{Xe}$$ 130 Xe , studies performed using an exposure of 300.7 kg yr.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SPLENDAQ: A Detector-Agnostic Data Acquisition System for Small-Scale Physics Experiments

Many scientific applications from rare-event searches to condensed matter system characterization to high-rate nuclear experiments require time-domain triggering on a raw stream of data, where the triggering is generally threshold-based or randomly acquired. When carrying out detector R &D, there is a need for a general data acquisition (DAQ) system to quickly and efficiently process such data. In the SPLENDOR collaboration, we are developing the Python-based SPLENDAQ package for this exact purpose—it offers two main features for offline analysis of continuous data: a threshold triggering algorithm based on the time-domain optimal filter formalism and an algorithm for randomly choosing nonoverlapping segments for noise measurements. Further, combined with the commercially available Moku platform, developed by Liquid Instruments, we have a full pipeline of event building off raw data with minimal setup. Here, we review the underlying principles of this detector-agnostic DAQ package and give concrete examples of its utility in various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Frictionless knowledge injection for few-shot learning

Cutting-edge machine learning methods often require large volumes of curated training data, precluding their use in national security problems with rare events in massive datasets. We present a method for incorporating abstract knowledge into models tailored for sparse data. A subject matter expert defines salient concepts using data examples, which are encoded in the model’s embedding space. Models are then trained to respect these concepts. This method enables knowledge injection, yielding effective models with limited labeled data and the ability to assess model sensitivity for subject matter expertise across the nonproliferation mission space, as demonstrated with Raman spectra analysis.

Stomps, Jordan [ORNL] (ORCID:0000000178114479)↗

Primary yields of protons measured using CR-39 in laser-induced deuteron–deuteron fusion reactions

The deuteron and deuteron (DD) fusion reactions is the most crucial reaction in the nuclear astrophysics and inertial confinement fusion, which is responsible for synthesizing chemical elements, and for powering the stellar evolution. The plasma environment generated by the high-intensity laser used in a DD fusion reaction is similar to the early stage of the Big Bang. Therefore, it is important to study laser-induced DD fusion reactions. Recently, we experimentally investigated such reactions using eight laser beams with the third harmonic impact on a deuterated polyethylene target at the ShenGuang-II Upgrade facility. In this work, we focused on the application of range-filter spectrometers assembled from a 70 μm aluminum filter and two CR-39 nuclear track detectors to measure the yields of primary DD protons. Based on the track diameter calibration results of 3 MeV protons used to diagnose the tracks on the range- filter spectrometers, we measured a primary DD proton yield of approximately (8:52 ± 1:7) × 10 6 , consistent with the yields from similar laser facilities worldwide, indicating that range-filter spectrometry is an effective way to measure primary DD protons. Furthermore, using other accurate detectors may help to measure the rare events of D 3 He protons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value. In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M (plus-minus sign) 1.09M USD and 104.99M (plus-minus sign) 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

25 ENERGY STORAGE↗

Development of ultralow-background cryogenic calorimeters for the measurement of surface α contamination

Next-generation experiments searching for rare events must satisfy increasingly stringent requirements on the bulk and surface radioactive contamination of their active and structural materials. The measurement of surface contamination is particularly challenging, as no existing technology is capable of separately measuring parts of the 232 Th and 238 U decay chains that are commonly found to be out of secular equilibrium. We will present the results obtained with a detector prototype consisting of 8 silicon wafers of 150mm diameter instrumented as bolometers and operated in a low-background dilution refrigerator at the Gran Sasso Underground Laboratory of INFN, Italy. Furthermore, the prototype was characterized by a baseline energy resolution of few keV and a background <100nBq/cm 2 in the full range of α energies, obtained with simple procedures for cleaning of all employed materials and no specific measures to prevent recontamination. Such performance, together with the modularity of the detector design, demonstrate the possibility to realize an alpha detector capable of separately measuring all alpha emitters of the 232 Th and 238 U chains, possibly reaching a sensitivity of few nBq/cm 2 .

07 ISOTOPE AND RADIATION SOURCES↗

Sensitivity of the GAPS experiment to low-energy cosmic-ray antiprotons

The General Antiparticle Spectrometer (GAPS) is an upcoming balloon mission to measure low-energy cosmic-ray antinuclei during at least three ~35-day Antarctic flights. With its large geometric acceptance and novel exotic atom-based particle identification, GAPS will detect ~500 cosmic antiprotons per flight and produce a precision cosmic antiproton spectrum in the kinetic energy range of ~0.07–0.21 GeV/n at the top of the atmosphere. With these high statistics extending to lower energies than any previous experiment, and with complementary sources of experimental uncertainty compared to traditional magnetic spectrometers, the GAPS antiproton measurement will be sensitive to dark matter, primordial black holes, and cosmic ray propagation. The antiproton measurement will also validate the GAPS antinucleus identification technique for the antideuteron and antihelium rare-event searches. Finally, this analysis demonstrates the GAPS sensitivity to cosmic-ray antiprotons using a full instrument simulation and event reconstruction, and including solar and atmospheric effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Variations in proton transfer pathways and energetics on pristine and defect-rich quartz surfaces in water: Insights into the bimodal acidities of quartz

Hypothesis. Understanding the mechanisms of proton transfer on quartz surfaces in water is critical for a range of processes in geochemical, environmental, and materials sciences. The wide range of surface acidities (>9 pKa units) found on the ubiquitous mineral quartz is caused by the structural variations of surface silanol groups. Molecular scale simulations provide essential tools for elucidating the origin of site-specific surface acidities. Simulations. Here, we used density-functional tight-binding-based molecular dynamics combined with rare-event metadynamics simulations to probe the mechanisms of deprotonation reactions from ten representative surface silanol groups found on both pristine and defect-rich quartz (1 0 1) surfaces with Si vacancies. Findings. The results show that deprotonation is a highly dynamic process where both the surface hydroxyls and bridging oxygen atoms serve as the proton acceptors, in addition to water. Deprotonation of embedded silanols through intrasurface proton transfer exhibited lower pKa values with less H-bond participation and higher energy barriers, suggesting a new mechanism to explain the bimodal acidity observed on quartz surface. Defect sites, recently shown to comprise a significant portion of the quartz (1 0 1) surface, diversify the coordination and local H-bonding environments of the surface silanols, changing both the deprotonation pathways and energetics, leading to a wider range of pKa values (2.4 to 11.5) than that observed on pristine quartz surface (10.4 and 12.1).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗