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At least 91 records · Page 5

Multivariate discrimination in quantum target detection

In this work, we describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. Furthermore, the technique combines two independent variables, time difference and summed energy, of a photon pair from the spontaneous parametric down-conversion source into an optimal discriminant. The discriminant performance was studied in experimental data and in Monte-Carlo modelling with clear improvement shown compared to previous techniques. As novel detectors become available, we expect this type of multivariate analysis to become increasingly important in multi-dimensional quantum optics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A functional form for liquid scintillator pulse shapes

Digitization of detector signals enables analysis of the original waveform to extract timing, particle identification, and energy deposition information. Here we present the use of analytical functions based on sigmoids to model and fit such pulse shapes from liquid organic scintillators, though the method should also be applicable to other detector systems. Neutron and gamma interactions in NE213 detectors were digitized from the phototube anode and fit using a sigmoid-based function. The acuity of the fit in extracting timing information and performing neutron-gamma pulse-shape discrimination are presented and discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Inferring Neutron Star Merger Ejecta Morphology with Kilonovae

In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.

79 ASTRONOMY AND ASTROPHYSICS↗

The essential character of the neutrino mechanism of core-collapse supernova explosions

Abstract Calibrating with detailed 2D core-collapse supernova (CCSN) simulations, we derive a simple CCSN explosion condition based solely upon the terminal density profiles of state-of-the-art stellar evolution calculations of the progenitor massive stars. This condition captures the vast majority of the behaviour of the one hundred 2D state-of-the-art models we performed to gauge its usefulness. The goal is to predict, without resort to detailed simulation, the explodability of a given massive star. We find that the simple maximum fractional ram pressure jump discriminant we define works well ∼90 per cent of the time and we speculate on the origin of the few false positives and false negatives we witness. The maximum ram pressure jump generally occurs at the time of accretion of the silicon/oxygen interface, but not always. Our results depend upon the fidelity with which the current implementation of our code F ornax adheres to Nature and issues concerning the neutrino–matter interaction, the nuclear equation of state, the possible effects of neutrino oscillations, grid resolution, the possible role of rotation and magnetic fields, and the accuracy of the numerical algorithms employed remain to be resolved. Nevertheless, the explodability condition we obtain is simple to implement, shows promise that it might be further generalized while still employing data from only the unstable Chandrasekhar progenitors, and is a more credible and robust simple explosion predictor than can currently be found in the literature.

Astronomy & Astrophysics↗

Improving qubit readout with hidden Markov models

We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit-state transitions and makes for a robust classification scheme with higher starting-state assignment fidelity than when compared to a multivariate Gaussian or a support vector machine scheme. Therefore, the method also eliminates the qubit-dependent readout time optimization requirement in current schemes. Using a HMM state discriminator we estimate fidelities reaching the ideal limit. Unsupervised learning gives access to transition matrix, priors, and IQ distributions, providing a toolbox for studying qubit-state dynamics during strong projective readout.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

Determining the depths of small crustal earthquakes is challenging in many regions of the world, because most seismic networks are too sparse to resolve trade-offs between depth and origin time with conventional arrival-time methods. Precise and accurate depth estimation is important, because it can help seismologists discriminate between earthquakes and explosions, which is relevant to monitoring nuclear test ban treaties and producing earthquake catalogs that are uncontaminated by mining blasts. Here, we examine the depth sensitivity of several physics-based waveform features for ~8000 earthquakes in southern California that have well-resolved depths from arrival-time inversion. We focus on small earthquakes (2 < M L < 4) recorded at local distances (<150 km), for which depth estimation is especially challenging. We find that differential magnitudes (M w /M L –M c ) are positively correlated with focal depth, implying that coda wave excitation decreases with focal depth. We analyze a simple proxy for relative frequency content, Φ≡log 10 (M 0 )+3log 10 (f c ), and find that source spectra are preferentially enriched in high frequencies, or “blue-shifted,” as focal depth increases. Here, we also find that two spectral amplitude ratios Rg 0.5–2 Hz/Sg 0.5–8 Hz and Pg/Sg at 3–8 Hz decrease as focal depth increases. Using multilinear regression with these features as predictor variables, we develop models that can explain 11%–59% of the variance in depths within 10 subregions and 25% of the depth variance across southern California as a whole. We suggest that incorporating these features into a machine learning workflow could help resolve focal depths in regions that are poorly instrumented and lack large databases of well-located events. Some of the waveform features we evaluate in this study have previously been used as source discriminants, and our results imply that their effectiveness in discrimination is partially because explosions generally occur at shallower depths than earthquakes.

58 GEOSCIENCES↗

The propagation of seismic waves, misinformation, and disinformation from the 2024-10-05 M 4.5 Iran earthquake

The 2024-10-05 Iran M 4.5 earthquake took place at a time of heightened tensions in the Middle East. We perform a discrimination and moment tensor analysis and identify a shallow-dipping, reverse fault source commensurate with the compressional setting of the Iranian interior. Nonetheless, the event's aftermath saw widespread dissemination of misinformation, and potentially active disinformation, concluding that it was in fact a test of an Iranian nuclear weapon. The 'evidence' for many of these claims was based on inaccurate interpretation of seismic data. In this paper, we analyze how geophysical 'fake news' propagated through social media (mainly Twitter/X) following this event, eventually gaining traction in mainstream, earned media. This event is an illustrative warning of how seismic data can be misinterpreted and/or manipulated in public discourse.

58 GEOSCIENCES↗

Discriminating Quantum States with Quantum Machine Learning

Quantum machine learning (QML) algorithms have obtained great relevance in the machine learning (ML) field due to the promise of quantum speedups when performing basic linear algebra subroutines (BLAS), a fundamental element in most ML algorithms. By making use of BLAS operations, we propose, implement and analyze a quantum k-means (qk-means) algorithm with a low time complexity of O(NKlog(D)I/C) to apply it to the fundamental problem of discriminating quantum states at readout. Discriminating quantum states allows the identification of quantum states |0⟩ and |1⟩ from low-level in-phase and quadrature signal (IQ) data, and can be done using custom ML models. In order to reduce dependency on a classical computer, we use the qk-means to perform state discrimination on the IBMQ Bogota device and managed to find assignment fidelities of up to 98.7% that were only marginally lower than that of the k-means algorithm. We also performed a cross-talk benchmark on the quantum device by applying both algorithms to perform state discrimination on a combination of quantum states and using Pearson Correlation coefficients and assignment fidelities of discrimination results to conclude on the presence of cross-talk on qubits. Evidence shows cross-talk in the (1, 2) and (2, 3) neighboring qubit couples for the analyzed device.

Quiroga, David↗

A proximity-focusing RICH detector for the ePIC Experiment at the EIC

The Electron-Proton/Ion Collider Experiment (ePIC) will be a large, multi-purpose detector to be installed at the Electron-Ion Collider (EIC) being built at Brookhaven National Laboratory. As robust particle identification (PID) capabilities are essential for fully realizing the EIC science program, ePIC contains several PID subsystems spanning different angular ranges. PID capability in the electron-going endcap is provided by a proximity-focusing Ring Imaging Cherenkov detector (pfRICH) designed to deliver at least 3σ separation between pions and kaons for momenta up to 7 GeV/ c . It will also aid with electron-hadron discrimination at low momentum and assist in the determination of the collision time (t 0 ). This contribution will summarize the design of the pfRICH as well as ongoing fabrication and component testing efforts. geant-based performance simulations will also be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advances in Autoradiography Systems for Nuclear Forensic Analysis

Nuclear forensic analysis techniques work to determine the contents of radiological samples with nondestructive and destructive analysis methods. Autoradiography is a nondestructive analysis method that creates an image of the distribution of radioactivity within the sample. These images allow the location of the radiological content within a sample to be ascertained, which can be used for further analysis. Autoradiography has been used since the discovery of radiation and has been continuously developed to better suit the needs of the medical, nuclear security, nuclear safeguards, and nuclear forensic communities. Recent developments in autoradiography have led to a higher spatial resolution down to a level of tens of microns, real-time capabilities that minimize the risk of overexposure, and the ability to discriminate particles. All of these developments in autoradiography would assist the nuclear forensics community in understanding the placement of radiological content within a sample and in understanding the locations of beta-particle interactions versus those for alpha-particle interactions. This article aims to discuss the history of autoradiography as well as multiple different autoradiographic technologies while focusing on imaging plates, the BeaQuant system, and the ionizing-radiation Quantum Imaging Detector system. This article reviews three autoradiographic techniques and detectors, discusses how they relate to nuclear forensics, and addresses the drawbacks and benefits of each detector.

Autoradiography↗

Characterization of the ORNL SiPM PSD ASIC's Basic Properties

ORNL has developed an ASIC intended for reading out arrays of Silicon Photomultipliers coupled to scintillator materials that exhibit neutron/gamma pulse shape discrimination. The ASIC's basic properties: power consumption, linearity, PSD FoM, and timing resolution have all been measured and the results are presented here.

47 OTHER INSTRUMENTATION↗

Characterization of Neutron Emission Rates of Commercial 252 Cf Sources

Accurate knowledge of 252 Cf neutron emission rates is critical for modeling and fast-neutron experiments, yet commercial sources are often supplied without traceable calibration or uncertainty estimates. This report describes a method to characterize 252 Cf sources using a pulse-shape-discrimination (PSD) scintillator. The scintillator was efficiency-calibrated against a time-tagged 252 Cf fission chamber manufactured at ORNL over 40 years ago. Isotopic evolution of the calibration source was modeled using Bateman equations to account for changes in the effective average neutrons per fission at the time of measurement. The calibrated scintillator was then used to measure absolute emission rates of several commercial 252 Cf sources, revealing deviations of up to 12% from nominal manufacturer values. This methodology provides a practical approach for establishing uncertainty-quantified 252 Cf neutron emission rates, improving fidelity in simulations and supporting the accurate interpretation of measurements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Identifying neutron sources using recoil and time-of-flight spectroscopy

Identification of neutron sources is central to nuclear physics and its applications, from planetary science to nuclear security, yet direct source discrimination from measured neutron spectra remains fundamentally elusive. Here, we introduce a Bayesian protocol that directly infers source ensembles from measured neutron spectra by combining full-spectrum template matching with probabilistic evidence evaluation. Applying this protocol to recoil and time-of-flight spectroscopy, we recover single- and two-source configurations with strong statistical significance (beyond 4⁢𝜎) at event counts as low as ∼10 3 . These results demonstrate that neutron spectral signatures can be leveraged for robust source identification, opening a new observational window for both fundamental research and operationally driven applications.

neutron physics↗

Characterization of EJ-270 and Ce-doped LiCAF scintillators for the development of high-rate neutron reflectometer detectors

The Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory is anticipated to provide a neutron source with ∼20 times increase in peak brightness than the First Target Station. The neutron reflectometers currently in operation at the First Target Station need to be upgraded due to the increased neutron flux. A prototype neutron detector module based upon a pixelated scintillator array readout by silicon photomultipliers is being developed to address the high-rate challenge faced with future neutron reflectometer instruments at the Second Target Station. Two types of scintillator materials were considered for this detector development, i.e., 6 Li-loaded EJ-270 plastic scintillator and Ce-doped LiCAF single crystal. This paper reports the scintillator characterization results, including light yield, pulse shape discrimination performance, capability to detect thermal neutrons in a high γ-ray field, and γ-ray sensitivity. The number of photons produced per neutron capture by EJ-270 and LiCAF:Ce was measured to be 2176 ± 91 and 2651 ± 108, respectively. EJ-270 demonstrated a good capability to discriminate between neutrons and γ-rays by employing the commonly used charge comparison method (figure-of-merit: 1.13 ± 0.01 for an energy cut of 292–426 keVee) and a reasonable performance when using the time-over-threshold techniques; however, no discrimination was observed from LiCAF:Ce regardless of the pulse shape discrimination approaches utilized, making pulse height discrimination necessary for LiCAF:Ce to differentiate between neutrons and γ-rays. Both EJ-270 and LiCAF:Ce exhibited an acceptable capacity to detect thermal neutrons at high exposure rates up to approximately 584 mR/h. Furthermore, the γ-ray sensitivities measured with a 60 Co source at an exposure rate of around 1145 mR/h were determined to be (6.11 ± 0.87) × 10 −6 and (7.64 ± 1.08) × 10 −7 for EJ-270 and LiCAF:Ce, respectively.

EJ-270↗

Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models

Well-log interpretation estimates in situ rock properties along well trajectory, such as porosity, water saturation, and permeability, to support reserve-volume estimation, production forecasts, and decision making in reservoir development. However, due to measurement errors, variability of well logs caused by multiple measurement vendors, different borehole tools, and nonuniform drilling/borehole conditions, estimations of rock properties with original well logs without proper preprocessing may not be accurate, especially in the context of multiwell estimation. Well-log normalization techniques such as two-point scaling and mean-variance normalization are commonly used to improve the robustness of multiwell rock-property estimation. However, these techniques do not consider the correlation between well logs and require subjective knowledge for their effective implementation. To reduce uncertainties and processing time associated with multiwell rock-property estimation from well logs, we develop discriminative adversarial (DA) and linear constraint models for well-log normalization and rock-property estimation. The DA neural network model developed for well-log normalization and interpretation can perform linear and nonlinear well-log normalization while considering the joint distribution of each well log and rock properties. However, the linear constraint model uses an ensemble of predictions from linear models to constrain well-log normalization and rock-property estimation. We also develop a divergence-based type well identification method to select type (training) wells for a test well based on the statistical similarity of associated well-log distributions instead of the interwell distance. We apply the DA model to perform well-log normalization and prediction of permeability for the Seminole San Andres Unit carbonate reservoir. Compared with the permeability predicted with the classical machine learning model without well-log normalization and models with two-point scaling normalization, the DA model yields the most accurate permeability prediction by decreasing the mean-squared error of permeability prediction by 20%–50%.

Geochemistry & Geophysics↗

Comparison of NMC estimates with trans-stilbene, EJ-309, and He-3 detection systems

Neutron multiplicity counting (NMC) is a technique for the assay of fissile material. In this work, three detection systems are utilized for active interrogation assay of shells of the Rocky Flats shells (highly enriched uranium, 93% 235U) stacked from 13.25-54.92 kg assemblies. The singles ($R_1$) and doubles ($R_2$) rates are calculated with each system to estimate two sample parameters: $M_L$- the leakage multiplication and F - the sample fission rate. The estimated mass, m, is found by dividing F by a constant activity per unit mass. Since we are interrogating HEU, the α ratio of (α; n) to fission neutrons is taken to be zero. The system of equations to calculate these quantities was originally derived. The Neutron Multiplicity 3 He Array Detector (NOMAD) consists of 15 3 He tubes inside polyethylene and is the traditional, capture-based detection system for NMC. The polyethylene moderates incoming neutrons for thermal capture in individual tubes. The low gamma background, discrete capture signals, and high efficiency of the NOMAD are beneficial for NMC. However, the time to slow down neutrons to thermal energies leads to a system die away time on the scale of microseconds. Comparatively, the Rossi-alpha Measurements – Rapid Organic (n, γ) Discrimination Detector (RAMRODD) and the Organic Scintillator Array (OSCAR) are scatter-based detection systems. RAMRODD consists of 8, 5.08 by 5.08 cm EJ-309 liquid scintillators in 4 pairs, evenly-spaced with 90 degrees separation about the center of each assembly. OSCAR consists of a single array of 12, 5.08 by 5.08 cm trans-stilbene crystals aligned with the center of the assembly. Scatter-based systems detect fast neutrons without any moderation, leading to system die away times on the scale of tens of nanoseconds. This allows much shorter timing gate widths compared to thermal systems, thus increasing counting statistics of true correlated fission events. However, scatter-based systems are susceptible to neutron cross-talk when an incident neutron scatters off one detector and interacts in an adjacent detector, causing two seemingly correlated detection signals. The equations developed adjust for cross-talk to conduct NMC with scatter-based systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Emission phases of implosion sources for x-ray absorption fine structure spectroscopy

At the Laboratory for Laser Energetics' Omega Laser Facility, thin plastic shells were directly driven with ∼20 kJ resulting in a time-integrated x-ray yield of ∼1012 ph/eV/sr at 7 keV. Using temporally, spatially, and spectrally discriminating diagnostics, three x-ray emission phases were identified: corona emission produced by the laser ablation of the shell, core stagnation, and afterglow emission due to the expanding hot material after stagnation. The newly measured corona and afterglow emission phases account for ∼25% of the total x-ray signal and produce x-ray emission at a different time or larger radius than previously considered. The resulting implications of this additional emission for x-ray absorption fine structure spectroscopy are discussed. Finally, improvements to the laser drive intensity and uniformity produced a factor-of-2 increase in total x-ray emission while decreasing the size of the stagnated core.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗