Cosmology from HSC Y1 weak lensing data with combined higher-order statistics and simulation-based inference
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Novaes, Camila P. (ORCID:0000000258453649)↗
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Results for “DISTRIBUTION FUNCTION”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Selective single-atom adsorption for precision separation of lead ions in tap water via capacitive deionization
Capacitive deionization (CDI) offers a cost-effective and low-energy method for selective removal of Pb 2+ from drinking water. Modifying CDI electrode surfaces with functional groups presents a versatile approach to enhancing selective ion adsorption capacity. However, a comprehensive understanding of the selectivity and removal efficiency of Pb 2+ among diverse functional groups remains unexplored. Here, we investigated the effects of different functional groups (-SH, -COOH, and -NH 2 ) attached to the graphene oxide (GO) electrode surfaces on Pb 2+ selectivity and removal efficiency. Surprisingly, GO-COOH demonstrated single-atom adsorption of Pb 2+ , displaying superior removal efficiency and selectivity compared with -SH and -NH 2 , although -SH possesses significant chelation capability for Pb 2+ . Both density functional theory (DFT) calculations and X-ray pair distribution function (PDF) analyses confirmed that Pb 2+ exhibits a theoretically higher affinity to -COOH. Further, this research deepens our understanding of the interactions between functional groups and heavy metal ions, enabling selective and rapid separation of target cations for water purification.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Wavelength modulation laser-induced fluorescence for plasma characterization
Laser-Induced Fluorescence (LIF) spectroscopy is an essential tool for probing ion and atom velocity distribution functions (VDFs) in complex plasmas. VDFs carry information about the kinetic properties of species that is critical for plasma characterization. Accurate interpretation of these functions is challenging due to factors such as multicomponent distributions, broadening effects, and background emissions. Our research investigates the use of Wavelength Modulation (WM) LIF to enhance the sensitivity of VDF measurements. Unlike standard Amplitude Modulation (AM) methods, WM–LIF measures the derivative of the LIF signal. This approach makes variations in VDF shape more pronounced. VDF measurements with WM–LIF were investigated with both numerical modeling and experimental measurements. The developed model enables the generation of both WM and AM signals, facilitating comparative analysis of fitting outcomes. Experiments were conducted in a weakly collisional argon plasma with magnetized electrons and non-magnetized ions. Measurements of the argon ion VDFs employed a narrow-band tunable diode laser, which scanned the 4p 4 D 7/2 –3d 4 F 9/2 transition centered at 664.553 nm in vacuum. A lock-in amplifier detected the second harmonic WM signal, which was generated by modulating the laser wavelength with an externally controlled piezo-driven mirror of the diode laser. Finally, our findings indicate that the WM–LIF signal is more sensitive to fitting parameters, allowing for better identification of VDF parameters such as the number of distribution components, their temperatures, and velocities. In addition, WM–LIF can serve as an independent method to verify AM measurements and is particularly beneficial in environments with substantial light noise or background emissions, such as those involving thermionic cathodes and reflective surfaces.
47 OTHER INSTRUMENTATION↗
Statistical estimates of the binary properties of rotational variables
ABSTRACT We present a model to estimate the average primary masses, companion mass ranges, the inclination limit for recognizing a rotational variable, and the primary mass spreads for populations of binary stars. The model fits a population’s binary mass function distribution and allows for a probability that some mass functions are incorrectly estimated. Using tests with synthetic data, we assess the model’s sensitivity to each parameter, finding that we are most sensitive to the average primary mass and the minimum companion mass, with less sensitivity to the inclination limit and little to no sensitivity to the primary mass spread. We apply the model to five populations of binary spotted rotational variables identified in ASAS-SN, computing their binary mass functions using RV data from APOGEE. Their average primary mass estimates are consistent with our expectations based on their CMD locations ($\sim 0.75 \, {\rm M}_{\odot }$ for lower main sequence primaries and $\sim 0.9$–$1.2 \, {\rm M}_{\odot }$ for RS CVn and sub-subgiants). Their companion mass range estimates allow companion masses down to $M_2/M_1\simeq 0.1$, although the main sequence population may have a higher minimum mass fraction ($\sim 0.4$). We see weak evidence of an inclination limit $\gtrsim 50^{\circ }$ for the main sequence and sub-subgiant groups and no evidence of an inclination limit in the other groups. No groups show strong evidence for a preferred primary mass spread. We conclude by demonstrating that the approach will provide significantly better estimates of the primary mass and the minimum mass ratio and reasonable sensitivity to the inclination limit with 10 times as many systems.
Phillips, Anya (ORCID:000900051914974X)↗
Tomography of Atomic Nuclei
We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to $^{16}$O. These distributions provide a form of quantum tomography of the spatial and momentum structure of the system. They also help identify the location of high-momentum regions in atomic nuclei and provide insight into the onset of alpha clustering. Besides their intrinsic interest, these distributions will be useful for neutrino event generators, as they correlate the positions and momenta of nucleons in the initial target state. To facilitate their application, we address the need to store them compactly by developing an accurate Gaussian Process emulator that automatically preserves their normalization.
Rocco, Noemi [Valencia U., IFIC; Fermilab]↗
An update to the Sandia method for creating Typical Meteorological Years from a limited pool of calendar years
Typical Meteorological Years (TMYs) are essential for the efficient evaluation of energy system performance. Ideally, 30 years of weather data are required to generate TMYs, but significantly fewer years are typically available due to practical limitations. To address this issue, an update to the Sandia method was developed, referred to as the Argonne method, to create TMYs from a limited number of years. Furthermore, this method enhances candidate diversity by systematically shifting original candidate months forward or backward by specific days, creating an expanded pool of candidates. The effectiveness of the Argonne method was validated through statistical testing, comparison of monthly average weather parameters, and numerical simulations. The results demonstrate a high probability of identifying at least one shifted month whose cumulative distribution functions of weather parameters closely align with long-term distributions. In 67 % of all comparisons, the monthly average weather parameters in TMYs generated using the Argonne method exhibit better agreement with long-term averages than TMY3. Moreover, in 74 % of the 318 building simulation cases, the Argonne method outperforms TMY3 in estimating long-term average building heating and cooling demands. Therefore, the Argonne method effectively diversifies the candidate pool and produces typical years that provide more accurate estimations of long-term averages compared to TMY3 when only a limited pool of calendar years (10 years or fewer) is available.
Building energy modeling↗
Transverse single-spin asymmetries in $γ$ SIDIS as a direct probe of quark-gluon-quark longitudinal momentum structure
Transverse single-spin asymmetries in the semi-inclusive deep-inelastic production of isolated photons ($\gamma$SIDIS), $A_{UT}^{\gamma {\rm SIDIS}}$, provide an unprecedented opportunity to extract the quark-gluon-quark correlators $F_{FT}(x,x')$ and $G_{FT}(x,x')$ point-by-point in their full support $x,x'$. We utilize realistic models for these functions, based on input from the Sivers transverse momentum dependent parton distribution function and imposing constraints from the $d_2$ matrix element calculated in lattice QCD, in order to provide numerical estimates for $A_{UT}^{\gamma {\rm SIDIS}}$ at the Electron-Ion Collider (EIC). We thoroughly explore the EIC phase space in order to isolate in which regions the asymmetry can be sizable, finding it can be as much as $10\%$ or larger for certain kinematics. Given that $F_{FT}(x,x')$ and $G_{FT}(x,x')$ are basically unknown, $A_{UT}^{\gamma {\rm SIDIS}}$ will be an important future measurement to learn about multi-parton correlations in the nucleon.
Electron-Ion Collider↗
Complexity in the medium-range order of gallium as a polyvalent liquid metal
Simplicity in chemical composition does not always translate into simplicity in the structures and dynamics of liquids and solids. Some elementary liquid metals, such as gallium, show unusual behaviors in thermodynamic and transport properties as a result of their complex atomic structure and dynamics. Here, in this work, we study the real-space atomic correlation function of liquid gallium by neutron scattering. In the pair-distribution function, there exist two kinds of medium-range order (MRO), characterized by oscillations beyond the first nearest neighbors. On the other hand, the first neighbor shell shows only one kind of bond. The two types of MRO are strongly overlapping in space and fluctuating in time. We propose that they are the basis for anomalous behavior of liquid gallium. This view challenges the current view that liquid gallium consists of fluctuating metallic and insulating domains. These findings shed light on the interpretation of similar microscopic anomalies observed in other semimetallic liquids.
Hua, Chengyun [Oak Ridge National Laboratory (ORNL↗
Characterization and Optimization of the Fitting of Quantum Correlation Functions
This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.
Chuang, Pi-Yueh [Virginia Tech,Dept. of Computer S↗
BCS-BEC crossover of the strongly interacting 6 Li − 40 K mixture
Here, we present quantum Monte Carlo calculations of the properties of a two-component mass-imbalanced Fermi gas, corresponding to the 6 Li − 40 K mixture. We compute the equation of state of the unpolarized system as a function of the scattering length with particular attention paid to the unitary limit, where the effect of the effective range of the interaction is explored. In order to investigate differences from the equal-mass case we also compute the pair-distribution function and the momentum distribution over a range of interaction strengths, which can provide information about the structure of the system. Finally, we compute the heavy-light quasiparticle spectrum for the full crossover regime. Our theoretical predictions, based on quantum Monte Carlo calculations, should inform future theoretical studies and can be tested by experiments with ultracold fermionic gases.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Collins-Soper kernel and reduced soft function in lattice QCD
We evaluate the Collins-Soper kernel and the reduced soft function in lattice QCD, incorporating 𝒪(𝛼 𝑠 ) matching corrections. The calculation relies on the evaluation of the quasitransverse momentum–dependent wave function with asymmetric staple-shaped quark bilinear operators and four-point meson form factors. These quantities are computed nonperturbatively using two 𝑁 𝑓 =2 + 1 + 1 twisted-mass fermion ensembles with the same lattice spacing of 𝑎 = 0.093 fm: the first ensemble has a lattice size of 24 3 × 48 and a pion mass of 346 MeV, and the second one has a lattice size of 32 3 × 64 and a pion mass of 261 MeV. The Collins-Soper kernel and the soft function are needed for the determination of the transverse momentum–dependent parton distribution functions.
Lattice QCD↗
Off-shell pion properties: Electromagnetic form factors and light-front wave functions
The off-shell pion electromagnetic form factors are explored with corresponding off-shell light-front wave functions modeled by constituent quark and antiquark. We apply the Mandelstam approach for the microscopic computation of the form factors relating the model parameters with the pion decay constant and charge radius. Analyzing the existing data on the cross sections for the Sullivan process, 1 H(e,e',π + )n, Charged pion form factor between Q 2 = 0.60, and 2.45 GeV 2 . I. Measurements of the cross section for the 1 H(e,e'π + )n reaction, we extract the off-shell pion form factor using the relation derived from the generalized Ward-Takahashi identity for the pion electromagnetic current. They are compared with our previous results from exactly solvable manifestly covariant model of a (3+1)-dimensional fermion field theory. We find that the adopted constituent quark model reproduces the extracted off-shell form factor F 1 (Q 2 ,t) from the experimental data within a few percent difference and matches well with our previous theoretical simulation which exhibits a variation of about 10% for the extracted off-shell pion form factor g(Q 2 ,t). We also identify the pion valence parton distribution function (PDF) and transverse momentum distribution (TMD) in terms of the light-front wave function and discuss their off-shell properties.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Measurement of the Drell–Yan forward-backward asymmetry and of the effective leptonic weak mixing angle in proton-proton collisions at $\sqrt{s}$ 13 TeV
The forward-backward asymmetry in Drell-Yan production and the effective leptonic electroweak mixing angle are measured in proton-proton collisions at $\sqrt{s}$ = 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb$^{-1}$. The measurement uses both dimuon and dielectron events, and is performed as a function of the dilepton mass and rapidity. The unfolded angular coefficient $A_4$ is also extracted, as a function of the dilepton mass and rapidity. Using the CT18Z set of parton distribution functions, we obtain $\sin^{2}\theta^\ell_\text{eff}$ = 0.23152 $\pm$ 0.00031, where the uncertainty includes the experimental and theoretical contributions. The measured value agrees with the standard model fit result to global experimental data. This is the most precise $\sin^{2}\theta^\ell_\text{eff}$ measurement at a hadron collider, with a precision comparable to the results obtained at LEP and SLD.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A generative artificial intelligence framework for long-time plasma turbulence simulations
Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.
Artificial intelligence↗
Representing Complex Systems as Graphs for Debugging and Predictive Maintenance-Preliminary Thoughts
Representing complex systems as graphs enables use of mathematical tools to identify faults or predict failures. Graph nodes correspond to individual modules or subsystems, and edges link coupled system parts. ‘Probes’ measure the node outputs, monitoring the system health for unexpected behavior. Assuming one cannot probe every point, within a system, the fault correlates to a region—not necessarily the specific location. Bayesian networks trained to understand fault patterns can accurately identify the source. The diagnostic tool described aides debugging by pinpointing system failure causes. For predictive maintenance, probe data develop probability distribution functions describing subsystem mean time to failure. Unit lifetime can be estimated through these probability distributions. Two approaches include using Bayesian classifiers to infer the system failure source and developing maintenance schedules by treating systems as collections of random variables. When failure behavior does not follow a closed form function, use of similarity models is proposed.
97 MATHEMATICS AND COMPUTING↗
Task Sharing of Proton Incorporation in Vertically Aligned Nanocomposite Triple Conductors: Growth, Structure, and Surface Exchange Kinetics
As protonic ceramic electrolysis cells emerge for efficient H 2 production, there is a need to develop air electrode materials enabling fast, durable steam splitting and proton incorporation. Single-phase triple conductors may fail to satisfy the myriad performance/stability requirements, and their critical charge-carriers (holes, oxygen vacancies, and protons) are in competition, limiting their concentrations. Instead, we propose task-sharing, vertically aligned nanocomposites (VANs), comprising a proton conductor (BaZr 0.9 Y 0.1 O 3-δ ) and a redox-active mixed ionic electronic conductor (Ce 0.9 Pr 0.1 O 2-δ ), that may enable rapid proton surface exchange at the solid–gas interface and transport along the solid–solid heterointerfaces. We grew VANs by pulsed laser deposition and investigated the interplay between their processing conditions, structure, and proton and oxygen surface exchange kinetics. We varied the substrate temperature, laser repetition rate, laser fluence, and processing oxygen pressure. The crystallinity and phases were characterized by grazing-incidence X-ray diffraction, and the strain and structural order as a function of depth were evaluated by angle-dependent synchrotron X-ray pair distribution function analysis. To evaluate the potential for interdiffusion, the formation energies of substitutional defects were simulated with density functional theory. Corresponding structural analysis and elemental mapping were performed by scanning/transmission electron microscopy, energy-dispersive X-ray spectroscopy, and electron energy-loss spectroscopy, indicating distinct nanoscale compositional regions with a hierarchical structure embedded in individual VANs columns and minimal interdiffusion across a bilayer film. Proton and oxygen surface exchange coefficients (k H , k O ) and polarization resistances were evaluated by electrical and optical relaxations and impedance spectroscopy of VAN-incorporated protonic ceramic electrochemical cells, respectively, at 400–500 °C, demonstrating values comparable to some of the best-known triple and mixed conductors.
36 MATERIALS SCIENCE↗
Resolving length-scale-dependent transient disorder through an ultrafast phase transition
Abstract Material functionality can be strongly determined by structure extending only over nanoscale distances. The pair distribution function presents an opportunity for structural studies beyond idealized crystal models and to investigate structure over varying length scales. Applying this method with ultrafast time resolution has the potential to similarly disrupt the study of structural dynamics and phase transitions. Here we demonstrate such a measurement of CuIr 2 S 4 optically pumped from its low-temperature Ir-dimerized phase. Dimers are optically suppressed without spatial correlation, generating a structure whose level of disorder strongly depends on the length scale. The redevelopment of structural ordering over tens of picoseconds is directly tracked over both space and time as a transient state is approached. This measurement demonstrates the crucial role of local structure and disorder in non-equilibrium processes as well as the feasibility of accessing this information with state-of-the-art XFEL facilities.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Impact of LHC precision measurements of inclusive jet and dijet production on the CTEQ-TEA global PDF fit
In this study, we investigate the impact of new Large Hadron Collider (LHC) inclusive jet and dijet measurements on parton distribution functions (PDFs) that describe the proton structure, with a particular focus on the gluon distribution at large momentum fraction, x , and the corresponding partonic luminosities. We assess constraints from these datasets using next-to-next-to-leading-order (NNLO) theoretical predictions, accounting for a range of uncertainties from scale dependence and numerical integration. From the scale choices available for the calculations, our analysis shows that the central predictions for inclusive jet production show a smaller scale dependence than dijet production. We examine the relative constraints on the gluon distribution provided by the inclusive jet and dijet distributions, and also explore the phenomenological implications for inclusive H , t t ¯ , and t t ¯ H production at the LHC at 14 TeV. Published by the American Physical Society 2025
Ablat, Alim (ORCID:0009000519877755)↗