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At least 181 records · Page 10

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)↗

Nucleon momentum fraction, helicity and transversity from 2+1-flavor lattice QCD

A detailed analysis of the systematic uncertainties in the calculation of the isovector momentum fraction, ( x ) u - d , helicity moment, ( x ) Δ u - Δ d , and the transversity moment, ( x ) δu - δd , of the nucleon is presented using high-statistics data on seven ensembles of gauge configurations generated by the JLab/W&M/LANL/MIT collaborations using 2 + 1-flavors of dynamical Wilson-clover quarks. The much higher statistics have facilitated better control over all systematics compared to previous lattice calculations. The least understood systematic — excited-state contamination — is quantified by studying the variation of the results as a function of different estimates of the mass gap of the first excited state, obtained from two- and three-point correlation functions, and as a function of the pion mass M π . The final results are obtained using a simultaneous fit in the lattice spacing a , pion mass M π and the finite volume parameter M π L keeping leading order corrections. The data show no significant dependence on the lattice spacing and some evidence for finite-volume corrections. Our final results, in the $ \overline{\mathrm{MS}} $ scheme at 2 GeV, are ( x ) u - d = 0 . 155(17)(20), ( x ) Δ u - Δ d = 0 . 183(14)(20) and ( x ) δu - δd = 0 . 220(18)(20), where the first error is the overall analysis uncertainty assuming excited-state contributions have been removed, and the second is an additional systematic uncertainty due to possible residual excited-state contributions. These results are consistent with phenomenological global fit values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transforming a Simple Structure Model to Represent a Complex Dynamic System with Unknown Boundary Restraints

Imposing a boundary condition on a structure can significantly alter its dynamic properties. However, sometimes the specifics of the new boundary conditions are not known. When the effects of a boundary condition are uncertain or there is not enough information, engineers need to excite the complex structure to obtain these modified properties. In order to experimentally obtain the new properties, engineers need multiple experiments and many outputs for interpolation in order to sufficiently represent the entire structure. In this study, the researchers attached a stinger to a cantilever beam, acting as a new transverse restraint of unknown properties. This paper presents a conversion expression that predicts the dynamic behavior of any point in the system with the new boundary condition. This expression relies only on one impact hammer experiment with one output and the model of the stinger-free cantilever beam, referred to as the simple structure. Researchers estimated the Transfer Function (TRF) of the beam and compared it with an experimentally measured TRF to validate the method. The mean absolute error of the estimated TRF compared to the experimental TRF is 1.99 dB. This demonstrates the use of the proposed method for estimating unmeasured TRFs in a system with an uncertain boundary condition using a single input, single output (SISO) test and a model of the simple structure.

42 ENGINEERING↗

Bootstrapping the 3d Ising model at finite temperature

We estimate thermal one-point functions in the 3d Ising CFT using the operator product expansion (OPE) and the Kubo-Martin-Schwinger (KMS) condition. Several operator dimensions and OPE coefficients of the theory are known from the numerical bootstrap for flat-space four-point functions. Taking this data as input, we use a thermal Lorentzian inversion formula to compute thermal one-point coefficients of the first few Regge trajectories in terms of a small number of unknown parameters. We approximately determine the unknown parameters by imposing the KMS condition on the two-point functions (σσ) and (ϵϵ). As a result, we estimate the one-point functions of the lowest-dimension $\mathbb{Z}_2$-even scalar ϵ and the stress energy tensor T μν . Our result for (σσ) at finite-temperature agrees with Monte-Carlo simulations within a few percent, inside the radius of convergence of the OPE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Heisenberg-scaling measurement protocol for analytic functions with quantum sensor networks

Here we generalize past work on quantum sensor networks to show that, for d input parameters, entanglement can yield a factor O(d) improvement in mean-squared error when estimating an analytic function of these parameters. We show that the protocol is optimal for qubit sensors, and we conjecture an optimal protocol for photons passing through interferometers. Our protocol is also applicable to continuous variable measurements, such as one quadrature of a field operator. We outline a few potential applications, including calibration of laser operations in trapped ion quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electronic structure and exchange interactions in altermagnetic MnGeP 2 in the quasiparticle self-consistent G W approach

The quasiparticle self-consistent 𝐺⁡𝑊 method is used to study the electronic band structure, optical dielectric function, and exchange interactions in chalcopyrite, 𝐼⁢ ‾ 4 ⁢2⁢𝑑, structure MnGeP 2 . The material is found to be an antiferromagnetic semiconductor with a lowest direct gap of 2.44 eV at the Γ point and a lower indirect gap of 1.87 eV from Γ to 𝑀. The material is an altermagnet because the two magnetic atoms of opposite spin are related by a twofold rotation operation perpendicular to the main fourfold rotation inversion axis. The spin splittings along a low symmetry line like 𝑃⁢𝑁 is sizable while at k points on the diagonal mirror planes or on the twofold symmetry axes the spin splitting is zero. The exchange interactions are calculated using a linear response approach. The antiferromagnetic exchange interaction between nearest neighbors in the primitive unit cell is dominating and found to be slightly decreasing upon carrier doping but not sufficiently to change the interaction to become ferromagnetic. The bare (noninteracting) and interacting transverse spin susceptibilities, which provide interatomic site exchange interactions after averaging over the muffin-tin spheres, are calculated from the 𝐺⁡𝑊 band structure and wave functions. From these exchange interactions, the spin wave spectra are obtained along the high symmetry lines and the Néel temperature is calculated using the mean-field and Tyablikov estimations. The dielectric function and the optical absorption spectra are calculated including excitonic effects using the Bethe Salpeter equation. The exchange interactions around Mn Ge defect sites is also studied. While we find it can generate ferromagnetic interactions with neighboring spins, we did not find direct evidence of producing an overall ferromagnetic phase. First, if Mn antisites are introduced by exchanging Mn with a nearby Ge, the interactions stay largely antiferromagnetic. Second, when we add additional Mn, in other words in Mn-rich stoichiometry, the Mn Ge antisites produce a strong ferromagnetic interaction primarily with the Mn in the same basal plane but weaker ferromagnetic interaction with adjacent plane Mn. The interactions between regular lattice Mn stay antiferromagnetic as before and thus favor keeping the antiferromagnetic order along the [001] direction. Adding Mn antisites, however, does lead to a metallic band structure.

36 MATERIALS SCIENCE↗

Anisotropy of the Surface Energy and Work Function of IIB Metals

On the basis of electron-statistical method of calculation of the surface energy of metals, a technique for estimating the electron work function of hexagonal and rhombohedral metallic crystals has been developed. This technique relates surface energy to work function and can thus be applied to estimate the surface energy of crystal faces from experimental data for a work function. Computations have been made for cadmium, zinc, and mercury macrocrystals. The temperature and orientation dependences of both quantities have been constructed. Our results are in good agreement with literature experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Thermosteam: BioSTEAM's Premier Thermodynamic Engine

Thermosteam is a thermodynamic engine capable of solving mass and energy balances, estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. All chemical data in Thermosteam is imported from the chemicals library, an open-source compilation of data and functions for the estimation of pure component chemical and mixture properties. Thermosteam’s fast and flexible platform has enabled the evaluation of conceptual and emerging biochemical production processes. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) — capable of modeling reactors, distillation columns, heat exchangers, and other unit operations — has adopted Thermosteam as its premier thermodynamic engine. Published biorefinery designs modeled in BioSTEAM implement thermodynamic property packages created with Thermosteam, including a cornstover biorefinery for the production of cellulosic ethanol, a lipid-cane biorefinery for the co-production of ethanol and biodiesel, and a wheatstraw biorefinery for the production of cellulosic ethanol.

97 MATHEMATICS AND COMPUTING↗

The Contributions of Shear and Turbulence to Cloud Overlap for Cumulus Clouds

The causes of vertical cloud overlap, the ratio between the cloud fraction by area and the cloud fraction by volume, are studied for fields of cumulus convection. Using large-eddy simulations, the structure of individual clouds within the cloud field is inspected and connected to the overall cloud cover of the entire cloud field. First, it is shown that the cloud overlap of the entire field can be well approximated by the total cloud overlap of the individual clouds. It is then shown that a simple maximum overlap assumption, which is commonly used for cloud fields with small layer depth, can only account for roughly half of the overlap inefficiency. This is due to the fact that maximum overlap only represents variations in cloud width as a function of depth but does not take other factors into account, most notably shear or turbulence. The effects of turbulence and wind shear on the overlap of individual clouds are first estimated as a function of cloud depth, which closes the discrepancy between observed cloud overlap and the maximum overlap assumption. Then, an empirical model is developed for the shear and turbulence contributions on overlap as a function of cloud depth and of synoptic conditions. Finally, it is shown that our model is capable of accurately predicting overlap for a large number of cloud fields and under a variety of meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗

XRISM spectroscopy on orbital modulation of Fe Ly α lines in Cygnus X-3

To understand physical processes such as mass transfer and binary evolution in X-ray binaries, the orbital parameters of the system are fundamental and crucial information. Cygnus X-3 is a high-mass X-ray binary composed of a compact object of unknown nature and a Wolf–Rayet star, which is of great interest in the context of wind-fed mass accretion and binary evolution. Here we present XRISM/Resolve high-resolution spectroscopy, focusing on the Fe Ly$\alpha$ lines when the source was in its hypersoft state. We perform an orbital phase-resolved spectral analysis of the lines to study the orbital modulation of the emission and absorption lines. It is found that the emission lines reflect the orbital motion of the compact object whose estimated velocity amplitude is $430^{+150}_{-140}$ km s$^{-1}$, while the absorption lines show a variation that can be interpreted as originating from the stellar wind. We discuss possible mass ranges for the binary components using the mass function with the estimated value of the velocity amplitude in this work, combined with the relation between the mass-loss rate and the orbital period derivative and the empirical mass and mass-loss rate relation for Galactic Wolf–Rayet stars. They are constrained to be (1.3–5.1) and (9.3–12) M$_\odot$, respectively, for the assumed inclination angle of $i =25^\circ$, and become more relaxed, (1.3–24) and (9.3–16) M$_\odot$, for $i = 35^\circ$. Thus, it remains unclear whether the system harbors a black hole or a neutron star.

X-rays: binaries↗

Cost Analysis and Projections for U.S.-Manufactured Automotive Lithium-ion Batteries

This document reports on a study conducted to estimate the cost of U.S-produced automotive battery packs for model years (MY) 2023 to 2035, using Argonne National Laboratory’s BatPaC tool. The costs were estimated by designing batteries for several classes of vehicles for four discrete model years (2023, 2026, 2030, and 2035), where a representative battery technology and material prices are selected based on information available today. Correlations were developed from the four discrete years to enable annual pack cost estimates as a function of pack size (kWh) and model year. A consolidated cost curve was then developed that includes battery size, technology by model year, and the anticipated sales volumes of each class of vehicles over the years. This cost curve estimates the volume-averaged, U.S.-manufactured battery pack cost of PHEVs and BEVs in the United States to be $\$140$/kWh for the model year 2023, which will reduce to $\$86$/kWh in MY2035. Applying tax credits from section 45X of the Inflation Reduction Act can further reduce the average pack cost to as low as $\$56$/kWh in MY2029. The report also includes several sensitivity studies that investigate the effect of pack production volume, material prices, fast charge requirements, and labor rates.

25 ENERGY STORAGE↗

Compressed Natural Gas Component Leak Frequency Estimation

The frequency of unintended releases in a compressed natural gas system is an important aspect of the system quantitative risk assessment. The frequencies for possible release scenarios, along with engineering models, are utilized to quantify the risks for compressed natural gas facilities. This report documents component leakage frequencies representative of compressed natural gas components that were estimated as a function of the normalized leak size. A Bayesian statistical method was used which results in leak frequency distributions for each component which represent variation and uncertainty in the leak frequency. The analysis shows that there is high uncertainty in the estimated leak frequencies due to sparsity in compressed natural gas data. These leak frequencies may still be useful in compressed natural gas system risk assessments, as long as this high uncertainty is acknowledged and considered appropriately.

03 NATURAL GAS↗

The Initial Mass Function of Low-mass Stars and Brown Dwarfs in the W3 Complex

We have used archival infrared images obtained with the Wide Field Camera 3 on board the Hubble Space Telescope to constrain the initial mass function of low-mass stars and brown dwarfs in the W3 star-forming region. The images cover 438 arcmin{sup 2}, which encompasses the entire complex, and were taken in the filters F110W, F139M, and F160W. We have estimated extinctions for individual sources in these data from their colors and have dereddened their photometry accordingly. By comparing an area of the images that contains the richest concentration of previously identified W3 members to an area that has few members and is dominated by background stars, we have estimated the luminosity function for members of W3 with masses of 0.03–0.4 M {sub ⊙}. That luminosity function closely resembles data in typical nearby star-forming regions that have much smaller stellar populations than W3 ( ≲ 500 versus several thousand objects). Thus, we do not find evidence of significant variations in the initial mass function of low-mass stars and brown dwarfs with star-forming conditions, which is consistent with recent studies of other distant massive star-forming regions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Estimating the Acute Health Impacts of Fire-Originated PM 2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM 2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM 2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM 2.5 . Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

58 GEOSCIENCES↗

Formation energy puzzle in intermetallic alloys: Random phase approximation fails to predict accurate formation energies

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke- Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) meta-GGA. In addition, we utilized two nonlocal DFT functionals, the hybrid HSE06, and the state-of-the-art random phase approximation (RPA). The nonlocal functionals such as HSE06 and RPA yield accurate formation energies of binary alloys with completely-filled d-band metals, where semilocal functionals underperform. The accuracy at the nonlocal functionals is greatly reduced when a partially-filled d-band metal is present in an alloy, while PBE-GGA outperforms in these cases. We show that the accurate prediction of formation energies by any DFT method depends on its ability to predict the accurate electronic properties, e.g., valence d-band contribution to the density of states (DOS). The SCAN meta-GGA often corrects the PBE-DOS, however, it does not provide accurate formation energies compared to PBE. This is assumed to be due to the lack of proper error cancellation that should be expected due to the similar bulk nature of both alloys and their constituents, which may improve with the modification of meta-GGA ingredients. RPA yields too negative formation energies of alloys with partially-filled d-band metals. RPA results can be corrected by restoring the exchange-correlation kernel, thereby improving the short-range electron-electron correlation in metallic densities.

36 MATERIALS SCIENCE↗

Simple and accurate estimation of metal, semiconductor, and insulator work functions

Work-function Φ measures the work needed for an electron to escape a solid. For simple metals, it is almost exclusively the result of the surface dipole created by spill-out of electrons from bulk into the vacuum as shown in the seminal work by Lang and Kohn [Phys. Rev. B 3, 1215 (1971)] using a jellium model. Despite a half century of intense efforts, however, such understanding has not been extended past metals. Here we present a universal model for Φ which contains a previously unrecognized bulk contribution Φ I [Phys. Rev. Lett. 121, 196802 (2018)]. By incorporating Φ I into the jellium model, we find that it dictates the dipole due to charge spill out and provides a description which applies to a wide range of materials, ranging from metals, semiconductors, to insulators.

36 MATERIALS SCIENCE↗