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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Stochastically estimated covariance matrices for independent and cumulative fission yields in the ENDF/B-VIII.0 and JEFF-3.3 evaluations

A Monte-Carlo method for the generation of correlation and covariance matrices for independent and cumulative fission yields has been developed. The method uses a constrained Monte-Carlo resampling structure in order to vary evaluated fission yield libraries in a way that meets basic conservation principles. This results in the generation of correlation/covariance matrices with limited model bias and uncertainty; the matrices are primarily reflective of the evaluated fission yield uncertainties and correlations that arise from the evaluation process. This method has been applied to generate correlation and covariance matrices for all of the fissioning systems of the ENDF/B-VIII.0 and JEFF-3.3 evaluations, marking the first time such matrices have been generated for all of these systems. These covariance matrices have been published online for immediate public use. These correlation and covariance matrices can be used to improve uncertainty estimation in calculations of reactor antineutrino emission rates, decay heat problems, and nuclear forensics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Dust and gas absorption in the high mass X-ray binary IGR J16318-4848

With an absorption column density on the order of 10 24 cm -2 , IGR J16318-4848 is one of the most extreme cases of a highly obscured high mass X-ray binary. In addition to the overall continuum absorption, the source spectrum exhibits a strong iron and nickel fluorescence line complex at 6.4 keV. Previous empirical modeling of these features and comparison with radiative transfer simulations raised questions about the structure and covering fraction of the absorber and the profile of the fluorescence lines. We aim at a self-consistent description of the continuum absorption, the absorption edges, and the fluorescence lines to constrain the properties of the absorbing material, such as ionization structure and geometry. We further investigate the effects of dust absorption on the observed spectra and the possibility of fluorescence emission from dust grains. We used XMM-Newton and NuSTAR spectra to first empirically constrain the incident continuum and fluorescence lines. Next we used XSTAR to construct a customized photoionization model where we vary the ionization parameter, column density, and covering fraction. In the third step we modeled the absorption and fluorescence in a dusty olivine absorber and employed both a simple analytical model for the fluorescence line emission and a Monte Carlo simulation of radiative transfer that generates line fluxes, which are very close to the observational data. Our empirical spectral modeling is in agreement with previous works. Our second model, the single gas absorber does not describe the observational data. In particular, irrespective of the ionization state or column density of the absorber, a much higher covering fraction than previously estimated is needed to produce the strong fluorescence lines and the large continuum absorption. A dusty, spherical absorber (modeled as consisting of olivine dust, although the nature of dust cannot be constrained) is able to produce the observed continuum absorption and edges. A dense, dusty absorber in the direct vicinity of the source consisting of dust offers a consistent description of both the strong continuum absorption and the strong emission features in the X-ray spectrum of IGR J16318-4848. In particular, for low optical depth of individual grains, which is the case for typical volume densities and grain size distribution models, the dust will contribute significantly to the fluorescence emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Towards constraining cosmological parameters with SPT-3G observations of 25% of the sky

The South Pole Telescope (SPT), using its third-generation camera, SPT-3G, is conducting observations of the cosmic microwave background (CMB) in temperature and polarization across approximately 10 000 deg$^2$ of the sky at 95, 150, and 220 GHz. This comprehensive dataset should yield stringent constraints on cosmological parameters. In this work, we explore its potential to address the Hubble tension by forecasting constraints from temperature, polarization, and CMB lensing on early dark energy (EDE) and the variation in electron mass in spatially flat and curved universes. For this purpose, we investigate first whether analyzing the distinct SPT-3G observation fields independently, as opposed to as a single, unified region, results in a loss of information relevant to cosmological parameter estimation. We develop a realistic temperature and polarization likelihood pipeline capable of analyzing these fields in these two ways, and subsequently forecast constraints on cosmological parameters. Our findings indicate that any loss of constraining power from analyzing the fields separately is primarily concentrated at low multipoles ($\ell$ < 50) and the overall impact on the relative uncertainty on standard $Λ$ cold dark matter parameters is minimal (< 3%). Our forecasts suggest that SPT-3G data should improve by more than a factor of 90 and 190 the figure of merit of the EDE and the varying electron mass models, respectively, when combined with Planck data. The likelihood pipeline developed and used in this work is made publicly available online.

Vitrier, A. [Paris, Inst. Astrophys.]↗
DOE OSTI2026

Toward real-time optimization through model reduction and model discrepancy sensitivities

Optimization problems arise in a range of scenarios, from optimal control to model parameter estimation. In many applications, such as the development of digital twins, it is essential to solve these optimization problems within wall-clock-time limitations. However, this is often unattainable for complex systems, such as those modeled by nonlinear partial differential equations. One strategy for mitigating this issue is to construct a reduced-order model (ROM) that enables more rapid optimization. In particular, the use of nonintrusive ROMs—those that do not require access to the full-order model at evaluation time—is popular because they facilitate the computation of optimization solutions within the wall-clock time requirements. However, the optimization solution will be unreliable if the iterates move outside the ROM training data. This article proposes the use of hyper-differential sensitivity analysis with respect to model discrepancy (HDSA-MD) as a computationally efficient tool to augment ROM-constrained optimization and improve its reliability. The proposed approach consists of two phases: (i) an offline phase where several full-order model evaluations are computed to train the ROM, and (ii) an online phase where a ROM-constrained optimization problem is solved, a limited number of full-order model evaluations are computed, and HDSA-MD is used to enhance the optimization solution. Numerical results are demonstrated for two examples, atmospheric contaminant control and wildfire ignition location estimation, in which a ROM is trained offline using inaccurate atmospheric data. In conclusion, the HDSA-MD update yields a significant improvement in the ROM-constrained optimization solution using only one full-order model evaluation online with corrected atmospheric data.

PDE-constrained optimization↗
DOE OSTI2025

The Cosmic Evolution of C IV Absorbers at 1.4 < z < 4.5: Insights from 100,000 Systems in DESI Quasars

We present the largest catalog to date of triply ionized carbon (C IV ) absorbers detected in quasar spectra from the Dark Energy Spectroscopic Instrument. Using an automated matched-kernel convolution method with adaptive signal-to-noise thresholds, we identify 101,487 C IV systems in the redshift range 1.4 < z < 4.5 from 300,637 quasar spectra. Completeness is estimated via Monte Carlo simulations, and the catalog is 50% complete at EW C IV ≥ 0.4 Å. The differential equivalent width frequency distribution declines exponentially and shows weak redshift evolution. The absorber incidence per unit comoving path increases by a factor of 2–5 from z ≈ 4.5 to z ≈ 1.4, with stronger redshift evolution for strong systems. Using column densities derived from the apparent optical depth method, we constrain the cosmic mass density of C IV , Ω C IV , which increases by a factor of ∼3.8 from (0.82 ± 0.05) × 10 −8 at z ≈ 4.5 to (3.16 ± 0.2) × 10 −8 at z ≈ 1.4. From Ω C IV , we estimate a lower limit on intergalactic medium metallicity ${\mathrm{log}}({Z}_{{\rm{IGM}}}/{Z}_{\odot })\gtrsim -3.25$ at z ∼ 2.3, with a smooth decline at higher redshifts. These trends trace the cosmic star formation history and He II photoheating rate, suggesting a link between C IV enrichment, star formation, and UV background over ∼3 Gyr. The catalog also provides a critical resource for future studies connecting circumgalactic metals to galaxy evolution, especially near cosmic noon.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Quantifying uncertainty in physics-based predictions of rare-isotope production cross sections via Bayesian-inspired model averaging across nuclear mass tables

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction models and phenomenological cross-section parametrizations often exhibit significant deviations over broad regions of mass and charge. In this work, a Bayesian-inspired model-averaging framework is developed to combine abrasion-ablation (AA) calculations based on multiple nuclear mass tables into a single statistically weighted estimate. For the calibrated systems, the model weights are assigned empirically according to the relative quality of fit to measured cross sections, thereby reducing systematic model bias while preserving the underlying physics content of the AA description. The weights are constrained using proton-rich fragmentation data for the 78 Kr and 124 Xe projectiles. The resulting parameter trends are then propagated to the 92 Mo and 144 Sm systems through a controlled scaling procedure. In the present implementation, the excitation-energy prescription is fixed, while the averaging is performed across nuclear-mass inputs; the framework provides both weighted cross sections and associated uncertainty estimates. Applied to proton-rich fragmentation, the present approach provides a practical basis for interpolation and limited extrapolation in regions relevant to rare-isotope production. The resulting predictions are used to assess the production of very proton-rich nuclei, and candidate new isotopes are discussed.

Bayesian methods↗
DOE OSTI2022

The impact of multi-sensor land data assimilation on river discharge estimation

River discharge is one of the most critical renewable water resources. Accurately estimating river discharge with land surface models (LSMs) remains challenging due to the difficulty in estimating land water storages such as snow, soil moisture, and groundwater. While data assimilation (DA) ingesting optical, microwave, and gravity measurements from space can help constrain theses storage states, its impacts on runoff and eventually river discharge are not fully understood. In this study, by taking advantage of recently published land DA results that jointly assimilate eight different combinations of observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), we quantify to what degree multi-sensor land DA improves the river discharge simulation skills over 40 global river basins, and investigate the complementary strengths of different satellite measurements on river discharge. To be more specific, river discharge is updated by feeding gridded runoff from the eight multi-sensor DA simulations into a vector-based river routing model named the Routing Application for Parallel computatIon of Discharge (RAPID). Our modeling results, including 7-year simulations at 177,458 river reaches globally, are used to study the seasonal to interannual variability of river discharge. It is found that assimilating GRACE has the greatest impact on global runoff patterns, leading to the most pronounced improvements in spatial river discharge in the middle and high latitudes with the R 2 increased by 0.16. The seasonal variation of spatial discharge is most skillful during the boreal summer. However, our evaluation also shows model and DA still struggle to generate reasonable variability and averaged discharge over permafrost regions. Finally, by assessing how different satellites add value to discharge forecasts, this study paves the way for more advanced multi-sensor satellite data assimilation to predict the terrestrial hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Foreground removal with ILC methods for AliCPT-1

One of the main goals of most future CMB experiments is the precise measurement of CMB B-mode polarization, whose major obstacle is the Galactic foregrounds. In this paper, we evaluate the foreground cleaning performance of the variants of the ILC method on partial sky B-modes and analyze the main sources of biases on the BB power spectrum. Specially, we compare the NILC, the cILC (in three domains) and the cMILC methods for AliCPT-1 simulations. We find that the cILC methods implemented in harmonic space and needlet space are both competent to clean different models of foregrounds, which bias the tensor-to-scalar ratio about 0.008 at maximum, and constrain the tensor-to-scalar ratio to r < 0.043(95%CL) for the AliCPT-1 configuration. We also note that the deviation of the estimated noise bias from the actual one for ILC, dubbed the noise bias error (NBE) in this paper, might make significant effects on the power spectrum for a small footprint and low signal-to-noise ratio CMB experiment. We finally obtain its relation with respect to the noise residual which fits well with the simulated results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Assessing the accuracy of compound formation energies with quantum Monte Carlo

Accurately predicting the formation energy of a compound, which describes its thermodynamic stability, is a key challenge in materials physics. Here, we employ a many-body quantum Monte Carlo (QMC) with single-reference trial functions to compute the formation energy of two electronically disparate compounds, the intermetallic VPt2 and the semiconductor CuI, for which standard density functional theory (DFT) predictions using both the Perdew-Burke-Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) density functional approximations deviate markedly from available experimental values. For VPt2, we find an agreement between QMC, SCAN, and PBE0 estimates, which therefore remain in disagreement with the much less exothermic experimental value. For CuI, the QMC result agrees with neither SCAN nor PBE pointing towards DFT exchange-correlation biases, likely related to the localized Cu 3d electrons. Compared to the behavior of some density functional approximations within DFT, spin-averaged QMC exhibits a smaller but still appreciable deviation when compared to experiment. The QMC result is slightly improved by incorporating spin-orbit corrections for CuI and solid I 2 , so that experiment and theory are brought into imperfect but reasonable agreement within about 120 meV/atom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Determining Stress Orientation in Rock Valley, Nevada, Using Ambient Seismic Noise

The stress field and the mechanical properties of rocks are important to consider for nuclear explosion monitoring due to their effect on seismic wave radiation from earthquakes and explosions. At the Rock Valley Direct Comparison site, the regional orientation of the maximum horizontal compressive stress (SH max ) is well constrained, but it is unknown whether there are local heterogeneities. Here, I show that stress-induced anisotropy in nonlinear elasticity can be used to estimate the orientation of SH max . Rocks have compliant internal contacts, such as fractures and mineral grain boundaries, that respond to applied strains more strongly than individual mineral crystals. This strain response is asymmetric between compressive and dilatational strains and is affected by anisotropy in the ambient stress field. Traditional seismic velocity measurements are of strain-averaged velocity, which is less sensitive than nonlinear elasticity to the behavior of compliant internal contacts and therefore the stress field and fracture behavior. My results show that the orientation of SH max measured using ambient seismic noise aligns with regional estimates, with some heterogeneity that can also be explained by the limitations of the seismic array. I demonstrate the potential of a passive technique for monitoring the stress field in places that currently lack local measurements.

58 GEOSCIENCES↗
DOE OSTI2022

Inferring and evaluating satellite-based constraints on NO x emissions estimates in air quality simulations

Satellite observations of tropospheric NO 2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NO x ). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NO x emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NO x emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO 2 and O 3 . OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO 2 retrievals. Updated lightning NO x emissions from either satellite improve the chemical transport model's low tropospheric O 3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi-fidelity parametric sensitivity estimation for large eddy simulation with the Spalart–Allmaras model

A computationally affordable approach to estimate parametric sensitivities of engineering relevant quantities of interest for a large eddy simulation (LES) is explored. The method is based on defining a Reynolds-averaged Navier–Stokes (RANS) problem that is constrained to reproduce the LES mean flow field. Here, the proposed method is described and assessed for a shock/boundary layer interaction problem, where the shock angle and wall temperature are considered variable or uncertain. In the current work, we show that the proposed method offers improved sensitivity predictions for certain flow features as compared to standalone RANS simulations, while using a fraction of the LES cost.

42 ENGINEERING↗
DOE OSTI2023

Consequences and benefits of utilizing continuous vibro-impact representations in constrained pipeline conveying fluid systems

Here, the effectiveness of continuous vibro-impact forcing representations for the cantilevered pipe that conveys fluid is explored and analyzed. The previously accepted forcing model utilizing a smoothened trilinear spring is estimated using three continuous forcing representations, namely, polynomial, rational polynomial, and hyperbolic tangent. The accuracy of the estimated forcing functions is investigated and analyzed by calculating the root mean square error, and bifurcation diagrams are generated and compared to the nominal system. Additionally, the dynamic response of the system is further characterized using Poincare maps, power spectra, and basins of attraction. Once all continuous forcing representations are analyzed and compared to the nominal system, the computational cost of each method is examined, and further limitations of the hyperbolic tangent method are discovered. It is proved that the hyperbolic tangent forcing representation most accurately captures the dynamic response of the pipeline, and the least accurate representation is the rational polynomial representation. Additionally, considerable computational cost is saved when employing the hyperbolic tangent representation compared to the discontinuous representation.

42 ENGINEERING↗
DOE OSTI2020

Multiplicity and pseudo-rapidity density distributions of charged particles produced in pp, pA and AA collisions at RHIC & LHC energies

Multiplicity and pseudorapidity (η) density (d N ch /dη) distributions of charged hadrons provide key information towards understanding the particle production mechanisms and initial conditions of high-energy heavy-ion collisions. However, detector constraints limit the η-range across which charged particle measurements can be carried out. Extrapolating the measured distributions to large η-range by parameterizing measured distributions and by using calculations from event generators, we characterize the production of charged particles over the full kinematic range. In the present study, we use three different ansätze to obtain quantitative descriptions of the shape of pseudorapidity distributions of charged hadrons produced in pp, p–A, and A–A collisions for beam energies ( s NN ) ranging from a few GeV to a few TeV corresponding to RHIC and LHC energies. We study the limiting fragmentation behavior in these collisions and report evidence for participant-scaling violations in high-energy collisions at the TeV scale. We additionally examine measured pseudorapidity distributions to constrain models describing initial conditions of particle production. We predict the centrality dependence of charged particle multiplicity distributions at FAIR and NICA energies and give an estimation of charged particle multiplicity at η = 0 for the proposed HE-LHC and FCC energies.

Physics↗
DOE OSTI2023

OzDES Reverberation Mapping Program: Hβ lags from the 6-yr survey

ABSTRACT Reverberation mapping measurements have been used to constrain the relationship between the size of the broad-line region and luminosity of active galactic nuclei (AGN). This R–L relation is used to estimate single-epoch virial black hole masses, and has been proposed to use to standardize AGN to determine cosmological distances. We present reverberation measurements made with Hβ from the 6-yr Australian Dark Energy Survey (OzDES) Reverberation Mapping Program. We successfully recover reverberation lags for eight AGN at 0.12 < z < 0.71, probing higher redshifts than the bulk of Hβ measurements made to date. Our fit to the R–L relation has a slope of α = 0.41 ± 0.03 and an intrinsic scatter of σ = 0.23 ± 0.02 dex. The results from our multi-object spectroscopic survey are consistent with previous measurements made by dedicated source-by-source campaigns, and with the observed dependence on accretion rate. Future surveys, including LSST, TiDES, and SDSS-V, which will be revisiting some of our observed fields, will be able to build on the results of our first-generation multi-object reverberation mapping survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

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↗
DOE OSTI2020

Measuring the Weak Mixing Angle in the DUNE near-Detector Complex

The planned DUNE experiment will have excellent sensitivity to the vector and axial couplings of the electron to the $Z$-boson via precision measurements of neutrino--electron scattering. We investigate the sensitivity of DUNE-PRISM, a movable near detector in the direction perpendicular to the beam line, and find that it will qualitatively impact our ability to constrain the weak couplings of the electron. We translate these neutrino--electron scattering measurements into a determination of the weak mixing angle at low scales and estimate that, with seven years of data taking, the DUNE near-detector can be used to measure $\sin^2\theta_W$ with better than 2% precision. We also discuss the impact of combining neutrino--electron scattering data with neutrino trident production at DUNE-PRISM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗