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At least 757 records · Page 42

Coulomb excitation of 102 Ru with 12 C and 16 O

Here, the Coulomb excitation of 102 Ru was performed with beams of 12 C and 16 O ions. The beam particles scattered at forward angles were momentum analyzed with a magnetic spectrograph. The resolution achieved enabled the populations of the $2^{+}_{1}$ state, the unresolved $2^{+}_{2}$/ $4^{+}_{1}$, and $2^{+}_{4}$/$3^{-}_{1}$, doublets of states, and the $3^{-}_{2}$ state to be determined as a function of the scattering angle. These populations are compared with gosia calculations, yielding B(E2; $2^{+}_{1}$→$0^{+}_{1}$) = 41.5 ± 2.3 W.u., B(E2; $2^{+}_{2}$→$0^{+}_{1}$) = 1.75 ± 0.11 W.u., B(E3; $3^{-}_{1}$→$0^{+}_{1}$) = 31.5 ± 3.5 W.u., and B(E3; $3^{-}_{2}$→$0^{+}_{1}$) = 6.8 ± 0.5 W.u. The B(E3; $3^{-}_{1}$→$0^{+}_{1}$) value is significantly larger than previously measured. The weakly populated $2^{+}_{3}$ state, presumed to be a member of the band built on the $0^{+}_{2}$ state, was observed clearly for a single angle only, and a fit to its population results in B(E2; $2^{+}_{3}$→$0^{+}_{1}$) = 0.053 ± 0.011 W.u. Using the known γ -ray branching ratios for the $2^{+}_{3}$ level, the B(E2; $2^{+}_{3}$→$0^{+}_{2}$) value is calculated to be 18 ± 4 W.u., substantially less than the B(E2; $2^{+}_{1}$→$0^{+}_{1}$) . This suggests that the deformation of the $0^{+}_{2}$ state is lower than that of the $0^{+}_{1}$ state. The results are compared with beyond-mean-field calculations with the Gogny-D1S interaction using the symmetry-conserving configuration-mixing method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement of the Centrality Dependence of the Dijet Yield in p + Pb Collisions at s NN = 8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165 nb − 1 of p + Pb data collected at s NN = 8.16 TeV in 2016. The event centrality, which reflects the p + Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R CP , is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R CP shows a scaling with the Bjorken x of the parton originating from the proton, x p , while no such trend is observed as a function of x Pb . This analysis provides unique input to understanding the role of small proton spatial configurations in p + Pb collisions by covering parton momentum fractions from the valence region down to x p ∼ 10 − 3 and x Pb ∼ 4 × 10 − 4 . © 2024 CERN, for the ATLAS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multi-Agent Deep Reinforcement Learning for Realistic Distribution System Voltage Control Using PV Inverters

Over the last few decades, the deployment of distributed solar photovoltaic (PV) systems has increased consistently. High PV penetration could cause adverse effects on the grid, such as voltage violations. This paper proposes a new distributed soft actor-critic based multi-agent deep reinforcement learning (SAC-MADRL) control solution to minimize the PV real power curtailment while keeping the grid voltage in an acceptable range. New reward functions have been designed to coordinate different agents during the learning process, yielding improved convergence. Comparison results with other control methods on a real feeder in western Colorado U.S. with 80% penetration of PVs demonstrate that the proposed method has better capability of effectively regulating voltage while minimizing the PV real power curtailment.

distribution system↗

$\mathrm {K_S}^{0}$- and (anti-)$\Lambda $-hadron correlations in $pp$ collisions at ${\sqrt{s}} = 13$ TeV

Two-particle Azimuthal correlations are measured with the ALICE apparatus in pp collisions at √s = 13 TeV to explore strangeness- and multiplicity-related effects in the fragmentation of jets and the transition regime between bulk and hard production, probed with the condition that a strange meson (KS o ) or baryon (Λ) with transverse momentum p T > 3 GeV/c is produced. Azimuthal correlations between kaons or Λ hyperons with other hadrons are presented at midrapidity for a broad range of the trigger (3 < $p$$^{trigg}_{T}$ < 20 GeV/c) and associated particle p T (1 GeV/c < $p$$^{assoc}_{T}$< $p$$^{trigg}_{T}$), for minimum-bias events and as a function of the event multiplicity. The near- and away-side peak yields are compared for the case of either K S o or Λ(Λ¯) being the trigger particle with that of inclusive hadrons (a sample dominated by pions). In addition, the measurements are compared with predictions from PYTHIA 8 and EPOS LHC event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance Enhancement of APW+lo Calculations by Simplest Separation of Concerns

Full-potential linearized augmented plane wave (LAPW) and APW plus local orbital (APW+lo) codes differ widely in both their user interfaces and in capabilities for calculations and analysis beyond their common central task of all-electron solution of the Kohn–Sham equations. However, that common central task opens a possible route to performance enhancement, namely to offload the basic LAPW/APW+lo algorithms to a library optimized purely for that purpose. To explore that opportunity, we have interfaced the Exciting-Plus (“EP”) LAPW/APW+lo DFT code with the highly optimized SIRIUS multi-functional DFT package. This simplest realization of the separation of concerns approach yields substantial performance over the base EP code via additional task parallelism without significant change in the EP source code or user interface. We provide benchmarks of the interfaced code against the original EP using small bulk systems, and demonstrate performance on a spin-crossover molecule and magnetic molecule that are of size and complexity at the margins of the capability of the EP code itself.

Zhang, Long↗

First-principles theory for Schottky barrier physics

We develop a first-principles theory for Schottky barrier physics. The Poisson equation is solved selfconsistently with the electrostatic charge density over the entire barrier using the density functional theory (DFT) electronic structure converged locally, allowing computation of a Schottky barrier entirely from DFT involving thousands of atomic layers in the semiconductor (SC). Here, the induced charge in the bulk consists of conduction and valence band charges from doping and band bending, as well as charge from the evanescent states in the gap of the SC. The Schottky barrier height (SBH) is determined when the induced charge density and the induced electrostatic potential reach self-consistency. Tests on the GaAs-graphene and Si/Al heterostructures yield SBH, width, along with depletion and inversion layers obtained self-consistently as functions of temperature and bulk doping.

36 MATERIALS SCIENCE↗

Strongly Correlated States of Transition Metal Spin Defects: The Case of an Iron Impurity in Aluminum Nitride

We investigate the electronic properties of an exemplar transition metal impurity in an insulator, with the goal of accurately describing strongly correlated defect states. Here, we consider iron in aluminum nitride, a material of interest for hybrid quantum technologies, and we carry out calculations with quantum embedding methods, density matrix embedding theory (DMET) and quantum defect embedding theory (QDET), and with spin-flip time-dependent density functional theory (TDDFT). We show that both DMET and QDET accurately describe the ground state and low-lying excited states of the defect and that TDDFT yields photoluminescence spectra in agreement with experiments. In addition, we provide a detailed discussion of the convergence of our results as a function of the active space used in the embedding methods, thus defining a protocol to obtain converged data directly comparable with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cell-free production of a functional oligomeric form of a Chlamydia major outer-membrane protein (MOMP) for vaccine development

Chlamydia is a prevalent sexually transmitted disease that infects more than 100 million people worldwide. Although most individuals infected with Chlamydia trachomatis are initially asymptomatic, symptoms can arise if left undiagnosed. Long-term infection can result in debilitating conditions such as pelvic inflammatory disease, infertility, and blindness. Chlamydia infection, therefore, constitutes a significant public health threat, underscoring the need for a Chlamydia-specific vaccine. Chlamydia strains express a major outer-membrane protein (MOMP) that has been shown to be an effective vaccine antigen. However, approaches to produce a functional recombinant MOMP protein for vaccine development are limited by poor solubility, low yield, and protein misfolding. For this study, we used an Escherichia coli-based cell-free system to express a MOMP protein from the mouse-specific species Chlamydia muridarum (MoPn-MOMP or mMOMP). The codon-optimized mMOMP gene was co-translated with Δ49apolipoprotein A1 (Δ49ApoA1), a truncated version of mouse ApoA1 in which the N-terminal 49 amino acids were removed. This co-translation process produced mMOMP supported within a telodendrimer nanolipoprotein particle (mMOMP–tNLP). The cell-free expressed mMOMP–tNLPs contain mMOMP multimers similar to the native MOMP protein. This cell-free process produced on average 1.5 mg of purified, water-soluble mMOMP–tNLP complex in a 1-ml cell-free reaction. The mMOMP–tNLP particle also accommodated the co-localization of CpG oligodeoxynucleotide 1826, a single-stranded synthetic DNA adjuvant, eliciting an enhanced humoral immune response in vaccinated mice. Using our mMOMP–tNLP formulation, we demonstrate a unique approach to solubilizing and administering membrane-bound proteins for future vaccine development. This method can be applied to other previously difficult-to-obtain antigens while maintaining full functionality and immunogenicity.

59 BASIC BIOLOGICAL SCIENCES↗

National Ignition Campaign Data Analysis by an ICF Outsider

A simple DT burn model, with no alpha-particle warming feedback, using a combination of ICF inputs and the measured ion temperature, T, volume compression, C, ablator velocity, v, and burn width time, Δt, can reproduce the national-ignition campaign (NIC) fusion yields with a rms percent difference of ~40%. Analysis suggestion the fusion-yield reproducibility of NIC events with nominally identically measured T, C, v, and Δt is <30%. The highest fusion yields, at a fixed laser energy are obtained with depleted-uranium (DU) hohlraums and high-density carbon (HDC) ablators. Small diameter fit tubes (≤5 μm) enhance fusion yields by an average of 26±15% relative to 10-μm diameter fit tubes. A dependence of fusion yield on the diameter of the capsule relative to the diameter of the hohlraum is inferred for fixed T, C, v, and Δt. No evidence of conditions close to ignition, or alpha-particle warming is found in the existing NIC data with LEH< 2MJ. To obtain a predictive model for extrapolation proposes we map the T, C, and v into power laws as a function of LEH. The above mentioned extrapolatable model has a rms percent difference from the yields of the second half of the NIC of (56 ± 4)%. Higher (and significantly lower) DT temperatures are obtained with HDC ablators (and low-foot drives). The highest compressions are obtained via low-foot drives, but this does not compensate for the corresponding lower temperatures. An extrapolation of the presented model suggests significant alpha-particle heating at an LEH of ~5 MJ. It is hoped that others more familiar it the conditions needed for ignition will use to presented model to estimate the LEH required for ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Adversarial autoencoder ensemble for fast and probabilistic reconstructions of few-shot photon correlation functions for solid-state quantum emitters

Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Observation of the ϒ ( 3 S ) Meson and Suppression of ϒ States in Pb-Pb Collisions at s N N = 5.02 TeV

The production of ϒ ( 2 S ) and ϒ ( 3 S ) mesons in lead-lead (Pb-Pb) and proton-proton ( p p ) collisions is studied in their dimuon decay channel using the CMS detector at the LHC. The ϒ ( 3 S ) meson is observed for the first time in Pb-Pb collisions, with a significance above 5 standard deviations. The ratios of yields measured in Pb-Pb and p p collisions are reported for both the ϒ ( 2 S ) and ϒ ( 3 S ) mesons, as functions of transverse momentum and Pb-Pb collision centrality. These ratios, when appropriately scaled, are significantly less than unity, indicating a suppression of ϒ yields in Pb-Pb collisions. This suppression increases from peripheral to central Pb-Pb collisions. Furthermore, the suppression is stronger for ϒ ( 3 S ) mesons compared to ϒ ( 2 S ) mesons, extending the pattern of sequential suppression of quarkonium states in nuclear collisions previously seen for the J / ψ , ψ ( 2 S ) , ϒ ( 1 S ) , and ϒ ( 2 S ) mesons. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multiplicity and rapidity dependence of $\textrm{K}^{*}(\mathrm {{\textbf {892}}})^{0}$ and $\mathrm {\phi ({\textbf {1020}})}$ production in p–Pb collisions at $\sqrt{s_{\textrm{NN}}} =$ 5.02 TeV

The transverse-momentum (p T ) spectra of K*(892) 0 and Φ(1020) measured with the ALICE detector up to p T = 16 GeV/c in the rapidity range -1.2 < y < 0.3, in p–Pb collisions at the center-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV are presented as a function of charged particle multiplicity and rapidity. The measured p T distributions show a dependence on both multiplicity and rapidity at low p T whereas no significant dependence is observed at high p T . A rapidity dependence is observed in the p T -integrated yield (dN/dy), whereas the mean transverse momentum ($\langle$p T $\rangle$) shows a flat behavior as a function of rapidity. The rapidity asymmetry (Y asym ) at low p T (< 5 GeV/c) is more significant for higher multiplicity classes. At high p T , no significant rapidity asymmetry is observed in any of the multiplicity classes. Both K*(892) 0 and Φ(1020) show similar Y asym . The nuclear modification factor (Q CP ) as a function of p T shows a Cronin-like enhancement at intermediate p T , which is more prominent at higher rapidities (Pb-going direction) and in higher multiplicity classes. At high p T (> 5 GeV/c), the Q CP values are greater than unity and no significant rapidity dependence is observed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First-Principles Quantum Transport Modeling of Spin-Transfer and Spin-Orbit Torques in Magnetic Multilayers

A unified approach for computing (i) spin-transfer torque in magnetic trilayers like spin valve and magnetic tunnel junction, where injected charge current flows perpendicularly to interfaces, and (ii) spin-orbit torque in magnetic bilayers of the type ferromagnet/spin-orbit-coupled material, where injected charge current flows parallel to the interface, was reviewed. The experimentally explored and technologically relevant spin-orbit-coupled materials include 5d heavy metals, topological insulators, Weyl semimetals, and transition metal dichalcogenides. This approach requires to construct the torque operator for a given Hamiltonian of the device and the steady-state nonequilibrium density matrix, where the latter is expressed in terms of the nonequilibrium Green’s functions and split into three contributions. Tracing these contributions with the torque operator automatically yields field-like and damping-like components of spin-transfer torque or spin-orbit torque vector, which is particularly advantageous for spin-orbit torque where the direction of these components depends on the unknown-in-advance orientation of the current-driven nonequilibrium spin density in the presence of spin-orbit coupling. Illustrative examples are provided by computing spin-transfer torque in a one-dimensional toy model of a magnetic tunnel junction and realistic Co/Cu/Co spin valve, both of which are described by first-principles Hamiltonians obtained from noncollinear density functional theory calculations, as well as by computing spin-orbit torque in a ferromagnetic layer described by a tight-binding Hamiltonian which includes spin-orbit proximity effect within ferromagnetic monolayers assumed to be generated by the adjacent monolayer transition metal dichalcogenide. In addition, it is shown here how spin-orbit proximity effect, quantified by computing (via first-principles retarded Green’s function) spectral functions and spin textures on monolayers of realistic ferromagnetic material like Co in contact with heavy metal or monolayer transition metal dichalcogenide, can be tailored to enhance the magnitude of spin-orbit torque. Furthermore, errors made in the calculation of spin-transfer torque are quantified when using Hamiltonian from collinear density functional theory, with rigidly rotated magnetic moments to create noncollinear magnetization configurations, instead of proper (but computationally more expensive) self-consistent Hamiltonian obtained from noncollinear density functional theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Extracting Natural Biosurfactants from Humus Deposits for Subsurface Engineering Applications

Environmentally benign, economical, and effective surfactants and additives are needed in engineering subsurface energy recovery processes. Biosurfactants have some advantages over chemically synthesized surfactants, but the high costs of microbial-biosynthesis limit their applications in subsurface engineering. In this work, we propose to use naturally occurring biosurfactants contained within Earth's readily available and inexpensive humus deposits for subsurface engineering applications. We collected humus samples of different types from four different regions, and developed a simple method for extracting natural biosurfactant (NBS) using only four common chemicals. The average NBS extraction yields are 16 ± 3% of the raw humus. No significant differences in elemental composition and functional group chemistry were found among the NBS extracted from humus of different origins, suggesting that any humus deposit can be used for NBS extraction. Measurements of interfacial tensions between air-water and supercritical (sc) CO 2 -water interfaces indicate that the NBS is a highly effective surfactant. NBS has good foaming ability. Preliminary tests with only 0.5 mass % NBS in the aqueous phase (no other additives) yielded scCO 2 -in-water foams of 83% foam quality. The apparent viscosity of 13 cP measured at a shear rate of 2320 s -1 indicates that much higher viscosities are achievable at lower shear rates. Finally, these results suggest that NBS merits further research and development for potential applications in subsurface energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Predictive Power of Exact Constraints and Appropriate Norms in Density Functional Theory

Ground-state Kohn-Sham density functional theory provides, in principle, the exact ground-state energy and electronic spin densities of real interacting electrons in a static external potential. In practice, the exact density functional for the exchange-correlation (xc) energy must be approximated in a computationally efficient way. About 20 mathematical properties of the exact xc functional are known. In this work, we review and discuss these known constraints on the xc energy and hole. By analyzing a sequence of increasingly sophisticated density functional approximations (DFAs), we argue that (a) the satisfaction of more exact constraints and appropriate norms makes a functional more predictive over the immense space of many-electron systems and (b) fitting to bonded systems yields an interpolative DFA that may not extrapolate well to systems unlike those in the fitting set. We discuss both how the class of well-described systems has grown along with constraint satisfaction and the possibilities for future functional development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of angular and momentum distributions of charged particles within and around jets in Pb+Pb and p p collisions at s NN = 5.02 TeV with the ATLAS detector

CERN-LHC. Studies of the fragmentation of jets into charged particles in heavy-ion collisions can provide information about the mechanism of jet-quenching by the hot and dense QCD matter created in such collisions, the quark-gluon plasma. This paper presents a measurement of the angular distribution of charged particles around the jet axis in sNN=5.02 TeV Pb+Pb and pp collisions, using the ATLAS detector at the LHC. The Pb+Pb and pp data sets have integrated luminosities of 0.49 nb−1 and 25 pb−1, respectively. The measurement is performed for jets reconstructed with the anti-kt algorithm with radius parameter R=0.4 and is extended to an angular distance of r=0.8 from the jet axis. Results are presented as a function of Pb+Pb collision centrality and distance from the jet axis for charged particles with transverse momenta in the 1−63 GeV range, matched to jets with transverse momenta in the 126−316 GeV range and an absolute value of jet rapidity of less than 1.7. Modifications to the measured distributions are quantified by taking a ratio to the measurements in pp collisions. Yields of charged particles with transverse momenta below 4 GeV are observed to be increasingly enhanced as a function of angular distance from the jet axis, reaching a maximum at r=0.6. Charged particles with transverse momenta above 4 GeV have an enhanced yield in Pb+Pb collisions in the jet core for angular distances up to r=0.05 from the jet axis, with a suppression at larger distances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗