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At least 613 records · Page 34

Enhancement of Parametric Effects in Polariton Waveguides Induced by Dipolar Interactions

Exciton-polaritons are hybrid light-matter excitations arising from the nonperturbative coupling of a photonic mode and an excitonic resonance. Behaving as interacting photons, they show optical third-order nonlinearities providing effects such as optical parametric oscillation or amplification. It has been suggested that polariton-polariton interactions can be greatly enhanced by inducing aligned electric dipoles in their excitonic part. However, direct evidence of a true particle-particle interaction, such as superfluidity or parametric scattering, is still missing. In this Letter, we demonstrate that dipolar interactions can be used to enhance parametric effects such as self-phase modulation in waveguide polaritons. By quantifying these optical nonlinearities, we provide a reliable experimental measurement of the direct dipolar enhancement of polariton-polariton interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic Interactions of the Centrosymmetric Skyrmion Material Gd 2 PdSi 3

The experimental realization of magnetic skyrmion crystals in centrosymmetric materials has been driven by theoretical understanding of how a delicate balance of anisotropy and frustration can stabilize topological spin structures in applied magnetic fields. Recently, the centrosymmetric material Gd 2 PdSi 3 was shown to host a field-induced skyrmion crystal, but the skyrmion stabilization mechanism remains unclear. Here, we employ neutron-scattering measurements on an isotopically enriched polycrystalline Gd 2 PdSi 3 sample to quantify the interactions that drive skyrmion formation. Our analysis reveals spatially extended interactions in triangular planes, and large ferromagnetic interplanar magnetic interactions that are modulated by the Pd/Si superstructure. The skyrmion crystal emerges from a zero-field helical magnetic order with magnetic moments perpendicular to the magnetic propagation vector, indicating that the magnetic dipolar interaction plays a significant role. To conclude, our experimental results establish an interaction space that can promote skyrmion formation, facilitating identification and design of centrosymmetric skyrmion materials.

36 MATERIALS SCIENCE↗

Neutron matter from local chiral effective field theory interactions at large cutoffs

Neutron matter is an important many-body system that provides valuable constraints for the equation of state (EOS) of neutron stars. Neutron-matter calculations employing chiral effective field theory (EFT) interactions have been extensively used for this purpose. Among the various many-body methods, quantum Monte Carlo (QMC) methods stand out due to their nonperturbative nature and the achievable precision. However, QMC methods require local interactions as input, which leads to the appearance of stronger regulator artifacts compared to nonlocal interactions. To circumvent this, we employ large-cutoff interactions derived within chiral EFT (400 MeV ≤ Λ 𝑐 ≤ 700MeV) for studies of pure neutron matter. These interactions have been adjusted to nucleon-nucleon scattering phase shifts, the triton binding energy, as well as the triton 𝛽-decay half-life. We find that regulator artifacts significantly decrease with increasing cutoff, leading to a significant reduction of uncertainties in the neutron-matter EOS. We discuss implications for the symmetry energy and demonstrate how our new calculations lead to a reduction in the theoretical uncertainty of predicted neutron-star radii by up to 30% for low-mass stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Role of Matter Interactions in Superradiant Phenomena

The superradiant phenomenon, usually described by the Dicke model, is a hallmark of strong light-matter interaction. Here, we explore how matter-matter interactions influence this phenomenon by performing ground-state simulations of Dicke-like models with both isotropic and anisotropic interactions. We find that Ising-type interactions produce two qualitatively distinct phase boundaries, one of which gives rise to an antiferromagnetic-normal phase connected to the superradiant regime via a first-order phase transition. Under anisotropic couplings, we uncover a strongly correlated phase where in-plane spin order coexists with superradiance, exhibiting sublinear scaling of the photon occupation per site and power-law decay of spin correlations. Furthermore, superradiance is strengthened by tuning either isotropic or anisotropic interactions, highlighting the role of intrinsic many-body correlations in shaping light-matter quantum phases.

Dicke model↗

Understanding the selectivity of nonsteroidal anti-inflammatory drugs for cyclooxygenases using quantum crystallography and electrostatic interaction energy

Quantum crystallography methods have been employed to investigate complex formation between nonsteroidal anti-inflammatory drugs (NSAIDs) and cyclooxygenase (COX) enzymes, with particular focus on the COX-1 and COX-2 isoforms. This study analyzed the electrostatic interaction energies of selected NSAIDs (flurbiprofen, ibuprofen, meloxicam and celecoxib) with the active sites of COX-1 and COX-2, revealing significant differences in binding profiles. Flurbiprofen exhibited the strongest interactions with both COX-1 and COX-2, indicating its potent binding affinity. Celecoxib and meloxicam showed a preference for COX-2, consistent with their known selectivity for this isoform, while ibuprofen showed comparable interaction energies with both isoforms, reflecting its nonselective inhibition pattern. Key amino-acid residues, including Arg120, Arg/His513 and Tyr355, were identified as critical determinants of NSAID selectivity and binding affinity. The findings highlight the complex interplay between interaction energy and selectivity, suggesting that while electrostatic interactions play a fundamental role, additional factors such as enzyme dynamics and the hydrophobic effect also contribute to the therapeutic efficacy and safety profiles of NSAIDs. These insights provide valuable guidance for the rational design of NSAIDs with enhanced therapeutic benefits and minimized adverse effects.

60 APPLIED LIFE SCIENCES↗

Analysis and Mitigation of Cascading Failures Using a Stochastic Interaction Graph with Eigen-analysis

In studies on complex network systems using graph theory, eigen-analysis is typically performed on an undirected graph model of the network. However, when analyzing cascading failures in a power system, the interactions among failures suggest the need for a directed graph beyond the topology of the power system to model directions of failure propagation. To accurately quantify failure interactions for effective mitigation strategies, this paper proposes a stochastic interaction graph model and associated eigen-analysis. Different types of modes on failure propagations are defined and characterized by the eigenvalues of a stochastic interaction matrix, whose absolute values are unity, zero, or in between. Finding and interpreting these modes helps identify the probable patterns of failure propagation, either local or widespread, and the participating components based on eigenvectors. Then, by lowering the failure probabilities of critical components highly participating in a mode of widespread failures, cascading can be mitigated. Here, the validity of the proposed stochastic interaction graph model, eigen-analysis and the resulting mitigation strategies is demonstrated using simulated cascading failure data on an NPCC 140-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Interactive effects of elevated CO 2 , warming, reduced rainfall, and nitrogen on leaf gas exchange in five perennial grassland species

Abstract Global changes can interact to affect photosynthesis and thus ecosystem carbon capture, yet few multi‐factor field studies exist to examine such interactions. Here, we evaluate leaf gas exchange responses of five perennial grassland species from four functional groups to individual and interactive global changes in an open‐air experiment in Minnesota, USA, including elevated CO 2 (eCO 2 ), warming, reduced rainfall and increased soil nitrogen supply. All four factors influenced leaf net photosynthesis and/or stomatal conductance, but almost all effects were context‐dependent, i.e. they differed among species, varied with levels of other treatments and/or depended on environmental conditions. Firstly, the response of photosynthesis to eCO 2 depended on species and nitrogen, became more positive as vapour pressure deficit increased and, for a C 4 grass and a legume, was more positive under reduced rainfall. Secondly, reduced rainfall increased photosynthesis in three functionally distinct species, potentially via acclimation to low soil moisture. Thirdly, warming had positive, neutral or negative effects on photosynthesis depending on species and rainfall. Overall, our results show that interactions among global changes and environmental conditions may complicate predictions based on simple theoretical expectations of main effects, and that the factors and interactions influencing photosynthesis vary among herbaceous species.

Pastore, Melissa A.↗

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗

Programming van der Waals interactions with complex symmetries into microparticles using liquid crystallinity

Asymmetric interactions such as entropic (e.g., encoded by nonspherical shapes) or surface forces (e.g., encoded by patterned surface chemistry or DNA hybridization) provide access to functional states of colloidal matter, but versatile approaches for engineering asymmetric van der Waals interactions have the potential to expand further the palette of materials that can be assembled through such bottom-up processes. We show that polymerization of liquid crystal (LC) emulsions leads to compositionally homogeneous and spherical microparticles that encode van der Waals interactions with complex symmetries (e.g., quadrupolar and dipolar) that reflect the internal organization of the LC. Experiments performed using kinetically controlled probe colloid adsorption and complementary calculations support our conclusion that LC ordering can program van der Waals interactions by ~20 k B T across the surfaces of microparticles. Because diverse LC configurations can be engineered by confinement, these results provide fresh ideas for programming van der Waals interactions for assembly of soft matter.

36 MATERIALS SCIENCE↗

The NEUT neutrino interaction simulation program library

Abstract is a neutrino–nucleus interaction simulation program library. It can be used to simulate interactions for neutrinos with between 100 MeV and a few TeV of energy. is also capable of simulating hadron interactions within a nucleus and is used to model nucleon decay and hadron–nucleus interactions for particle propagation in detector simulations. This article describes the range of interactions modelled and how each is implemented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

3-3-1 Self interacting dark matter and the galaxy core-cusp problem

The core–cusp problem remains a challenging discrepancy between observations and simulations in the standard Λ CDM model for the formation of galaxies. The problem is that Λ CDM simulations predict a steep power-law mass density profile at the center of galactic dark matter halos. However, observations of dwarf galaxies in the Local Group reveal a density profile consistent with a nearly flat distribution of dark matter near the center. A number of solutions to this dilemma have been proposed. In this paper we summarize investigations into the possibility that the dark matter particles themselves self interact and scatter. Such self-interacting dark matter (SIDM) particles can smooth out the dark-matter profile in high-density regions. We also review the theoretical proposal that self-interacting dark matter may arise as an additional Higgs scalar in the 3–3–1 extension of the Standard Model (SM). We present new simulations of galaxy formation and evolution for this formulation of self-interacting dark matter. Current constraints on this self-interacting dark matter are then summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche

Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Microbiology↗

Elastic interaction-induced anisotropic growth of dislocation loop arrays

The elastic interactions and reactions of dislocations lead to the formation of complex dislocation substructures, which is critical to the strain hardening and fatigue failure. Phase field dislocation dynamics simulations are conducted as a first step to understand the elastic interactions between dislocation loops. When the interloop spacing is small, the elastic interactions with neighboring loops become strong, rendering the edge segments strongly pinned, while allowing for the screw segments to propagate more easily. The interactions are found to result in an anisotropic stress distribution around the dislocation loops, leading to the formation of arrays of long, straight edge dislocations that could act as barriers to subsequent slip. Furthermore, the effect of initial loop size and applied strain rate on the elastic interaction-induced anisotropic pinning effect is investigated and discussed. Furthermore, the results are important for coarse-graining dislocation substructures formation into continuum level models of deformation in crystalline solids.

36 MATERIALS SCIENCE↗

Spin-Coherent Transport under Strong Spin-Orbit Interaction (Final Technical Report)

The major goals of the project consisted of acquiring insight in spin-dependent quantum coherent electronic transport phenomena arising from spin-orbit interaction, via experiments on semiconductor heterostructures and thin film semimetals patterned into mesoscopic and nanoscale geometries. The solid-state physics findings contain insight potentially useful for the creation of new quantum states of matter, for spin operations in quantum information processing, for future spin electronics, and for other future functionalities of power-saving electronic devices. The subject was of fundamental interest, but was also of long-term applied interest for quantum devices, spintronics devices, and general electronic devices. The experiments were conducted by low-temperature electronic magnetotransport in nanoscale structures of length scales similar to the quantum phase- and spin-coherence lengths and the carrier mean-free paths in the materials. Emphasis was placed on quantum coherence and spin coherence, to understand coherent spin-dependent electronic processes, on transport of electrons with very long mean-free path (ballistic transport), on the transfer of electron spin to nuclear spin (dynamic nuclear spin polarization in bismuth), and on the study of materials with quantum states emerging from spin-orbit interaction and electron-electron interaction (bismuth iridates). In two-dimensional electron systems in quantum wells of the narrow-bandgap semiconductors InAs and InGaAs the objectives included the characterization of quantum states arising from the Aharonov-Casher quantum-mechanical phase as an electromagnetic dual of the Aharonov-Bohm phase. Objectives also included quantum electronic transport at the mesoscopic scale on the semimetal bismuth in thin film form, and particularly on its strongly spin-orbit coupled surface states. An almost-strain-free method was developed to grow high-quality bismuth thin films. Devices fabricated on these films were then used to study a novel nuclear spin torque, whereby the bismuth carrier spin was transferred to the bismuth nuclei by the agency of both spin-orbit interaction and hyperfine interaction. Aspects of ballistic transport were studied in GaAs/AlGaAs heterostructures of very high mobility, and a hitherto unsuspected similarity was discovered between ballistic transport and hydrodynamic transport, of potential use in future power-saving electronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Progress toward double-differential cross-section measurements of single charged-pion production in charged current muon neutrino interactions on argon with SBND

Resonant neutrino–nucleus processes constitute a significant portion of neutrino interactions in the few-GeV energy region. Charged-current interactions with a muon and one single charged pion in the final state (CC1$\pi$) are primarily sensitive to resonant processes, while also receiving contributions from non-resonant processes and being strongly affected by nuclear effects and final-state interactions. A precise understanding of this channel is essential for improving neutrino interaction models and reducing systematic uncertainties in oscillation measurements. The Short-Baseline Near Detector (SBND) at Fermilab has collected the largest neutrino–argon dataset to date, providing an excellent opportunity to study CC1$\pi$ interactions on argon. This analysis aims to improve existing single-differential cross-section measurements by reporting results in a variety of kinematic variables and to perform the first double-differential CC1$\pi$ cross-section measurement on argon, using novel techniques for pion energy reconstruction.

Pelegrina-Gutiérrez, Luis [Granada U.] (ORCID:0000↗

Molecular Dynamics Investigation of Lipid-Specific Interactions with a Fusion Peptide

The HIV-1 fusion peptide, which is a short hydrophobic peptide from the gp41 coat glycoprotein that participates in the infection of a cell, interacts with model lipid bilayer membranes in a concentration-dependent manner. The interaction of the peptide with the bilayer also strongly depends on the lipid composition. Here, molecular dynamics simulations were performed to investigate lipid-specific interactions that arise shortly after the binding of a less-fusogenic variant of the HIV-1 fusion peptide to a lipid bilayer composed of a mixture of dimyristoyl phosphatidylcholine and dimyristoyl phosphatidylglycerol. The impact of peptide concentration was also studied. An improved understanding was gained of the lipid-specific interactions experienced by the FP. New insight was also gained into how the peptide concentration changes these interactions.

60 APPLIED LIFE SCIENCES↗

Effect of Dipole Interactions on Blocking Temperature and Relaxation Dynamics of Superparamagnetic Iron-Oxide (Fe 3 O 4 ) Nanoparticle Systems

The effects of dipole interactions on magnetic nanoparticle magnetization and relaxation dynamics were investigated using five nanoparticle (NP) systems with different surfactants, carrier liquids, size distributions, inter-particle spacing, and NP confinement. Dipole interactions were found to play a crucial role in modifying the blocking temperature behavior of the superparamagnetic nanoparticles, where stronger interactions were found to increase the blocking temperatures. Consequently, the blocking temperature of a densely packed nanoparticle system with stronger dipolar interactions was found to be substantially higher than those of the discrete nanoparticle systems. The frequencies of the dominant relaxation mechanisms were determined by magnetic susceptibility measurements in the frequency range of 100 Hz–7 GHz. The loss mechanisms were identified in terms of Brownian relaxation (1 kHz–10 kHz) and gyromagnetic resonance of Fe 3 O 4 (~1.12 GHz). It was observed that the microwave absorption of the Fe 3 O 4 nanoparticles depend on the local environment surrounding the NPs, as well as the long-range dipole–dipole interactions. These significant findings will be profoundly important in magnetic hyperthermia medical therapeutics and energy applications.

36 MATERIALS SCIENCE↗

Classical Swine Fever Virus Structural Glycoprotein E2 Interacts with Host Protein ACADM during the Virus Infectious Cycle

The E2 glycoprotein is one of the four structural proteins of the classical swine fever virus (CSFV) particle. E2 has been shown to be involved in many virus functions, including adsorption to host cells, virus virulence and interaction with several host proteins. Using a yeast two-hybrid screen, we have previously shown that the CSFV E2 specifically interacts with swine host protein medium-chain-specific acyl-Coenzyme A dehydrogenase (ACADM), an enzyme that catalyzes the initial step of the mitochondrial fatty acid beta-oxidation pathway. Here, we show that interaction between ACADM and E2 also happens in swine cells infected with CSFV using two different procedures: coimmunoprecipitation and a proximity ligation assay (PLA). In addition, the amino acid residues in E2 critically mediating the interaction with ACADM, M49 and P130 were identified via a reverse yeast two-hybrid screen using an expression library composed of randomly mutated versions of E2. A recombinant CSFV, E2ΔACADMv, harboring substitutions at residues M49I and P130Q in E2, was developed via reverse genomics from the highly virulent Brescia isolate. E2ΔACADMv was shown to have the same kinetics growth in swine primary macrophages and SK6 cell cultures as the parental Brescia strain. Similarly, E2ΔACADMv demonstrated a similar level of virulence when inoculated to domestic pigs as the parental Brescia. Animals intranasally inoculated with 10 5 TCID 50 developed a lethal form of clinical disease with virological and hematological kinetics changes undistinguishable from those produced by the parental strain. Therefore, interaction between CSFV E2 and host ACADM is not critically involved in the processes of virus replication and disease production.

60 APPLIED LIFE SCIENCES↗