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At least 433 records · Page 24

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization

Herein this article presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types. Our proposed new hybrid models (named hybridM) merge the Monte Carlo Tree Search structure (MCTS) for categorical variables with Gaussian Processes (GP) for continuous ones. hybridM leverages the upper confidence bound tree search (UCTS) for MCTS strategy, showcasing the tree architecture’s integration into Bayesian optimization. Our innovations, including dynamic online kernel selection in the surrogate modeling phase and a unique UCTS search strategy, position our hybrid models as an advancement in mixed-variable surrogate models. Numerical experiments underscore the superiority of hybrid models, highlighting their potential in Bayesian optimization.

97 MATHEMATICS AND COMPUTING↗

Photoemission from hybrid states of Cl@C 60 before and after a stabilizing charge transfer

Photoionization calculations of the endofullerene molecule Cl@C 60 with an open-shell chlorine atom are performed in the linear response density functional theory based on a spherical jellium model of C 60 . Cross sections for atom–fullerene hybrid photoemission studied show the effects of the hybridization symmetry, the giant plasmon and the molecular cavity. Comparisons with the results of Ar@C 60 provide insights into the role of a shell-closing electron and its influence on the dynamics. The results for Cl@C 60 are further compared with those of a more stable configuration that results after a C 60 electron transfers to Cl forming Cl–@${{\text{C}}_{60}}^{+}$. This comparison reveals noticeable differences in the ionization properties of the antibonding hybrid state while the bonding hybrid remains nearly unaltered showing a magnification covering the entire giant plasmon energy range. Furthermore, these predictions should raise interest in probing the molecular configuration using photoelectron spectroscopy.

74 ATOMIC AND MOLECULAR PHYSICS↗

Electron vacancy-level dependent hybrid photoionization of the F–@C60+molecule: A novel effect

Our previous studies [J. Phys. B 53, 125101 (2020); Euro. Phys. J. D 74, 191 (2020)] have predicted that the atom-fullerene hybrid photoionization properties for X = Cl, Br and I endohedrally confined in C60 are different before and after an electron transfers from C60 to the halogen. It was further found as a rule that the ionization dynamics is insensitive to the C60level the electron originates from to produce X–@C60+ . In the current study, we report an exception to this rule in F@C60. It is found that when the electron vacancy is situated in the C60level that participates in the hybridization in F–@C60+, the mixing becomes dramatically large leading to strong modifications in the photoionization of the hybrid levels. This novel effect is fundamentally based on a level-crossing phenomenon driven by the electron transfer in F@C60. But when the vacancy is at any other pure level of C60, the level-invariance is retained showing weak hybridization. Even though this case of F@C60 is an exception in the halogen@C60 series, the phenomenon can be more general and can occur with compounds of other atoms caged in a variety of fullerenes. Possible experimental studies are suggested to benchmark the present results.

74 ATOMIC AND MOLECULAR PHYSICS↗

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermal hybrid exchange-correlation density functional for improving the description of warm dense matter

Finite-temperature density functional theory (FT-DFT) has become a standard tool for first principles calculations of the properties of warm dense matter (WDM) relevant to high-energy density physics (HEDP) applications. In this work we introduce theoretical grounds of thermal hybrid exchange-correlation (XC) functionals within the generalized Mermin-Kohn-Sham scheme for an improved description of WDM. Building on the previously developed KSDT (Karasiev-Sjostrom-Dufty-Trickey) [Karasiev et al., Phys. Rev. Lett. 112, 076403 (2014)] local density approximation (LDA) and the KDT16 (Karasiev-Dufty-Trickey 2016) [Karasiev et al., Phys. Rev. Lett. 120, 076402 (2018)] generalized-gradient approximation (GGA) XC free-energy density functionals, we construct a new thermal hybrid XC functional, referred to here as KDT0. The KDT0 model at low temperature reduces to the popular ground-state PBE0 hybrid due to properties of the used KDT16 density functional approximation. Application to static calculations of electronic band gap and band structure at a wide range of temperatures for various systems of interest to HEDP show that KDT0 provides a significant improvement to the lower LDA and GGA rung XC functionals and to the ground-state PBE0 hybrid.

36 MATERIALS SCIENCE↗

Multiband superconductivity in strongly hybridized 1 T ' - WTe 2 / NbSe 2 heterostructures

The interplay of topology and superconductivity has become a subject of intense research in condensed-matter physics for the pursuit of topologically nontrivial forms of superconducting pairing. An intrinsically normal-conducting material can inherit superconductivity via electrical contact to a parent superconductor via the proximity effect, usually understood as Andreev reflection at the interface between the distinct electronic structures of two separate conductors. However, at high interface transparency, strong coupling inevitably leads to changes in the band structure, locally, owing to hybridization of electronic states. Here, we investigate such strongly proximity-coupled heterostructures of monolayer $1T$' - $\mathrm{WTe_2}$ grown on NbSe 2 by van der Waals epitaxy. The superconducting local density of states, resolved in scanning tunneling spectroscopy down to 500 mK, reflects a hybrid electronic structure well described by a multiband framework based on the McMillan equations which captures the multiband superconductivity inherent to the NbSe 2 substrate and that is induced by proximity to $\mathrm{WTe_2}$ self-consistently. Our material-specific tight-binding model captures the hybridized heterostructure quantitatively and confirms that strong interlayer hopping gives rise to a semimetallic density of states in the two-dimensional $\mathrm{WTe_2}$ bulk, even for nominally band-insulating crystals. The model further accurately predicts the measured order parameter Δ ≅ 0.6 meV induced in the $\mathrm{WTe_2}$ monolayer bulk, stable beyond a 2 T magnetic field. So we believe that our detailed multiband analysis of the hybrid electronic structure provides a useful tool for sensitive spatial mapping of induced order parameters in proximitized atomically thin topological materials.

36 MATERIALS SCIENCE↗

g -mode oscillations in hybrid stars: A tale of two sounds

We study the principal core g-mode oscillation in hybrid stars containing quark matter and find that they have an unusually large frequency range ( ≈ 200 - 600 Hz) compared to ordinary neutron stars or self-bound quark stars of the same mass. Theoretical arguments and numerical calculations that trace this effect to the difference in the behaviour of the equilibrium and adiabatic sound speeds in the mixed phase of quarks and nucleons are provided. We propose that the sensitivity of core g-mode oscillations to non-nucleonic matter in neutron stars could be due to the presence of a mixed quark-nucleon phase. Based on our analysis, we conclude that for binary mergers where one or both components may be a hybrid star, the fraction of tidal energy pumped into resonant g-modes in hybrid stars can exceed that of a normal neutron star by a factor of 2-3, although resonance occurs during the last stages of inspiral. A self-bound star, on the other hand, has a much weaker tidal overlap with the g-mode. The cumulative tidal phase error in hybrid stars, ΔΦ = 0.5 rad, is comparable to that from tides in ordinary neutron stars, presenting a challenge in distinguishing between the two cases. Furthermore, should the principal g-mode be excited to sufficient amplitude for detection in a postmerger remnant with quark matter in its interior, its frequency would be a possible indication for the existence of non-nucleonic matter in neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Anisotropic c – f Hybridization in the Ferromagnetic Quantum Critical Metal CeRh 6 Ge 4

Heavy fermion compounds exhibiting a ferromagnetic quantum critical point have attracted considerable interest. Common to two known cases, i.e., CeRh 6 Ge 4 and YbNi 4 P 2 , is that the 4f moments reside along chains with a large interchain distance, exhibiting strong magnetic anisotropy that was proposed to be vital for the ferromagnetic quantum criticality. Here, we report an angle-resolved photoemission study on CeRh 6 Ge 4 in which we observe sharp momentum-dependent 4f bands and clear bending of the conduction bands near the Fermi level, indicating considerable hybridization between conduction and 4f electrons. The extracted hybridization strength is anisotropic in momentum space and is obviously stronger along the Ce chain direction.The hybridized 4f bands persist up to high temperatures, and the evolution of their intensity shows clear band dependence. Our results provide spectroscopic evidence for anisotropic hybridization between conduction and 4f electrons in CeRh 6 Ge 4 , which could be important for understanding the electronic origin of the ferromagnetic quantum criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reconciling monolayer and bilayer Jeff = 1/2 square lattices in hybrid oxide superlattice

The number of atomic layers confined in a two-dimensional structure is crucial for the electronic and magnetic properties. Single-layer and bilayer J eff = 1/2 square lattices are well-known examples where the presence of the extra layer turns the XY anisotropy to the c-axis anisotropy. We report on experimental realization of a hybrid SrIrO 3 /SrTiO 3 superlattice that integrates monolayer and bilayer square lattices in one layered structure. By synchrotron x-ray diffraction, resonant x-ray magnetic scattering, magnetization, and resistivity measurements, we found that the hybrid superlattice exhibits properties that are distinct from both the single-layer and bilayer systems and cannot be explained by a simple addition of them. In particular, the entire hybrid superlattice orders simultaneously through a single antiferromagnetic transition at temperatures similar to the bilayer system but with all the J eff = 1/2 moments mainly pointing in the ab plane similar to the single-layer system. The results show that bringing monolayer and bilayer with orthogonal properties in proximity to each other in a hybrid superlattice structure is a powerful way to stabilize a unique state not obtainable in a uniform structure.

2-dimensional systems↗

Range-separated thermal hybrid exchange-correlation density functional for accurate band-gap calculations of warm dense matter

Here, in this study, we present a range-separated thermal hybrid exchange-correlation (XC) functional, termed RS-KDT0, which provides highly accurate band-gap predictions at elevated temperature while reducing the computational cost relative to thermal global hybrid functionals. At zero temperature, RS-KDT0 recovers the widely used ground-state range-separated hybrid functional HSE06. To assess its performance across temperature regimes, we conducted static calculations of electronic pressure, band gaps, and band structures. RS-KDT0 exhibits the same level of accuracy as HSE06 in the low-temperature regime and demonstrates improved agreement with finite-temperature GW calculations at elevated temperatures when compared to other thermal XC functionals such as the generalized gradient approximation (GGA)-level KDT16 and the global hybrid KDT0.

density functional theory↗

Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Cuillier, Paul↗

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows

In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities by scheduling data analytics close to the data source. Hybrid in-situ processing splits data analytics into two stages: the data processing that runs in-situ aims to extract regions of interest, which are then transferred to staging services for further in-transit analytics. To facilitate this type of hybrid in-situ processing, the data staging service needs to support complex intermediate data representations generated/consumed by the in-situ tasks. Unstructured (or irregular) mesh is one such derived data representation that is typically used and bridges simulation data and analytics. However, how staging services efficiently support unstructured mesh transfer and processing remains to be explored. This paper investigates design options for transferring and processing unstructured mesh data using staging services. Using polygonal mesh data as an example, we show that hybrid in-situ workflows with staging-based unstructured mesh processing can effectively support hybrid in-situ workflows, and can significantly decrease data movement overheads.

data-driven↗

Paired Hydro-Battery Hybrid System Operations Using MIQP Based Multi-Objective Optimization

Hybridizing a hydropower plant with a battery energy storage system is often a very expensive decision. So to make the case for feasibility of hybridization the cost benefit analysis must be comprehensive. Most literature found on this subject only uses one out of many different available value streams to carry out a feasibility analysis. To that end, in this study we propose a multi-objective optimization formulation and a mixed-integer quadratic programming optimization engine that considers multiple different value streams and optimizes hydro-battery hybrid system paired operations to maximize revenue generated from energy arbitrage while simultaneously minimizing the total hydro turbine mileage thus reducing turbine starts and stops and improving turbines life all while following all environmental constraints and not violating any limitations either regulatory or preferential (i.e., to support recreational activities like white water rafting, etc.). In this study we also implemented the developed optimization methodology to a real-world case study of Bagnell dam hydropower facility (8 units totaling 240 MW rated power capacity) which is owned and operated by our industry partner Ameren Energy Inc. The case study outcomes shows that by hybridizing the Bagnell dam hydropower facility with a 60 MW x 2-hr battery energy storage system, the annual benefits can be increased over \$6 million while reducing the annual mileage averaged per turbine and number of start/stops by over 98\% and 85\% respectively.

Chalishazar, Vishvas H.↗

Hybrid Power Plant Bidding in Models of Future Electricity Systems

This paper proposes a stochastic model for hybrid power plants participation in day-ahead electricity markets, considering uncertainty in market prices and renewable generation. Additionally, it presents a methodology to incorporate this hybrid participation into existing production cost models (PCM), allowing the analysis and market design of future systems with high penetration of hybrids. These developments are illustrated using a wind-battery hybrid located in New York Independent System Operator (NYISO) footprint.

Kemp, Julie Mulvaney↗

Quantum Engineering With Hybrid Magnonic Systems and Materials (Invited Paper)

Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitations or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and exibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization.

42 ENGINEERING↗

Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture

Finding, characterizing and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19 933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. Here we provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement.

59 BASIC BIOLOGICAL SCIENCES↗

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Engineering↗