Two-dimensional Configuration Research Articles

Solving optimization problems with local light-shift encoding on Rydberg quantum annealers

We provide a non-unit-disk framework to solve combinatorial optimization problems such as maximum cut and maximum independent set on a Rydberg quantum annealer. Our setup consists of a many-body interacting Rydberg system where locally controllable light shifts are applied to individual qubits in order to map the graph problem onto the Ising spin model. Exploiting the flexibility that optical tweezers offer in terms of spatial arrangement, our numerical simulations implement the local-detuning protocol while globally driving the Rydberg annealer to the desired many-body ground state, which is also the solution to the optimization problem. Using optimal control methods, these solutions are obtained for prototype graphs with varying sizes at timescales well within the system lifetime and with approximation ratios close to one. The nonblockade approach facilitates the encoding of graph problems with specific topologies that can be realized in two-dimensional Rydberg configurations and is applicable to both unweighted as well as weighted graphs. A comparative analysis with fast simulated annealing is provided which highlights the advantages of our scheme in terms of system size, hardness of the graph, and the number of iterations required to converge to the solution. Published by the American Physical Society 2024

Effect of Surface Roughness on Aerodynamic Loads of Bluff Body in Vicinity of Smoothed Moving Wall

This paper contributes to a new Lagrangian vortex method for the statistical control of turbulence in two-dimensional flow configurations around a rough circular cylinder in ground effect when considering higher subcritical Reynolds numbers, namely 3 × 104 ≤ Re ≤ 2 × 105. A smoothed moving wall (active control technique) is used to include the blockage effect in association with the variation in cylinder surface roughness (passive control technique), characterizing a hybrid approach. In contrast with the previous approaches of our research group, the rough cylinder surface is here geometrically constructed, and a new momentum source term is introduced and calculated for the investigated problem. The methodology is structured by coupling the random Discrete Vortex Method, the Lagrangian Dynamic Roughness Model, and the Large Eddy Simulation with turbulence closure using the truncated Second-Order Velocity Structure Function model. This methodological option has the advantage of dispensing with the use of both a refined near-wall mesh and wall functions. The disadvantage of costly processing is readily solved with Open Multi-Processing. The results reveal that intermediate and high roughness values are most efficient for Reynolds numbers on the orders of 105 and 104, respectively. In employing a moving wall, the transition from the large-gap to the intermediate-gap regime is satisfactorily characterized. For the conditions studied with the hybrid technique, it was concluded that the effect of roughness is preponderant and acts to anticipate the characteristics of a lower gap-to-diameter ratio regime, especially with regard to intermittency.

All-in-one: Multi-parameter engineering on γ-Fe2O3 for ultra-broadband microwave absorption

The functionality and property of materials are normally controlled by changing their composition, defects, morphology, lattice, crystallinity, etc. However, achieving a wide effective absorption bandwidth through multiple-parameter optimization is less reported. Simultaneously adjusting these parameters can serve as an effective control knob to increase dielectric loss, including conduction and polarization, thereby providing a broadband absorption toward radiated microwave for potential applications. Herein, magnetic γ-Fe2O3 in a two-dimensional configuration was synthesized through a molten salt process, which was further modified by Co and Al heteroatoms to facilitate more polarization processes. The reinforcement of conduction loss is achieved by increasing the crystallinity of the absorber, which facilitates the rapid transfer of free electrons and reduces scattering. Controlled alkaline etching was employed to extract a portion of the intercalated Al atoms. Henceforth, appropriate lattice distortion and numerous O vacancies are constructed, which can not only generate new polarization centers on the absorber matrix but also maintain a high crystalline structure with good conduction loss feature. In addition, the magnetic loss and impedance matching characters are optimized. As a result, the composition, structure, defects, and crystallinity of magnetic γ-Fe2O3 nanosheets have all been optimized, which enable an impressive microwave absorption performance with an effective absorption bandwidth of 7.82 GHz and a minimum reflection loss of −54.9 dB. This work explores improving the electromagnetic parameters of absorbers through collaborative regulation of multiple parameters and provides guidance for a novel and facile strategy for controlling microwave absorbers.

Instabilities of a circular moderately dense particle cloud impacted by an incident shock

Shock-driven gas-particle flows exist in a wide variety of physical systems, covering the range from dilute to dense regime. There are a lot of fundamental questions remaining to be answered, like the evolutions of flow instability, two-phase interactions, and inter-particle collision effects. In this work, the Eulerian-Lagrangian approach with gas-particle four-way coupling is applied to model two-dimensional shock-driven gas-particle flow under the moderately dense regime. For the gas flow, the formation mechanism of primary and secondary vortexes is discussed. The primary vortex is caused by the roll-up of slip line, while the secondary vortexes are induced by the velocity and density difference between the penetrating flow of particle-laden zone and the outside mainstream. Parametric studies of different Mach numbers, particle diameters and initial volume fractions have been performed to investigate the effects on shock behaviours and slip line instabilities. For the particle phase, a high-volume-fraction compression region forms at the upstream cloud zone, which blocks the penetrating gas, and results in the formation of slip line. The cloud tail is mainly composed of the upstream edge particles. The inter-particle collisions have impact on the particle distributions, and greatly affect the slip line stability at the upstream cloud edge. This work provides valuable insights into the instability mechanism of compressible gas-solid flow and the particle dispersion behaviours. However, it is important to note that our analysis is based on a two-dimensional configuration. In a real three-dimensional context, the generation of vortices is likely to differ, and may affect the particle dynamics to a certain degree.

Study of image reconstruction method for 2D gamma scan technique by anti-aliasing line "Xiaolin Wu" algorithm combined with simultaneous algebraic reconstruction algorithms and testing on MCNP simulation data

Gamma scanning technique is known to be an effective method for survey the condition of distillation columns in petrochemical refineries and has been widely applied. The result of the gamma scanning is a 1-dimensional graph showing the transmittance counts according to the height of the column. To illuminate the important phenomena occurring on the tray such as foaming; flooding; weeping due to valve failure on the tray needs experienced people and the interpretation results are still quite qualitative. The method of 2-D gamma scanning and reconstruction (2D Tomography), which has just appeared in the world in recent years, is considered as a potential method to help detect the above phenomena. This report presents the two-dimensional gamma scanning configuration, mathematical calculation and noise processing methods by using the combination of Xiaolin Wu’s line drawing algorithm with simultaneous algebraic reconstruction algorithm (SART) based on data from Monte Carlo simulation.

Effect of gas temperature on carbon soot oxidation via non-thermal plasma: two-dimensional numerical study integrating reactive flow and discharge models.

Non-thermal plasma (NTP) efficiently regenerates diesel particulate filters by oxidizing carbon soot (CS) at low temperatures. However, numerical studies on the spatial characteristics of CS oxidation by NTP are scarce. In addition, the influence of background gas heating on the CS-oxidizing performance by NTP remains inadequately understood. This research investigates the impact of gas temperature (323-573K) on heterogeneous CS oxidation using NTP in a two-dimensional configuration. The results indicate that CS is mainly oxidized by [Formula: see text], [Formula: see text], and [Formula: see text] during NTP treatment. The energy efficiency of CS removal by NTP ranges from 0.1 to 2.6g kWh-1 for varying gas temperature and applied voltage, consistent with previous research. Higher gas temperatures enhance both CS removal rate and efficiency, whereas higher applied voltages enhance rate at the expense of efficiency. The study also assesses energy conversion efficiency from electrical power input to chemical bonding energy during CS oxidation by NTP, yielding 0.03 to 0.23% efficiency for the considered gas temperature and voltage ranges, with higher temperatures leading to better efficiency.

Two-dimensional reductions of the Whitham modulation system for the Kadomtsev–Petviashvili equation

Two-dimensional reductions of the Kadomtsev–Petviashvili(KP)–Whitham system, namely the overdetermined Whitham modulation system for five dependent variables that describe the periodic solutions of the KP equation, are studied and characterized. Three different reductions are considered corresponding to modulations that are independent of x, independent of y, and of t (i.e. stationary), respectively. Each of these reductions still describes dynamic, two-dimensional spatial configurations since the modulated cnoidal wave, generically, has a nonzero speed and a nonzero slope in the xy plane. In all three of these reductions, the integrability of the resulting systems of equations is proven, and various other properties are elucidated. Compatibility with conservation of waves yields a reduction in the number of dependent variables to two, three and four, respectively. As a byproduct of the stationary case, the Whitham modulation system for the classical Boussinesq equation is explicitly obtained.

Structure of Current Sheets Formed in 2D Magnetic Configurations with X-Type Null Lines in the Presence of the Hall Currents and Inverse Currents

We present experimental results on the formation and evolution of current sheets in two-dimensional magnetic configurations with an X-type null line. Typical features of both the initial magnetic field and the current sheet are their symmetry properties. The experiments were carried out using the CS-3D setup. The formation of a current sheet occurs just after the magneto-sonic wave converges at the null line; then, both the electric current and plasma become compressed in a planar 2D sheet, which accumulates an excess of magnetic energy. The excitation of the Hall currents, which build up the out-of-plane magnetic fields inside the 2D current sheet, brings about the modification of the sheet structure. As a result, the magnetic fields and plasma currents become 3D. The dynamic plasma processes give rise to additional current sheet deformations, which are caused by the excitation of inverse currents at the side edges of the sheet. As a consequence, the out-of-plane magnetic fields are reversed, and strong Ampère’s forces of the opposite directions come into play. These forces slow down the previously accelerated high-speed plasma flows so that the flows become limited in time and space.

Heat Capacity of Indium or Gallium Sesqui-Chalcogenides.

The chalcogenides of p-block elements constitute a significant category of materials with substantial potential for advancing the field of electronic and optoelectronic devices. This is attributed to their exceptional characteristics, including elevated carrier mobility and the ability to fine-tune band gaps through solid solution formation. These compounds exhibit diverse structures, encompassing both three-dimensional and two-dimensional configurations, the latter exemplified by the compound In2Se3. Sesqui-chalcogenides were synthesized through the direct reaction of highly pure elements within a quartz ampoule. Their single-phase composition was confirmed using X-ray diffraction, and the morphology and chemical composition were characterized using scanning electron microscopy. The compositions of all six materials were also confirmed using X-ray photoelectron spectroscopy and Raman spectroscopy. This investigation delves into the thermodynamic properties of indium and gallium sesqui-chalcogenides. It involves low-temperature heat capacity measurements to evaluate standard entropies and Tian-Calvet calorimetry to elucidate the temperature dependence of heat capacity beyond the reference temperature of 298.15 K, as well as the enthalpy of formation assessed from DFT calculations.

Design and analysis of Cpm and Cpmk indices for uncertainty environment by using two dimensional fuzzy sets

Process capability analysis (PCA) is an important stage to check variability of process by using process capability indices (PCIs) that are very effective statistics to summarize process’ performance. Traditional PCIs can produce some incorrect results and declare misinterpretation about process’ quality if the process includes uncertainties. Additionally, definitions of process’ parameters with exact values is not possible when there are uncertainty caused by measurement errors, sensitivities of measuring instruments or quality engineers’ hesitancies. Although the fuzzy set theory (FST) has been successfully used in PCA, it is the first time to use of Pythagorean fuzzy sets (PFSs) to model uncertainties of process more than traditional fuzzy sets in PCA. Since the PFSs has two-dimensional configurations by defining membership and non-membership values, they also have a huge ability to model uncertainty that arises from the human’s thinking and hesitancies, and has brought flexibility, sensitivity and reality for PCA. In this paper, specification limits (SLs), mean (μp), standard deviation (σ) and target value (T) main parameters of PCIs have been analyzed by using PFSs and Pythagorean fuzzy process capability indices (PFPCIs) for two well-known PCIs such as ( C ˜ pm ) and ( C ˜ pmk ) have been derived. The Pythagorean ( C ˜ pm ) and ( C ˜ pmk ) indices have also been applied and tested on some numerical examples based on real case applications from manufacturing industry. The obtained results show that PFPCIs provide wider knowledge about capability of process and to obtain more realistic results. As a result of considering all possibilities about the process, it has been concluded that the process is incapable. In light of this information, the results obtained using different fuzzy set extensions for (Cpm) and (Cpmk) indices can be compared.

Dominant higher-order vortex gyromodes in circular magnetic nanodots.

The transition to the third dimension enables the creation of spintronic nanodevices with significantly enhanced functionality compared to traditional 2D magnetic applications. In this study, we extend common two-dimensional magnetic vortex configurations, which are known for their efficient dynamical response to external stimuli without a bias magnetic field, into the third dimension. This extension results in a substantial increase in vortex frequency, reaching up to 5 GHz, compared to the typical sub-GHz range observed in planar vortex oscillators. A systematic study reveals a complex pattern of vortex excitation modes, explaining the decrease in the lowest gyrotropic mode frequency, the inversion of vortex mode intensities, and the nontrivial spatial distribution of vortex dynamical magnetization noted in previous research. These phenomena enable the optimization of both oscillation frequency and frequency reproducibility, minimizing the impact of uncontrolled size variations in those magnetic nanodevices.

Transfer Learning Soft Sensor Modeling based on Two-dimensional Domain-adaption Stochastic Configuration Network

Transfer Learning Soft Sensor Modeling based on Two-dimensional Domain-adaption Stochastic Configuration Network

Experimental observation of two-dimensional phase in compressed FeF2

Iron difluoride (FeF2) has attracted considerable attention for its physical characteristics and practical applications, and its compression behaviors usually play a key role in the in-depth understanding of this compound. Since its high-pressure crystal structure evolution determining a more profound comprehension remains disputable, we carried out extensive experiments to focus on the pressure-induced structural phase transitions of FeF2. Through in situ high-pressure synchrotron x-ray diffraction measurements, we not only confirmed a reported high-pressure orthorhombic Pbca phase at 11 GPa but also identified an interesting two-dimensional structure with hexagonal close packed symmetry (P-3m1) that appears above 25 GPa at room temperature. Furthermore, the spontaneous strain fitting and electronic transport measurements suggest that its ambient rutile-type structure (P42/mnm) evolves into an orthorhombic structure (Pnnm) through a second-order phase transition at 5 GPa. These experimental results elaborate on the pressure-induced phase transitions of FeF2 on the order of P42/mnm → Pnnm → Pbca → P-3m1, shedding light on a rare three-dimensional to two-dimensional configuration transition in difluorides.

Visible metasurface using an Sb[formula omitted]S[formula omitted] nanodisk structure for stretchable color application

Herein, we examine a tunable phase-change material (PCM) metasurface that features an active switchable optical response, facilitating the excitation of electric dipole resonances within the visible wavelength spectrum. The tunability of this metasurface is realized by combining a PCM with a flexible polydimethylsiloxane (PDMS) substrate exhibiting a two-dimensional configuration. By adjusting the mechanical strain of the PDMS substrate, we can actively influence the near-field interactions among the resonant dielectric components, resulting in a broad spectrum of color changes. Furthermore, the overall color spectrum of the reflected light can be dynamically switched through the Sb2S3 amorphous-to-crystalline transition. This study highlights the constraints of traditional solid dielectric designs and provides novel perspectives and approaches for the advancement of tunable optical materials and devices.

A neural networks approach for designing compact all-optical photonic crystal based AND logic gate

Abstract This paper introduces a new method for creating an all-optical AND gate by utilizing a two-dimensional photonic crystal configuration for the first time. This gate design is intended for applications in optical computing and all-optical logic, offering the potential for rapid computation and parallel processing. The described gate is characterized by its compact dimensions and comprises two inputs and a single output. The high and low logic states are defined based on power values, where logic 0 corresponds to low power and logic 1 corresponds to high power emitted from the light source. To enhance the design process, artificial neural networks (ANNs) are utilized. ANNs offer a powerful tool for optimizing and fine-tuning the photonic crystal structure parameters to achieve the desired logic functionality. With the help of the applied ANNs, the design process is eased and high performance is achieved for the proposed photonic crystal structure. By integrating ANNs into the design process, this research opens up new possibilities for advancing the field of photonic logic circuits. Combining photonic crystals and ANN optimization provides a powerful approach to designing complex and efficient optical computing systems. The results show that the obtained power values are high for 1 logic state and low for the 0 logic state, which verifies the AND gate accuracy table. The achieved accurate results verify the validity of the proposed approach for achieving precise and reliable all-optical logic operations.

Subsets of without L-shaped configurations

Fix a prime $p\geq 11$. We show that there exists a positive integer $m$ such that any subset of $\mathbb {F}_p^n\times \mathbb {F}_p^n$ containing no nontrivial configurations of the form $(x,y)$, $(x,y+z)$, $(x,y+2z)$, $(x+z,y)$ must have density $\ll 1/\log _{m}{n}$, where $\log _{m}$ denotes the $m$-fold iterated logarithm. This gives the first reasonable bound in the multidimensional Szemerédi theorem for a two-dimensional four-point configuration in any setting.

Simulation of Interaction Processes of C20 Fullerene with Graphene

Graphene, a carbon sheet one atom thick, with carbon atoms arranged in a two-dimensional honeycomb configuration, has a number of intriguing properties. Fullerenes are a promising material for creating electro-active elements in solar cells and active layers in thin-film organic transistors. A computer model of the C20 fullerene molecule was constructed using the energy minimization method with the second-generation Brenner potential (REBO). A computer model of "infinite" defect-free graphene was built, designed to consider the process of adsorption of a C20 fullerene molecule on its surface. To study adsorption process computer models of fullerene and "infinite" graphene were approached to the required distance with a different set of geometric arrangement of fullerene with respect to the graphene surface. It has been established that the adsorption of fullerene C20 on the surface of graphene can be carried out in three different ways, differing in the number of interacting fullerene and graphene atoms. The binding energies and adsorption lengths for C20 fullerene molecules adsorbed on the graphene surface in different ways are calculated. The way of adsorption corresponding to the highest binding energy and the shortest adsorption length was revealed.

MHD and Cross-Diffusion Fluid Flow for Free Convection of Casson Fluid Due to A Stretching Cylinder

The present communication is dedicated for understanding the control of Lorentz force, Soret, Dufour effect and body force on the convection-free flow of Casson fluid on heat and mass transfer due to a stretching cylinder. For the considered two-dimensional physical configuration, a non-linear partial differential equation which are coupled are derived as a governing equation to study the behaviour of concentration, temperature and velocity which in turn modified to differential equations which are ordinary and non-linear by employing a suitable similarity transformation. A well-known shooting technique is employed to understand the characteristic variations of the fluid flow with the influence of some of the non-dimensional parameters viz., Schmidt’s, Reynolds number, Soret and Dufour parameters, Hartmann number, Prandtl number. These parameters take a vital role in controlling fluid flow, heat and mass transfer in various real problem applications. The present results are contrast with the results of earlier study as a particular case and good agreement is found.

Plasmonic bimetallic two-dimensional supercrystals for H2 generation

Sunlight-driven H2 generation is a central technology to tackle our impending carbon-based energy collapse. Colloidal photocatalysts consisting of plasmonic and catalytic nanoparticles are promising for H2 production at solar irradiances, but their performance is hindered by absorption and multiscattering events. Here we present a two-dimensional bimetallic catalyst by incorporating platinum nanoparticles into a well-defined supercrystal of gold nanoparticles. The bimetallic supercrystal exhibited an H2 generation rate of 139mmolgcat−1h−1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$139\\,{\\mathrm{mmol}}\\,{\\mathrm{g}}_{\\mathrm{cat}}^{-1}\\,{\\mathrm{h}}^{-1}$$\\end{document} via formic acid dehydrogenation under visible light illumination and solar irradiance. This configuration makes it possible to study the interaction between the two metallic materials and the influence of this in catalysis. We observe a correlation between the intensity of the electric field in the hotspots and the boosted catalytic activity of platinum nanoparticles, while identifying a minor role of heat and gold-to-platinum charge transfer in the enhancement. Our results demonstrate the benefits of two-dimensional configurations with optimized architecture for liquid-phase photocatalysis.

Efficient analysis of hydrological connectivity using 1D and 2D Convolutional Neural Networks

Understanding hydrological connectivity is essential to investigate ecological processes in river catchments and floodplains. Assessing flooding behavior, including flooded areas and connection times, is required to analyze hydrological connectivity in river floodplains. Deep learning, especially Convolutional Neural Networks (CNNs), is an attractive alternative to hydrodynamic modeling, which is more computationally expensive. This paper aims to develop a methodology to analyze the functional connectivity in remote and field measurement data-scarce areas using remote sensing data, CNN models, and connectivity metrics. The northern Lakes of the Narran River catchment, located in the Condamine–Balonne River floodplain in New South Wales, Australia, is the showcase for this method. One-dimensional CNN and two-dimensional U-Net configurations were applied and yielded comparable flood extents to the satellite images with Hit Rate values of 0.853 and 0.873, respectively. Two algorithms for determining hydrological connectivity were investigated, including the geostatistical Connectivity Function (CF) and the newly proposed Potential Connection Length (PCL). It was found that the connection along the main Narran River stream was more substantial than between the river and the floodplain lakes. The analysis using the PCL shows that the connectivity patterns in different stages of a flood event can vary depending on the initial condition of the floodplain. The overall conclusion from this work is that hydrological connectivity can be assessed computationally efficiently using only remote sensing, discharge data, and CNN models.