Multidimensional Field Research Articles

The analytic field as bipersonal and multidimensional container

The title of this article encapsulates an approach to the notion of the analytic field where the contributions of the Barangers and Bion converge, opening up new perspectives that the author began to explore together with Antonino Ferro in the late 1980s and early 1990s. While the explicit formulation of a bipersonal field model should be credited to the Barangers, it is perhaps less widely known that the term “field” also features in Bion’s writings, with a meaning that is often generic but occasionally bears more specific connotations: for example, when he assimilates the analytic situation into a multidimensional field. In the light of Bion’s theory of thinking, the unconscious dynamics of the analytic field is determined not only by crossed projective identifications, but also by the dream-work of the couple, resulting from the alpha-function of both subjects. Thus, the Barangers’ concept of bastions can be combined with that of functional aggregates (Bezoari and Ferro), understood as animated holograms allowing a shared representation of the ongoing emotional experiences.

Design Strategies and Applications of Dimensional Optical Field Manipulation Based on Metasurfaces.

Recent rapid progress in metasurfaces is underpinned by the physics of local and nonlocal resonances and the modes coupling among them, leading to tremendous applications such as optical switching, information transmission, and sensing. In this review paper, we provide an overview of the recent advances in a broad range of dimensional optical field manipulation based on metasurfaces categorized into different classes based on design strategies. We start from the near-field optical resonances of artificial nanostructures and discuss the far-field optical wave manipulation based on fundamental mechanisms such as mode generation and mode coupling. We summarize the recent advances in optical field manipulation based on metasurfaces in different optical dimensions such as phase and polarization and discuss newly-developed dimensions, such as the orbital angular momentum and the coherence dimensions resulting from phase modulation. Then, we review the recent achievements of multiplexing and multifunctional metasurfaces empowered by multidimensional optical field manipulation for optical information transmission and integrated applications. Finally, we conclude with a few perspectives on emerging trends, possible directions, and existing challenges in this fast-developing field. This article is protected by copyright. All rights reserved.

Mapping 26years of climate change research in finance and accounting: a systematic scientometric analysis.

Climate change and climate finance continue to attract substantial research interest in several dimensions and categories through COVID-19 breakout and resulting disruptions were crucial. An in-depth scientometric analysis was undertaken to gain concise insights on evolution and publication trends of this multi-dimensional field. Corpus of 657 articles, extracted from Web of Science from 1995 to 2020, were used to identify networks of co-authorship, keywords, subject categories, institutions, and countries engaged in publishing on climate finance along with co-citation and cluster analysis. Networks and interactive visualizations created using CiteSpace revealed new research areas where climate finance may be beneficial along with potential directions of development for climate finance discipline. We identify carbon neutrality, accounting for sustainability, planetary boundaries framework, sustainable finance, managing climate risk for third pole, financial innovation and green finance, green swans, COVID pandemic and corporate law and governance in climate finance as emerging domains of climate finance research, seeking overwhelming research attention globally.

Reconstruction of Unsteady Wind Field Based on CFD and Reduced-Order Model

Short-term wind power forecasting is crucial for updating the wind power trading strategy, equipment protection and control regulation. To solve the difficulty surrounding the instability of the statistical model and the time-consuming nature of the physical model in short-term wind power forecasting, two innovative wind field reconstruction methods combining CFD and a reduced-order model were developed. In this study, POD and Tucker decomposition were employed to obtain the spatial–temporal information correlation of 2D and 3D wind fields, and their inverse processes were combined with sparse sensing to reconstruct multi-dimensional unsteady wind fields. Simulation and detailed discussion were performed to verify the practicability of the proposed algorithms. The simulation results indicate that the wind speed distributions could be reconstructed with reasonably high accuracy (where the absolute velocity relative error was less than 0.8%) using 20 sensors (which only accounted for 0.04% of the total data in the 3D wind field) based on the proposed algorithms. The factors influencing the results of reconstruction were systematically analyzed, including all-time steps, the number of basis vectors and 4-mode dimensions, the diversity of CFD databases, and the reconstruction time. The results indicated that the reconstruction time could be shortened to the time interval of data acquisition to synchronize data acquisition with wind field reconstruction, which is of great significance in the reconstruction of unsteady wind fields. Although there are still many studies to be carried out to achieve short-term predictions, both unsteady reconstruction methods proposed in this paper enable a new direction for short-term wind field prediction.

Rings Generated by Convergence Sets of Multidimensional Complete Field

The convergence sets of a multidimensional complete field are those having the property that all power series over it converge when substituting an element of the maximal ideal for a variable. It is proved that a convergence set lies in the ring of integers if and only if it is contained in some convergence ring.

Continuum perturbation field in quiescent ambience: Common foundation of flows and acoustics

Here, the perturbation equation for a dissipative medium is derived from the first principles for the linearized compressible Navier–Stokes equation without Stokes' hypothesis. Dispersion relations of this generic governing equation are obtained, which exhibits both the dispersive and dissipative nature of perturbations traveling in a dissipative medium, depending upon the length scale. We specifically provide a theoretical cutoff wave number above which the perturbation equation represents diffusive and dissipative nature of the quiescent flow. It is shown that perturbation equations for pressure and velocity retain the same form in one-dimension, but it is not the same for multi-dimensional perturbation fields. Such behavior has not been reported before, as per the knowledge of the authors.

Turning in the landscape: A new mechanism for generating primordial black holes

We propose a new model-independent mechanism for producing primordial black holes from a period of multi-field inflation. This requires an enhancement of primordial fluctuations at short scales compared to their value at CMB scales. We show that such an amplification naturally occurs when the inflationary trajectory exhibits a strong turn, that is a limited period during which the trajectory strongly deviates from a geodesic in field space, and is sufficient for subsequently producing primordial black holes with the abundance to be all or a fraction of dark matter. Our mechanism is generic to models of inflation realized in a multi-dimensional field space with an overlying potential and geometry, also referred to as the inflationary landscape, as arises in embeddings of inflation in high-energy theories. We study analytically and numerically how the duration and the strength of the turn impact the primordial fluctuation power spectrum and the abundance of primordial black holes. Our mechanism has the potential of exhibiting unique features accessible to observation through the primordial black hole spectrum and the stochastic background of gravitational waves, offering a precious glimpse at the dynamics of inflation.

Recovering density disturbance spectra from FLDI. Part 2: comparisons with previous methods.

An exact analytical method for recovering density disturbance spectra in multi-frequency, multi-dimensional fields from focused laser differential interferometry (FLDI) measurements, developed in Part 1 [Appl. Opt.62, 3042 (2023)APOPAI0003-693510.1364/AO.480352], is compared with previous methods for quantitative interpretation of FLDI. It is shown that previous exact analytical solutions can be recovered as special cases of the more general present method. It is also found that despite outwards dissimilarity, a previous approximate method that is becoming widely used can be related to the general model. It is demonstrated that the previous approach-while a suitable approximation for spatially restricted disturbance fields such as conical boundary layers it was originally applied to-does not work well in general applications. While corrections can be made, informed by results from the exact method, doing so offers no computational or analytical advantages.

Monocular metasurface camera for passive single-shot 4D imaging

It is a grand challenge for an imaging system to simultaneously obtain multi-dimensional light field information, such as depth and polarization, of a scene for the accurate perception of the physical world. However, such a task would conventionally require bulky optical components, time-domain multiplexing, and active laser illumination. Here, we experimentally demonstrate a compact monocular camera equipped with a single-layer metalens that can capture a 4D image, including 2D all-in-focus intensity, depth, and polarization of a target scene in a single shot under ambient illumination conditions. The metalens is optimized to have a conjugate pair of polarization-decoupled rotating single-helix point-spread functions that are strongly dependent on the depth of the target object. Combined with a straightforward, physically interpretable image retrieval algorithm, the camera can simultaneously perform high-accuracy depth sensing and high-fidelity polarization imaging over an extended depth of field for both static and dynamic scenes in both indoor and outdoor environments. Such a compact multi-dimensional imaging system could enable new applications in diverse areas ranging from machine vision to microscopy.

Two dimension-reduction probabilistic models for simulating nonstationary turbulent wind fields

The reasonable modeling of a nonstationary stochastic turbulent wind field is an important basis and premise for the analysis of the wind-induced response and reliability of engineering structures. In the present study, two dimension-reduction probabilistic models are established for simulating the multi-dimensional and multi-variable nonstationary turbulent wind fields based on the double proper orthogonal decomposition (DPOD) and the double spectral representation method (DSRM). Among them, the DPOD, originally used to simulate a stationary turbulent wind field, is extended to a nonstationary one, and the DSRM is a newly proposed method for a nonstationary turbulent wind field with a large number of simulation points. In essence, the DPOD is a discrete method with explicit physical significance and flexible spatial location of simulation points, while the DSRM is a continuous method, of which the simulation efficiency is theoretically independent of the number of simulation points. Furthermore, by introducing the dimension-reduction methods based on random function and POD-FFT (Fast Fourier transform) technique into the DPOD and the DSRM, the nonstationary stochastic turbulent wind field can be effectively described with merely three elementary random variables. Numerical examples of the nonstationary stochastic turbulent wind fields acting on a long-span bridge and a communication tower fully verify the effectiveness and superiority of the proposed methods.

Multidimensional Optimization of CSM With Different Algorithms for Investigating the Electric Field in the Vicinity of a Point Electrode

In this article, the combined charge simulation method (CSM) with the optimization methods for calculating the electric field produced by a point electrode (hyperbolic needle) is introduced. The simulation has been carried out using the combination between ring charges and finite line charges with variable charge density for the onset field simulation. In CSM, the combination of different types of these fictitious charges increases the degree of consistency between the results and avoids disparity. To determine the location of these charges, three different optimization algorithms are used [particle swarm optimization (PSO), gray wolf optimization (GWO), and bald eagle search (BES)] as a comparative case study. The presented model for investigating the electric field due to a point electrode is a multidimensional field problem. Optimization results and discussion confirm that the BES results, compared with other used algorithms, are the best results and offer the most stable performance with repeated operations. The best value of maximum percent error of electric field is 0.068 using the BES algorithm. Finally, the simulation results have been compared with the available analytical results, at axial line of needle-to-plane configuration, and previous works.

A discrete spectral contributions based statistical narrow-band model for high-temperature combustion systems

In this work, we present a discrete spectral contribution based statistical narrow-band model (DSC-SNB) to solve the radiative transfer of high-temperature combustion systems, which employs a discrete spectral strategy to considerably improve the accuracy of the traditional SNB model. Based on the contribution of different gases to radiation, the DSC-SNB model divides the spectral lines into different groups within the spectral interval based on the low-level transition energies (E“). Treating the Line-by-Line (LBL) approach as the benchmark solution, several inhomogeneous high-temperature H2O-CO2-CO mixture columns are adopted to evaluate the DSC-SNB model. Results show that the DSC-SNB model performance is comparable with the traditional SNB model for isothermal gas mixture columns. The DSC-SNB model exhibits high accuracy under mid-high temperature or pure high temperature without low-temperature wrapping, outperforming the traditional SNB model. These findings could be used to reconstruct the multi-dimensional flame temperature field by building a highly accurate and efficient mathematical model for flame radiation prediction.

Advances in Multi-Dimensional Light Field Modulation Based on Liquid Crystal

Advances in Multi-Dimensional Light Field Modulation Based on Liquid Crystal

Multi-Dimensional Light Field Manipulation by Metasurfaces and Holographic Display Technology

Multi-Dimensional Light Field Manipulation by Metasurfaces and Holographic Display Technology

Характеристики социального поля спорта: некоторые элементы теории П. Бурдье

The article raises the problem of transformation of modern society sports space affecting the public perception of sports activities and actors involved in it. The aim of the scientific article is to identify the characteristics of the sports social field through the prism of sociological cognition of social space by P. Bourdieu. As a result, the description of the sports field was made using the following identified characteristics: integration into the body of society; hierarchical structure of the sports field; the ability of the sports field of to transform; practical meaning of the field; dynamic development of the field; oppositional nature of the field of sports; social field; the ability of the sports field to subordinate the agents; multidimensional social sport field; ability of the sports field of to influence other fields and society itself; realization of the concept of recognition in the sports field of social space. The existence and development of the social field of modern sports is possible only under the combination of the theory of rational choice and the theory of practical sense.

Development of a model for stochastic analysis of vehicle–track interaction considering spatial variability of track parameters

In this work, a model for achieving stochastic analysis of vehicle–track interaction systems is proposed based on random field realization of track parameters and the finite element coupling of rigid-elastic bodies. Aiming at the clarification of the spatial variability and correlation of track parameters on the influence of vehicle–track dynamic performance, a general scheme based on Karhunen–Loève Expansion and cyclic calculation method is developed to realize a multi-dimensional random field that holds an arbitrary marginal distribution function and correlation structure, and to consider the inhomogeneity of system parameters along the longitudinal direction efficiently. Furthermore, the validation of the random field expansion against the vehicle–track system is implemented, and the dynamic effects of random track parameters are investigated through two special issues. Numerical results show that the spatial correlation of fastener stiffness affects the extreme response, especially the low-frequency component of rail displacement. The spatial dependence of the filling layer has little influence on the dynamic behavior of the vehicle subsystem, but it obviously changes the extreme stress and strain of the filling layer. Ignoring the spatial correlation of random variables might underestimate the performance of the track system.

Cultivation of Humanity: How we can stagnate within the eternal flow

By introducing Taoism— the understanding of flow—and the meaning of cultivation as a basic human ability, an essential challenge in our current understanding of science can be discovered. Human interaction with nature is a meaningful process, which can reveal a better understanding of the inner cultivation processes and with it a multidimensional field of endless inputs triggering an ongoing process of growth. For this purpose, MyCu-cultivation ( My cultural cultivation) is introduced as new terminology. A construct that allows to separately elaborate the social concepts of culture and the process of metaphysical reality perception—generated in our mind. At the same time, the layers of physical experienced reality and imagination are reintroduced in an alternative interrelation, leading to new insights in the layers of metaphysical understandings. Therefore, the central manifestation of meaning-making will be elaborated through the metaphorical use of bookshelves, allowing to perceive new insights in the raw information processing of individuals—underlining the human limitations, in processing the overwhelming meaning flow. This theoretical knowledge leads us further to a new possibility of understanding the constructive externalization of the imagination, highlighting the diversity of phenomenological insights in our everyday life, resulting in a complex theoretical repositioning between semiotics, cultural psychology, and Naturwissenschaften.

Computational spectropolarimetry with a tunable liquid crystal metasurface

While conventional photodetectors can only measure light intensity, the vectorial light field contains much richer information, including polarization and spectrum, that are essential for numerous applications ranging from imaging to telecommunication. However, the simultaneous measurement of multi-dimensional light field information typically requires the multiplexing of dispersive or polarization-selective elements, leading to excessive system complexity. Here, we demonstrate a near-infrared spectropolarimeter based on an electrically-tunable liquid crystal metasurface. The tunable metasurface, which acts as an encoder of the vectorial light field, is tailored to support high-quality-factor guided-mode resonances with diverse and anisotropic spectral features, thus allowing the full Stokes parameters and the spectrum of the incident light to be computationally reconstructed with high fidelity. The concept of using a tunable metasurface for multi-dimensional light field encoding may open up new horizons for developing vectorial light field sensors with minimized size, weight, cost, and complexity.

Tensor Calculus in Digital Colorimetry

Any object can have many implementations in the form of digital images and any digital image can be processed many times increasing or decreasing accuracy and reliability. Digital colorimetry faces the need to work out issues of ensuring accuracy, metrological traceability and reliability. The purpose of this work was to generalize approaches to the description of multidimensional quantized spaces and show the possibilities of their adaptation to digital colorimetry. This approach will minimize the private and global risks in measurements.For color identification digital colorimetry uses standard color models and spaces. Most of them are empirical and are improved during the transition from standard to real observation conditions taking into account the phenomena of vision and the age of observers. From the point of view of measurement, a digital image can be represented by a combinatorial model of an information and measurement channel with the appearance of the phenomenon of a color covariance hypercube requiring a significant amount of memory for data storage and processing. The transition from the covariance hypercube to high-dimensional matrices and tensors of the first, second and higher ranks provides the prospect of optimizing the color parameters of a digital image by the criterion of information entropy.Tensor calculus provides opportunities for expanding the dynamic range in color measurements describing multidimensional vector fields and quantized spaces with indexing tensors and decomposing them into matrices of low orders.The proposed complex approach based on tensor calculus. According to this approach the color space is a set of directed vector fields undergoing sampling, quantization and coding operations. Also it is a dynamic open system exchanging information with the environment at a given level and to identify color with specified levels of accuracy, reliability, uncertainty and entropy.

A novel eigenvalue-based iterative simulation method for multi-dimensional homogeneous non-Gaussian stochastic vector fields

The generation of sample functions of stochastic fields or processes is a prerequisite to use the Monte Carlo method in stochastic mechanics and structural reliability analysis. When it comes to non-Gaussian characteristics such as the spatial variability of material or structural properties, the simulation of multi-dimensional non-Gaussian stochastic vector fields becomes necessary. However, the conventional Cholesky decomposition-based iterative simulation method requires three times of decomposition operations at each iteration and a complex procedure of random shuffle, which inevitably augment the model complexity. To this end, this study develops a novel eigenvalue-based iterative simulation method which only requires one decomposition operation in the whole simulation process. Central to this method is to represent the cross power spectral density matrix with its eigenvalue matrix during the iteration procedure, which avoids the cumbersome Cholesky decomposition and random shuffle procedure. Meanwhile, it can yield unique convergence result and present a powerful ability in addressing cases with the complex-valued spectral matrix. Numerical example demonstrates that the proposed method has a similar accuracy as that of the Cholesky decomposition-based iterative simulation method. Meanwhile, the estimated cumulative distribution function from one simulated sample and the estimated ensemble correlation function from 1000 simulated samples are all consistent with their respective targets. In addition, the sensitive analysis is performed to demonstrate that the proposed method has a relatively wide applicability. Therefore, this method may have a great potential to simulate multi-dimensional homogeneous non-Gaussian stochastic vector fields in practice.