Configuration Space Research Articles

Kontsevich-Segal criterion in the no-boundary state constrains anisotropy

We show that the Kontsevich-Segal-Witten (KSW) criterion applied to the no-boundary state constrains anisotropic deformations of de Sitter space. We consider squashed S3 and S1×S2 boundaries and find that, in both models, the KSW criterion excludes a significant range of homogeneous but anisotropic configurations. For squashed S3 boundaries, the excluded range includes all surface geometries with negative scalar curvature, in line with dS/CFT reasoning. For S1×S2 boundaries, we find that KSW selects the low-temperature regime of configuration space where the S1 is sufficiently large compared to the S2. In both models, the KSW criterion renders the semiclassical wave function normalizable, up to one-loop effects. Published by the American Physical Society 2025

Resonant x-ray emission across the L3 edge of uranium compounds

Abstract A narrow bandwidth x-ray beamline and a multi-crystal von Hamos spectrometer were used to record x-ray absorption and x-ray emission (XES) across the uranium L 3 edge of UO2, UO3, Cs2UO2Cl4, and Cs2UCl6. Measurements were made over 17150–17250 eV with an instrumental resolution of ∼2 eV. This resolution allowed the use of Lorentzian peak fits to the L 3 N 4 and L 3 N 5 characteristic x-ray fluorescence lines that have ∼12–13 eV lifetime widths. The fluorescence yields of the four compounds display strong white lines near threshold and multiple scattering features at higher energies. The XES spectra were fit with three Lorentzians, two for the L 3 N 4 and L 3 N 5 lines and one for inelastic scattering by 2p–6d excitations and 4d–6d final states. The intensities of the white lines were largely due to the inelastic scattering component. To support the measurements, relativistic equation-of-motion coupled-cluster and restricted active space configuration interaction calculations were performed for uranium core-excitation energies in Cs2UO2Cl4 and Cs2UCl6. These calculations with rigorous treatments of relativistic effects are shown to provide accurate uranium L 3-edge binding energies, L 3 N 5 emission energies, as well as the energy losses in the inelastic scattering process. The measured and calculated results show variations between compounds with U(IV) oxidation states that contain 6d05f2 electrons in their ground configurations (UO2 and Cs2UCl6) compared with U(VI) compounds (UO3 and Cs2UO2Cl4) with empty 5f and 6d configurations.

Investigating the influence of urban green spaces on urban heat island mitigation – taking four districts in Shijiazhuang as an example

The primary objective of this scholarly investigation is to elucidate the intricate interplay between the urban heat island (UHI) effect and municipal green spaces. The geographical focus includes the four areas with the highest urbanization rate in Shijiazhuang, China. To conduct this survey, ECOSTRESS remote sensing imagery was acquired during distinct temporal intervals–morning, midday, and evening. The data were collected using the equal-scale city blocks performed by the OpenStreetMap urban network and ECOSTRESS remote sensing images at different times (morning, noon and evening). Surface temperature inversion of satellite images was performed using ArcGIS 10.7 software to obtain surface temperature. The overarching aim was to discern the nuanced impact of urban parks on the surface temperatures of their proximate environs during the summer season. The findings of this investigation revealed that, in order to effectively ameliorate the discernible heat island effect (SUH), rejuvenation initiatives ought to be directed toward sites maintaining a distance from green spaces within the range of 160 to 370 meters. Furthermore, augmentation of green space configurations is recommended in vicinities characterized by building densities falling within the range of 0.2 to 0.3. Notably, in locales marked by high building density, park layouts should adhere to a more regularized design during the renovation process. Additionally, it is advisable to ensure that the spatial separation between distinct urban parks exceeds 900 meters. These empirical insights are poised to enhance the comprehension of urban planners regarding the intricate dynamics through which urban parks exert influence on municipal surface temperatures. Furthermore, the discerned patterns furnish pragmatic guidance for mitigating the heat island effect, thereby offering invaluable recommendations for urban planning endeavors.

Dirac Operators on Configuration Spaces: Fermions with Half‐integer Spin, Real Structure, and Yang–Mills Quantum Field Theory

AbstractIn this paper, the development of a spectral triple‐like construction on a configuration space of gauge connections is continued. It has previously been shown that key elements of bosonic and fermionic quantum field theory emerge from such a geometrical framework. In this paper, a central problem concerning the inclusion of fermions with half‐integer spin into this framework is solved. The tangent space of the configuration space is mapped into a similar space based on spinors, and this map is used to construct a Dirac operator on the configuration space. A real structure acting in a Hilbert space over the configuration space is also constructed. Finally, it is shown that the self‐dual and anti‐self‐dual sectors of the Hamiltonian of a nonperturbative quantum Yang‐Mills theory emerge from a unitary transformation of a Dirac equation on a configuration space of gauge fields. The dual and anti‐dual sectors are shown to emerge in a two‐by‐two matrix structure.

Accelerating the identification of stable configurations in mixed-anion perovskite materials

Mixed-anion perovskite materials exhibit tunable properties, such as band gaps, stability, and charge transport, by modulating the composition and arrangement of the anions. This tunability enables a wide range of applications in fields such as optoelectronics, catalysis, and energy storage. The structural diversity enriches the material properties and enhances performance; however, it also poses a significant challenge in determining stable structures. The stability of such alloy materials depends not only on the elemental composition but also on the arrangement of X/Y elements within the lattice. To improve the understanding of the structure–property relationship in these alloy systems, a thorough exploration of the vast compositional and configurational space is essential. Herein, we integrate the cluster expansion (CE) method with the atom classification model (ACM) to efficiently pre-screen candidate structures and identify stable configurations. By considering the arrangement of anions, which exhibit short-range ordering within octahedra and randomness between octahedra, we have designed correlation functions for the ACM to reasonably reflect these characteristics. This approach enabled us to identify configurations of BaTa(O1−xNx)3, RbPb(F1−xOx)3 and CsPb(Br1−xClx)3 with higher stabilities without significantly increasing computational costs.

Optimizing urban green space configurations for enhanced heat island mitigation: A geographically weighted machine learning approach

Optimizing urban green space configurations for enhanced heat island mitigation: A geographically weighted machine learning approach

ASSESSMENT OF MORPHOLOGICAL CHARACTERISTICS OF BARLEY (<i>Hordeum vulgare L.</i>) VARIETIES IN VARYING INTER-ROW SPACINGS AND NITROGEN LEVELS UNDER IRRIGATED CONDITIONS IN NORTH CENTRAL, NIGERIA

A field experiment was conducted over two successive cropping seasons, 2021/2022 and 2022/2023, at the National Root Crop Research Institute outstation in Vom, located in the Jos South Local Government Area of Plateau State (Latitude 9º56' N, Longitude 8°53' E) at an altitude of 1,217 meters. The primary aim was to evaluate the effects of various barley genotypes, inter-row spacing, and nitrogen application rates on barley production. The study involved three barley genotypes (Traveler, Zhana, and Arupo’s), four nitrogen levels (0, 80, 100, and 120 kg N/ha), and three inter-row spacing configurations (20, 30, and 40 cm), organized in a split-split plot design with three replications. Results indicated that the control group exhibited significantly earlier heading days (49.00 days) in the 2021/2022 season and 49.30 days with 80 kg N/ha in 2022/2023. In contrast, the treatments with 120 kg N/ha showed delayed heading in both years. Notably, the 120 kg N/ha and control treatments achieved earlier flowering days at the 40 cm inter-row spacing in both growing seasons. Among the genotypes, Arupo’s recorded the highest grain yields of 1,251.0 kg/ha in 2021/22 and 1,876.4 kg/ha in 2022/23, achieved with 120 kg N/ha at 20 cm inter-row spacing. The parameters of days to heading, flowering, physiological maturity, and grain yield showed significant interactions concerning nitrogen levels and spacing, as well as between nitrogen and variety, and spacing and variety across the two seasons. In conclusion, the findings demonstrated that the genotype Arupo’s was the earliest to reach heading, flowering, and maturity, and produced the highest grain yield at a spacing of 20 cm and a nitrogen level of 120 kg N/ha. Therefore, it is recommended that farmers utilize the Arupo’s genotype, maintain a 20 cm inter-row spacing, and apply 120 kg N/ha for optimal barley production.

Evaluation of Semiempirical Quantum Mechanical Methods for Zr-Based Metal-Organic Framework Catalysts.

Zr-based metal-organic frameworks (MOFs) are typically employed in heterogeneous catalysis due to their porosity, chemical and thermal stability, and well-defined active sites. Density functional theory (DFT) is the workhorse to compute their electronic structure; however, it becomes very costly when dealing with reaction mechanisms involving large unit cells and vast configurational spaces. Semiempirical quantum mechanical (SQM) methods appear as an alternative approach to simulate such chemical systems at low computational cost, but their feasibility to model catalysis with MOFs is still unexplored. Thus, here we present a benchmark study on UiO-66 to evaluate the performance of SQM methods (PM6, PM7, GFN1-xTB, GFN2-xTB) against hybrid DFT (M06). We evaluate defective nodes, ligand exchange reactions, barrier heights, and host-guest interactions with metal nanoclusters. Despite some caveats, GFN1-xTB on properly constrained models is the best SQM method across all studied properties. Under proper supervision, this protocol holds promise for application in exploratory high-throughput screenings of Zr-based MOF catalysts, subject to further refinement with more accurate methods.

Relating Madelung–Bohm trajectories

In this work, we use the quantum potential approach to quantum mechanics to show that the Madelung–Bohm trajectories for a particle in a constant gravitational field can be related to those of a free particle by means of a quantum point transformation defined in the extended configuration space. We find that the point transformation also gives a connection between the corresponding quantum Hamiltonians determined by the solutions of the corresponding Schrödinger equations for these two problems. We show that the Madelung–Bohm trajectories determined by the stationary solutions to the Schrödinger equation for the particle in a constant gravitational field are straight ones, while the corresponding ones for the free particle are parabolic trajectories. The Airy beam is one example of this type of solution. We study the properties of a solution to the Schrödinger equation for a free particle with phase singularities (zeroes), and we find that the corresponding solution to the Schrödinger equation for the particle in a constant gravitational field also has zeroes at the same spacetime points. However, the Madelung–Bohm trajectories determined by the two solutions are totally different. Furthermore, we remark that similar results can be directly obtained for the paraxial wave equation.

Nonholonomic Motion Planning with Special Restrictions on the End and Via Points of the Control Function

This paper introduces a new modification to the motion planning algorithm of nonholonomic robotic systems using the Endogenous Configuration Space Approach which allows imposing restrictions on control functions. The end and via points define the values which the control function should take in a predefined time, either at the beginning, the end or during the motion time horizon. Such a modification can be used to set the values of the control function, which usually are of velocity–like type, to be physically realizable. The constraints are introduced to the algorithm through the extension of the Jacobian. The efficiency of the presented method is shown with the computer simulation results for a nonholonomic space manipulator. A modified Jacobian motion planning algorithm is used for planning consisting of a sequence of two subtasks.

Spikes and spines in 3D Lorentzian simplicial quantum gravity

Abstract Simplicial approaches to quantum gravity such as Quantum Regge Calculus and Spin Foams include configurations where bulk edges can become arbitrarily large while keeping the lengths of the boundary edges small. Such configurations pose significant challenges in Euclidean Quantum Regge Calculus, as they lead to infinities for the partition function and length expectation values. 
Here we investigate such configurations in three-dimensional Lorentzian Quantum Regge Calculus, and find that the partition function and length expectation values remain finite. This shows that the Lorentzian approach can avoid a key issue of the Euclidean approach. We also find that the space of configurations, for which bulk edges can become very large, is much richer than in the Euclidean case. In particular, it includes configurations with irregular light-cone structures, which lead to imaginary terms in the Regge action and branch cuts along the Lorentzian path integral contour. Hence, to meaningfully define the Lorentzian Regge path integral, one needs to clarify how such configurations should be handled.

Topology optimization design of the ‘Beam Shaping Assembly’ of an AB-BNCT facility—application to the case of glioblastoma treatment

Objective. This study aims to determine the optimal structure of the Beam Shaping Assembly (BSA) for an accelerator-based boron neutron capture therapy (BNCT) facility. The aim is to maximize the possible depth of treatment for glioblastoma while ensuring that a treatment time constraint is not exceeded.Approach. To achieve this goal, we utilize a new optimization procedure known as topology optimization. This technique can accurately identify the most optimal structure of a nuclear device, in this case a BSA, to be identified among 9 × 101206possible structures for the example given in this study. The exploration of such a vast space of configurations is inaccessible to any other method available to date.Main results. The topology optimization generated Air-AlF3-LiF-LiFPE BSA has an original structure that differs significantly from the structures previously tested by the BNCT community. This structure, which combines a ring collimator and a filter cone to mimic the effect of multi-field treatment, generates unprecedented treatment depths, with a treatable depth TD = 10.01 cm and an advantage depth AD = 12.48 cm (for 15 ppm of Boron-10 in blood, with a 3.5 tumor-to-blood Boron-10 concentration ratio), or TD = 10.30 cm and AD = 12.69 cm (for 18 ppm of Boron-10). These depths are much greater than any other design proposed to date by the community. The structure also verifies the latest proposed radiation protection constraints, which set limit values on its out-of-field leakages.Significance. The findings of this study indicate that topology optimization procedures are highly beneficial for the design of BSAs. In particular, the use of ring collimators could significantly improve the quality of BNCT treatments of brain tumors.

Dynamics over cocycle double cross-products

In this paper, we present the Euler–Lagrange and Hamilton’s equations for a system whose configuration space is a unified product Lie group [Formula: see text], for some [Formula: see text]. By reduction, then, we obtain the Euler–Lagrange-type and Hamilton’s-type equations of the same form for the quotient space [Formula: see text], although it is not necessarily a Lie group. We observe, through further reduction, that it is possible to formulate the Euler–Poincaré-type and Lie–Poisson-type equations on the corresponding quotient [Formula: see text] of Lie algebras, which is not a priori a Lie algebra. Moreover, we realize the [Formula: see text]th order iterated tangent group [Formula: see text] of a Lie group [Formula: see text] as an extension of the [Formula: see text]th order tangent group [Formula: see text] of the same type. More precisely, [Formula: see text] is the Lie algebra of [Formula: see text], [Formula: see text] for some [Formula: see text]. We thus obtain the [Formula: see text]th order Euler–Lagrange (and then the [Formula: see text]th order Euler–Poincaré) equations over [Formula: see text] by reduction from those on [Formula: see text]. Finally, we illustrate our results in the realm of the Kepler problem, and the nonlinear tokamak plasma dynamics.

Modeling Hypergraphs with Diversity and Heterogeneous Popularity

While relations among individuals make an important part of data with scientific and business interests, existing statistical modeling of relational data has mainly been focusing on dyadic relations, i.e., those between two individuals. This article addresses the less studied, though commonly encountered, polyadic relations that can involve more than two individuals. In particular, we propose a new latent space model for hypergraphs using determinantal point processes, which is driven by the diversity within hyperedges and each node’s popularity. This model mechanism is in contrast to existing hypergraph models, which are predominantly driven by similarity rather than diversity. Additionally, the proposed model accommodates broad types of hypergraphs, with no restriction on the cardinality and multiplicity of hyperedges, which previous models often have. Consistency and asymptotic normality of the maximum likelihood estimates of the model parameters have been established. The proof is challenging, owing to the special configuration of the parameter space. Further, we apply the projected accelerated gradient descent algorithm to obtain the parameter estimates, and we show its effectiveness in simulation studies. We also demonstrate an application of the proposed model on the What’s Cooking data and present the embedding of food ingredients learned from cooking recipes using the model.

On properties of effective topological complexity and effective Lusternik–Schnirelmann category

Abstract The notion of effective topological complexity, introduced by Błaszczyk and Kaluba, deals with using group actions in the configuration space in order to reduce the complexity of the motion planning algorithm. In this article, we focus on studying several properties of this notion of topological complexity. We introduce a notion of effective LS category which mimics the behaviour the usual LS category has in the non-effective setting. We use it to investigate the relationship between these effective invariants and the orbit map with respect to the group action, and we give numerous examples. Additionally, we investigate non-vanishing criteria based on a cohomological dimension bound of the saturated diagonal.

Metallic Sliding Ferroelectricity in Trilayer Penta‐NiN2

AbstractThe experimental observation of metallic ferroelectricity has challenged the traditional understanding in recent years, as metallicity and ferroelectricity are historically considered mutually exclusive. This breakthrough has sparked significant interest in this field. However, the coexistence of metallicity and sliding ferroelectricity in 2D pentagonal materials has not been reported yet. Here, this is theoretically studied that the sliding ferroelectricity in metallic trilayer penta‐NiN2. By scanning the configuration space of stacking patterns, a pair of polarized configurations is identified with strong out‐of‐plane ferroelectric polarization of ± 5.39 × 10−13 C m−1 and a low polarization switching barrier of 14.33 meV/atom together with a non‐polarized configuration as the intermediate state for the ferroelectric transition. It is also found that there are substantial changes in the second harmonic generation of the stable configurations that would facilitate experimental observation. This work demonstrates the potential of pentagonal sheets as promising metallic sliding ferroelectrics, which would significantly expand the family of sliding ferroelectric materials.

Enhanced sampling of robust molecular datasets with uncertainty-based collective variables.

Generating a dataset that is representative of the accessible configuration space of a molecular system is crucial for the robustness of machine-learned interatomic potentials. However, the complexity of molecular systems, characterized by intricate potential energy surfaces, with numerous local minima and energy barriers, presents a significant challenge. Traditional methods of data generation, such as random sampling or exhaustive exploration, are either intractable or may not capture rare, but highly informative configurations. In this study, we propose a method that leverages uncertainty as the collective variable (CV) to guide the acquisition of chemically relevant data points, focusing on regions of configuration space where ML model predictions are most uncertain. This approach employs a Gaussian Mixture Model-based uncertainty metric from a single model as the CV for biased molecular dynamics simulations. The effectiveness of our approach in overcoming energy barriers and exploring unseen energy minima, thereby enhancing the dataset in an active learning framework, is demonstrated on alanine dipeptide and bulk silica.

Communication across time and space: chronotope in the linguistic landscape of a concession area

ABSTRACT The language items present in the linguistic landscape are deeply embedded in history, often bearing varied time references and indexical loads. This study explores the preserved linguistic landscape of a former concession area in Wuhan, China to elucidate the intricate interplay of multi-layered historical meanings that intersect and converge in the public space. By employing the theoretical constructs of chronotope and polyphony, this study examines how the area is transformed into a liminal space in linguistic and symbolic terms. The findings indicate that the preserved linguistic landscape can be categorised into three types based on time–space configurations: preliminal chronotope, liminal chronotope, and postliminal chronotope, corresponding to signs in original forms, signs refurbished while retaining the original texts, and signs incorporating original texts and new additions. These signs symbolically reference the past, present and future, embodying historical and cultural preservation, reflecting societal and economic development, and enhancing the city’s appeal as a tourist destination. This research contributes to understanding the complex discourses and communicative dynamics within linguistic landscape, offering insights into the interplay between history, culture, and language in public spaces.

Random Sampling Versus Active Learning Algorithms for Machine Learning Potentials of Quantum Liquid Water.

Training accurate machine learning potentials requires electronic structure data comprehensively covering the configurational space of the system of interest. As the construction of this data is computationally demanding, many schemes for identifying the most important structures have been proposed. Here, we compare the performance of high-dimensional neural network potentials (HDNNPs) for quantum liquid water at ambient conditions trained to data sets constructed using random sampling as well as various flavors of active learning based on query by committee. Contrary to the common understanding of active learning, we find that for a given data set size, random sampling leads to smaller test errors for structures not included in the training process. In our analysis, we show that this can be related to small energy offsets caused by a bias in structures added in active learning, which can be overcome by using instead energy correlations as an error measure that is invariant to such shifts. Still, all HDNNPs yield very similar and accurate structural properties of quantum liquid water, which demonstrates the robustness of the training procedure with respect to the training set construction algorithm even when trained to as few as 200 structures. However, we find that for active learning based on preliminary potentials, a reasonable initial data set is important to avoid an unnecessary extension of the covered configuration space to less relevant regions.

INOVAÇÃO EM AMBIENTES INTERNOS: UMA REVISÃO DA LITERATURA

Abstract The characteristics of indoor environments are significantly influenced by lighting and colors, which play fundamental roles in the perception of spaces and the well-being of users. This study analyzed how colors and lighting can be applied in indoor environments to promote innovation and well-being. To this end, a comprehensive literature review was conducted, using scientifically based descriptors related to the topic. The results confirm that colors and lighting are essential elements in the configuration of indoor spaces, influencing spatial perception, user well-being, and the environment's functionality. The research highlights that the strategic planning of these elements enhances the functionality of environments, promoting innovation, comfort, and environmental quality in the design context. Keywords: design, innovation, ergonomics