Interaction Strength Research Articles

Mass concentration near the boundary for attractive Bose–Einstein condensates in bounded domains

We are devoted to studying the ground states of trapped attractive Bose–Einstein condensates in a bounded domain Ω⊂R2, which can be described by minimizers of L2-critical constraint Gross–Pitaevskii energy functional. It has been shown that there is a threshold a∗>0 such that minimizers exist if and only if the interaction strength a satisfies a<a∗. In present paper, we prove that when the trapping potential V(x) attains its flattest global minimum only at the boundary of Ω, the mass of minimizers must concentrate near the boundary of Ω as a↗a∗. This result extends the work of Luo and Zhu (2019).

Effects of the control of an invasive tree on the structure of a plant-frugivore network.

Invasive non-native species are one of the main causes of degradation of ecosystems worldwide. The control of invasive species is key to reducing threats to ecosystem viability in the long term. Observations of structural changes in ecological interaction networks following invasive species suppression can be useful to monitor the success of ecological restoration initiatives. We evaluated the structure of plant-bird frugivory interaction networks in a plant community invaded by the guava tree (Psidium guajava L.) by comparing network metrics before and after control actions. Psidium guajava was relevant in all metrics for the unmanaged network in this study, with high degree centrality and high nestedness contribution. Based on the asymmetry of species interactions, we found that birds were highly dependent on the invasive plant before suppression. Once P. guajava trees were eliminated, bird and plant species richness, total number of interactions, and modularity increased, whereas nestedness and interaction strength asymmetry decreased. The diet of the bird community became more diversified once P. guajava was no longer available and relevant species roles in community structure emerged. Our results corroborate the fact that ecological restoration interventions should include the control of non-native plant species that attract frugivorous animals in order to diversify plant-frugivore interactions and thus maintain biodiversity in natural ecosystems.

Microwave Remote Sensing with Hybrid Quantum Receiver.

Detecting a microwave signal that is emitted or reflected by distant targets is a powerful tool in fundamental science and industrial technology. Solid-state spins provide an opportunity to realize quantum-enhanced remote sensing under ambient conditions. However, the weak interaction between the free-space signal and atomic size sensor limits the sensitivity. This hinders the realization of practical quantum remote sensing. Here, we demonstrate active microwave remote sensing with a diamond-based hybrid quantum receiver by combining electromagnetic field localization at nanoscale with quantum spin manipulation. A method of differential spin refocusing (DSR) is developed to overcome the challenge of reducing the impact of inhomogeneities in spin-signal interaction, while the strength of interaction is enhanced by more than 3 orders with nanostructure. It improves the coherent interaction time of quantum receiver by 30-fold, substantially enhancing the sensitivity and stability. By detecting the reflected microwave with picotesla sensitivity, diamond remote sensing monitors the real-time status of a centimeter-sized target at 2 m distance. Our method is general to various solid-state spins. The results will expand the applications of solid-state spin quantum sensors in areas ranging from medical imaging to resource survey.

The assembly and dynamics of ecological communities in an ever‐changing world

AbstractAlternative perspectives on the maintenance of biodiversity and the assembly of ecological communities suggest that both processes cannot be investigated simultaneously. In this concept and synthesis, we challenge this view by presenting major theoretical advances in structural stability and permanence theory. These advances, which provide complementary views, allow studying the short‐ and long‐term dynamics of ecological communities as changes in species richness, composition, and abundance. Here, the global attractor, technically named informational structure (IS), is the central element to construct from information of species' intrinsic growth rates and their strength and sign of interactions. The global attractor has four main properties: (1) It contains all the limits of what is feasible and unfeasible of the dynamical behavior of an ecological system, therefore, (2) it provides a thorough characterization of all combinations of species' richness and composition in which species can coexist (i.e., feasible and stable equilibrium), (3) as well as all connections (paths) of assembly between coexisting communities. Importantly, (4) such topology of coexisting communities and their connections changes when environmental (abiotic and biotic) variation affects the ability of species to grow and interact with others. Overall, these four properties allow switching from a traditional evaluation of species coexistence at equilibrium to a much more realistic nonequilibrium perspective where changes in the structure of the global attractor underlie the transient ecological dynamics. Several fields in ecology can benefit from the study of an IS. For instance, it can serve to evaluate community responses after the end of a perturbation, to design restoration trajectories, to study the consequences of biological invasions on the persistence of native species within communities, or to assess ecosystem health status. We illustrate this latter possibility with empirical observations of 7 years in Mediterranean annual grasslands. We document that extremely wet or dry years generate ISs supporting few coexisting communities and few assembly paths. The remaining communities distinguish winners from losers of ongoing climate change and indicate the limits to future community assembly opportunities. A fully tractable operational framework is readily available to understand and predict the assembly and dynamics of ecological communities in an ever‐changing world.

CoiTAD: Detection of Topologically Associating Domains Based on Clustering of Circular Influence Features from Hi-C Data.

Topologically associating domains (TADs) are key structural units of the genome, playing a crucial role in gene regulation. TAD boundaries are enriched with specific biological markers and have been linked to genetic diseases, making consistent TAD detection essential. However, accurately identifying TADs remains challenging due to the lack of a definitive validation method. This study aims to develop a novel algorithm, termed coiTAD, which introduces an innovative approach for preprocessing Hi-C data to improve TAD prediction. This method employs a proposed "circle of influence" (COI) approach derived from Hi-C contact matrices. The coiTAD algorithm is based on the creation of novel features derived from the circle of influence in input contact matrices, which are subsequently clustered using the HDBSCAN clustering algorithm. The TADs are extracted from the clustered features based on intra-cluster interactions, thereby providing a more accurate method for identifying TADs. Rigorous tests were conducted using both simulated and real Hi-C datasets. The algorithm's validation included analysis of boundary proteins such as H3K4me1, RNAPII, and CTCF. coiTAD consistently matched other TAD prediction methods. The coiTAD algorithm represents a novel approach for detecting TADs. At its core, the circle-of-influence methodology introduces an innovative strategy for preparing Hi-C data, enabling the assessment of interaction strengths between genomic regions. This approach facilitates a nuanced analysis that effectively captures structural variations within chromatin. Ultimately, the coiTAD algorithm enhances our understanding of chromatin organization and offers a robust tool for genomic research. The source code for coiTAD is publicly available, and the URL can be found in the Data Availability Statement section.

Herbivore regulation of savanna vegetation: Structural complexity, diversity, and the complexity–diversity relationship

AbstractLarge mammalian herbivores exert strong top‐down control on plants, which in turn influence most ecological processes. Accordingly, the decline, displacement, or extinction of wild large herbivores in African savannas is expected to alter the physical structure of vegetation, the diversity of plant communities, and downstream ecosystem functions. However, herbivore impacts on vegetation comprise both direct and indirect effects and often depend on herbivore body size and plant type. Understanding how herbivores affect savanna vegetation requires disaggregating the effects of different herbivores and the responses of different plants, as well as accounting for both the structural complexity and composition of plant assemblages. We combined high‐resolution Light Detection and Ranging (LiDAR) with field measurements from size‐selective herbivore exclosures in Kenya to determine how herbivores affect the diversity and physical structure of vegetation, how these impacts vary with body size and plant type, and whether there are predictable associations between plant diversity and structural complexity. Herbivores generally reduced the diversity and abundance of both overstory and understory plants, though the magnitude of these impacts varied substantially as a function of body size and plant type: only megaherbivores (elephants and giraffes) affected tree cover, whereas medium‐ and small‐bodied herbivores had stronger effects on herbaceous diversity and abundance. We also found evidence that herbivores altered the strength and direction of interactions between trees and herbaceous plants, with signatures of facilitation in the presence of herbivores and of competition in their absence. While megaherbivores uniquely affected tree structure, medium‐ and small‐bodied species had stronger (and complementary) effects on metrics of herbaceous vegetation structure. Plant structural responses to herbivore exclusion were species‐specific: of five dominant tree species, just three exhibited significant individual morphological variation across exclosure treatments, and the size class of herbivores responsible for these effects varied across species. Irrespective of exclosure treatment, more species‐rich plant communities were more structurally complex. We conclude that the diversity and architecture of savanna vegetation depend on consumptive and nonconsumptive plant–herbivore interactions; the roles of herbivore diversity, body size, and plant traits in mediating those interactions; and a positive feedback between plant diversity and structural complexity.

Multiple stressors drive multitrophic biodiversity and ecological network dynamics in a shrinking sandy lake

Stressors endanger lake ecosystem biodiversity and networks, especially in sandy lakes of arid/semiarid regions, where impacts are poorly understood. Here, we investigate the changes in multitrophic biodiversity and ecological networks under increasing stress (temperature, nutrients, lake area) by using sedimentary DNA from a shrinking sandy lake in China over nearly 100 years. With increasing stress, species richness and stability increased, whereas species turnover decreased. Species synchronism decreased at high-trophic levels but increased at low-trophic levels. Empirical dynamic modeling showed network connectance and strength of species interactions decreased–increased–decreased over time, signaling a potential adaption–resistance–degradation change in ecosystem responses with increasing stress. Models also indicated network structure primarily depended on direct effects of nutrients and temperature under low/medium stress and on a diversity-mediated pathway under high stress. Thus, maintaining ecological network structure complexity and integrity in lake ecosystems is essential to mitigate the effects of multiple stresses.

Universal correlation between H-linear magnetoresistance and T-linear resistivity in high-temperature superconductors

The signature feature of the ‘strange metal’ state of high-Tc cuprates—its linear-in-temperature resistivity—has a coefficient α1 that correlates with Tc, as expected were α1 derived from scattering off the same bosonic fluctuations that mediate pairing. Recently, an anomalous linear-in-field magnetoresistance (=γ1H) has also been observed, but only over a narrow doping range, leaving its relation to the strange metal state and to the superconductivity unclear. Here, we report in-plane magnetoresistance measurements on three hole-doped cuprate families spanning a wide range of temperatures, magnetic field strengths and doping. In contrast to expectations from Boltzmann transport theory, γ1 is found to correlate universally with α1. A phenomenological model incorporating real-space inhomogeneity is proposed to explain this correlation. Within this picture, superconductivity in hole-doped cuprates is governed not by the strength of quasiparticle interactions with a bosonic bath, but by the concentration of strange metallic carriers.

Surface excitation of Rydberg dressed quantum droplet of Bose–Einstein Condensates

We have considered a quantum droplet of two components of Bose–Einstein condensate (BEC) inside the electron of a Rydberg atom to study the surface mode of collective excitation using the Bogoliubov theory of excitation. We have calculated the surface excitation spectrum for various Rydberg electron-atom interaction strengths. From the energy spectrum, we calculated the surface tension of the droplet as a function of Rydberg electron-atom interaction strength. Our study shows that the electron-atom interaction enhances the surface energy; hence, the droplet will be more stable inside the electron of a Rydberg atom.

Human activities reshape the spatial overlap between North Chinese leopard and its wild ungulate prey

BackgroundRapidly expanding human activities have profoundly changed the habitat use of both large carnivores and their prey, but whether and how human activities affect the interactions between them has received relatively less attention. In this study, we conducted a systematically designed camera-trapping survey on an endangered large carnivore (North Chinese leopard Panthera pardus japonensis) and its wild ungulate prey (Siberian roe deer Capreolus pygargus and wild boar Sus scrofa) in the Taihang Mountains of central North China. Using conditional two-species occupancy model based on data derived from the extensive sampling effort (15,654 camera-days at 102 camera sites), we examined the relationship of spatial use between leopards and each prey species under the effects of human presence, free-ranging cattle, roads and settlements.ResultsHumans and cattle had contrasting effects on the relationship of spatial use between leopard and roe deer, with higher and lower spatial segregation between them at human and cattle-frequented sites, respectively. Roads might create a shelter for wild boar from leopard predation, with less spatial segregation between them at sites close to the roads.ConclusionsOur findings demonstrate that human activities are reshaping the spatial overlap between large carnivores and their prey, and have non-equivalent effects among different types of human activity. Such effects may further alter the strength of interspecific interactions between predator and prey, with far-reaching influences on the community and ecosystem that require more research.

A Novel Method to Constrain Tidal Quality Factor from A Nonsynchronized Exoplanetary System

We propose a novel method to constrain the tidal quality factor, Q′ , from an observed nonsynchronized star–planet system consisting of a slowly rotating low-mass star and a close-in Jovian planet, taking into account the coevolution of stellar spin and planetary orbit due to the tidal interaction and the magnetic braking. On the basis of dynamical system theory, the track of the coevolution of angular momentum from the fast-rotator regime for such a system exhibits the existence of a forbidden region in the Ωorb–Ωspin plane, where Ωspin and Ωorb denote the angular velocity of the stellar spin and planetary orbit, respectively. The forbidden region is determined primarily by the strength of the tidal interaction. By comparing the (Ωorb, Ωspin) of a single star–planet system to the forbidden region, we can constrain the tidal quality factor regardless of the evolutionary history of the system. The application of this method to the star–planet system NGTS-10–NGTS-10 b gives Q′≳108 , leading to a tight upper bound on the tidal torque. Since this cannot be explained by previous theoretical predictions for nonsynchronized star–planet systems, our result requires mechanisms that suppress the tidal interaction in such systems.

Different effective Hamiltonians in a periodic-driven Bose-Josephson junction.

The bosonic Josephson junction, one of the maximally simple models for periodic-driven many-body systems, has been intensively studied in the past two decades. Here, we revisit this problem with five different methods, all of which have solid theoretical reasoning. We find that to the order of ω^{-2} (ω is the modulating frequency), these approaches will yield slightly different effective Hamiltonians. In particular, the parameters in the effective Hamiltonians may be unchanged, increased, or decreased, depending on the approximations used. Especially, some of the methods generate new interactions, which still preserve the total number of particles, and the others do not. The validity of these five effective models is verified using dynamics of population imbalance and self-trapping phase transition, and we find thatthe method based on the rotating frame by a unitary transformation has the highest accuracy. The difference between these methods will become significant when the driving amplitude or interaction strengths are comparable with the driving frequency. These differences can also be manifested from their long-time dynamics. We demonstrate this physics using a Bose-Josephson junction, and it is to be hoped that the validity of these methods and their tiny differences put forward in this paper can be verified in realistic experiments in the future using quantum simulating platforms, including but not limited to ultracold atoms.

Global spectrum model of discrete dislocation equation

The fully discrete dislocation equation can be rationally derived from the spectrum model. In this paper, the previous spectrum model is reinterpreted to cover the global feature of the spectrum. Instead of the local behavior around the origin of the Brilouin zone, the global spectrum model focuses the maximum at the boundary of the Brillouin as well as the slope at the origin of the Brilouin zone. The strength of the point-contact interaction that effectively describes the discreteness effect becomes larger because the whole lattice effect is included in the global spectrum model. The validness and signification of the new model are illustrated by a solvable lattice dynamical model of the cubic lattice.

Self‐organized Patterns in Non‐reciprocal Active Droplet Systems

Non‐equilibrium patterns are widespread in nature and often arise from the self‐organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil‐in‐water droplet mixtures with predator‐prey interactions can result in a variety of self‐organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self‐organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids.

Self-Organized Patterns in Non-Reciprocal Active Droplet Systems.

Non-equilibrium patterns are widespread in nature and often arise from the self-organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil-in-water droplet mixtures with predator-prey interactions can result in a variety of self-organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self-organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids.

GraphBNC: Machine Learning-Aided Prediction of Interactions Between Metal Nanoclusters and Blood Proteins.

Hybrid nanostructures between biomolecules and inorganic nanomaterials constitute a largely unexplored field of research, with the potential for novel applications in bioimaging, biosensing, and nanomedicine. Developing such applications relies critically on understanding the dynamical properties of the nano-bio interface. This work introduces and validates a strategy to predict atom-scale interactions between water-soluble gold nanoclusters (AuNCs) and a set of blood proteins (albumin, apolipoprotein, immunoglobulin, and fibrinogen). Graph theory and neural networks are utilized to predict the strengths of interactions in AuNC-protein complexes on a coarse-grained level, which are then optimized in Monte Carlo-based structure search and refined to atomic-scale structures. The training data is based on extensive molecular dynamics (MD) simulations of AuNC-protein complexes, and the validating MD simulations show the robustness of the predictions. This strategy can be generalized to any complexes of inorganic nanostructures and biomolecules provided that one generates enough data about the interactions, and the bioactive parts of the nanostructure can be coarse-grainedrationally.

Halogen Bonding in N-Alkyl-bromo-/iodo-pyridinium Salts and its Application in Chromatography.

The alkylation of 3-/4-bromo- and -iodopyridine with methyl triflate smoothly affords the correspondingN-methylpyridinium triflate salts. An anion exchange with NaI or [PPh4]Y (Y = Cl, Br, I) yields the corresponding halide salts. Most of them could be structurally characterized and their strong halogen bonds were investigated. While the halogen atom of 4-halogenopyridinium is susceptible to nucleophilic substitution, 3-halogenopyridinium ions are far more stable against nucleophilic attacks. Due to the comparable interaction strength of halogen bonds and hydrogen bonds, the latter of which is widely used in chromatography, the potential of 3-halogenopyridinium moieties for an application in chromatography is obvious and wassuccessfully employed in affinity chromatography of differentproteins.

New physics at a neutron beam dump

We find a new utility of neutrons, usually treated as an experimental nuisance causing unwanted background, in probing new physics signals. The new physics signals can either be radiated from neutrons (neutron bremsstrahlung) or appear through secondary particles from neutron-on-target interactions, dubbed “neutron beam dump.” As a concrete example, we take the FASER/FASER2 experiment as a “factory” of high-energy neutrons that interact with the iron dump. We find that if new physics particles had the same interaction strength to protons and neutrons, their production rate via neutron-initiated bremsstrahlung would be comparable to that via proton-initiated ones, in terms of the resulting flux and the range of couplings that can be probed. The neutron bremsstrahlung can be used, for instance, to probe dark gauge bosons with nonzero neutron coupling. In particular, we investigate protophobic gauge bosons and find that FASER/FASER2 can probe new parameter space. We also illustrate the possibility of neutron-induced secondary particles by considering axionlike particles with electron couplings. We conclude that the physics potential of FASER/FASER2 in terms of new physics searches can be greatly extended and improved with the inclusion of neutron interactions. Published by the American Physical Society 2024

A prediction of high temperature magnetic coupling in transition metal phthalocyanines.

In spintronics, a perennial goal has been the generation of organic spin-bearing semiconductor materials with magnetic ordering stable at room temperature. To this end, the class of transition metal phthalocyanines has shown much promise in fulfilling this ambition. In particular, alpha-phase cobalt (II) phthalocyanine (α-CoPc) exhibits strong antiferromagnetic exchange interactions producing a long range order up to ∼100K. However, the underlying mechanism by which this magnetic interaction proceeds is not well understood. In this report, a simple mechanism has been proposed based on the Hubbard Hamiltonian, which elucidates the exchange coupling in α-CoPc. The mechanism provides stipulations for increasing the magnetic coupling, and this directs to a proposal that substitution of the central cobalt ion for rhodium will lead to a significant increase in coupling strength. The strength of this exchange interaction has been evaluated using broken symmetry hybrid exchange density functional theory and indicates that the novel rhodium (II) phthalocyanine system is indeed predicted to exhibit significantly stronger magnetic ordering. This study, therefore, identifies the coupling mechanism in α-CoPc as primarily attributable to kinetic exchange, explains its previously reported strong coupling relative to its first-row transition metal counterparts, and suggests that rhodium (II) phthalocyanine is likely to exhibit stable magnetic ordering at room temperature.

Origin and fate of the pseudogap in the doped Hubbard model

The relationship between the pseudogap and underlying ground-state phases has not yet been rigorously established. We investigated the doped two-dimensional Hubbard model at finite temperature using controlled diagrammatic Monte Carlo calculations, allowing for the computation of spectral properties in the infinite-size limit and with arbitrary momentum resolution. We found three distinct regimes as a function of doping and interaction strength: a weakly correlated metal, a correlated metal with strong interaction effects, and a pseudogap regime at low doping. We show that the pseudogap forms both at weak coupling, when the magnetic correlation length is large, and at strong coupling, when it is shorter. As the temperature goes to zero, the pseudogap regime extrapolates precisely to the ordered stripe phase found by ground-state methods.