Small Spatial Region Research Articles

Linearly Polarized Broadband Emission and Multiwavelength Lasing in Solution-Processed Quantum Dots.

A miniature laser with linear polarization is a long sought-after component of photonic integrated circuits. In particular, for multiwavelength polarization lasers, it supports simultaneous access to multiple, widely varying laser wavelengths in a small spatial region, which is of great significance for advancing applications such as optical computing, optical storage, and optical sensing. However, there is a trade-off between the size of small-scale lasers and laser performance, and multiwavelength co-gain of laser media and multicavity micromachining in the process of laser miniaturization remain as significant challenges. Herein, room-temperature linearly polarized multiwavelength lasers in the visible and near-infrared wavelength ranges are demonstrated, by fabricating random cavities scattered with silica in an Er-doped Cs2Ag0.4Na0.6In0.98Bi0.02Cl6 double-perovskite quantum dots gain membrane. By regulating the local symmetry and enabling effective energy transfer in nanocrystals, multiwavelength lasers with ultralow thresholds are achieved at room temperature. The maximum degree of polarization reaches 0.89. With their advantages in terms of miniaturization, ultralow power consumption, and adaptability for integration, these lasers offer a prospective light source for future photonic integrated circuits aimed at high-capacity optical applications.

Automatic Encoding of Unlabeled Two Dimensional Data Enabling Similarity Searches: Electron Diffusion Regions and Auroral Arcs

AbstractCritically important phenomena in Earth’s magnetosphere often occur briefly, or in small spatial regions. These processes are sampled with orbiting spacecraft or by fixed ground observatories and so rarely appear in data. Identifying such intervals can be an incredibly time consuming task. We apply a novel, powerful method by which two dimensional data can be automatically processed and embeddings created that contain key features of the data. The distance between embedding vectors serves as a measure of similarity. We apply the state‐of‐the‐art method to two example datasets: MMS electron velocity distributions and auroral all sky images. We show that the technique creates embeddings that group together visually similar observations. When provided with novel example images the method correctly identifies similar intervals: when provided with an electron distribution sampled during an encounter with an electron diffusion region the method recovers similar distributions obtained during two other known diffusion region encounters. Similarly, when provided with an interesting auroral structure the method highlights the same structure observed from an adjacent location and at other close time intervals. The method promises to be a useful tool to expand interesting case studies to multiple events, without requiring manual data labeling. Further, the models could be fine‐tuned with relatively small set of labeled example data to perform tasks such as classification. The embeddings can also be used as input to deep learning models, providing a key intermediary step—capturing the key features within the data.

Pincushion point-spread function for computer-generated holography.

Point-spread functions (PSFs) are non-stationary signals whose spatial frequency increases with the radius. These signals are only meaningful over a small spatial region when being propagated over short distances and sampled with regular sampling pitch. Otherwise, aliasing at steep incidence angles leads to the computation of spurious frequencies. This is generally addressed by evaluating the PSF in a bounded disk-shaped region, which has the added benefit that it reduces the required number of coefficient updates. This significantly accelerates numerical diffraction calculations in, e.g., wavefront recording planes for high-resolution holograms. However, the use of a disk-shaped PSF is too conservative since it only utilizes about 78.5% of the total bandwidth of the hologram. We therefore derive a novel, to the best of our knowledge, optimally shaped PSF fully utilizing the bandwidth formed by two bounding hyperbola. A number of numerical experiments with the newly proposed pincushion PSF were performed, reporting over three-fold reductions of the signal error and significant improvements to the visual quality of computer-generated holograms at high viewing angles.

Turning points in the age–metallicity relations – created by late satellite infall and enhanced by radial migration

ABSTRACT The present-day age–metallicity relation (AMR) is a record of the star formation history of galaxies, as this traces the chemical enrichment of the gas over time. We use a zoomed-in cosmological simulation that reproduces key signatures of the Milky Way (MW), g2.79e12 from the NIHAO-UHD project, to examine how stellar migration and satellite infall shape the AMR across the disc. We find in the simulation, similar to the MW, the AMR in small spatial regions (R, z) shows turning points that connect changes in the direction of the relations. The turning points in the AMR in the simulation are a signature of late satellite infall. This satellite infall has a mass radio similar as that of the Sagittarius dwarf to the MW (∼0.001). Stars in the apex of the turning points are young and have nearly not migrated. The late satellite infall creates the turning points via depositing metal-poor gas in the disc, triggering star formation of stars in a narrow metallicity range compared to the overall AMR. The main effect of radial migration on the AMR turning points is to widen the metallicity range of the apex. This can happen when radial migration brings stars born from the infallen gas in other spatial bins, with slightly different metallicities, into the spatial bin of interest. These results indicate that it is possible that the passage of the Sagittarius dwarf galaxy played a role in creating the turning points that we see in the AMR in the Milky Way.

High-altitude nuclear explosion energy accumulation law in atmosphere

An accumulation model of X-ray and debris in a high altitude nuclear explosion is built in this work. Using the established model, we simulate the energy accumulations of four large scale experiments (i.e. the Checkmate, Starfish, K3 and K4) conducted by the United States and the Soviet Union. The dynamics of the kinetic accumulation at 100–200 km altitude is analyzed. Our simulation results show that the kinetic patch spreads a relatively small spatial region and has a large energy density compared with the X-ray patch. The accumulation of the debris ions can be finished within around 0.5 s, and two absorption peaks (hence two kinetic patches) can be observed at an altitude of about 115 km and the burst point. The shape of the kinetic region projected onto the horizontal plane is roughly elliptical, the eccentricity will be smaller at higher latitudes, and the area will be larger at higher altitudes. Away from the bursting point, the maximum energy density of the kinetic patch is near the magnetic field line that crosses the bursting point. Within the magnetic bubble, the maximum energy density of the kinetic patch occurs near the bursting point.

A Retrospective Analysis ofb-Value Changes Preceding Strong Earthquakes

AbstractEarthquake precursors have long been sought as a means to predict earthquakes with very limited success. Recently, it has been suggested that a decrease in the Gutenberg–Richter b-value after a magnitude 6 earthquake is predictive of an imminent mainshock of larger magnitude, and a three-level traffic-light system has been proposed. However, this method is dependent on parameters that must be chosen by an expert. We systematically explore the parameter space to find an optimal set of parameters based on the Matthews correlation coefficient. For each parameter combination, we analyze the temporal changes in the frequency–magnitude distribution for every M ≥ 6 earthquake sequence in the U.S. Geological Survey Comprehensive Earthquake Catalog for western North America. We then consider smaller events, those with a foreshock magnitude as small as 5, and repeat the analysis to assess its performance for events that modify stresses over smaller spatial regions. We analyze 25 M ≥ 6 events and 88 M 5–6 events. We find that no perfect parameter combination exists. Although the method generates correct retrodictions for some M 5 events, the predictions are dependent on the retrospectively selected parameters. About 80%–95% of magnitude 5–6 events have too little data to generate a result. Predictions are time dependent and have large uncertainties. Without a precise definition of precursory b-value changes, this and similar prediction schemes are incompatible with the IASPEI criteria for evaluating earthquake precursors. If limitations on measuring precursory changes in seismicity and relating them to the state of stress in the crust can be overcome, real-time forecasting of mainshocks could reduce the loss of lives.

Giant Second Harmonic Generation Enhancement by Ag Nanoparticles Compactly Distributed on Hexagonal Arrangements.

The association of plasmonic nanostructures with nonlinear dielectric systems has been shown to provide useful platforms for boosting frequency conversion processes at metal-dielectric interfaces. Here, we report on an efficient route for engineering light–matter interaction processes in hybrid plasmonic-χ(2) dielectric systems to enhance second harmonic generation (SHG) processes confined in small spatial regions. By means of ferroelectric lithography, we have fabricated scalable micrometric arrangements of interacting silver nanoparticles compactly distributed on hexagonal regions. The fabricated polygonal microstructures support both localized and extended plasmonic modes, providing large spatial regions of field enhancement at the optical frequencies involved in the SHG process. We experimentally demonstrate that the resonant excitation of the plasmonic modes supported by the Ag nanoparticle-filled hexagons in the near infrared region produces an extraordinary 104-fold enhancement of the blue second harmonic intensity generated in the surface of a LiNbO3 crystal. The results open new perspectives for the design of efficient hybrid plasmonic frequency converters in miniaturized devices.

Drifting inwards in protoplanetary discs

In previous laboratory experiments, we measured the temperature dependence of sticking forces between micrometer grains of chondritic composition. The data showed a decrease in surface energy by a factor ~5 with increasing temperature. Here, we focus on the effect of surface water on grains. Under ambient conditions in the laboratory, multiple water layers are present. At the low pressure of protoplanetary discs and for moderate temperatures, grains likely only hold a monolayer. As dust drifts inwards, even this monolayer eventually evaporates completely in higher temperature regions. To account for this, we measured the tensile strength for the same chondritic material as was prepared and measured under normal laboratory conditions in our previous work, but now introducing two new preparation methods: drying dust cylinders in air (dry samples), and heating dust pressed into cylinders in vacuum (super-dry samples). For all temperatures up to 1000 K, the data of the dry samples are consistent with a simple increase in the sticking force by a factor of ~10 over wet samples. Up to 900 K super-dry samples behave like dry samples. However, the sticking forces then exponentially increase up to another factor ~100 at about 1200 K. The increase in sticking from wet to dry extends a trend that is known for amorphous silicates to multimineral mixtures. The findings for super-dry dust imply that aggregate growth is boosted in a small spatial high-temperature region around 1200 K, which might be a sweet spot for planetesimal formation.

Are charged tips driving TERS-resolution? A full quantum chemical approach.

Experimental evidence suggests an extremely high, possibly even sub-molecular, spatial resolution of tip-enhanced Raman spectroscopy (TERS). While the underlying mechanism is currently still under discussion, two main contributions are considered: The involved plasmonic particles are able to highly confine light to small spatial regions in the near-field, i.e., the electromagnetic effect and the chemical effect due to altered molecular properties of the sample in close proximity to the plasmonic tip. Significant theoretical effort is put into the modeling of the electromagnetic contribution by various groups. In contrast, we previously introduced a computational protocol that allows for the investigation of the local chemical effect-including non-resonant, resonant, and charge transfer contributions-on a plasmonic hybrid system by mapping the sample molecule with a metallic tip model at the (time-dependent) density functional level of theory. In the present contribution, we evaluate the impact of static charges localized on the tip's frontmost atom, possibly induced by the tip geometry in the vicinity of the apex, on the TERS signal and the lateral resolution. To this aim, an immobilized molecule, i.e., tin(II) phthalocyanine (SnPc), is mapped by the plasmonic tip modeled by a single positively vs negatively charged silver atom. The performed quantum chemical simulations reveal a pronounced enhancement of the Raman intensity under non-resonant and resonant conditions with respect to the uncharged reference system, while the contribution of charge transfer phenomena and of locally excited states of SnPc is highly dependent on the tip's charge.

Evanescent ergosurface instability

Some exotic compact objects possess evanescent ergosurfaces: timelike submanifolds on which a Killing vector field, which is timelike everywhere else, becomes null. We show that any manifold possessing an evanescent ergosurface but no event horizon exhibits a linear instability of a peculiar kind: either there are solutions to the linear wave equation which concentrate a finite amount of energy into an arbitrarily small spatial region, or the energy of waves measured by a stationary family of observers can be amplified by an arbitrarily large amount. In certain circumstances we can rule out the first type of instability. We also provide a generalisation to asymptotically Kaluza-Klein manifolds. This instability bears some similarity with the "ergoregion instability" of Friedman, and we use many of the results from the recent proof of this instability by Moschidis.

Non-bouncing solutions in loop quantum cosmology

According to the Belinskii-Khalatnikov-Lifshitz scenario, a collapsing universe approaching a spacelike singularity can be approximated by homogeneous cosmological dynamics, but only if asymptotically small spatial regions are considered. It is shown here that the relevant small-volume behavior in solvable models of loop quantum cosmology is crucially different from the large-volume behavior exclusively studied so far. While bouncing solutions exist and may even be generic within a given quantum representation, they are not generic if quantization ambiguities such as choices of representations are taken into account. The analysis reveals an interesting interplay between sl(2,R)-representation theory and canonical effective theory.

Hybrid purification and sampling approach for thermal quantum systems

We propose an algorithm which combines the beneficial aspects of two different methods for studying finite-temperature quantum systems with tensor networks. One approach is the ancilla method, which gives high-precision results but scales poorly at low temperatures. The other method is the minimally entangled typical thermal state (METTS) sampling algorithm which scales better than the ancilla method at low temperatures and can be parallelized, but requires many samples to converge to a precise result. Our proposed hybrid of these two methods purifies physical sites in a small central spatial region with partner ancilla sites, sampling the remaining sites using the METTS algorithm. Observables measured within the purified cluster have much lower sample variance than in the METTS approach, while sampling the sites outside the cluster reduces their entanglement and the computational cost of the algorithm. The sampling steps of the algorithm remain straightforwardly parallelizable. The hybrid approach also solves an important technical issue with METTS that makes it difficult to benefit from quantum number conservation. By studying S=1 Heisenberg ladder systems, we find the hybrid method converges more quickly than both the ancilla and METTS algorithms at intermediate temperatures and for systems with higher entanglement.

Predicting West Nile virus transmission in North American bird communities using phylogenetic mixed effects models and eBird citizen science data

BackgroundWest Nile virus (WNV) is a mosquito-transmitted disease of birds that has caused bird population declines and can spill over into human populations. Previous research has identified bird species that infect a large fraction of the total pool of infected mosquitoes and correlate with human infection risk; however, these analyses cover small spatial regions and cannot be used to predict transmission in bird communities in which these species are rare or absent. Here we present a mechanistic model for WNV transmission that predicts WNV spread (R0) in any bird community in North America by scaling up from the physiological responses of individual birds to transmission at the level of the community. We predict unmeasured bird species’ responses to infection using phylogenetic imputation, based on these species’ phylogenetic relationships with bird species with measured responses.ResultsWe focused our analysis on Texas, USA, because it is among the states with the highest total incidence of WNV in humans and is well sampled by birders in the eBird database. Spatio-temporal patterns: WNV transmission is primarily driven by temperature variation across time and space, and secondarily by bird community composition. In Texas, we predicted WNV R0 to be highest in the spring and fall when temperatures maximize the product of mosquito transmission and survival probabilities. In the most favorable months for WNV transmission (April, May, September and October), we predicted R0 to be highest in the “Piney Woods” and “Oak Woods & Prairies” ecoregions of Texas, and lowest in the “High Plains” and “South Texas Brush County” ecoregions. Dilution effect: More abundant bird species are more competent hosts for WNV, and predicted WNV R0 decreases with increasing species richness. Keystone species: We predicted that northern cardinals (Cardinalis cardinalis) are the most important hosts for amplifying WNV and that mourning doves (Zenaida macroura) are the most important sinks of infection across Texas.ConclusionsDespite some data limitations, we demonstrate the power of phylogenetic imputation in predicting disease transmission in heterogeneous host communities. Our mechanistic modeling framework shows promise both for assisting future analyses on transmission and spillover in heterogeneous multispecies pathogen systems and for improving model transparency by clarifying assumptions, choices and shortcomings in complex ecological analyses.

Quantum causal influence

We introduce a framework to study the emergence of time and causal structure in quantum many-body systems. In doing so, we consider quantum states which encode spacetime dynamics, and develop information theoretic tools to extract the causal relationships between putative spacetime subsystems. Our analysis reveals a quantum generalization of the thermodynamic arrow of time and begins to explore the roles of entanglement, scrambling and quantum error correction in the emergence of spacetime. For instance, exotic causal relationships can arise due to dynamically induced quantum error correction in spacetime: there can exist a spatial region in the past which does not causally influence any small spatial regions in the future, but yet it causally influences the union of several small spatial regions in the future. We provide examples of quantum causal influence in Hamiltonian evolution, quantum error correction codes, quantum teleportation, holographic tensor networks, the final state projection model of black holes, and many other systems. We find that the quantum causal influence provides a unifying perspective on spacetime correlations in these seemingly distinct settings. In addition, we prove a variety of general structural results and discuss the relation of quantum causal influence to spacetime quantum entropies.

Challenges in the NEGF Simulation of Quantum‐Well Photovoltaics Posed by Non‐Locality and Localization

In this paper, the implications of non‐locality and localization for the implementation and performance of quantum‐opto‐electronic device simulators based on the non‐equilibrium Green's function formalism are considered. It is shown that in the case of electron–photon interaction enabling interband transitions, restriction of the non‐locality range (the spatial distance over which the coupling acts) not only leads to an underestimation of the coupling strength as for intraband electron‐phonon scattering, but also to an inaccurate spectral shape of the response functions and to the violation of selection rules applying to the scattering rates. On the other hand, localization of electronic states (the restriction of finite probability density to a small spatial region) induced by discontinuities and fluctuations in the band profile has a detrimental impact on the speed of convergence of the self‐consistent evaluation of Green's functions and scattering self‐energies, as illustrated by the example of photocarrier extraction from different quantum well configurations.

Person-Independent Facial Expression Recognition with Histograms of Prominent Edge Directions

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.

Establishing a microscopic model for nonfullerene organic solar cells: Self-accumulation effect of charges.

A one-dimensional many-body tight-binding model is established to mimic the charge distribution and dynamics in nonfullerene organic solar cells. Two essential issues are taken into account in the model: the alternating donor and acceptor structure, which is beneficial for the direct generation of charge transfer state, and the local imbalance of the intrinsic electrons and holes. The most remarkable outcome of the model is that, due to the strong Coulomb attractive potential energy, the intrinsic charges in the cells are self-accumulated in a small spatial region and outside the self-accumulation region the charge density vanishes so that the recombination is regarded to be largely suppressed. The photogenerated electrons are subsequently observed to spread freely outside the self-accumulation region, implying that the Coulomb attraction does not matter in the ultrafast charge separation dynamics. These findings enable the understanding of the high performance of emerging nonfullerene cells, and the designing rules of molecules and devices are then comprehensively discussed.

Spatial Joint Species Distribution Modeling using Dirichlet Processes.

Species distribution models usually attempt to explain presence-absence or abundance of a species at a site in terms of the environmental features (so-called abiotic features) present at the site. Historically, such models have considered species individually. However, it is well-established that species interact to influence presence-absence and abundance (envisioned as biotic factors). As a result, there has been substantial recent interest in joint species distribution models with various types of response, e.g., presence-absence, continuous and ordinal data. Such models incorporate dependence between species response as a surrogate for interaction. The challenge we address here is how to accommodate such modeling in the context of a large number of species (e.g., order 102) across sites numbering on the order of 102 or 103 when, in practice, only a few species are found at any observed site. Again, there is some recent literature to address this; we adopt a dimension reduction approach. The novel wrinkle we add here is spatial dependence. That is, we have a collection of sites over a relatively small spatial region so it is anticipated that species distribution at a given site would be similar to that at a nearby site. Specifically, we handle dimension reduction through Dirichlet processes, enabling clustering of species, joined with spatial dependence across sites through Gaussian processes. We use both simulated data and a plant communities dataset for the Cape Floristic Region (CFR) of South Africa to demonstrate our approach. The latter consists of presence-absence measurements for 639 tree species at 662 locations. Through both data examples we are able to demonstrate improved predictive performance using the foregoing specification.

Necking instabilities in elastoviscoplastic materials

Necking instabilities, in which tensile (extensional) deformation localizes into a small spatial region, are generic failure modes in elasto-viscoplastic materials. Materials in this very broad class --- including amorphous, crystalline, polycrystalline and other materials --- feature a predominantly elastic response at small stresses, plasticity onset at a rather well-defined yield stress and rate-dependence. Necking instabilities involve a unique coupling between the system's geometry and its constitutive behavior. We consider generic elasto-viscoplastic constitutive relations involving an internal-state field, which represents the structural evolution of the material during plastic deformation, and study necking in the long-wavelength approximation (sometimes termed the lubrication or slender-bar approximation). We derive a general expression for the largest time-dependent eigenvalue in an approximate WKB-like linear stability analysis, highlighting various basic physical effects involved in necking. This expression is then used to propose criteria for the onset of necking and more importantly for the emergence of strong localization. Applications to strain-softening amorphous plasticity, in the framework of the Shear-Transformation-Zone model, and to strain-hardening crystalline/polycrystalline plasticity, in the framework of the Kocks-Mecking model, are presented. These quantitative analyses of widely different material models support the theoretical predictions, most notably for the strong localization during necking.

Hitchhiking in space: Ancestry in adapting, spatially extended populations.

Selective sweeps reduce neutral genetic diversity. In sexual populations, this "hitchhiking" effect is thought to be limited to the local genomic region of the sweeping allele. While this is true in panmictic populations, we find that in spatially extended populations the combined effects of many unlinked sweeps can affect patterns of ancestry (and therefore neutral genetic diversity) across the whole genome. Even low rates of sweeps can be enough to skew the spatial locations of ancestors such that neutral mutations that occur in an individual living outside a small region in the center of the range have virtually no chance of fixing in the population. The fact that nearly all ancestry rapidly traces back to a small spatial region also means that relatedness between individuals falls off very slowly as a function of the spatial distance between them.