Large Parameter Research Articles

Lightweight land cover classification via semantic segmentation of remote sensing imagery and analysis of influencing factors

Land cover classification is of great value and can be widely used in many fields. Earlier land cover classification methods used traditional image segmentation techniques, which cannot fully and comprehensively extract the ground information in remote sensing images. Therefore, it is necessary to integrate the advanced techniques of deep learning into the study of semantic segmentation of remote sensing images. However, most of current high-resolution image segmentation networks have disadvantages such as large parameters and high network training cost. In view of the problems above, a lightweight land cover classification model via semantic segmentation, DeepGDLE, is proposed in this paper. The model DeepGDLE is designed on the basis of DeeplabV3+ network and utilizes the GhostNet network instead of the backbone feature extraction network in the encoder. Using Depthwise Separable Convolution (DSC) instead of dilation convolution. This reduces the number of parameters and increases the computational speed of the model. By optimizing the dilation rate of parallel convolution in the ASPP module, the “grid effect” is avoided. ECANet lightweight channel attention mechanism is added after the feature extraction module and the pyramid pooling module to focus on the important weights of the model. Finally, the loss function Focal Loss is utilized to solve the problem of category imbalance in the dataset. As a result, the model DeepGDLE effectively reduces the parameters of the network model and the network training cost. And extensive experiments compared with several existing semantic segmentation algorithms such as DeeplabV3+, UNet, SegNet, etc. show that DeepGDLE improves the quality and efficiency of image segmentation. Therefore, compared to other networks, the DeepGDLE network model can be more effectively applied to land cover classification. In addition, in order to investigate the effects of different factors on the semantic segmentation performance of remote sensing images and to verify the robustness of the DeepGDLE model, a new remote sensing image dataset, FRSID, is constructed in this paper. This dataset takes into account more influences than the public dataset. The experimental results show that on the WHDLD dataset, the experimental metrics mIoU, mPA, and mRecall of the proposed model, DeepGDLE, are 62.29%, 72.85%, and 72.46%, respectively. On the FRSID dataset, the metrics mIoU, mPA, and mRecall are 65.89%, 74.43%, and 74.08%, respectively. For the future scope of research in this field, it may focus on the fusion of multi-source remote sensing data and the intelligent interpretation of remote sensing images.

Search for top-philic heavy resonances in pp collisions at s=13\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{s}=13$$\\end{document} TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document} with the ATLAS detector

A search for the associated production of a heavy resonance with a top-quark or a top-antitop-quark pair, and decaying into a tt¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$t{\\bar{t}}$$\\end{document} pair is presented. The search uses the data recorded by the ATLAS detector in pp collisions at s=13\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{s}= 13$$\\end{document} TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document} at the Large Hadron Collider during the years 2015–2018, corresponding to an integrated luminosity of 139 fb-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {fb}^{-1}$$\\end{document}. Events containing exactly one electron or muon are selected. The two hadronically decaying top quarks from the resonance decay are reconstructed using jets clustered with a large radius parameter of R=1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R=1$$\\end{document}. The invariant mass spectrum of the two top quark candidates is used to search for a resonance signal in the range of 1.0 TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document} to 3.2 TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document}. The presence of a signal is examined using an approach with minimal model dependence followed by a model-dependent interpretation. No significant excess is observed over the background expectation. Upper limits on the production cross section times branching ratio at 95% confidence level are provided for a heavy Z′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z^\\prime $$\\end{document} boson based on a simplified model, for Z′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z^\\prime $$\\end{document} mass between 1.0 TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document} and 3.0 TeV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {TeV}$$\\end{document}. The observed (expected) limits range from 21 (14) fb to 119 (86) fb depending on the choice of model parameters.

Coronal dimming parameters and their variations in the 24th solar cycle

We analyzed coronal dimming parameters and their relation to coronal mass ejections to determine the location of possible ejections sources on the solar disk in the 24th solar cycle. We used Solar Demon database that contains flares and dimmings parameters obtained from SDO/AIA image. Coronal mass ejections from the CACTus database were associated with 16% of all the dimmings for the period 2010–2018. On average, dimmings associated with coronal mass ejections are events with large absolute parameter values. Correlation coefficient between dimming position angle and associated coronal mass ejection position angle is 0.96. Correlation coefficients between the coronal mass ejection speed and dimming parameters are close to 0.5 for dimmings in the central region of the solar disk. Obtained results can be used to model coronal mass ejections propagation and to define the probability of their arrival in near-Earth space.

Conventional and Unconventional Dicke Models: Multistabilities and Nonequilibrium Dynamics.

The Dicke model describes the collective behavior of a subwavelength-size ensemble of two-level atoms (i.e., spin-1/2) interacting identically with a single quantized radiation field of a cavity. Across a critical coupling strength it exhibits a zero-temperature phase transition from the normal state to the superradiant phase where the field is populated and the collective spin acquires a nonzero x component, which can be imagined as ferromagnetic ordering of the atomic spins along x. Here we introduce a variant of this model where two subwavelength-size ensembles of spins interact with a single quantized radiation field with different strengths. Subsequently, we restrict ourselves to a special case where the coupling strengths are opposite (which is unitarily equivalent to equal-coupling strengths). Because of the conservation of the total spin in each ensemble individually, the system supports two distinct superradiant states with x-ferromagnetic and x-ferrimagnetic spin ordering, coexisting with each other in a large parameter regime. The stability and dynamics of the system in the thermodynamic limit are examined using a semiclassical approach, which predicts nonstationary behaviors due to the multistabilities. At the end, we also perform small-scale full quantum-mechanical calculations, with results consistent with the semiclassical ones.

The AGORA High-resolution Galaxy Simulations Comparison Project. VI. Similarities and Differences in the Circumgalactic Medium

We analyze the circumgalactic medium (CGM) for eight commonly-used cosmological codes in the AGORA collaboration. The codes are calibrated to use identical initial conditions, cosmology, heating and cooling, and star formation thresholds, but each evolves with its own unique code architecture and stellar feedback implementation. Here, we analyze the results of these simulations in terms of the structure, composition, and phase dynamics of the CGM. We show properties such as metal distribution, ionization levels, and kinematics are effective tracers of the effects of the different code feedback and implementation methods, and as such they can be highly divergent between simulations. This is merely a fiducial set of models, against which we will in the future compare multiple feedback recipes for each code. Nevertheless, we find that the large parameter space these simulations establish can help disentangle the different variables that affect observable quantities in the CGM, e.g., showing that abundances for ions with higher ionization energy are more strongly determined by the simulation’s metallicity, while abundances for ions with lower ionization energy are more strongly determined by the gas density and temperature.

MTLink: Adaptive multi-task learning based pre-trained language model for traceability link recovery between issues and commits

Traceability links between issues and commits (issue-commit links recovery (ILR)) play a significant role in software maintenance tasks by enhancing developers’ observability in practice. Recent advancements in large language models, particularly pre-trained models, have improved the effectiveness of automated ILR. However, these models’ large parameter sizes and extended training time pose challenges in large software projects. Besides, existing methods often overlook the association and distinction among artifacts, leading to the generation of erroneous links. To mitigate these problems, this paper proposes a novel link recovery method called MTLink. It utilizes multi-teacher knowledge distillation (MTKD) to compress the model and employs an adaptive multi-task strategy to reduce information loss and improve link accuracy. Experiments are conducted on four open-source projects. The results show that (i) MTLink outperforms state-of-the-art methods; (ii) The multi-teacher knowledge distillation maintains accuracy despite model size reduction; (iii) The adaptive multi-task tracing method effectively handles confusion caused by similar artifacts and balances each task. In conclusion, MTLink offers an efficient solution for ILR in software traceability. The code is available at https://zenodo.org/records/10321150.

Gravitational Regge bounds

We review the basic assumptions and spell out the detailed arguments that lead to the bound on the Regge growth of gravitational scattering amplitudes. The minimal extra ingredient compared to the gapped case - in addition to unitarity, analyticity, subexponentiality, and crossing - is the assumption that scattering at large impact parameters is controlled by known semi-classical physics. We bound the Regge growth of amplitudes both with the fixed transferred momentum and smeared over it. Our basic conclusion is that gravitational scattering amplitudes admit dispersion relations with two subtractions. For a sub-class of smeared amplitudes, black hole formation reduces the number of subtractions to one. Finally, using dispersion relations with two subtractions we derive bounds on the local growth of relativistic scattering amplitudes. Schematically, the local bound states that the amplitude cannot grow faster than s^2s2. The results obtained in the paper are valid for d> 4d>4 for which the 2\to22→2 scattering amplitude is well-defined.

N scaling of large-sample collective decay in inhomogeneous ensembles

We experimentally study collective decay of an extended disordered ensemble of N atoms inside a hollow-core fiber. We observe up to 300-fold enhanced decay rates, strong optical bursts, and a coherent ringing. Due to inhomogeneities limiting the synchronization of atoms, the data does not show the typical scaling with N. We show that an effective number of collective emitters can be determined to recover the N scaling known to homogeneous ensembles over a large parameter range. This provides physical insight into the limits of collective decay and allows for its optimization in extended ensembles as used, e.g., in quantum optics, precision time-keeping, or waveguide QED. Published by the American Physical Society 2024

Adaptive time-varying state safety constraint control for discrete-time nonlinear systems with random actuator failures

This work investigates the adaptive time-varying state safety constraint control problem for a class of discrete-time nonlinear systems subject to large parameter uncertainties and stochastic actuator failures for the first time. The existence of time-varying full-state constraints, large parameter uncertainties and stochastic actuator failures leads to a series of difficulties for realizing all control objectives. Due to the absence of the linearity property of the derivative in discrete-time log type barrier Lyapunov functions, they are not used to deal with the state constraint problem of nonlinear discrete-time systems. The discrete quadratic-fraction time-varying barrier Lyapunov function is employed to guarantee that all states are constrained in the time-varying predefined regions. By virtue of the constructed multiple-model set, an adaptive identification algorithm is developed to deal with large parameter uncertainties and it has a clear advantage that this method does not requires cn (where n is the dimension of the parameter vector and c is an integer) identification models and only relies on n+1 identification models, thereby heavily reducing the computational burden. By employing the discrete-time filter and backstepping techniques, the adaptive failure compensation controller is designed to ensure the boundedness in probability of the considered systems with respect to stochastic actuator failures. Finally, the effectiveness of the proposed scheme is proved by two simulation examples.

Multivariable robust tube-based nonlinear model predictive control of mammalian cell cultures

In this paper, the application of a robust nonlinear model predictive control (NMPC) framework to mammalian cell cultures is proposed, dealing with possible large kinetic parameter uncertainties. Industrial constraints formulated in view of good manufacturing practice and quality-by-design approach are also considered, namely the assurance that all state trajectories are contained within a corridor defined by lower and upper safety bounds. The latter are assimilated to the well-known tube-based paradigm which is used to formulate the corresponding robust NMPC problem. Both classical and tube-based NMPC performances are assessed in numerical simulations where specific key-species are regulated while dealing with an uncertain plant model. The capability of the tube-based method to reduce the impact of the parameter variations on the state trajectories and the violation of the constraints is highlighted, suggesting the transfer of the method on a real pharmaceutical process.

Critical states and anomalous mobility edges in two-dimensional diagonal quasicrystals

We study the single-particle properties of two-dimensional quasicrystals where the underlying geometry of the tight-binding lattice is crystalline but the on-site potential is quasicrystalline. We will focus on the two-dimensional (2D) generalized Aubry-André model which has a varying form to its quasiperiodic potential, through a deformation parameter and varied irrational periods of cosine terms, which allows a continuous family of on-site quasicrystalline models to be studied. We show that the 2D generalized Aubry-André model exhibits many single-particle mobility edges which we confirm for finite systems and supports critical states across large parameter regions. Critical states are neither fully localized nor extended. We observe that diagonal quasicrystalline models can support many energy intervals of critical states in the spectrum while stabilizing both localized and extended states in other energy intervals; we refer to these as anomalous mobility edges. We show that critical states are present independent of system size through a scaling analysis of the inverse participation ratio and that they are present in spectra that also contain extended and localized states, confirming that at least one anomalous mobility edge is present. Due to this, these models exhibit anomalous diffusion of initially localized states across the majority of parameter regions, including deep in the normally localized regime. The presence of critical states in large parameter regimes and throughout the spectrum will have consequences for the many-body properties of quasicrystals, including the formation of the Bose glass and the potential to host a many-body localized phase. Published by the American Physical Society 2024

Aiming for tops of ALPs with a muon collider

Future muon colliders with center-of-mass energy of O\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{O} $$\\end{document}(1 − 10) TeV can provide a clean high-energy environment with advantages in searches for TeV-scale axion-like particles (ALPs), pseudo-Nambu-Goldstone bosons associated with spontaneously broken global symmetries, which are widely predicted in physics beyond the Standard Model (SM). We exploit ALP couplings to SM fermions, and guided by unitarity constraints, build a search strategy focusing on the ALP decay to top quark pairs at muon colliders. It is found that a large parameter space of TeV-scale ALPs with TeV-scale decay constants can be probed by utilizing the ALP-top quark coupling.

Dipolar Spin Ice Regime Proximate to an All-In-All-Out Néel Ground State in the Dipolar-Octupolar Pyrochlore Ce2Sn2O7

The dipolar-octupolar (DO) pyrochlores, R2M2O7 (R=Ce,Sm,Nd), are key players in the search for realizable novel quantum spin liquid (QSL) states as a large parameter space within the DO pyrochlore phase diagram is theorized to host QSL states of both dipolar and octupolar nature. New single crystals and powders of Ce2Sn2O7, synthesized by hydrothermal techniques, present an opportunity for a new characterization of the exchange parameters in Ce2Sn2O7 using the near-neighbor XYZ model Hamiltonian associated with DO pyrochlores. Utilizing quantum numerical linked cluster expansion fits to heat capacity and magnetic susceptibility measurements, and classical Monte Carlo calculations to the diffuse neutron diffraction of the new hydrothermally grown Ce2Sn2O7 samples, we place Ce2Sn2O7’s ground state within the ordered dipolar all-in-all-out (AIAO) Néel phase, with quantum Monte Carlo calculations showing a transition to long-range order at temperatures below those accessed experimentally. Indeed, our new neutron diffraction measurements on the hydrothermally grown Ce2Sn2O7 powders show a broad signal at low scattering wave vectors, reminiscent of a spin ice, in striking contrast from previous powder neutron diffraction on samples grown from solid-state synthesis, which found diffuse scattering at high scattering wave vectors associated with magnetic and suggested an octupolar quantum spin ice state. We conclude that new hydrothermally grown Ce2Sn2O7 samples host a finite-temperature proximate dipolar spin ice phase, above the expected transition to AIAO Néel order. Published by the American Physical Society 2024

Logistic elliptic equation with a nonlinear boundary condition arising from coastal fishery harvesting II

We study positive solutions of a logistic elliptic equation with a nonlinear boundary condition that models coastal fishery harvesting ([18]). An essential role is played by the smallest eigenvalue of the Dirichlet eigenvalue problem, in terms of which, a noncritical case is studied in [32]. In this paper, we extend our analysis to the critical case. We also further study the noncritical case for a more precise description of the positive solution set, including uniqueness and stability analysis for large parameters. Our approach relies on an energy method, sub- and supersolutions, and implicit function analysis.

Modelling the asymmetric impact of fintech, natural resources, and environmental regulations on ecological footprint in G7 countries

Ecological sustainability is one of the utmost agenda for policymakers across the world. In this dimension, identifying the innovative role of Fintech is imperative to ensure an efficient resource allocation with inclusive economic and environmental performance. G7 countries are divergent in resource endowment, technological advancement, financial integrity, environmental controls and structural shifts. Therefore, the study employs the nonlinear method of moments quantile regression (MMQR) for the empirical investigation to evaluate the asymmetric influence of Fintech, natural resources rent, and ecological regulations on ecological footprints (EF) from 2000 to 2020. The pre-requisite analysis affirms the abnormal data distribution and structural variations. The estimated outcomes demonstrate that Fintech significantly reduces EF across all quantiles except the highest (0.95th) quantile. Likewise, ecological governance significantly discourages the EF from lower to higher quantiles and has large parameter coefficients at higher ecological deficits. In contrast, natural resources significantly increases EF from lower to upper EF quantiles, whereas the positive marginal influences are prominent at upper quantiles. The robustness check verifies the consistent results. Panel causality analysis exhibits a one-way causal relationship between Fintech, environmental regulations, and EF and a two-way causality connection among natural resources, economic growth, and EF.

Cryogenic Fiber-coupled Electro-optic Characterization Platform for High-speed Photodiodes

We have developed a cryogenic characterization platform for ultrafast photodiodes, whose time domain responses are extracted by electro-optic sampling using femtosecond laser pulses in a pump-probe configuration. The excitation of the photodiodes with the pump beam and the electro-optic sampling crystals with the probe beam are realized in a fully fiber-coupled manner. This allows us to use the characterization platform at different temperatures, ranging from cryogenic to room temperature. As an application example, we characterize the time-domain response of commercial p-i-n photodiodes with a nominal bandwidth of 20 GHz and 60 GHz at temperatures of 4 K and 300 K and in a large parameter range of photocurrent and reverse bias. For these photodiodes, we detect frequency components up to approximately 250 GHz, while the theoretical bandwidth of our sampling method exceeds 1 THz. Our measurements demonstrate a significant excitation power and temperature dependence of the photodiodes’ ultrafast time responses, reflecting, most likely, changes in carrier mobilities and electric field screening. Since our system is an ideal tool to characterize and optimize the response of fast photodiodes at cryogenic temperatures, it has a direct impact on applications in superconducting quantum technology such as the enhancement of optical links to superconducting qubits and quantum-accurate waveform generators.

A comprehensive diversity analysis on the gut microbiomes of ASD patients: from alpha, beta to gamma diversities.

Autism spectrum disorder (ASD) is estimated to influence as many as 1% children worldwide, but its etiology is still unclear. It has been suggested that gut microbiomes play an important role in regulating abnormal behaviors associated with ASD. A de facto standard analysis on the microbiome-associated diseases has been diversity analysis, and nevertheless, existing studies on ASD-microbiome relationship have not produced a consensus. Here, we perform a comprehensive analysis of the diversity changes associated with ASD involving alpha-, beta-, and gamma-diversity metrics, based on 8 published data sets consisting of 898 ASD samples and 467 healthy controls (HC) from 16S-rRNA sequencing. Our findings include: (i) In terms of alpha-diversity, in approximately 1/3 of the studies cases, ASD patients exhibited significantly higher alpha-diversity than the HC, which seems to be consistent with the "1/3 conjecture" of diversity-disease relationship (DDR). (ii) In terms of beta-diversity, the AKP (Anna Karenina principle) that predict all healthy microbiomes should be similar, and every diseased microbiome should be dissimilar in its own way seems to be true in approximately 1/2 to 3/4 studies cases. (iii) In terms of gamma-diversity, the DAR (diversity-area relationship) modeling suggests that ASD patients seem to have large diversity-area scaling parameter than the HC, which is consistent with the AKP results. However, the MAD (maximum accrual diversity) and RIP (ratio of individual to population diversity) parameters did not suggest significant differences between ASD patients and HC. Throughout the study, we adopted Hill numbers to measure diversity, which stratified the diversity measures in terms of the rarity-commonness-dominance spectrum. It appears that the differences between ASD patients and HC are more propounding on rare-species side than on dominant-species side. Finally, we discuss the apparent inconsistent diversity-ASD relationships among different case studies and postulate that the relationships are not monotonic.

A deep transfer learning approach to construct the allowable load space of notched composite laminates

Allowable load is one of the core parameters for the design and service of composite structures (CSs). However, due to the large design parameters, cumbersome design procedure and complicated simulation model of CSs, considerable amounts of experiments and simulations are needed to determine the allowable load of CSs, which is costly and inefficient, hindering the wide application of CSs in industry. In this work, we present a general deep transfer learning approach to construct the allowable load space (ALS) of notched laminates by considering various design parameters such as geometries, materials, stacking angles, ply numbers, laminate types and load types. Initially, an ensemble deep neural network (Ensemble) is trained, which can predict the allowable loads of notched laminate with known design parameters well. Here the Ensemble guided by ensemble learning is trained to reduce the errors generated by manually setting. Then, the pre-trained Ensemble is transferred to new design parameters by fine-tuning it with scarce new samples. Finally, the ALS of notch laminates is constructed by integrating the pre-trained and fine-tuned models, covering both known and diverse new design parameters. Our approach can easily be extended to other CSs.

Treams – a T-matrix-based scattering code for nanophotonics

We report the publication of treams, a new software for electromagnetic scattering computations based on the T-matrix method. Besides conventional T-matrix calculations for individual scatterers and finite clusters of particles, a unique feature of the code is its full support for periodic boundaries in one, two, and all three spatial dimensions. We use highly efficient and quickly converging lattice summation techniques based on the Ewald method to evaluate the arising lattice sums in these cases. In addition to the common use of vector spherical waves as a basis set for the T-matrix, vector cylindrical waves are also implemented. To describe stratified media, vector plane waves are used with an S-matrix description of the electromagnetic scattering. All basis sets and the associated methods can be used together with chiral constitutive relations. Thereby, chiral embedding media are supported, as well as scatterers made from chiral materials.This contribution outlines the basic methods implemented and the program structure. Two interfaces to the implemented functionality are available: a flexible and fast low-level interface and a high-level interface for added convenience and plausibility checks. We conclude with two examples: a demonstration of the field calculation in various lattices and the explorations of quasi-bound states in the continuum. The presented code was already used in calculations for various physical systems: from the mode properties of molecular arrays in cavities to analytical models for metasurfaces and from moiré lattices to the homogenization of artificial photonic materials. With the publication of treams and the associated documentation, we hope to empower more scientists to make an efficient, fast, and precise exploration of nanophotonic systems that can be described in the broader framework of scattering theory. Program summaryProgram title: treamsCPC Library link to program files:https://doi.org/10.17632/2np8snmzfx.1Developer's repository link:https://github.com/tfp-photonics/treamsLicensing provisions: MITProgramming language: Python and CythonNature of problem: Simulating electromagnetic scattering in periodic nanophotonic structures, when different length scales are present or for large parameter sweeps, require specialized tools that can solve Maxwell's equations more efficiently than general-purpose solvers. A possible tool for these computations is the T-matrix method, which needs to be amended by suitable lattice summation schemes in the presence of periodic boundary conditions.Solution method: The properties of the individual scatterers are described by T-matrices, such that the interaction can be solved analytically. The slowly converging lattice sums that appear in the presence of periodic boundary conditions are computed by converting them to two quickly converging series using Ewald's method. Depending on the lattice dimensions and the geometry of the scatterers, vector spherical, cylindrical, or plane waves are used. Using modes of well-defined helicity enables the straightforward inclusion of chiral material parameters for scatterers and embedding media.

On the evolution of a twisted thin accretion disc in eccentric inclined supermassive binary black holes

ABSTRACT We propose a model of a twisted accretion disc around a Kerr black hole interacting with a secondary black hole of a smaller mass on an inclined eccentric orbit. We use parameters of the system, which may be appropriate for the so-called precessing massive model of OJ 287. We calculate expressions for torque exerted on the disc by the secondary and a contribution of the secondary to the apsidal precession of disc elements by a double averaging procedure over the periods of the secondary and the disc elements. These expressions are used at all scales of interest, including the ones inside the binary orbit. We calculate numerically the evolution of the disc tilt and twist assuming a flat initial configuration. We consider the disc aspect ratio h/r = 10−3, a rather large viscosity parameter α = 0.1 and several values of the primary rotational parameter, χ. We find that, after a few periods of Lense–Thirring precession of the orbit, the disc relaxes to a quasi-stationary configuration in the precessing frame with a non-trivial distribution of the disc inclination angle, β, over the radial scale. We propose an analytic model for this configuration. We show that the presence of the twisted disc leads to multiple crossings of the disc by the secondary per one orbital period, with time periods between the crossings being different from the flat disc model. Our results should be taken into account in the modelling of OJ 287. They can also be applied to similar sources.