Symmetry Requirements Research Articles

Second harmonic generation induced by gate voltage oscillation in few layer MnBi2Te4

Nonlinear charge transport, such as nonreciprocal longitudinal resistance and nonlinear Hall effect, has attracted considerable interest in probing the symmetries and topological properties of new materials. Recent research has revealed significant nonreciprocal longitudinal resistance and nonlinear Hall effect in MnBi2Te4, an intrinsic magnetic topological insulator, induced by the quantum metric dipole. However, the inconsistent response with charge density and conflicting C3z symmetry requirement necessitate a thorough understanding of factors affecting the nonlinear transport measurement. This study uncovers an experimental factor leading to significant nonlinear transport signals in MnBi2Te4, attributed to gate voltage oscillation from the application of large alternating current. Additionally, a methodology is proposed to suppress this effect by individually grounding the voltage electrodes during second-harmonic measurements. The investigation underscores the critical importance of assessing gate voltage oscillation’s impact before determining the intrinsic nature of nonlinear transport in 2D material devices with an electrically connected operative gate electrode.

A Switching Memory-Based Event-Trigger Scheme for Synchronization of Lur'e Systems With Actuator Saturation: A Hybrid Lyapunov Method.

This article is concerned with the event-triggered synchronization of Lur'e systems subject to actuator saturation. Aiming at reducing control costs, a switching-memory-based event-trigger (SMBET) scheme, which allows a switching between the sleeping interval and the memory-based event-trigger (MBET) interval, is first presented. In consideration of the characteristics of SMBET, a piecewise-defined but continuous looped-functional is newly constructed, under which the requirement of positive definiteness and symmetry on some Lyapunov matrices is dropped within the sleeping interval. Then, a hybrid Lyapunov method (HLM), which bridges the gap between the continuous-time Lyapunov theory (CTLT) and the discrete-time Lyapunov theory (DTLT), is used to make the local stability analysis of the closed-loop system. Meanwhile, using a combination of inequality estimation techniques and the generalized sector condition, two sufficient local synchronization criteria and a codesign algorithm for the controller gain and triggering matrix are developed. Furthermore, two optimization strategies are, respectively, put forward to enlarge the estimated domain of attraction (DoA) and the allowable upper bound of sleeping intervals on the premise of ensuring local synchronization. Finally, a three-neuron neural network and the classical Chua's circuit are used to carry out some comparison analyses and to display the advantages of the designed SMBET strategy and the constructed HLM, respectively. Also, an application to image encryption is provided to substantiate the feasibility of the obtained local synchronization results.

Time-dependent scalings and Fock quantization of a massless scalar field in Kantowski–Sachs

Abstract We address the issue of inequivalent Fock representations in quantum field theory in a curved homogenous and anisotropic cosmological background, namely Kantowski–Sachs spacetime, which can also be used to describe the interior of a nonrotating black hole. A family of unitarily equivalent Fock representations that are invariant under the spatial isometries and implement a unitary dynamics can be achieved by means of a field redefinition that consists of a specific anisotropic scaling of the field configuration and a linear transformation of its momentum. Remarkably, we show that this kind of field redefinition is in fact unique under our symmetry and unitary requirements. However, the physical properties of the Hamiltonian dynamics that one obtains in this way are not satisfactory, inasmuch as the action of the Hamiltonian on the corresponding particle states is ill defined. To construct a quantum theory without this problem, we need a further canonical transformation that is time- and mode-dependent and is not interpretable as an anisotropic scaling. The old and new Fock representations, nevertheless, are unitarily equivalent. The freedom that is introduced when allowing for this further canonical transformation can be fixed by demanding an asymptotic diagonalization of the Hamiltonian and a minimal absorption of dynamical phases. In this way, the choice of vacuum and the associated Fock representation are asymptotically determined.

Universal Quantum Fisher Information and Simultaneous Occurrence of Landau‐Class and Topological‐Class Transitions in Non‐Hermitian Jaynes‐Cummings Models

AbstractLight‐matter interactions provide an ideal testground for interplay of critical phenomena, topological transitions, quantum metrology, and non‐Hermitian physics with high controllability and tunability. The present work considers two fundamental non‐Hermitian Jaynes‐Cummings models in light‐matter interactions that possess real energy spectra in parity‐time (PT) symmetry and anti‐PT symmetry. The quantum Fisher information is shown to be critical around the transitions at the exceptional points and exhibit a super universality, with respect to different parameters, all energy levels, both models, symmetric phases, and symmetry‐broken phases, which guarantees a universally high measurement precision in quantum metrology. In particular, the transitions are found to be both symmetry‐breaking Landau‐class transitions (LCTs) and symmetry‐protected topological‐class transitions (TCTs), thus realizing a simultaneous occurrence of critical LCTs and TCTs that are conventionally incompatible due to contrary symmetry requirements. Besides establishing a paradigmatic case to break the incompatibility of the LCTs and the TCTs in non‐Hermitian systems, the both availabilities of the sensitive critical feature and the robust topological feature can also provide more potential for designing quantum devices or sensors.

Management of Atypical M-Shaped Zygomatic Arch Fractures.

M-shaped zygomatic arch fractures can usually be treated effectively through closed reduction. It consists of 2 fracture segments: the anterior zygomatic segment and the posterior temporal bone segment. In clinical practice, atypical M-shaped fractures are often encountered, in which the anterior and posterior fracture segments are discontinuous and separated. Closed reduction usually cannot achieve the desired anatomic reduction effect for this type of fracture. The preoperative design showed that the anatomic reduction of the posterior zygomatic arch fracture segment was hindered due to bone spurs in the most concave area of the anterior zygomatic bone fracture segment. Open reduction and fixation were performed to achieve anatomic reduction and restore facial symmetry. The fracture sites were exposed through a hemicoronal incision. After the bone spurs are removed, the posterior bone segment can be anatomically reduced. Absorbable plates were used for fixation. The patient's facial appearance was restored after the surgery. The postoperative computed tomography scan showed a good alignment of the fracture. The authors believe that for patients with high requirements for facial symmetry, the presence of atypical M-shaped fractures can indicate open reduction and fixation.

Two-dimensional altermagnets from high throughput computational screening: Symmetry requirements, chiral magnons, and spin-orbit effects

We present a high throughput computational search for altermagnetism in two-dimensional (2D) materials based on the Computational 2D Materials Database (C2DB). We start by showing that the symmetry requirements for altermagnetism in 2D are somewhat more strict compared to bulk materials and applying these yields a total of seven altermagnets in the C2DB. The collinear ground state in these monolayers is verified by spin spiral calculations using the generalized Bloch theorem. We focus on four d-wave altermagnetic materials belonging to the P21′/c′ magnetic space group—RuF4, VF4, AgF2, and OsF4. The first three of these are known experimentally as van der Waals bonded bulk materials and are likely to be exfoliable from their bulk parent compounds. We perform a detailed analysis of the electronic structure and non-relativistic spin splitting in k-space exemplified by RuF4. The magnon spectrum of RuF4 is calculated from the magnetic force theorem, and it is shown that the symmetries that enforce degenerate magnon bands in anti-ferromagnets are absent in altermagnets and give rise to the non-degenerate magnon spectrum. We then include spin–orbit effects and show that these will dominate the splitting of magnons in RuF4. Finally, we provide an example of i-wave altermagnetism in the 2H-phase of FeBr3.

High precision 3 × 3 coupler demodulation algorithm with an additional phase shift judgment module

Ellipse fitting algorithms (EFAs) have been widely used in 3×3 coupler demodulation systems to reduce the requirement for symmetry of the 3×3 couplers. Based on the relative stability of the splitting ratio and phase difference after the establishment of the 3×3 coupler demodulation system, we solve the problem that EFA fails to work when the stimulating signal is small. Depending on the existence of a symmetry point about the origin, an additional phase shift judgment module is used to determine whether the Lissajous figure is larger than π rad. If the elliptical arc exceeds π rad, the EFA is executed. Otherwise, the previous parameters are used to correct the ellipse. Parameters are updated in real time to ensure high precision. The experimental results show that the total harmonic distortion (THD) of the ameliorated algorithm is improved by 1.28% compared to the EFA without the judgment module with a stimulus amplitude of 30 mV. The proposed scheme can effectively improve the dynamic range of the 3×3 coupler demodulation to reach 125.64 dB @ 1 kHz and 1% THD. The algorithm ensures the effective operation of the EFA under small phase shift conditions and improves the accuracy of phase demodulation.

Black holes, conformal symmetry, and fundamental fields

Cosmic censorship protects the outside world from black hole singularities and paves the way for assigning entropy to gravity at the event horizons. We point out a tension between cosmic censorship and the quantum backreacted geometry of Schwarzschild black holes, induced by vacuum polarization and driven by the conformal anomaly. A similar tension appears for the Weyl curvature hypothesis at the Big Bang singularity. We argue that the requirement of exact conformal symmetry resolves both conflicts and has major implications for constraining the set of fundamental constituents of the Standard Model.

Angle-resolved transport non-reciprocity and spontaneous symmetry breaking in twisted trilayer graphene.

The identification and characterization of spontaneous symmetry breaking is central to our understanding of strongly correlated two-dimensional materials. In this work, we utilize the angle-resolved measurements of transport non-reciprocity to investigate spontaneous symmetry breaking in twisted trilayer graphene. By analysing the angular dependence of non-reciprocity in both longitudinal and transverse channels, we are able to identify the symmetry axis associated with the underlying electronic order. We report that a hysteretic rotation in the mirror axis can be induced by thermal cycles and a large current bias, supporting the spontaneous breaking of rotational symmetry. Moreover, the onset of non-reciprocity with decreasing temperature coincides with the emergence of orbital ferromagnetism. Combined with the angular dependence of the superconducting diode effect, our findings uncover a direct link between rotational and time-reversal symmetry breaking. These symmetry requirements point towards exchange-driven instabilities in momentum space as a possible origin for transport non-reciprocity in twisted trilayer graphene.

Comprehensive Sensitivity Analysis Framework for Transfer Learning Performance Assessment for Time Series Forecasting: Basic Concepts and Selected Case Studies

Recently, transfer learning has gained popularity in the machine learning community. Transfer Learning (TL) has emerged as a promising paradigm that leverages knowledge learned from one or more related domains to improve prediction accuracy in a target domain with limited data. However, for time series forecasting (TSF) applications, transfer learning is relatively new. This paper addresses the need for empirical studies as identified in recent reviews advocating the need for practical guidelines for Transfer Learning approaches and method designs for time series forecasting. The main contribution of this paper is the suggestion of a comprehensive framework for Transfer Learning Sensitivity Analysis (SA) for time series forecasting. We achieve this by identifying various parameters seen from various angles of transfer learning applied to time series, aiming to uncover factors and insights that influence the performance of transfer learning in time series forecasting. Undoubtedly, symmetry appears to be a core aspect in the consideration of these factors and insights. A further contribution is the introduction of four TL performance metrics encompassed in our framework. These TL performance metrics provide insight into the extent of the transferability between the source and the target domains. Analyzing whether the benefits of transferred knowledge are equally or unequally accessible and applicable across different domains or tasks speaks to the requirement of symmetry or asymmetry in transfer learning. Moreover, these TL performance metrics inform on the possibility of the occurrence of negative transfers and also provide insight into the possible vulnerability of the network to catastrophic forgetting. Finally, we discuss a sensitivity analysis of an Ensemble TL technique use case (with Multilayer Perceptron models) as a proof of concept to validate the suggested framework. While the results from the experiments offer empirical insights into various parameters that impact the transfer learning gain, they also raise the question of network dimensioning requirements when designing, specifically, a neural network for transfer learning.

Frequency-independent optical spin injection in Weyl semimetals

We demonstrate that in Weyl semimetals, the momentum-space helical spin texture can couple to the chirality of the Weyl node to generate a frequency-independent optical spin injection. This frequency-independence is rooted in the topology of the Weyl node. Since the helicity and the chirality are always locked for Weyl nodes, the injected spin from a pair of Weyl nodes always add up, implying no symmetry requirements for Weyl semimetals. Finally, we show that such frequency-independent spin injection is robust against multiband corrections and lattice-regularization effect and capable of realizing all-optical magnetization switching in the THz regime.

SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations.

Recently, we introduced a class of molecular representations for kernel-based regression methods─the spectrum of approximated Hamiltonian matrices (SPAHM)─that takes advantage of lightweight one-electron Hamiltonians traditionally used as a self-consistent field initial guess. The original SPAHM variant is built from occupied-orbital energies (i.e., eigenvalues) and naturally contains all of the information about nuclear charges, atomic positions, and symmetry requirements. Its advantages were demonstrated on data sets featuring a wide variation of charge and spin, for which traditional structure-based representations commonly fail. SPAHM(a,b), as introduced here, expand the eigenvalue SPAHM into local and transferable representations. They rely upon one-electron density matrices to build fingerprints from atomic and bond density overlap contributions inspired from preceding state-of-the-art representations. The performance and efficiency of SPAHM(a,b) is assessed on the predictions for data sets of prototypical organic molecules (QM7) of different charges and azoheteroarene dyes in an excited state. Overall, both SPAHM(a) and SPAHM(b) outperform state-of-the-art representations on difficult prediction tasks such as the atomic properties of charged open-shell species and of π-conjugated systems.

Time warping between main epidemic time series in epidemiological surveillance.

The most common reported epidemic time series in epidemiological surveillance are the daily or weekly incidence of new cases, the hospital admission count, the ICU admission count, and the death toll, which played such a prominent role in the struggle to monitor the Covid-19 pandemic. We show that pairs of such curves are related to each other by a generalized renewal equation depending on a smooth time varying delay and a smooth ratio generalizing the reproduction number. Such a functional relation is also explored for pairs of simultaneous curves measuring the same indicator in two neighboring countries. Given two such simultaneous time series, we develop, based on a signal processing approach, an efficient numerical method for computing their time varying delay and ratio curves, and we verify that its results are consistent. Indeed, they experimentally verify symmetry and transitivity requirements and we also show, using realistic simulated data, that the method faithfully recovers time delays and ratios. We discuss several real examples where the method seems to display interpretable time delays and ratios. The proposed method generalizes and unifies many recent related attempts to take advantage of the plurality of these health data across regions or countries and time, providing a better understanding of the relationship between them. An implementation of the method is publicly available at the EpiInvert CRAN package.

On the use of double‐double design philosophy in the redesign of composite fuselage barrel frame components

AbstractThe use of optimization procedures can provide a valuable contribution in optimizing the laminate design of composite components for mass minimization and mechanical performance maximization. Design for weight and strength requirements of composite structures can be efficiently provided with the newly developed double‐double laminates concept, which allows to overcome the conventional 0, 90, and ±45° ply orientations and symmetry requirements in laminates. In the double‐double designed components, composite laminates are made up stacking thin sub‐laminates with four [±Φ, ±Ψ] oriented plies without symmetry requirements. In the present paper, the lay‐up and thickness profile of the composite frames in a fuselage section have been redesigned according to the double‐double design concept taking into account the operating loads. The starting quad configuration has been replaced by an optimized double‐double configuration with suitable lay‐up and thickness profile for each of the frames, while achieving a reduction in the total components mass.Highlights Double‐double laminates offer a novel approach to composite laminate design. Double‐doubles aim to simplify design with composites as with metals. Laminate optimization performed varying plies orientations and number. Double‐double design of components optimized with respect to the acting loads. In aviation double‐doubles allow lightening of composite laminate components.

Polarization differential interference contrast microscopy with physics-inspired plug-and-play denoiser for single-shot high-performance quantitative phase imaging.

We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.

Modification of the elastic field of an edge dislocation

ABSTRACT The classical description of the elastic field of an edge dislocation is modified by the addition of a line force to the Burgers vector. Also, partitioning of displacements is imposed, consistent with the topological theory of defects at interfaces, agreeing with symmetry requirements as are inherent in nonlinear or atomistic calculations. Much of the classical theory is unchanged. However, displacement fields and image effects differ.

Homogenization assumptions for the two-scale analysis of first-order shear deformable shells

This contribution presents a multiscale approach for the analysis of shell structures using Reissner–Mindlin kinematics. A distinctive feature is that the thickness of the representative volume element (RVE) corresponds to the shell thickness. The main focus of this paper is on the choice of correct boundary conditions for the RVE. Three different types of boundary conditions, which fulfil the Hill–Mandel condition, are presented to bridge the two scales. A common feature is the application of zero-traction boundary conditions at the top and bottom surfaces of the RVE. Furthermore, an internal constraint is used to reduce the dependency of the stiffness components on the RVE size. The introduced boundary conditions differ mainly in the application of shear strains and their symmetry requirements on the RVE. The characteristic features are compared by means of linear-elastic benchmark tests. It is shown that the stress resultants and tangent stiffness components are obtained correctly. Moreover, the presented approach is verified using different macroscopic shell structures and different mesostructures. Both, linear and nonlinear small strain examples are compared to analytical values or full-scale solutions and demonstrate a wide applicability of the present formulation.

Stabilization of the Solution to the Initial-Boundary Value Problem for One-Dimensional Isothermal Equations of Viscous Compressible Multicomponent Media

The paper considers the initial-boundary value problem for one-dimensional isothermal equations of viscous compressible multicomponent media, commonly known as a generalization of the Navier — Stokes equations. The studied equations include higher derivatives of the velocities of all components, unlike the Navier — Stokes equations, where viscosity is a scalar variable. Viscosity forms a matrix of elements responsible for viscous friction due to the composite structure of viscous stress tensors for the multicomponent case. Diagonal elements of the matrix stand for viscous friction within each component, and off-diagonal elements stand for friction between components. Such complication does not allow the automatic extension of the known results for the Navier — Stokes equations to the multicomponent case. Thus, for the diagonal matrix, the equations would be linked only through the lower terms. The paper considers a more complex case of an off-diagonal viscosity matrix. We prove the stabilization of the solution of the initial-boundary value problem with an unlimited increase in time without simplifying assumptions about the structure of the viscosity matrix, except for the standard physical requirements of symmetry and positive definiteness.

Numerical simulation of turbidity currents using consistent particle method

This paper expands the Consistent Particle Method (CPM) to simulation of turbidity currents with focus on turbulent water-sediment flow. A mixture model is adopted in solving the sediment transport equation to simulate the sediment mass transfer due to settling convection and turbulent diffusion. To compute the gravity-driven convection term, the proposed CPM-upwind scheme is relatively easy to implement as it avoids the use of a kernel function which has the requirements of symmetry and unity. Two sand settling problems demonstrate the good accuracy of the CPM-upwind scheme. For suspended sediment diffusion caused by turbulence, CPM is able to model anisotropic diffusion without the averaging effect caused by the isotropy requirement if a kernel function is used. The validated CPM methodology is then applied to simulate a sudden flow of water-sediment mixture into ambient water. The results of the mixture front motion and sediment deposit density agree well with published experimental results.

GNN-Based Hierarchical Annotation for Analog Circuits

Analog designs consist of multiple hierarchical functional blocks. Each block can be built using one of several design topologies, where the choice of topology is based on circuit performance requirements. A major challenge in automating analog design is in the identification of these functional blocks, which enables the creation of hierarchical netlist representations. This can facilitate a variety of design automation tasks such as circuit layout optimization because the layout is dictated by constraints at each level, such as symmetry requirements, that depend on the topology of the hierarchical block. Traditional graph-based methods find it hard to automatically identify the large number of structural variants of each block. To overcome this limitation, this paper leverages recent advances in graph neural networks (GNNs). A variety of GNN strategies is used to identify netlist elements for circuit functional blocks at higher levels of the design hierarchy, where numerous design variants are possible. At lower levels of hierarchy, where the degrees of freedom in circuit topology are limited, structures are identified using graph-based algorithms. The proposed hierarchical recognition scheme enables the identification of layout constraints such as symmetry and matching, which enable high-quality hierarchical layouts. This method is scalable across a wide range of analog designs. An experimental evaluation shows a high degree of accuracy over a wide range of analog designs, identifying functional blocks such as low-noise amplifiers, operational transconductance amplifiers, mixers, oscillators, and band-pass filters in larger circuits.