Arbitrary Set Of Parameters Research Articles

Running beyond ALPs: shift-breaking and CP-violating effects

We compute the renormalization group equations (RGEs) of the Standard Model effective field theory (EFT) extended with a real scalar singlet, up to dimension-five and one-loop accuracy. We compare our renormalization results with those found in the shift-symmetry preserving limit, which characterizes axion-like particles (ALPs). The matching and running equations below the electroweak scale are also obtained, including the mixing effects in the scalar sector. Such mixing leads to interesting phenomenological consequences that are absent in the EFT at the renormalizable level, namely new correlations among the triplet and quartic Higgs couplings are predicted. All RGEs obtained in this work are implemented in a new Mathematica package — ALPRunner, together with functions to solve the running numerically for an arbitrary set of UV parameters. As an application, we obtain electric dipole moment constraints on particular regions of the singlet parameter space, and quantify the level of shift-breaking in these regions.

Towards the use of Unsupervised Causal Learning in Wireless Networks Operation

The current paradigm in Mobile Wireless Networks (MWNs) operation is being defied by the increasing importance of Machine Learning (ML) and Artificial Intelligence (AI). Nevertheless, another paradigm shift is rising with recent developments in causal inference and causal discovery, which, although having the potential to be applied to MWNs, have been relatively unexplored. This paper aims to develop a data-driven methodology using unsupervised ML and Conditional Independence Tests (CITs), typically used in causal discovery tasks, to identify distinct network performance patterns and pinpoint causal factors to explain them. The proposed methodology was first evaluated with crowdsourcing data from User Equipments (UEs). Afterwards, a dataset from a Long-Term Evolution (LTE) network, composed of a set of arbitrary performance indicators and configuration parameters, was considered. The crowdsourcing dataset, containing multiple network speed tests, revealed that the measured uplink throughput contributed the most to the observed performance patterns due to the used Radio Access Technologies (RATs). Furthermore, the LTE dataset revealed a causal relationship between the number of reserved signalling resources in the Physical Uplink Control Channel (PUCCH) and the UE uplink throughput. Notwithstanding, the key contribution of this paper is the consideration of causal-based concepts and methods for network operations enhancement.

Task graph-based performance analysis of parallel-in-time methods

In this paper, we present a performance model based on task graphs for various iterative parallel-in-time (PinT) methods. PinT methods have been developed to speed up the simulation time of time-dependent problems using modern parallel supercomputers. The performance model is based on a data-driven notation of the methods, from which a task graph is generated. Based on this task graph and a distribution of time points across processes typical for PinT methods, a theoretical lower runtime bound for the method can be obtained, as well as a prediction of the runtime for a given number of processes. In particular, the model is able to cover the large parameter space of PinT methods and make predictions for arbitrary parameter settings. Here, we describe a general procedure for generating task graphs based on three iterative PinT methods, namely, Parareal, multigrid-reduction-in-time (MGRIT), and the parallel full approximation scheme in space and time (PFASST). Furthermore, we discuss how these task graphs can be used to analyze the performance of the methods. In addition, we compare the predictions of the model with parallel simulation times using five different PinT libraries.

Quantization noise analysis in FBMC receivers and its effect on the BER performance

This paper analyzes the fixed-point and floating-point roundoff errors in different Filter Bank MultiCarrier (FBMC) receiver implementations. Two different structures are considered: the polyphase network based and frequency spreading based. Theoretical closed-form formulas for the total Quantization Noise Power (QNP) are derived and verified through simulation. The results show the effects of each parameter and signal processing block on the overall QNP. Also, the results show that the total QNP for an arbitrary set of parameters can be determined using the derived results without performing exhaustive simulations. The effects of the chosen bit-resolution on the bit-error rate performance are also analyzed. Furthermore – based on the theoretical results – FBMC receivers can be designed with an optimal number of bits used in the arithmetic units without significantly affecting the receiver performance.

Quantum Limits of Transmission Electron Microscopy.

New-generation transmission electron microscopes (TEMs) are equipped with detectors that approach the shot-noise limit. Hence it is pertinent to ask: What are the quantum limits of electron scattering experiments in the TEM? For example, for a given electron dose, what is the ultimate accuracy allowed by quantum mechanics for the atomic structure of a material? We provide quantitative answers based on quantum estimation theory. We also show that, for an arbitrary set of sample parameters, the quantum limit is achievable under conditions of weak scattering, but not strong multiple scattering (this conclusion extends to scattering of other types of radiation). Implications for structure determination of radiation-sensitive materials are discussed.

Multidisciplinary Optimization and Analysis of Stratospheric Airships Powered by Solar Arrays

Stratospheric airships have much potential in military and commercial applications. Design, analysis and optimization of stratospheric airships involves complex trade-off of different disciplines, and hence a multidisciplinary approach is essential. This paper describes a methodology coupling several disciplines and involving seven design variables to obtain the optimal design of a stratospheric airship powered by solar arrays. A numerical method is established to calculate the output power of the solar array in the optimization process. The optimal solutions are obtained using hybrid algorithms. The methodology can obtain the optimal envelope shape, solar array layout and other general configurations of subsystems. Results show that the methodology was able to achieve a solution with a 19.2% reduction in airship volume compared to the value being part of an arbitrary initial set of airship parameters. In addition, a comparative study is carried out to highlight the importance of considerations of solar array layouts and array circumferential location. Furthermore, detailed sensitivity analysis shows that operating parameters of latitudes, heading angles and average resisting wind speeds have significant effects on the airship design and solar array layouts.

On extension of the Yang-Baxter equation and the fermionic R-operator

We consider the fermionic R-operator based on Bazhanov-Stroganov's three-parameter elliptic parametrization of the free fermion model, and find the most general solution of the related tetrahedral Zamolodchikov algebra in the trigonometric limit for an arbitrary set of parameters. This allows to construct an extension of the R-operator and the corresponding Yang-Baxter equation, which are of the difference type in one of the spectral parameters.

A Stochastic SEIRS Epidemic Model with Infection Forces and Intervention Strategies.

The spread of epidemics has been extensively investigated using susceptible-exposed infectious-recovered-susceptible (SEIRS) models. In this work, we propose a SEIRS pandemic model with infection forces and intervention strategies. The proposed model is characterized by a stochastic differential equation (SDE) framework with arbitrary parameter settings. Based on a Markov semigroup hypothesis, we demonstrate the effect of the proliferation number R0S on the SDE solution. On the one hand, when R0S < 1, the SDE has an illness-free solution set under gentle additional conditions. This implies that the epidemic can be eliminated with a likelihood of 1. On the other hand, when R0S > 1, the SDE has an endemic stationary circulation under mild additional conditions. This prompts the stochastic regeneration of the epidemic. Also, we show that arbitrary fluctuations can reduce the infection outbreak. Hence, valuable procedures can be created to manage and control epidemics.

Oscillations of a quasi-one-dimensional dipolar supersolid

The properties of a supersolid state (SS) in quasi-one-dimensional dipolar Bose–Einstein condensate is studied, considering two possible mechanisms of realization—due to repulsive three-body atomic interactions and quantum fluctuations in the framework of the Lee–Huang–Yang theory. The role of both mechanisms in the formation of SS properties has been emphasized. The proposed theoretical model, based on minimization of the energy functional, allows evaluating the amplitude of the SS for an arbitrary set of parameters in the extended Gross–Pitaevskii equation (eGPE). To explore the dynamics of the SS first we numerically construct its ground state in different settings, including periodic boundary conditions, box-like trap and parabolic potential, then impose a perturbation. In oscillations of the perturbed supersolid we observe the key manifestation of SS, namely the free flow of the superfluid fraction through the crystalline component of the system. Two distinct oscillation frequencies of the supersolid associated with the superfluid fraction and crystalline components of the wave function are identified from numerical simulations of the eGPE.

The importance of uncertainty quantification in model reproducibility.

Many computer models possess high-dimensional input spaces and substantial computational time to produce a single model evaluation. Although such models are often ‘deterministic’, these models suffer from a wide range of uncertainties. We argue that uncertainty quantification is crucial for computer model validation and reproducibility. We present a statistical framework, termed history matching, for performing global parameter search by comparing model output to the observed data. We employ Gaussian process (GP) emulators to produce fast predictions about model behaviour at the arbitrary input parameter settings allowing output uncertainty distributions to be calculated. History matching identifies sets of input parameters that give rise to acceptable matches between observed data and model output given our representation of uncertainties. Modellers could proceed by simulating computer models’ outputs of interest at these identified parameter settings and producing a range of predictions. The variability in model results is crucial for inter-model comparison as well as model development. We illustrate the performance of emulation and history matching on a simple one-dimensional toy model and in application to a climate model.This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’.

Real classical geometry with arbitrary deficit parameter(s) alpha (_{I}) in deformed Jackiw\u2013Teitelboim gravity

An interesting deformation of Jackiw–Teitelboim (JT) gravity has been proposed by Witten by adding a potential term U(phi ) as a self-coupling of the scalar dilaton field. During calculating the path integral over fields, a constraint comes from integration over phi as R(x)+2=2alpha delta (vec {x}-vec {x}'). The resulting Euclidean metric suffered from a conical singularity at vec {x}=vec {x}'. A possible geometry is modeled locally in polar coordinates (r,varphi ) by mathrm{d}s^2=mathrm{d}r^2+r^2mathrm{d}varphi ^2,varphi cong varphi +2pi -alpha . In this letter we show that there exists another family of ”exact” geometries for arbitrary values of the alpha . A pair of exact solutions are found for the case of alpha =0. One represents the static patch of the AdS and the other one is the non-static patch of the AdS metric. These solutions were used to construct the Green function for the inhomogeneous model with alpha ne 0. We address a type of phase transition between different patches of the AdS in theory because of the discontinuity in the first derivative of the metric at x=x'. We extended the study to the exact space of metrics satisfying the constraint R(x)+2=2sum _{i=1}^{k}alpha _idelta ^{(2)}(x-x'_i) as a modulus diffeomorphisms for an arbitrary set of deficit parameters (alpha _1,alpha _2,ldots ,alpha _k). The space is the moduli space of Riemann surfaces of genus g with k conical singularities located at x'_k, denoted by mathcal {M}_{g,k}.

WITHDRAWN: Alexandroff soft topological spaces

In this paper, we characterized another kind of topological space known as Alexandroff Soft Topological space. It is characterized over a general set X alongside an arbitrary set of parameters. This space satisfies a more grounded condition that an arbitrary intersection of open sets are open. We have likewise contemplated different ideas like basis of a topology, sub base, subspace, closure of a space and so on. Further, different separation axioms known as Alexo Ti-spaces have been presented alongside their properties. This space is also the parametrized type of general topology.

Discovering Tonal Profiles with Latent Dirichlet Allocation

Music analysis, in particular harmonic analysis, is concerned with the way pitches are organized in pieces of music, and a range of empirical applications have been developed, for example, for chord recognition or key finding. Naturally, these approaches rely on some operationalization of the concepts they aim to investigate. In this study, we take a complementary approach and discover latent tonal structures in an unsupervised manner. We use the topic model Latent Dirichlet Allocation and apply it to a large historical corpus of musical pieces from the Western classical tradition. This method conceives topics as distributions of pitch classes without assuming a priori that they correspond to either chords, keys, or other harmonic phenomena. To illustrate the generative process assumed by the model, we create an artificial corpus with arbitrary parameter settings and compare the sampled pieces to real compositions. The results we obtain by applying the topic model to the musical corpus show that the inferred topics have music-theoretically meaningful interpretations. In particular, topics cover contiguous segments on the line of fifths and mostly correspond to diatonic sets. Moreover, tracing the prominence of topics over the course of music history over [Formula: see text]600 years reflects changes in the ways pitch classes are employed in musical compositions and reveals particularly strong changes at the transition from common-practice to extended tonality in the 19th century.

The Runtime of the Compact Genetic Algorithm on Jump Functions

In the first and so far only mathematical runtime analysis of an estimation-of-distribution algorithm (EDA) on a multimodal problem, Hasen\"ohrl and Sutton (GECCO 2018) showed for any $k = o(n)$ that the compact genetic algorithm (cGA) with any hypothetical population size $\mu = \Omega(ne^{4k} + n^{3.5+\varepsilon})$ with high probability finds the optimum of the $n$-dimensional jump function with jump size $k$ in time $O(\mu n^{1.5} \log n)$. We significantly improve this result for small jump sizes $k \le \frac 1 {20} \ln n -1$. In this case, already for $\mu = \Omega(\sqrt n \log n) \cap \text{poly}(n)$ the runtime of the cGA with high probability is only $O(\mu \sqrt n)$. For the smallest admissible values of $\mu$, our result gives a runtime of $O(n \log n)$, whereas the previous one only shows $O(n^{5+\varepsilon})$. Since it is known that the cGA with high probability needs at least $\Omega(\mu \sqrt n)$ iterations to optimize the unimodal OneMx function, our result shows that the cGA in contrast to most classic evolutionary algorithms here is able to cross moderate-sized valleys of low fitness at no extra cost. For large $k$, we show that the exponential (in $k$) runtime guarantee of Hasen\"ohrl and Sutton is tight and cannot be improved, also not by using a smaller hypothetical population size. We prove that any choice of the hypothetical population size leads to a runtime that, with high probability, is at least exponential in the jump size $k$. This result might be the first non-trivial exponential lower bound for EDAs that holds for arbitrary parameter settings.

Development of inline closed-loop vibration control in progressive die stamping using finite element simulation

Modern progressive dies are increasingly equipped with integrated sensors and actuators, thus enabling an improvement of the manufacturing process and an inline monitoring of the component quality. The design of the tooling is determined at an early stage and is largely based on the desired product and the specific production stages such as blanking, forming and punching. Nevertheless, malfunctions such as strip vibrations cannot always be foreseen and may occur during operation time, which may lead to reduced component quality and in the worst case to component collision or a damage of the tooling. Therefore, complex reworking or a reduction of the stroke rate and thus lower output quantity are often necessary for a reliable and stable process. Strip vibrations are often caused by the highly dynamic transportation of the strip in the tool and can have various causes. Among others, passive tooling components such as spring-loaded, hard stop limited strip lifter can be the cause of such vibrations. Strip lifter are always necessary when three-dimensional components are produced and have to be lifted out of the die for the feeding phase. The feeding phase takes place between two strokes of the stamping process. This work is aiming for a control strategy to suppress strip vibrations in various progressive die stamping processes based on closed-loop controlled active strip lifter. These strip lifter combine the spring-loaded passive standard strip lifter with an additional PID-controlled actuator. Taking the dynamics of the flexible strip during operation into account, a Finite Element Analysis (FEA) model of a progressive die tooling system is created. For the design of the control algorithm, the FEA model is connected to an environment for model-based design in a co-simulation. This approach allows modelling the influence of arbitrary control parameter settings on the movement curve of the strip, aiming for an increased stroke rate.

(In)stability of black holes in the 4D Einstein–Gauss–Bonnet and Einstein–Lovelock gravities

A (3+1)-dimensional Einstein-Gauss-Bonnet effective description of gravity has been recently formulated as the $D \to 4$ limit of the higher dimensional field equations after the rescaling of the coupling constant. This approach has been recently extended to the four-dimensional Einstein-Lovelock gravity. Although validity of the regularization procedure has not been shown for the general case, but only for a wide class of metrics, the black-hole solution obtained as a result of such a regularization is also an exact solution in the well defined 4D Einstein-Gauss-Bonnet theory suggested by Aoki, Gorji and Mukohyama [arXiv:2005.03859] and in the scalar-tensor effective classical theories. Here we study the eikonal gravitational instability of asymptotically flat, de Sitter and anti-de Sitter black holes in the four dimensional Einstein-Gauss-Bonnet and Einstein-Lovelock theories. We find parametric regions of the eikonal instability for various orders of the Lovelock gravity, values of coupling and cosmological constants, and share the code which allows one to construct the instability region for an arbitrary set of parameters. For the four-dimensional Gauss-Bonnet black holes we obtain the region of stability in analytic form. Unlike the higher dimensional Einstein-Lovelock case, the eikonal instability serves as an effective cut-off of higher curvature Lovelock terms for the 4D black holes.

Generation of density waves in dipolar quantum gases by time-periodic modulation of atomic interactions

We study the emergence of density waves in dipolar Bose-Einstein condensates (BEC) when the strength of dipole-dipole atomic interactions is periodically varied in time. The proposed theoretical model, based on the evolution of small perturbations of the background density, allows to compute the growth rate of instability (gain factor) for arbitrary set of input parameters, thus to identify the regions of instability against density waves. We find that among other modes of the system the roton mode is most effectively excited due to the contribution of sub-harmonics of the excitation frequency. The frequency of temporal oscillations of emerging density waves coincides with the half of the driving frequency, this being the hallmark of the parametric resonance, is characteristic to Faraday waves. The possibility to create density waves in dipolar BECs, which can persist after the emergence, has been demonstrated. The existence of a stationary spatially periodic solution of the nonlocal Gross-Pitaevskii equation has been discussed. The effect of three-body atomic interactions, which is relevant to condensates with increased density, upon the properties of emerging waves has been analyzed too. Significant modification of the condensate's excitation spectrum owing to three-body effects is shown.

Numerical analysis of mechanical properties and particle cracking probability of metal matrix composites

Particle-reinforced metal matrix composites (PRMMCs) are characterized by inhomogeneity and heterogeneity. The shape as well as volume fraction of the reinforcing particles and the mechanical properties of particles and matrix greatly affect the macro-mechanical properties of the metal matrix composites. Several analytical models were established to study the mesco-mechanical properties of the metal matrix composites based on the numerical simulation method combined with user-defined subroutine VUMAT in finite element codes ABAQUS in this article. Then the Weibull statistics model was adopted to study the effects of particle geometry shape and volume fraction on the probability of particle cracking under different applied strains. After that, an empirical formula for computing the probability of particle cracking was proposed which is a ternary function of the particle aspect ratio, the particle volume fraction and the applied strain based on the analysis of the computed data from different models. Finally, the validity and accuracy of the empirical formula in a certain range were verified through a model with an arbitrary set of particle parameters (particle aspect ratio AR and volume fraction Vf), which can provide a necessary guidance for the development and preparation of particle reinforced metal matrix composites.

Algorithmic differentiation of an industrial airfoil design tool coupled with the adjoint CFD method

Computer Aided Design (CAD) systems and tools are considered essential for industrial design. They construct and manipulate the geometry of a certain component with an arbitrary set of design parameters. However, it is a challenging task to incorporate the parametric definition in a gradient-based shape optimization loop, since the CAD libraries usually do not provide shape sensitivities w.r.t. the design parameters of the model to be optimized. Typically, these derivatives are evaluated with inaccurate finite differences. On the contrary, to obtain the exact derivative information, algorithmic differentiation (AD) can be applied if the CAD sources are available. In this study, the Rolls-Royce in-house airfoil design and blade generation tool Parablading is differentiated using the AD software tools ADOL-C and Tapenade. The differentiated CAD tool is coupled with a discrete adjoint CFD solver that is part of the Rolls-Royce in-house HYDRA suite of codes, also produced by algorithmic differentiation. This differentiated design chain is used to perform gradient-based shape optimization of the TU Berlin TurboLab stator test-case w.r.t. minimize the total pressure loss and exit angle deviation objectives.

Scalar dark matter in the conformally invariant extension of the standard model

We study a classically scale-invariant model with an electroweak singlet scalar mediator together with a scalar dark matter multiplet of global O(N) symmetry. Our most general conformally invariant scalar potential generates the electroweak symmetry breaking via the Coleman-Weinberg mechanism, and the new scalar singlet acquires its mass through radiative corrections of the SM particles and the scalar dark matter. Taking into account the collider bounds, we present the allowed region of new physics parameters satisfying the recent measurement of relic abundance. With the obtained parameter sets, we predict the elastic scattering cross section of the new scalar multiplet into target nuclei for a direct detection of the dark matter. We also perform a full analysis with arbitrary set of parameters for N≥2, and discuss the implication of the constraints from the on-going direct and indirect detections of dark matter.