Article
Astronomy & Astrophysics
B. Afshar, H. Moradpour, H. Shabani
Summary: This paper investigates the primary inflationary and reheating eras within the Rastall theory, considering the theory of slow-roll inflation and using a Lagrangian that may include poles. The study focuses on the exponential potential and finds that the results are consistent with observational data, supporting the viability of the model. Additionally, the model accurately describes the reheating phase and shows reasonable data fitting advantages compared to General Relativity in certain cases.
PHYSICS OF THE DARK UNIVERSE
(2023)
Article
Physics, Multidisciplinary
A. A. Abrashkin, E. N. Pelinovsky
Summary: This paper proposes a method to study stationary periodic weakly vortical waves on water and provides a complete problem solution in a cubic approximation. Explicit expressions for liquid particle trajectories and pressure are obtained, along with determining the quadratic correction to the wave velocity.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Astronomy & Astrophysics
Raimon Luna, Miguel Zilhao, Vitor Cardoso, Joao L. Costa, Jose Natario
Summary: The analysis of extending strong cosmic censorship to perturbations of highly charged Reissner-Nordstrom de Sitter spacetimes reveals the linear stability of the Cauchy horizon can be determined from the spectral gap of quasinormal modes, but becomes more complex with nonlinear backreaction. Confusion in literature arises from the subtleties involved in deriving conclusions about SCC violations from available numerical simulations, especially concerning near extremal RNdS black hole spacetimes where existing codes may be insufficient.
Article
Computer Science, Interdisciplinary Applications
Xiaofeng Cai, Jing-Mei Qiu, Yang Yang
Summary: The paper introduces a new method called ELDG, which incorporates a modified adjoint problem and integration of PDE over a space-time region partitioned by time-dependent linear functions. By introducing a new flux term to account for errors in characteristics approximation, the ELDG method combines the advantages of SL DG and classical Eulerian RK DG methods. The use of linear functions for characteristics approximation in the EL DG framework simplifies shapes of upstream cells and reduces time step constraints.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Mathematics, Applied
F. Revuelta, F. J. Arranz, R. M. Benito, F. Borondo
Summary: Using Lagrangian descriptors, we identify the phase-space structures responsible for the chaotic dynamics observed in the KCN molecular system. The vibrational dynamics of this molecule are strongly influenced by the invariant manifolds associated with a specific stretching periodic orbit. Additionally, we analyze the representation of these invariant manifolds on a Poincaré surface of section and find that its intricate depiction is a result of the complex behavior of the manifolds caused by strong anharmonicities in the potential energy surface.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Mathematics, Applied
Thomas J. Bridges, Daniel J. Ratliff
Summary: The paper develops a nonlinear theory for the coalescence of two characteristics, transitioning from hyperbolic to elliptic through collision. By establishing the structure of colliding characteristics and a nonlinear modulation theory, the paper reveals how coalescing characteristics transform the Whitham equations and demonstrates the application to coupled nonlinear Schrodinger equations.
JOURNAL OF NONLINEAR SCIENCE
(2021)
Article
Environmental Sciences
Hung-Chu Hsu, Meng-Syue Li
Summary: This paper investigates the particle dynamics of nonlinear flexural-gravity waves propagating in a finite water depth, which involves the interaction between ice sheets and water flows. The theoretical analysis and numerical simulations discuss the influences of flexural rigidity on the particle orbits and mass transport velocity.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Mathematics, Interdisciplinary Applications
M. Velasco-Juan, J. Fujioka
Summary: This paper investigates two new nonlocal NLS equations, demonstrating that these models possess Lagrangian structures, with solitary wave solutions trapped near the origin and others able to escape. The collisions of breathers obeying LN2 equation are studied numerically, showing these breathers are robust solutions.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Engineering, Multidisciplinary
Xiaohui Pei, Jingli Du, Guimin Chen
Summary: In this work, an approximate Jacobian matrix is proposed based on the total Lagrangian formulation of Finite Element Method for isotropic hyperelastic materials. The approximate Jacobian matrix can replace the exact Jacobian matrix in the Newton-Raphson method, which can avoid the frequent construction and factorization of the Jacobian matrix. Moreover, a new Quasi-Newton method utilizing the approximate Jacobian matrix is developed to significantly improve the convergence rate. The experimental results demonstrate that the proposed method is more efficient than ABAQUS and CALCULIX, without sacrificing accuracy. It is 100 times faster than the traditional Quasi-Newton method and at least 2.5 times faster than ABAQUS.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Mechanics
Ruihua Li, Ruihua Ding, Artin Hozuri
Summary: This paper presents a new approach to evaluate the instability of beams on a softening elastic foundation by solving a nonlinear frequency problem. The study focuses on multiscale composite materials based on carbon nanotubes and long fibers. The homogenization methods are applied to obtain the effective material properties of these composites. The effects of the thermal environment on the beam's response are also examined.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Economics
Anna Almosova, Niek Andresen
Summary: Motivated by recent literature, this study investigates if the forecasting performance of economic time-series, particularly inflation, can be improved further by using a specific type of neural network - a recurrent neural network. The study utilizes a long short-term memory recurrent neural network (LSTM), known for its efficiency in handling sequential data, to forecast the monthly US CPI inflation. The results indicate that while LSTM slightly outperforms autoregressive models, neural network models, and Markov-switching models, its performance is on par with the seasonal autoregressive model SARIMA.
JOURNAL OF FORECASTING
(2023)
Article
Business, Finance
Bogdan Andrei Dumitrescu, Meral Kagitci, Cosmin-Octavian Cepoi
Summary: This paper examines the nonlinear effects of public debt on inflation. The findings suggest the existence of threshold effects between inflation and public debt. Emerging countries with a relatively small shadow economy can accommodate increases in public debt without additional welfare costs, while those with a shadow economy exceeding 24.3% of GDP face greater macroeconomic costs in terms of inflation.
FINANCE RESEARCH LETTERS
(2022)
Article
Computer Science, Software Engineering
Chen Zhao, Naihua Xiu, Houduo Qi, Ziyan Luo
Summary: This paper proposes a fast Newton-type algorithm for solving the sparse nonlinear programming problem. By establishing a first-order optimality condition and introducing Lagrangian equations, the Lagrange-Newton algorithm is proposed, with proven convergence and iterative complexity, and demonstrated efficiency in compressed sensing and high-order portfolio selection problems.
MATHEMATICAL PROGRAMMING
(2022)
Article
Management
M. R. Torrealba, J. G. Silva, L. C. Matioli, O. Kolossoski, P. S. M. Santos
Summary: This study proposes a class of algorithms for solving the continuous nonlinear resource allocation problem and discusses its convergence properties and numerical applications. Compared to previous research, this method is more general and applicable to a wider range of problem domains.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Software Engineering
Sen Na, Mihai Anitescu, Mladen Kolar
Summary: We propose an active-set stochastic sequential quadratic programming (StoSQP) algorithm for solving nonlinear optimization problems with a stochastic objective and deterministic constraints. The algorithm uses a differentiable exact augmented Lagrangian as the merit function and adaptively selects penalty parameters. It has been shown to have global convergence and outperforms previous work in terms of nonlinear inequality constraints and sample complexity.
MATHEMATICAL PROGRAMMING
(2023)
Article
Astronomy & Astrophysics
Cornelia Arcaro, Michele Doro, Julian Sitarek, Dominik Baack
Summary: In this report, the performance of replacing PMTs with SiPMs in a 3rd generation IACT array (using MAGIC as an example) is investigated using generalized simulations. It is found that the use of SiPMs can improve sensitivity by a factor of three at the current trigger threshold energy, and the stronger sensitivity of SiPMs in the red part of the spectrum does not affect the performance of IACTs, which is a source of background.
ASTROPARTICLE PHYSICS
(2024)
Article
Astronomy & Astrophysics
L. R. Colaco, R. F. L. Holanda, Rafael C. Nunes, J. E. Gonzalez
Summary: Motivated by future gravitational wave observations, this study performs forecast analysis to constrain a possible time variation of the fine structure constant a. By considering mock data from standard sirens and current observations of strong gravitational lensing systems, it is found that future standard sirens observations can also play a significant role in the search for variations of a.
ASTROPARTICLE PHYSICS
(2024)
Article
Astronomy & Astrophysics
Igor Andreoni, Michael W. Coughlin, Alexander W. Criswell, Mattia Bulla, Andrew Toivonen, Leo P. Singer, Antonella Palmese, E. Burns, Suvi Gezari, Mansi M. Kasliwal, R. Weizmann Kiendrebeogo, Ashish Mahabal, Takashi J. Moriya, Armin Rest, Dan Scolnic, Robert A. Simcoe, Jamie Soon, Robert Stein, Tony Travouillon
Summary: Binary neutron star mergers and neutron star-black hole mergers can be detected through gravitational waves and electromagnetic radiation. Discovering kilonovae will provide valuable insights into element nucleosynthesis and nuclear matter. The unique features of the Nancy Grace Roman Space Telescope allow for the detection of gravitational wave counterparts missed by optical telescopes.
ASTROPARTICLE PHYSICS
(2024)
Review
Astronomy & Astrophysics
Federico Cattorini, Bruno Giacomazzo
Summary: This article presents recent numerical advances in the theoretical characterization of massive binary black hole (MBBH) mergers in astrophysical environments. These systems are significant sources of gravitational waves (GWs) and promising candidates for multimessenger astronomy. Coincident detection of GWs and electromagnetic (EM) signals from merging MBBHs is a leading area of study in contemporary astrophysics. The scarcity of strong predictions for EM signals before, during, and after merger poses a major challenge in observational efforts. To address this, significant theoretical work has focused on characterizing EM counterparts that accompany GW signals. Full general relativistic modeling using Einstein's field equations coupled with magnetohydrodynamics equations has been key in producing accurate EM predictions. This review explores numerical investigations into the astrophysical manifestations of MBBH mergers and their potentially observable EM signatures.
ASTROPARTICLE PHYSICS
(2024)
Article
Astronomy & Astrophysics
Michael Maziashvili, Vakhtang Tsintsabadze
Summary: Coupled models of quintessence are introduced to avoid or mitigate the parameter fine-tuning problem and also should avoid the fine-tuning problem related to the initial conditions. Coupled models can explain the timescale of the coincidence between dark energy and matter energy densities, as well as the transition of dark energy dominance. Studying the mass varying neutrino model of dark energy with inverse power-law potential helps to understand its naturalness.
ASTROPARTICLE PHYSICS
(2024)
