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The Smectic-A (SmA) phase is modeled by a modified Landau-de Gennes (mLdG) model proposed by Xia et al. [Phys. Rev. Lett., 126 (2021), 177801], in which a tensor order parameter $\mathbf{Q}$ for the orientational order is coupled with a…

Numerical Analysis · Mathematics 2026-04-21 Wenshuai Hu , Guanghua Ji , Xiao Li

This paper presents a gradient-based reconstruction approach for simulations of compressible single and multi-species Navier-Stokes equations. The novel feature of the proposed algorithm is the efficient reconstruction via derivative…

Fluid Dynamics · Physics 2022-11-29 Amareshwara Sainadh Chamarthi

We consider the statistical inverse problem of estimating a background flow field (e.g., of air or water) from the partial and noisy observation of a passive scalar (e.g., the concentration of a solute), a common experimental approach to…

Numerical Analysis · Mathematics 2019-06-12 Jeff Borggaard , Nathan E. Glatt-Holtz , Justin A. Krometis

In longitudinal observational studies with time-to-event outcomes, a common objective in causal analysis is to estimate the causal survival curve under hypothetical intervention scenarios. The g-formula is a useful tool for this analysis.…

Methodology · Statistics 2025-04-14 Xinyuan Chen , Liangyuan Hu , Fan Li

We study sum of squares (SOS) relaxations to optimize polynomial functions over a set $V\cap R^n$, where $V$ is a complex algebraic variety. We propose a new methodology that, rather than relying on some algebraic description, represents…

Optimization and Control · Mathematics 2017-11-21 Diego Cifuentes , Pablo A. Parrilo

In this work, we detail the GPU-porting of an in-house pseudo-spectral solver tailored towards large-scale simulations of interface-resolved simulation of drop- and bubble-laden turbulent flows. The code relies on direct numerical…

Fluid Dynamics · Physics 2024-06-04 Alessio Roccon

Global sensitivity analysis of complex numerical simulators is often limited by the small number of model evaluations that can be afforded. In such settings, surrogate models built from a limited set of simulations can substantially reduce…

Machine Learning · Statistics 2026-01-21 Guerlain Lambert , Céline Helbert , Claire Lauvernet

Generalized additive index models (GAIMs) offer a flexible semiparametric framework for capturing complex data relationships, balancing the interpretability of parametric models with the flexibility of nonparametric approaches. However,…

Methodology · Statistics 2026-05-29 Ziyu Peng , Linglingzhi Zhu , Yao Xie

Designing effective optimisation strategies for unsteady flows in the presence of complex dynamics is challenging. Gradient-based optimisation algorithms that rely on gradient information obtained from adjoint equations are efficient for…

The focus of this work is on spatial variable selection for scalar-on-image regression. We propose a new class of Bayesian nonparametric models, soft-thresholded Gaussian processes and develop the efficient posterior computation algorithms.…

Methodology · Statistics 2016-04-13 Jian Kang , Brian J. Reich , Ana-Maria Staicu

The generalized singular value decomposition (GSVD, a.k.a. "SVD triplet", "duality diagram" approach) provides a unified strategy and basis to perform nearly all of the most common multivariate analyses (e.g., principal components,…

Mathematical Software · Computer Science 2020-11-19 Derek Beaton

Grad-div stabilization, adding a term -gamma grad div u, has proven to be a useful tool in the simulation of incompressible flows. Such a term requires a choice of the coefficient gamma and studies have begun appearing with various…

Numerical Analysis · Mathematics 2017-04-14 V. Decaria , W. Layton , A. Pakzad , Y. Rong , N. Sahin , H. Zhao

Sharpness-aware Minimization (SAM) has been proposed recently to improve model generalization ability. However, SAM calculates the gradient twice in each optimization step, thereby doubling the computation costs compared to stochastic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Jiaxin Deng , Junbiao Pang , Baochang Zhang , Tian Wang

The Gaussian process latent variable model (GP-LVM) is a popular approach to non-linear probabilistic dimensionality reduction. One design choice for the model is the number of latent variables. We present a spike and slab prior for the…

Machine Learning · Statistics 2015-05-12 Zhenwen Dai , James Hensman , Neil Lawrence

In this paper, we present a novel strategy to systematically construct linearly implicit energy-preserving schemes with arbitrary order of accuracy for Hamiltonian PDEs. Such novel strategy is based on the newly developed exponential scalar…

Numerical Analysis · Mathematics 2023-07-27 Yonghui Bo , Yushun Wang , Wenjun Cai

The Swift-Hohenberg equation as a central nonlinear model in modern physics has a gradient flow structure. Here we introduce fully discrete discontinuous Galerkin (DG) schemes for a class of fourth order gradient flow problems, including…

Numerical Analysis · Mathematics 2019-10-02 Hailiang Liu , Peimeng Yin

The decay of a passive scalar in a three-dimensional chaotic flow is studied using high-resolution numerical simulations. The (volume-preserving) flow considered is a three-dimensional extension of the randomised alternating sine flow…

Chaotic Dynamics · Physics 2015-03-18 Keith Ngan , Jacques Vanneste

The generalized surface quasi-geostrophic (GSQG) equations are transport equations for an active scalar that depend on a parameter $0<\alpha \le 2$. Special cases are the two-dimensional incompressible Euler equations ($\alpha = 2$) and the…

Analysis of PDEs · Mathematics 2020-06-29 John K. Hunter , Jingyang Shu , Qingtian Zhang

In this paper, we present a numerical scheme designed for coupled systems of variable-topography shallow water flow and solute transport. By integrating a variable-density system with an expression for relative density of mixtures, a novel…

Numerical Analysis · Mathematics 2026-03-17 Jun She , Haiyun Dong , Maojun Li , Jianjun Ma

Shape optimization based on surface gradients and the Hadarmard-form is considered for a compressible viscous fluid. Special attention is given to the difference between the 'function composition' approach involving local shape derivatives…

Optimization and Control · Mathematics 2013-12-23 Matthias Sonntag , Stephan Schmidt , Nicolas R. Gauger