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Structural Identifiability of Compartmental Models: Recent Progress and Future Directions
Nicolette Meshkat, Anne Shiu
https://arxiv.org/abs/2507.04496 htt…

Structural Identifiability of Compartmental Models: Recent Progress and Future Directions
We summarize recent progress on the theory and applications of structural identifiability of compartmental models. On the applications side, we review identifiability analyses undertaken recently for models arising in epidemiology, oncology, and other areas; and we summarize common approaches for handling models that are unidentifiable. We also highlight recent theoretical and algorithmic results on how to reparametrize unidentifiable models and, in the context of linear compartmental models, h…

LaDEEP: A Deep Learning-based Surrogate Model for Large Deformation of Elastic-Plastic Solids
Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu
https://arxiv.org/abs/2506.06001

LaDEEP: A Deep Learning-based Surrogate Model for Large Deformation of Elastic-Plastic Solids
Scientific computing for large deformation of elastic-plastic solids is critical for numerous real-world applications. Classical numerical solvers rely primarily on local discrete linear approximation and are constrained by an inherent trade-off between accuracy and efficiency. Recently, deep learning models have achieved impressive progress in solving the continuum mechanism. While previous models have explored various architectures and constructed coefficient-solution mappings, they are desig…

This https://arxiv.org/abs/2505.11292 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Status of the International Linear Collider
This paper is not a proposal for a CERN future project but provides information on the International Linear Collider (ILC) considered for Japan in order to facilitate the European Strategy discussion in a global context. It describes progress to date, ongoing engineering studies, updated cost estimate for the machine at $\sqrt{s}=250~\rm GeV$ and the situation in Japan. The physics of the ILC is not presented here, but jointly for all Linear Collider projects in a separate document ``A Linear C…

An Overview of GPU-based First-Order Methods for Linear Programming and Extensions
Haihao Lu, Jinwen Yang
https://arxiv.org/abs/2506.02174 https://

An Overview of GPU-based First-Order Methods for Linear Programming and Extensions
The rapid progress in GPU computing has revolutionized many fields, yet its potential in mathematical programming, such as linear programming (LP), has only recently begun to be realized. This survey aims to provide a comprehensive overview of recent advancements in GPU-based first-order methods for LP, with a particular focus on the design and development of cuPDLP. We begin by presenting the design principles and algorithmic foundation of the primal-dual hybrid gradient (PDHG) method, which f…

Sequential Neural Operator Transformer for High-Fidelity Surrogates of Time-Dependent Non-linear Partial Differential Equations
Qibang Liu, Seid Koric
https://arxiv.org/abs/2507.03272

Sequential Neural Operator Transformer for High-Fidelity Surrogates of Time-Dependent Non-linear Partial Differential Equations
Partial differential equations (PDEs) are fundamental to modeling complex and nonlinear physical phenomena, but their numerical solution often requires significant computational resources, particularly when a large number of forward full solution evaluations are necessary, such as in design, optimization, sensitivity analysis, and uncertainty quantification. Recent progress in operator learning has enabled surrogate models that efficiently predict full PDE solution fields; however, these models…

Ensemble nonlinear optical learner by electrically tunable linear scattering
Tunan Xia, Cheng-Kuan Wu, Duan-Yi Guo, Lidan Zhang, Bofeng Liu, Tsung-Hsien Lin, Xingjie Ni, Iam-Choon Khoo, Zhiwen Liu
https://arxiv.org/abs/2506.19976

Ensemble nonlinear optical learner by electrically tunable linear scattering
Recent progress in effective nonlinearity, achieved by exploiting multiple scatterings within the linear optical regime, has been demonstrated to be a promising approach to enable nonlinear optical processing without relying on actual material nonlinearity. Here we introduce an ensemble nonlinear optical learner, via electrically tunable linear scattering in a liquid-crystal-polymer composite film under low optical power and low applied electrical voltages. We demonstrate, through several image…

A law of large numbers for kinetic interacting diffusions
Carlo Bellingeri, Fabio Coppini
https://arxiv.org/abs/2506.01769 https://ar…

A law of large numbers for kinetic interacting diffusions
We study the convergence of the empirical distribution associated with a system of interacting kinetic particles subject to independent Brownian forcing in a finite horizon setting, using some recent progress on kinetic non-linear partial differential equations. Under general assumptions that require only weak convergence on the initial datum -without assuming independence or moment conditions- we prove convergence in probability to the corresponding non-linear Fokker-Planck PDE.

Isoperimetric inequalities in Hadamard spaces of asymptotic rank two
Urs Lang, Stephan Stadler, David Urech
https://arxiv.org/abs/2506.04882 https://

Isoperimetric inequalities in Hadamard spaces of asymptotic rank two
Gromov's isoperimetric gap conjecture for Hadamard spaces states that cycles in dimensions greater than or equal to the asymptotic rank admit linear isoperimetric filling inequalities, as opposed to the inequalities of Euclidean type in lower dimensions. In the case of asymptotic rank 2, recent progress was made by Druţu-Lang-Papasoglu-Stadler who established a homotopical inequality for Lipschitz 2-spheres with exponents arbitrarily close to 1. We prove a homological inequality of the same ty…

Global linear drift-wave eigenmode structures on flux surfaces in stellarators: ion temperature gradient mode
Hongxuan Zhu, H. Chen, Z. Lin, A. Bhattacharjee
https://arxiv.org/abs/2506.12948

Global linear drift-wave eigenmode structures on flux surfaces in stellarators: ion temperature gradient mode
Turbulent transport greatly impacts the performance of stellarator magnetic confinement devices. While significant progress has been made on the numerical front, theoretical understanding of turbulence in stellarators is still lacking. In particular, due to nonaxisymmetry, different field lines couple within flux surfaces, the effects from which have yet to be adequately studied. In this work, we numerically simulate the linear electrostatic ion-temperature-gradient modes in stellarators using …

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Estimation of superconducting cavity bandwidth and detuning using a Luenberger observer
Bozo Richter, Andrea Bellandi, Julien Branlard, Leon Speidel, Annika Eichler
https://arxiv.org/abs/2506.21207

Estimation of superconducting cavity bandwidth and detuning using a Luenberger observer
Enabled by progress in superconducting technology, several continuous wave linear accelerators are foreseen in the next decade. For these machines, it is of crucial importance to track the main cavity parameters, such as the resonator bandwidth and detuning. The bandwidth yields information on the superconducting state of the cavity. The detuning should be minimized to limit the required power to operate the cavity. The estimation of these parameters is commonly implemented in the digital elect…