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We show that the dimension of the geometric shape formed by the phenomenologically valid points inside a multi-dimensional parameter space can be used to characterise different new physics models and to define a quantitative measure for the…

High Energy Physics - Phenomenology · Physics 2015-05-20 Thorsten Feldmann , Christoph Promberger , Stefan Recksiegel

Owing to the advances in computational techniques and the increase in computational power, atomistic simulations of materials can simulate large systems with higher accuracy. Complex phenomena can be observed in such state-of-the-art…

Materials Science · Physics 2022-02-16 Ryo Tamura , Momo Matsuda , Jianbo Lin , Yasunori Futamura , Tetsuya Sakurai , Tsuyoshi Miyazaki

Urban morphology, examining city spatial configurations, links urban design to sustainability. Morphology metrics play a fundamental role in performance-driven computational urban design (CUD) which integrates urban form generation,…

Computational Engineering, Finance, and Science · Computer Science 2025-06-16 Chenyi Cai , Biao Li , Qiyan Zhang , Xiao Wang , Filip Biljecki , Pieter Herthogs

Multiscale topology optimization is crucial for designing porous infill structures with high stiffness-to-weight ratios and excellent energy absorption. Although gradient-based methods provide a rigorous framework, they are computationally…

Optimization and Control · Mathematics 2025-10-13 Shuzhi Xu , Yifan Guo , Hiroki Kawabe , Kentaro Yaji

We study changes in metrics that are defined on a cartesian product of trees. Such metrics occur naturally in many practical applications, where a global metric (such as revenue) can be broken down along several hierarchical dimensions…

Databases · Computer Science 2017-03-24 Matthias Ruhl , Mukund Sundararajan , Qiqi Yan

Optimal transport (OT) is a central framework for modeling distribution shifts. Because OT compares distributions directly in input space, a well-designed ground metric between observations is essential to ensure that the optimizer does not…

Machine Learning · Computer Science 2026-05-07 Philip Naumann , Jacob Kauffmann , Klaus-Robert Müller , Grégoire Montavon

We develop a geometric foundation of microcanonical thermodynamics in which entropy and its derivatives are determined from the geometry of phase space, rather than being introduced through an a priori ensemble postulate. Once the minimal…

Statistical Mechanics · Physics 2025-12-30 Loris Di Cairano

Transformations accompanying shape-instability govern the morphological configuration and distribution of the phases in a microstructure. Owing to the influence of the microstructure on the properties of a material, the stability of…

Computational Engineering, Finance, and Science · Computer Science 2020-06-17 Tobias Mittnacht , Prince Gideon Kubendran Amos , Daniel Schneider , Britta Nestler

In the realm of computer vision and graphics, accurately establishing correspondences between geometric 3D shapes is pivotal for applications like object tracking, registration, texture transfer, and statistical shape analysis. Moving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Tung Le , Khai Nguyen , Shanlin Sun , Nhat Ho , Xiaohui Xie

Plasticity of metals is the emergent phenomenon of many crystal defects (dislocations) which interact and move on microscopic time and length scales. Two of the commonly used models to describe such dislocation dynamics are the…

Analysis of PDEs · Mathematics 2022-10-07 Patrick van Meurs , Stefania Patrizi

Modern information processing relies on the axiom that high-dimensional data lie near low-dimensional geometric structures. This paper revisits the problem of data-driven learning of these geometric structures and puts forth two new…

Machine Learning · Statistics 2018-03-06 Tong Wu , Waheed U. Bajwa

A micromorphic computational homogenization framework has recently been developed to deal with materials showing long-range correlated interactions, i.e. displaying patterning modes. Typical examples of such materials are elastomeric…

Soft Condensed Matter · Physics 2024-06-21 S. Maraghechi , O. Rokoš , R. H. J. Peerlings , M. G. D. Geers , J. P. M. Hoefnagels

We describe new approaches for distances between pairs of 2-dimensional surfaces (embedded in 3-dimensional space) that use local structures and global information contained in inter-structure geometric relationships. We present algorithms…

Numerical Analysis · Mathematics 2015-05-30 D. Boyer , Y. Lipman , E. St. Clair , J. Puente , T. Funkhouser , B. Patel , J. Jernvall , I. Daubechies

A multi-timescale hybrid model is proposed to study microscopically the degraded performance of electronic devices, covering three individual stages of radiation effects studies, including ultrafast displacement cascade, intermediate defect…

Materials Science · Physics 2014-09-16 Danhong Huang , Fei Gao , D. A. Cardimona

Traditional machine learning (ML) algorithms, such as multiple regression, require human analysts to make decisions on how to treat the data. These decisions can make the model building process subjective and difficult to replicate for…

Machine Learning · Computer Science 2022-01-31 William Franz Lamberti

Owing to additive manufacturing techniques, a structure at millimeter length scale (macroscale) can be produced by using a lattice substructure at micrometer length scale (microscale). Such a system is called a metamaterial at the…

Computational Engineering, Finance, and Science · Computer Science 2019-11-25 H. Yang , B. E. Abali , W. H. Müller , D. Timofeev

We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity on all scales simultaneously. We…

Statistics Theory · Mathematics 2015-03-19 Johannes Schmidt-Hieber , Axel Munk , Lutz Duembgen

Honeycomb-like microstructures have been shown to exhibit local elastic buckling under compression, with three possible geometric buckling modes, or pattern transformations. The individual pattern transformations, and consequently also…

Soft Condensed Matter · Physics 2020-04-14 O. Rokoš , M. M. Ameen , R. H. J. Peerlings , M. G. D. Geers

We numerically investigate the influence of self-attraction on the critical behaviour of a polymer in two dimensions, by means of an analysis of finite-size results of transfer-matrix calculations. The transfer matrix is constructed on the…

Statistical Mechanics · Physics 2015-06-25 H. W. J. Blöte , M. T. Batchelor , B. Nienhuis

The literature on panel cointegration is extensive but does not cover data sets where the cross section dimension, $n$, is larger than the time series dimension $T$. This paper proposes a novel methodology that filters out the short run…

Econometrics · Economics 2025-09-15 Alexander Chudik , M. Hashem Pesaran , Ron P. Smith