Discrete Geometry Research Articles

Tensor based approach for tooth contact analysis of planar and spatial gearing contact

This paper presents a new method for analyzing gear tooth contact, leveraging tensor notation and discrete differential geometry. Existing analytical and numerical methods often face challenges in convergence and computational efficiency. Our proposed approach involves defining a novel tensor notation and applying it to the gear tooth contact kinematics problem. By discretizing the tooth surfaces and using tensor operations, we can accurately determine the kinematics, path of contact, and transmission error of the gear pair. To validate our approach, we compared its results with those obtained from commercial software, KISSsoft and KiMOS. The results demonstrated high accuracy, with mean absolute errors below 0.08 for specific sliding, 0.003 for sliding factor, and 0.1μm for transmission error. Furthermore, we applied our method to analyze non-involute gear types, such as S-gears, pin gearing and cosine gears. Our findings revealed the kinematic performance and contact characteristics of these gear types, providing valuable insights for gear design and optimization. In conclusion, the proposed tensor-based approach offers a promising alternative for gear tooth contact analysis, providing accurate and efficient results for a wide range of gear types.

Symplectic topology and ideal-valued measures

We adapt Gromov’s notion of ideal-valued measures to symplectic topology, and use it for proving new results on symplectic rigidity and symplectic intersections. Furthermore, it allows us to discuss three “big fiber theorems”—the Centerpoint Theorem in combinatorial geometry, the Maximal Fiber Inequality in topology, and the Non-displaceable Fiber Theorem in symplectic topology—from a unified viewpoint. Our main technical tool is an enhancement of the symplectic cohomology theory recently developed by Varolgüneş.

Deep learning as Ricci flow.

Deep neural networks (DNNs) are powerful tools for approximating the distribution of complex data. It is known that data passing through a trained DNN classifier undergoes a series of geometric and topological simplifications. While some progress has been made toward understanding these transformations in neural networks with smooth activation functions, an understanding in the more general setting of non-smooth activation functions, such as the rectified linear unit (ReLU), which tend to perform better, is required. Here we propose that the geometric transformations performed by DNNs during classification tasks have parallels to those expected under Hamilton's Ricci flow-a tool from differential geometry that evolves a manifold by smoothing its curvature, in order to identify its topology. To illustrate this idea, we present a computational framework to quantify the geometric changes that occur as data passes through successive layers of a DNN, and use this framework to motivate a notion of 'global Ricci network flow' that can be used to assess a DNN's ability to disentangle complex data geometries to solve classification problems. By training more than 1500 DNN classifiers of different widths and depths on synthetic and real-world data, we show that the strength of global Ricci network flow-like behaviour correlates with accuracy for well-trained DNNs, independently of depth, width and data set. Our findings motivate the use of tools from differential and discrete geometry to the problem of explainability in deep learning.

Energy, Exergy, environmental and economic based experimental investigation of solar air heater using a novel arc rib geometry

To enhance the thermal efficacy of solar air heaters, the most efficient method is to disturb the viscous layer by roughening the surface using the artificial rib. In this research, a discrete apex-down arc-shape rib geometry on a roughened plate is used to examine the energy-exergo and economic- environmental based performance of solar air heater. By changing the Reynolds number from 3000 to 14,000 and maintaining a gap width to rib height ratio of 4, a relative height rib ratio of 0.045, and a pitch to rib height ratio of 10, the effects of arc rib angles of 30, 45, and 60 degrees are studied. The environmental exergy loss was determined to be substantial, between 70 % and 80 %. Maximum system to air exergy loss occurs at Reynolds number of 3000 with 5.64 W. At a temperature parameter of 0.0377 m2K/W, both the thermal and exergetic efficiencies are at their highest, at 77.60 % and 3.81 %, respectively. In comparison to a plate having a plain surface, the suggested apex-down discrete arc rib performs better based on energy payback time, usable yearly energy, and enviro-economic criteria. Finally, at rib angle of 30°, the conditions that optimize the heat transfer and energy payback time, energy cost, exergo-economic, and enviro-economic characteristic of the current artificially roughened geometry of solar air heater.

Simplified discrete model for axisymmetric dielectric elastomer membranes with robotic applications

Soft robots utilizing inflatable dielectric membranes can realize intricate functionalities through the application of non-mechanical fields. However, given the current limitations in simulations, including low computational efficiency and difficulty in dealing with complex external interactions, the design and control of such soft robots often require trial and error. Thus, a novel one-dimensional (1D) discrete differential geometry (DDG)-based numerical model is developed for analyzing the highly nonlinear mechanics in axisymmetric inflatable dielectric membranes. The model captures the intricate dynamics of these membranes under both inflationary pressure and electrical stimulation. Comprehensive validations using hyperelastic benchmarks demonstrate the model’s accuracy and reliability. Additionally, the focus on the electro-mechanical coupling elucidates critical insights into the membrane’s behavior under varying internal pressures and electrical loads. The research further translates these findings into innovative soft robotic applications, including a spherical soft actuator, a soft circular fluid pump, and a soft toroidal gripper, where the snap-through of electroelastic membrane plays a crucial role. Our analyses reveal that the functional ranges of soft robots are amplified by the snap-through of an electroelastic membrane upon electrical stimuli. This study underscores the potential of DDG-based simulations to advance the understanding of the nonlinear mechanics of electroelastic membranes and guide the design of electroelastic actuators in soft robotics applications.

Discrete Geometry

A number of important recent developments in various branches of discrete geometry were presented at the workshop. The presentations illustrated both the diversity of the area and its strong connections to other fields of mathematics such as convex geometry, combinatorics, or topology. Two open problem sessions highlighted the abundance of open questions and many of the results presented were obtained by young researchers, confirming the vitality of the field.

The Tropical and Zonotopal Geometry of Periodic Timetables

AbstractThe Periodic Event Scheduling Problem (PESP) is the standard mathematical tool for optimizing periodic timetables in public transport. A solution to a PESP instance consists of three parts: a periodic timetable, a periodic tension, and integer offset values. While the space of periodic tensions has received much attention in the past, we explore geometric properties of the other two components. The general aim of this paper is to establish novel connections between periodic timetabling and discrete geometry. Firstly, we study the space of feasible periodic timetables as a disjoint union of polytropes. These are polytopes that are convex both classically and in the sense of tropical geometry. We then study this decomposition and use it to outline a new heuristic for PESP, based on neighbourhood relations of the polytropes. Secondly, we recognize that the space of fractional cycle offsets is in fact a zonotope, and then study its zonotopal tilings. These are related to the hyperrectangle of fractional periodic tensions, as well as the polytropes of the periodic timetable space, and we detail their interplay. To conclude, we also use this new understanding to give tight lower bounds on the minimum width of an integral cycle basis.

Geometry transition in spinfoams

Abstract We show how the fixed-spin asymptotics of the EPRL model can be used to perform the spin-sum for spin foam amplitudes defined on fixed two-complexes without interior faces and contracted with coherent spin-network states peaked on a discrete simplicial geometry with macroscopic areas. We work in the representation given in Ref 1. We first rederive the latter in a different way suitable for our purposes. We then extend this representation to 2-complexes with a boundary and derive its relation to the coherent state representation. We give the measure providing the resolution of the identity for Thiemann's state in the twisted geometry parametrization. We then piece together these with other results in the literature and show how the spin sum can be performed analytically using the model asymptotics. These results are relevant to analytic investigations regarding the transition of a black hole to a white hole geometry. In particular, this work was the basis of the calculation presented in Ref 2.

Discrete differential geometry-based model for nonlinear analysis of axisymmetric shells

In this paper, we propose a novel one-dimensional (1D) discrete differential geometry (DDG)-based numerical method for geometrically nonlinear mechanics analysis (e.g., buckling and snapping) of axisymmetric shell structures. Our numerical model leverages differential geometry principles to accurately capture the complex nonlinear deformation patterns exhibited by axisymmetric shells. By discretizing the axisymmetric shell into interconnected 1D elements along the meridional direction, the in-plane stretching and out-of-bending potentials are formulated based on the geometric principles of 1D nodes and edges under the Kirchhoff–Love hypothesis, and elastic force vector and associated Hessian matrix required by equations of motion are later derived based on symbolic calculation. Through extensive validation with available theoretical solutions and finite element method (FEM) simulations in literature, our model demonstrates high accuracy in predicting the nonlinear behavior of axisymmetric shells. Importantly, compared to the classical theoretical model and three-dimensional (3D) FEM simulation, our model is highly computationally efficient, making it suitable for large-scale real-time simulations of nonlinear problems of shell structures such as instability and snap-through phenomena. Moreover, our framework can easily incorporate complex loading conditions, e.g., boundary nonlinear contact and multi-physics actuation, which play an essential role in the use of engineering applications, such as soft robots and flexible devices. This study demonstrates that the simplicity and effectiveness of the 1D discrete differential geometry-based approach render it a powerful tool for engineers and researchers interested in nonlinear mechanics analysis of axisymmetric shells, with potential applications in various engineering fields.

Rigidity of the Delaunay triangulations of the plane

We prove a rigidity result for Delaunay triangulations of the plane under Luo's notion of discrete conformality, extending previous results on hexagonal triangulations. Our result is a discrete analogue of the conformal rigidity of the plane. We follow Zhengxu He's analytical approach in his work on the rigidity of disk patterns, and develop a discrete Schwarz lemma and a discrete Liouville theorem. As a key ingredient to prove the discrete Schwarz lemma, we establish a correspondence between the Euclidean discrete conformality and the hyperbolic discrete conformality, for geodesic embeddings of triangulations. Other major tools include conformal modulus, discrete extremal length, and maximum principles in discrete conformal geometry.

Quantum entropy couples matter with geometry

Abstract We propose a theory for coupling matter fields with discrete geometry on higher-order networks, i.e. cell complexes. The key idea of the approach is to associate to a higher-order network the quantum entropy of its metric. Specifically we propose an action having two contributions. The first contribution is proportional to the logarithm of the volume associated to the higher-order network by the metric. In the vacuum this contribution determines the entropy of the geometry. The second contribution is the quantum relative entropy between the metric of the higher-order network and the metric induced by the matter and gauge fields. The induced metric is defined in terms of the topological spinors and the discrete Dirac operators. The topological spinors, defined on nodes, edges and higher-dimensional cells, encode for the matter fields. The discrete Dirac operators act on topological spinors, and depend on the metric of the higher-order network as well as on the gauge fields via a discrete version of the minimal substitution. We derive the coupled dynamical equations for the metric, the matter and the gauge fields, providing an information theory principle to obtain the field theory equations in discrete curved space.

On the connectedness of arithmetic hyperplanes

Discrete geometry is a geometry specific to computers that studies Zd structures. It appears naturally in image analysis or 3D printing. Our goal is to find efficient algorithms to characterise these geometric structures and their properties.We are interested in a fundamental structure of discrete geometry, the arithmetic hyperplanes, and more particularly in their connectedness. Many works have studied a connectedness defined from the neighbourhood by faces and have allowed to observe a percolation phenomenon. These studies have also allowed to decide the connectedness of a plane in an efficient way. We propose an extension of these results in the case of connectivity defined from general neighbourhoods.Beyond the new concepts that this extension requires, the main contribution of the paper lies in the use of analysis to solve this arithmetic problem and in the design of an algorithm that decides the general connectedness problem. The study of the thickness of connectedness as a function reveals discontinuities at each rational point. However, a much more regular underlying structure appears in the irrational case. Thus, the consideration of irrational vectors allows a simpler approach to the connectedness of arithmetic hyperplanes.

Generalised evasive subspaces

AbstractWe introduce and explore a new concept of evasive subspace with respect to a collection of subspaces sharing a common dimension, most notably partial spreads. We show that this concept generalises known notions of subspace scatteredness and evasiveness. We establish various upper bounds for the dimension of an evasive subspace with respect to arbitrary partial spreads, obtaining improvements for the Desarguesian ones. We also establish existence results for evasive spaces in a nonconstructive way, using a graph theory approach. The upper and lower bounds we derive have a precise interpretation as bounds for the critical exponent of certain combinatorial geometries. Finally, we investigate connections between the notion of evasive space we introduce and the theory of rank‐metric codes, obtaining new results on the covering radius and on the existence of minimal vector rank‐metric codes.

In Memoriam: Peter Benjamin Borwein (1953–2020)

Peter Borwein had wide-ranging mathematical interests, and was a pioneer in computational and experimental investigations in many areas. We fondly recall some of his interests and contributions in a number of topics in analysis, number theory, and other areas, especially work where computation and experimentation played an important role. This includes his work on a number of extremal problems regarding Littlewood polynomials and other families of integer polynomials with restricted coefficients, questions regarding the Mahler measure of an integer polynomial, problems on merit factors and Barker sequences, the Prouhet–Tarry–Escott problem, problems of Pólya and Turán regarding sums of the Liouville function, and questions in combinatorial geometry regarding arrangements of points and lines.

Unimodal sequences: From Isaac Newton to June Huh

In this paper, we present a simple proof of a famous result of Newton on unimodal sequences associated to polynomials with real roots. We then give a brief exposition of the recent work of Huh on such sequences arising from combinatorial geometries.

A reduced-order model of thermo-viscoelastic filaments in a material extrusion process

High-resolution and high-efficiency simulations are a great challenge in a material extrusion process. This paper developed a reduced-order thermo-viscoelastic model based on discrete differential geometry. This model successfully simulated the dynamic behaviors, heat transfer, and deformations of filaments during the material extrusion with high computational efficiency. The kinematics of filaments was constructed using a centerline and time-parallel frame combined scheme, and the dynamic system was derived based on the elastic and viscous potential energies of stretching, bending, and twisting. A Newmark implicit algorithm was applied to solve the dynamic equations of the model, and a collision detection and response strategy for filaments was proposed. The convergence, accuracy, and efficiency of this model were validated and tested from various aspects. This model was then utilized to examine the impact of printing parameters on the temperature distribution and sagging deformation of an overhanging filament, and its extended applications were further demonstrated.

Isometric deformations of discrete and smooth T-surfaces

Quad-surfaces are polyhedral surfaces with quadrilateral faces and the combinatorics of a square grid. Isometric deformation of the quad-surfaces can be thought of as transformations that keep all the involved quadrilaterals rigid. Among quad-surfaces, those capable of non-trivial isometric deformations are identified as flexible, marking flexibility as a core topic in discrete differential geometry. The study of quad-surfaces and their flexibility is not only theoretically intriguing but also finds practical applications in fields like membrane theory, origami, architecture and robotics.A generic quad-surface is rigid, however, certain subclasses exhibit a 1-parameter family of flexibility. One of such subclasses is the T-hedra which are originally introduced by Graf and Sauer in 1931.This article provides a synthetic and an analytic description of T-hedra and their smooth counterparts namely, the T-surfaces. In the next step the parametrization of their isometric deformation is obtained and their deformability range is discussed. The given parametrizations and isometric deformations are provided for general T-hedra and T-surfaces. However, specific subclasses are extensively examined and explored, particularly those that encompass notable and well-known structures, including the Miura fold, surfaces of revolution and molding surfaces.

A unified framework for simplicial Kuramoto models

Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified framework to describe different variants of these models, categorized into three main groups: “simple” models, “Hodge-coupled” models, and “order-coupled” (Dirac) models. Our framework is based on topology and discrete differential geometry, as well as gradient systems and frustrations, and permits a systematic analysis of their properties. We establish an equivalence between the simple simplicial Kuramoto model and the standard Kuramoto model on pairwise networks under the condition of manifoldness of the simplicial complex. Then, starting from simple models, we describe the notion of simplicial synchronization and derive bounds on the coupling strength necessary or sufficient for achieving it. For some variants, we generalize these results and provide new ones, such as the controllability of equilibrium solutions. Finally, we explore a potential application in the reconstruction of brain functional connectivity from structural connectomes and find that simple edge-based Kuramoto models perform competitively or even outperform complex extensions of node-based models.

이차계획법에 기반한 소파 이동 문제의 상한선 개선

The moving sofa problem is a problem in discrete geometry that involves finding a shape with the maximum area that can pass through a right-angled corner in a hallway with unit width, and has remained an open problem since it was posed by Moser in 1966. The largest lower bound on the maximum area known to date is 2.2195..., found by Gerver in 1992, and the smallest upper bound is 2.37, proved by Kallus and Romik in 2018. While the minimum upper bound of 2.37 appears to be somewhat loose, experimental evidence suggests that there is little room for improvement in the largest lower bound of 2.2195.... In this study, we aim to lower the upper bound to be closer to Gerver’s maximum lower bound. For this purpose, we construct an optimization algorithm based on geometric branch-and-bound and quadratic programming, and prove various geometric properties for efficient search of the algorithm. Under a reasonable geometric assumption, the proposed optimization algorithm obtains an improved upper bound of 2.3361 with much shorter computation time than Kallus and Romik.

De Casteljau's algorithm in geometric data analysis: Theory and application

For decades, de Casteljau's algorithm has been used as a fundamental building block in curve and surface design and has found a wide range of applications in fields such as scientific computing and discrete geometry, to name but a few. With increasing interest in nonlinear data science, its constructive approach has been shown to provide a principled way to generalize parametric smooth curves to manifolds. These curves have found remarkable new applications in the analysis of parameter-dependent, geometric data. This article provides a survey of the recent theoretical developments in this exciting area as well as its applications in fields such as geometric morphometrics and longitudinal data analysis in medicine, archaeology, and meteorology.