Localization of semi-Heyting algebras

In this note, we introduce the notion of ideal on semi-Heyting algebras which allows us to consider a topology on them. Besides, we define the concept of F−multiplier, where F is a topology on a semi-Heyting algebra L, which is used to construct the localization semi-Heyting algebra LF. Furthermore, we prove that the semi-Heyting algebra of fractions LS associated with an ∧−closed system S of L is a semi-Heyting of localization. Finally, in the finite case we prove that LS is isomorphic to a special subalgebra of L. Since Heyting algebras are a particular case of semi-Heyting algebras, all these results generalize those obtained in [11].Fil: Figallo, Aldo Victorio. Universidad Nacional de San Juan. Facultad de Filosofía, Humanidades y Artes. Instituto de Ciencias Básicas; ArgentinaFil: Pelaitay, Gustavo Andrés. Universidad Nacional de San Juan. Facultad de Filosofía, Humanidades y Artes. Instituto de Ciencias Básicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Filosofía, Humanidades y Artes. Departamento de Matemática; Argentin

Wave propagation in one-dimensional nonlinear acoustic metamaterials

The propagation of waves in the nonlinear acoustic metamaterials (NAMs) is fundamentally different from that in the conventional linear ones. In this article we consider two one-dimensional NAM systems featuring respectively a diatomic and a tetratomic meta unit-cell. We investigate the attenuation of the wave, the band structure and the bifurcations to demonstrate novel nonlinear effects, which can significantly expand the bandwidth for elastic wave suppression and cause nonlinear wave phenomena. Harmonic averaging approach, continuation algorithm, Lyapunov exponents are combined to study the frequency responses, the nonlinear modes, bifurcations of periodic solutions and chaos. The nonlinear resonances are studied and the influence of damping on hyper-chaotic attractors is evaluated. Moreover, a "quantum" behavior is found between the low-energy and high-energy orbits. This work provides an important theoretical base for the further understandings and applications of NAMs

A Topological Approach to Tense LMn×m-Algebras

In 2015, tense n × m-valued Lukasiewicz–Moisil algebras (or tense LMn×m-algebras) were introduced by A. V. Figallo and G. Pelaitay as an generalization of tense n-valued Łukasiewicz–Moisil algebras. In this paper we continue the study of tense LMn×m-algebras. More precisely, we determine a Priestley-style duality for these algebras. This duality enables us not only to describe the tense LMn×m-congruences on a tense LMn×m-algebra, but also to characterize the simple and subdirectly irreducible tense LMn×m-algebras

Generalized Martingale and stopping time techniques in Banach spaces.

Probability theory plays a crucial role in the study of the geometry of Banach spaces. In the literature, notions from probability theory have been formulated and studied in the measure free setting of vector lattices. However, there is little evidence of these vector lattice techniques being used in the study of geometry of Banach spaces. In this thesis, we fill this niche. Using the l-tensor product of Chaney-Shaefer, we are able to extend the available vector lattice techniques and apply them to the Lebesgue-Bochner spaces. As a consequence, we obtain new characterizations of the Radon Nikod´ym property and the UMD property

A node-based version of the cellular Potts model

The cellular Potts model (CPM) is a lattice-based Monte Carlo method that uses an energetic formalism to describe the phenomenological mechanisms underlying the biophysical problem of interest. We here propose a CPM-derived framework that relies on a node-based representation of cell-scale elements. This feature has relevant consequences on the overall simulation environment. First, our model can be implemented on any given domain, provided a proper discretization (which can be regular or irregular, fixed or time evolving). Then, it allowed an explicit representation of cell membranes, whose displacements realistically result in cell movement. Finally, our node-based approach can be easily interfaced with continuous mechanics or fluid dynamics models. The proposed computational environment is here applied to some simple biological phenomena, such as cell sorting and chemotactic migration, also in order to achieve an analysis of the performance of the underlying algorithm. This work is finally equipped with a critical comparison between the advantages and disadvantages of our model with respect to the traditional CPM and to some similar vertex-based approaches

Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning

The paper introduces the application of information geometry to describe the ground states of Ising models by utilizing parity-check matrices of cyclic and quasi-cyclic codes on toric and spherical topologies. The approach establishes a connection between machine learning and error-correcting coding. This proposed approach has implications for the development of new embedding methods based on trapping sets. Statistical physics and number geometry applied for optimize error-correcting codes, leading to these embedding and sparse factorization methods. The paper establishes a direct connection between DNN architecture and error-correcting coding by demonstrating how state-of-the-art architectures (ChordMixer, Mega, Mega-chunk, CDIL, ...) from the long-range arena can be equivalent to of block and convolutional LDPC codes (Cage-graph, Repeat Accumulate). QC codes correspond to certain types of chemical elements, with the carbon element being represented by the mixed automorphism Shu-Lin-Fossorier QC-LDPC code. The connections between Belief Propagation and the Permanent, Bethe-Permanent, Nishimori Temperature, and Bethe-Hessian Matrix are elaborated upon in detail. The Quantum Approximate Optimization Algorithm (QAOA) used in the Sherrington-Kirkpatrick Ising model can be seen as analogous to the back-propagation loss function landscape in training DNNs. This similarity creates a comparable problem with TS pseudo-codeword, resembling the belief propagation method. Additionally, the layer depth in QAOA correlates to the number of decoding belief propagation iterations in the Wiberg decoding tree. Overall, this work has the potential to advance multiple fields, from Information Theory, DNN architecture design (sparse and structured prior graph topology), efficient hardware design for Quantum and Classical DPU/TPU (graph, quantize and shift register architect.) to Materials Science and beyond.Comment: 71 pages, 42 Figures, 1 Table, 1 Appendix. arXiv admin note: text overlap with arXiv:2109.08184 by other author

Computational simulation of strain localization: From theory to implementation

Strain localization in the form of shear bands or slip surfaces has widely been observed in most engineering materials, such as metals, concrete, rocks, and soils. Concurrent with the appearance of localized deformation is the loss of overall load-carrying capacity of the material body. Because the deformation localization is an important precursor of material failure, computational modeling of the onset and growth of the localization is indispensable for the understanding of the complete mechanical response and post-peak behavior of materials and structures. Simulation results can also be used to judge the failure mechanisms of materials and structures so that the design of materials and structures can be improved. Although the mechanisms responsible for localized deformation vary widely from one material to another, strain softening behavior is often observed to accompany the deformation localization in geotechnical materials. In this dissertation, a rate-independent strain softening plasticity model with associated flow rule and isotropic softening law is formulated within the framework of classical continuum mechanics to simulate the strain localization. A stress integration algorithm is developed to solve the nonlinear system of equations that comes from the finite element formulation of the incremental boundary value problem for linear strain softening plasticity. Two finite element programs, EP1D and EPLAS, are developed to simulate strain localization for 1-D and 2-D problems. Numerical examples show that the developed strain softening model and computer programs can reproduce well the occurrence and development of strain localization or shear band localization. Because the classical strain softening model does not contain a material length scale, the finite element simulation suffers from pathological mesh dependence. To regularize the mesh dependence of a classical strain softening model, gradient plasticity theory or nonlocal plasticity theory has to be used. To provide correct boundary conditions for higher-order differential constitutive equations with regard to internal state variables, a comparison of boundary conditions for gradient elasticity with gradient plasticity is carried out to show that the Dirichlet boundary condition is the correct boundary condition to force the strain to be localized into a small region and to remove the mesh-dependence. A nonlocal plasticity model with C0 finite elements is proposed to simulate strain localization in a mesh independent manner. This model is based on the integral-type nonlocal plasticity model and the cubic representative volumetric element (RVE). Through a truncated Taylor expansion, a mathematical relationship between an integral-type nonlocal plasticity model and a gradient plasticity model is established, which makes it possible to use the C0 elements to approximate the internal state variable field. Variational formulae and Galerkin\u27s equations of the two coupled fields, displacement field and plastic multiplier field, are developed based on the C0 elements. An algorithm consisting of nonlocal elements and moving boundary technique is proposed to solve the two coupled fields. A numerical example shows the ability of the proposed model and algorithm to achieve mesh-independent simulation of strain localization