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Genetic algorithms (GAs) are an optimization technique that has been successfully used on many real-world problems. There exist different approaches to their theoretical study. In this paper we complete a recently presented approach to…

Neural and Evolutionary Computing · Computer Science 2017-07-04 Mauro Castelli , Gianpiero Cattaneo , Luca Manzoni , Leonardo Vanneschi

Genotype-phenotype (GP) maps specify how the random mutations that change genotypes generate variation by altering phenotypes, which, in turn, can trigger selection. Many GP maps share the following general properties: 1) The number of…

Populations and Evolution · Quantitative Biology 2014-02-07 Ard A Louis , Steffen Schaper

Homology-based invariants can be used to characterize the geometry of datasets and thereby gain some understanding of the processes generating those datasets. In this work we investigate how the geometry of a dataset changes when it is…

Algebraic Topology · Mathematics 2022-03-17 Jens Agerberg , Wojciech Chacholski , Ryan Ramanujam

Evolutionary algorithms usually explore a search space of solutions by means of crossover and mutation. While a mutation consists of a small, local modification of a solution, crossover mixes the genetic information of two solutions to…

Neural and Evolutionary Computing · Computer Science 2022-08-24 Henri Thölke , Jens Kosiol

In this paper, we use four-dimensional quaternionic algebra to describing space-time field equations in curvature form. The transformation relations of a quaternionic variable are established with the help of basis transformations of…

General Physics · Physics 2024-10-08 B. C. Chanyal

Spatial omics has transformed our understanding of tissue architecture by preserving spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enabled extraction of morphological features describing the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Eduard Chelebian , Christophe Avenel , Carolina Wählby

Matrix configurations coming from matrix models comprise many important aspects of modern physics. They represent special quantum spaces and are thus strongly related to noncommutative geometry. In order to establish a semiclassical limit…

High Energy Physics - Theory · Physics 2025-12-01 Laura Olivia Felder

Geometric and holonomic quantum computation utilizes intrinsic geometric properties of quantum-mechanical state spaces to realize quantum logic gates. Since both geometric phases and quantum holonomies are global quantities depending only…

Quantum Physics · Physics 2023-08-03 Jiang Zhang , Thi Ha Kyaw , Stefan Filipp , Leong-Chuan Kwek , Erik Sjöqvist , Dianmin Tong

Genetic algorithms have been used in recent decades to solve a broad variety of search problems. These algorithms simulate natural selection to explore a parameter space in search of solutions for a broad variety of problems. In this paper,…

Neural and Evolutionary Computing · Computer Science 2022-03-25 Yoshio Martinez , Katya Rodriguez , Carlos Gershenson

The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here we introduce a rich, intuitive, and biologically realistic genotype-phenotype (GP) map, that serves as a model of self-assembling…

Populations and Evolution · Quantitative Biology 2013-11-05 Sam F. Greenbury , Iain G. Johnston , Ard A. Louis , Sebastian E. Ahnert

Hard disks systems are often considered as prototypes for simple fluids. In a statistical mechanics context, the hard disk configuration space is generally quotiented by the action of various symmetry groups. The changes in the topological…

Statistical Mechanics · Physics 2022-05-31 O. B. Ericok , J. K. Mason

Phylogenetics uses alignments of molecular sequence data to learn about evolutionary trees relating species. Along branches, sequence evolution is modelled using a continuous-time Markov process characterised by an instantaneous rate…

The incorporation of quantum ansatz with machine learning classification models demonstrates the ability to extract patterns from data for classification tasks. However, taking advantage of the enhanced computational power of quantum…

Quantum Physics · Physics 2024-11-13 Arpita Ghosh , MD Muhtasim Fuad , Seemanta Bhattacharjee

In this paper, we study the geospatial ontologies that we are interested in together as a geospatial ontology system, consisting of a set of the geospatial ontologies and a set of geospatial ontology operations, without any internal details…

Artificial Intelligence · Computer Science 2023-09-22 Xiuzhan Guo , Wei Huang , Min Luo , Priya Rangarajan

Geometric quantum machine learning uses the symmetries inherent in data to design tailored machine learning tasks with reduced search space dimension. The field has been well-studied recently in an effort to avoid barren plateau issues…

Quantum Physics · Physics 2025-07-14 Zachary P. Bradshaw , Ethan N. Evans , Matthew Cook , Margarite L. LaBorde

In this work, we propose a cross-view learning approach, in which images captured from a ground-level view are used as weakly supervised annotations for interpreting overhead imagery. The outcome is a convolutional neural network for…

Computer Vision and Pattern Recognition · Computer Science 2018-08-06 Connor Greenwell , Scott Workman , Nathan Jacobs

The prevalence of neutral mutations implies that biological systems typically have many more genotypes than phenotypes. But can the way that genotypes are distributed over phenotypes determine evolutionary outcomes? Answering such questions…

Populations and Evolution · Quantitative Biology 2015-09-28 Kamaludin Dingle , Steffen Schaper , Ard A. Louis

An Interactive Genetic Algorithm is proposed to progressively sketch the desired side-view of a car profile. It adopts a Fourier decomposition of a 2D profile as the genotype, and proposes a cross-over mechanism. In addition, a formula…

Neural and Evolutionary Computing · Computer Science 2013-03-22 François Cluzel , Bernard Yannou , Markus Dihlmann

GPT-style language models are sensitive to single-token changes at generation points where the predicted probability distribution is spread across multiple tokens. Viewing this sensitivity as a geometric property, we derive an…

Machine Learning · Computer Science 2026-05-12 Albert F. Modenbach

We analyze the quantum penny flip game using geometric algebra and so determine all possible unitary transformations which enable the player Q to implement a winning strategy. Geometric algebra provides a clear visual picture of the quantum…

Quantum Physics · Physics 2015-05-13 James M. Chappell , Azhar Iqbal , M. A. Lohe , Lorenz von Smekal
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