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Computational Physics and Python Applications

Works Count: 54170

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This cluster of papers covers a wide range of topics related to scientific computing and data analysis using Python. It includes statistical modeling, machine learning, visualization, geospatial mapping, geomorphology, oceanography, and HF radio networking. The papers showcase the diverse applications and tools available for scientific research and data analysis in various fields.

Keywords

Python; Scientific Computing; Statistical Modeling; Machine Learning; Data Analysis; Visualization; Geospatial Mapping; Geomorphology; Oceanography; HF Radio Networking

The Feynman Lectures on Physics

1964-08-01

Richard P. Feynman , Robert B. Leighton , Matthew Sands +1 more

Share Icon Share Twitter Facebook Reddit LinkedIn Reprints and Permissions Cite Icon Cite Search Site Citation Richard P. Feynman, Robert B. Leighton, Matthew Sands, S. B. Treiman; The Feynman Lectures … Share Icon Share Twitter Facebook Reddit LinkedIn Reprints and Permissions Cite Icon Cite Search Site Citation Richard P. Feynman, Robert B. Leighton, Matthew Sands, S. B. Treiman; The Feynman Lectures on Physics. Physics Today 1 August 1964; 17 (8): 45–46. https://doi.org/10.1063/1.3051743 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentPhysics Today Search Advanced Search

Python: a programming language for software integration and development.

1999-02-01

M F Sanner

A Theoretical Foundation for the Gravity Equation.

1979-01-01

James E. Anderson

Hyberbolic Conservation Laws in Continuum Physics

2005-01-01

Constantine M. Dafermos

Computer Simulation Using Particles

1988-01-01

R. W. Hockney , J.W. Eastwood

Computer experiments using particle models A one-dimensional plasma model The simulation program Time integration schemes The particle-mesh force calculation The solution of field equations Collisionless particle models Particle-particle/particle-mesh algorithms Plasma … Computer experiments using particle models A one-dimensional plasma model The simulation program Time integration schemes The particle-mesh force calculation The solution of field equations Collisionless particle models Particle-particle/particle-mesh algorithms Plasma simulation Semiconductor device simulation Astrophysics Solids, liquids and phase changes Fourier transforms Fourier series and finite Fourier transforms Bibliography Index

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Encyclopedia of Machine Learning

2010-01-01

Claude Sammut , Geoffrey I. Webb

API design for machine learning software: experiences from the scikit-learn project

2013-09-23

Lars Buitinck , Gilles Louppe , Mathieu Blondel +7 more

Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this … Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss our design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. The paper also comments on implementation details specific to the Python ecosystem and analyzes obstacles faced by users and developers of the library.

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REVIEW OF PARTICLE PHYSICS Particle Data Group

2014-09-01

Keith A. Olive

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,283 new measurements from 899 Japers, we list, evaluate, and average measured properties of gauge … The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,283 new measurements from 899 Japers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as heavy neutrinos, supersymmetric and technicolor particles, axions, dark photons, etc. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as Supersymmetry, Extra Dimensions, Particle Detectors, Probability, and Statistics. Among the 112 reviews are many that are new or heavily revised including those on: Dark Energy, Higgs Boson Physics, Electroweak Model, Neutrino Cross Section Measurements, Monte Carlo Neutrino Generators, Top Quark, Dark Matter, Dynamical Electroweak Symmetry Breaking, Accelerator Physics of Colliders, High-Energy Collider Parameters, Big Bang Nucleosynthesis, Astrophysical Constants and Cosmological Parameters.

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Nonlinear Dynamical Control Systems

1990-01-01

Henk Nijmeijer , Arjan van der Schaft

Chaos in Dynamical Systems

1994-01-01

Edward Ott , Kurt Wiesenfeld

Over the past two decades scientists, mathematicians, and engineers have come to understand that a large variety of systems exhibit complicated evolution with time. This complicated behavior is known as … Over the past two decades scientists, mathematicians, and engineers have come to understand that a large variety of systems exhibit complicated evolution with time. This complicated behavior is known as chaos. In the new edition of this classic textbook Edward Ott has added much new material and has significantly increased the number of homework problems. The most important change is the addition of a completely new chapter on control and synchronization of chaos. Other changes include new material on riddled basins of attraction, phase locking of globally coupled oscillators, fractal aspects of fluid advection by Lagrangian chaotic flows, magnetic dynamos, and strange nonchaotic attractors. This new edition will be of interest to advanced undergraduates and graduate students in science, engineering, and mathematics taking courses in chaotic dynamics, as well as to researchers in the subject.

Matplotlib: A 2D Graphics Environment

2007-01-01

John D. Hunter

Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems

Fractals and chaos in geology and geophysics

1993-01-01

Donald L. Turcotte

This book introduces the fundamental concepts of fractal geometry and chaotic dynamics. These concepts are then related to a variety of geological and geophysical problems, illustrating just what chaos theory … This book introduces the fundamental concepts of fractal geometry and chaotic dynamics. These concepts are then related to a variety of geological and geophysical problems, illustrating just what chaos theory and fractals really tell us and how they can be applied to the earth sciences. Petroleum and mineral reserves, earthquakes, mantle convection and magnetic field generation are among the earth's properties that come under scrutiny. This is the first book that covers these topics at an accessible level; the concepts are introduced at the lowest possible level of mathematics and are consistently understandable, so that the reader requires only a background in basic physics and mathematics. Problems are also included for the reader to solve.

Equations of Mathematical Physics

1971-10-01

V. S. Vladimirov , Ludwig Streit

Shock Waves and Reaction—Diffusion Equations

1983-01-01

Joel Smoller

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IPython: A System for Interactive Scientific Computing

2007-01-01

Fernando Pérez , Brian Granger

Python offers basic facilities for interactive work and a comprehensive library on top of which more sophisticated systems can be built. The IPython project provides on enhanced interactive environment that … Python offers basic facilities for interactive work and a comprehensive library on top of which more sophisticated systems can be built. The IPython project provides on enhanced interactive environment that includes, among other features, support for data visualization and facilities for distributed and parallel computation

Python for Scientific Computing

2007-01-01

Travis E. Oliphant

Python is an excellent "steering" language for scientific codes written in other languages. However, with additional basic tools, Python transforms into a high-level language suited for scientific and engineering code … Python is an excellent "steering" language for scientific codes written in other languages. However, with additional basic tools, Python transforms into a high-level language suited for scientific and engineering code that's often fast enough to be immediately useful but also flexible enough to be sped up with additional extensions.

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Orange: data mining toolbox in python

2013-01-01

Janez Demšar , Tomaž Curk , Aleš Erjavec +7 more

Orange is a machine learning and data mining suite for data analysis through Python scripting and visual programming. Here we report on the scripting part, which features interactive data analysis … Orange is a machine learning and data mining suite for data analysis through Python scripting and visual programming. Here we report on the scripting part, which features interactive data analysis and component-based assembly of data mining procedures. In the selection and design of components, we focus on the flexibility of their reuse: our principal intention is to let the user write simple and clear scripts in Python, which build upon C++ implementations of computationally-intensive tasks. Orange is intended both for experienced users and programmers, as well as for students of data mining.

Mathematical Foundations of Quantum Mechanics

2018-04-11

John von Neumann

Quantum mechanics was still in its infancy in 1932 when the young John von Neumann, who would go on to become one of the greatest mathematicians of the twentieth century, … Quantum mechanics was still in its infancy in 1932 when the young John von Neumann, who would go on to become one of the greatest mathematicians of the twentieth century, published <italic>Mathematical Foundations of Quantum Mechanics</italic>—a revolutionary book that for the first time provided a rigorous mathematical framework for the new science. Robert Beyer's 1955 English translation, which von Neumann reviewed and approved, is cited more frequently today than ever before. But its many treasures and insights were too often obscured by the limitations of the way the text and equations were set on the page. This new edition of this classic work has been completely reset in TeX, making the text and equations far easier to read. The book has also seen the correction of a handful of typographic errors, revision of some sentences for clarity and readability, provision of an index for the first time, and prefatory remarks drawn from the writings of Léon Van Hove and Freeman Dyson have been added. The result brings new life to an essential work in theoretical physics and mathematics.

The Rapid Calculation of Potential Anomalies

1973-03-01

Robert L. Parker

It is shown how a series of Fourier transforms can be used to calculate the magnetic or gravitational anomaly caused by an uneven, non-uniform layer of material. Modern methods for … It is shown how a series of Fourier transforms can be used to calculate the magnetic or gravitational anomaly caused by an uneven, non-uniform layer of material. Modern methods for finding Fourier transforms numerically are very fast and make this approach attractive in situations where large quantities of observations are available.

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The Physics of Blown Sand and Desert Dunes

1971-01-01

R. A. Bagnold

Simulating physics with computers

1982-06-01

Richard P. Feynman

Statsmodels: Econometric and Statistical Modeling with Python

2010-01-01

Skipper Seabold , Josef Perktold

Statsmodels is a library for statistical and econometric analysis in Python. This paper discusses the current relationship between statistics and Python and open source more generally, outlining how the statsmodels … Statsmodels is a library for statistical and econometric analysis in Python. This paper discusses the current relationship between statistics and Python and open source more generally, outlining how the statsmodels package fills a gap in this relationship. An overview of statsmodels is provided, including a discussion of the overarching design and philosophy, what can be found in the package, and some usage examples. The paper concludes with a look at what the future holds.

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Python 3 Reference Manual

2009-03-20

Guido van Rossum , Fred L. Drake

PYTHON 3 Reference (Python Documentation MANUAL Part 2).Python is an easy to learn object-oriented programming language, which combines power with clear syntax. It has modules, classes, exceptions, very high level … PYTHON 3 Reference (Python Documentation MANUAL Part 2).Python is an easy to learn object-oriented programming language, which combines power with clear syntax. It has modules, classes, exceptions, very high level data types, and dynamic typing. is free software. It can be used with GNU (GNU/Linux), Unix, Microsoft Windows and many other systems.This is a printed softcover copy of the official documentation from the latest 3.0 distribution. For each copy sold $1 will be donated to the Software Foundation by the publisher.This book is part of a brand new six-part series of documentation books. Searching for Python Documentation Manual will show all six available books.ABOUT THE AUTHOR: Guido van Rossum, is the inventor of Python. Fred L. Drake, Jr. is the official editor of the documentation.

Data Structures for Statistical Computing in Python

2010-01-01

Wes McKinney

In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims … In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with relevant examples and some comparisons with the R language. We conclude by discussing possible future directions for statistical computing and data analysis using Python.

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corner.py: Scatterplot matrices in Python

2016-06-08

Daniel Foreman-Mackey

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More Is Different: Broken symmetry and the nature of the hierarchical structure of science.

1972-08-04

Philip W. Anderson

The Feynman Lectures on Physics

2013-07-23

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Quantum phase transitions

1999-04-01

Subir Sachdev

Nature abounds with phase transitions. The boiling and freezing of water are everyday examples of phase transitions, as are more exotic processes such as superconductivity and superfluidity. The universe itself … Nature abounds with phase transitions. The boiling and freezing of water are everyday examples of phase transitions, as are more exotic processes such as superconductivity and superfluidity. The universe itself is thought to have passed through several phase transitions as the high-temperature plasma formed by the big bang cooled to form the world as we know it today.

Numerical Recipes--The Art of Scientific Computing.

1988-01-01

Frederick N. Fritsch , William H. Press , Brian P. Flannery +2 more

The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package*

2018-08-23

Adrian M. Price-Whelan , Brigitta Sipőcz , Hans Moritz Günther +7 more

Abstract The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the … Abstract The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy , which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package, as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of interoperable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy Project.

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A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence

2019-07-17

Michael Haenlein , Andreas Kaplan

This introduction to this special issue discusses artificial intelligence (AI), commonly defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those … This introduction to this special issue discusses artificial intelligence (AI), commonly defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” It summarizes seven articles published in this special issue that present a wide variety of perspectives on AI, authored by several of the world’s leading experts and specialists in AI. It concludes by offering a comprehensive outlook on the future of AI, drawing on micro-, meso-, and macro-perspectives.

Scikit-learn: Machine Learning in Python

2011-11-01

PedregosaFabian , VaroquauxGaël , GramfortAlexandre +7 more

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing mach... Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing mach...

Equations of Mathematical Physics

1965-07-01

А. Н. Тихонов , A. A. Samarskiĭ , Peter B. Kahn

First Page First Page

Numerical Recipes, The Art of Scientific Computing

1987-01-01

William H. Press , Brian P. Flannery , Saul A. Teukolsky +2 more

First Page First Page

Review of Particle Physics

1998-03-01

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GPT-3: Its Nature, Scope, Limits, and Consequences

2020-11-01

Luciano Floridi , Massimo Chiriatti

Abstract In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. … Abstract In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic (that is, the Turing Test), and ethical questions and show that GPT-3 is not designed to pass any of them. This is a reminder that GPT-3 does not do what it is not supposed to do, and that any interpretation of GPT-3 as the beginning of the emergence of a general form of artificial intelligence is merely uninformed science fiction. We conclude by outlining some of the significant consequences of the industrialisation of automatic and cheap production of good, semantic artefacts.

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SciPy 1.0: fundamental algorithms for scientific computing in Python

2020-02-03

Pauli Virtanen , Ralf Gommers , Travis E. Oliphant +7 more

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in … SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

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A Treatise on Electricity and Magnetism

1873-04-01

Regular and Chaotic Dynamics

1992-01-01

A. J. Lichtenberg , M. A. Lieberman

Review of Convergent Real Number Sequences and Real Exponentiation

2025-06-25

Nicolas A. Pereyra | CRC Press eBooks

Probing topological entanglement on large scales

2025-06-25

NULL AUTHOR_ID | Physical Review Letters

Functional Tensor Regression

2025-06-23

Tongyu Li , Fang Yao , Anru R. Zhang | Statistica Sinica

Riemannian approach to the Lindbladian dynamics of a locally purified tensor network

2025-06-23

NULL AUTHOR_ID | Physical review. A/Physical review, A

Review article: Feature tracing in radio-echo sounding products of terrestrial ice sheets and planetary bodies

2025-06-23

Hameed Moqadam , Olaf Eisen | The cryosphere

Abstract. This paper aims to inform researchers and practitioners in radioglaciology about current and future trends in mapping the englacial stratigraphy of ice sheets. Radio-echo sounding (RES) is a useful … Abstract. This paper aims to inform researchers and practitioners in radioglaciology about current and future trends in mapping the englacial stratigraphy of ice sheets. Radio-echo sounding (RES) is a useful technique for measuring the subsurface properties of ice sheets and glaciers. One of the most important and unique outcomes is the mapping of ice sheets' englacial layer stratigraphy, mainly consisting of isochronous reflection horizons. Mapping those is still a labor-intensive task. This review provides an overview of state-of-the-art (semi-)automated methods for identifying ice surface, basal, and internal reflection horizons from radargrams in radioglaciology. Methods for segmenting (and detecting) different regions of radargrams are also included due to their data and methodological similarity to methods tracing internal reflection horizons. We discuss a variety of methods which have been developed or applied to RES data over the last few decades, including image processing, statistical techniques, and deep learning approaches. For each approach, we briefly summarize their procedures, challenges, and potential applications. Despite major advances, we conclude that gaps remain in effectively mapping internal reflection horizons in an automated way but with deep learning representing a potential advancement.

IEEE SYSTEMS, MAN, AND CYBERNETICS SOCIETY

2025-06-23

| IEEE Transactions on Cybernetics

TensorFlores: An enhanced Python-based TinyML framework

2025-06-23

Thommas Kevin Sales Flores , Daniel G. Costa , Ivanovitch Silva | SoftwareX

Explorations in Numerical Analysis and Machine Learning with Julia

2025-06-22

James V. Lambers , Amber Sumner Mooney , Vivian A Montiforte +1 more | WORLD SCIENTIFIC eBooks

THE MULTIPLICATIVE INTEGRAL AND THE EVOLUTION OF THE MAGNETIC FIELD IN THE MARKOV LINEAR MODEL

2025-06-21

Nursadyk Akanbai , Z.R. Suleimenova , Samal Tapeeva | Journal of Mathematics Mechanics and Computer Science

The paper is devoted to the probabilistic asymptotic analysis of the magnetic field and magnetic energy in a Markov linear model of an incompressible fluid. Firstly, the paper introduces a … The paper is devoted to the probabilistic asymptotic analysis of the magnetic field and magnetic energy in a Markov linear model of an incompressible fluid. Firstly, the paper introduces a brief history of the problem under consideration and presents the main results of the previous studies, which ultimately lead to the study of the product of independent random matrices with an increasing number of multiplicands. After that, the description of the Markov linear model considered in the paper is given, the so-called Lyapunov (generally speaking, random) bases for the multiplicative (stochastic) integral contained in the integral representation of the magnetic field are constructed. In conclusion, by decomposing the multiplicative integral over the constructed Lyapunov basis and relying on the properties of the basis, the main results - theorems on the asymptotic behavior of the magnetic field and magnetic energy - have been proven.

109.31 Did Tindley know the Archimedean property of $$\mathbb R$$ ?

2025-06-20

Bikash Chakraborty | The Mathematical Gazette

Real-Time Optical Imaging Acquisition and Processing in Python: A Practical Guide Using CAS

2025-06-17

Michael Hughes | Applied Optics

Pseudoentanglement from tensor networks

2025-06-16

NULL AUTHOR_ID | Physical Review Letters

Sentiment AI : Extraction and Analysis From Webblogs Using Python

2025-06-13

Sandeep Bhattacharjee | Research Square (Research Square)

<title>Abstract</title> Sentiment detection is a key to real time identification of human sentiments. Sentiment detection towards the recent developments in artificial intelligence holds the key for developments in all industries … <title>Abstract</title> Sentiment detection is a key to real time identification of human sentiments. Sentiment detection towards the recent developments in artificial intelligence holds the key for developments in all industries where applications of artificial intelligence exist or may exist in future. With the growing number of complexities in artificial intelligence applications for varied results, the onus lies on understanding the trends of the research community to detect the movement of development in different paths of development. Many existing methods can be used to identify the sentiments of researchers and learners in artificial intelligence. Several of such methods do exist to cater to such necessities. In this research paper, four methods namely word count, word space, word correlation and similarity algorithm, have been tested using python 3.10.13 codes on seven web sources which excels in discussions on research and developments in artificial intelligence.

A spontaneously emerging intelligence in a toroidal artificial world

2025-06-13

István Elek | Deleted Journal

Fractal dimensionality of a coiled helical coil

2025-06-12

Subhash Kak | Journal of Bioinformatics and Computational Biology

The helical coil is ubiquitous in biological and natural systems, and it is often the basic form in complex structures. This paper considers the question of its dimensionality, D, in … The helical coil is ubiquitous in biological and natural systems, and it is often the basic form in complex structures. This paper considers the question of its dimensionality, D, in biological information as the helical coil goes through recursive coiling as in DNA and RNA molecules in chromatin, in which the D-value is a function of the lengthening of the curve. It is shown that the dimensionality of coiled coils is virtually equal to e. Of the three forms of DNA, the dimensionality of the B-form is nearest to the optimal value, and this might be the reason why it is most common.

Using Modeling Software as an Alternative to Experiment: The Magnetic Field of a Helmholtz Coil

2025-06-11

Latif Hasi , Rilindë Raçi , Nazmi Hasi | International Journal of Computational and Experimental Science and Engineering

In physics education and research, the integration of modeling software has emerged as a promising alternative to traditional experimental approaches. This paper focuses on the specific case of examining the … In physics education and research, the integration of modeling software has emerged as a promising alternative to traditional experimental approaches. This paper focuses on the specific case of examining the magnetic field of a Helmholtz coil through computational simulation. Through a comparative analysis between simulated results and experimental data, we aim to evaluate the accuracy and reliability of using modeling software in replicating physical phenomena. Furthermore, we explore the potential of utilizing computational modeling as a viable tool for both didactic instruction and advanced research inquiries in the realm of magnetic field analysis. By addressing the overarching questions surrounding the efficacy and applicability of simulation-based methodologies, this study contributes to a deeper understanding of the role of computational physics in modern scientific exploration and educational practices.

Comparison of Cryptographic Performance in Python, Java, and C# Analyzing Language-Level Efficiency

2025-06-10

| International Journal of Advanced Trends in Computer Science and Engineering

In today’s world, safely transferring data is very important which means how cryptographic algorithms behave in different programming languages matters a lot to those designing systems. This work examines the … In today’s world, safely transferring data is very important which means how cryptographic algorithms behave in different programming languages matters a lot to those designing systems. This work examines the results of key cryptographic activities using Python, Java and C#—specifically, AES encryption, RSA key generation and SHA-256 hashing. Using standard ways to test benchmarks, the project measures the Execution Speed, Memory usage and Performance of all languages in handling cryptography. The analysis highlights those choices for language paradigm, type of runtime, approach to memory management and level of maturity in cryptographic libraries account for most of the variation among these frameworks. Python is quick to use in development, but Java offers a more balanced way and steadier speed according to the JCE. Compared to Java, C# shows better efficiency and is better suited for use on a tight budget. With the input from this study, programmers have better guidance in deciding which languages to use for high-performance programs.

Conservation of Baryon and Lepton Number is an Effect of Electric and Magnetic Charges

2025-06-10

Rainer Kühne

The conservation of baryon number and lepton number has not yet been explained. Here I present a new nomenclature where I redefine isospin and hypercharge. By doing so I explain … The conservation of baryon number and lepton number has not yet been explained. Here I present a new nomenclature where I redefine isospin and hypercharge. By doing so I explain baryon and lepton number conservation as an effect of the electric-magnetic duality and the U(1)×U(1) gauge symmetry of quantum electromagnetodynamics. By using this method I predict the quantum numbers of an octet of magnetic monopoles. Another surprising result is that both leptons and quarks have nonzero magnetic isospin, a new quantum number.

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The Power of the Anomaly Consistency Condition for the Master Ward Identity: Conservation of the Non-Abelian Gauge Current

2025-06-08

Michael Dütsch | Annales Henri Poincaré