Computational problems for physics : with guided solutions using Python Rubin H Landau; Manuel José Páez Mejía

By:

Landau, Rubin H

Contributor(s):

Páez Mejía, Manuel José

Material type: Text

9781138705418

DDC classification:

530.15 LAN

Contents:

Computational basics for physics -- Data analytics for physics -- Classical and nonlinear dynamics -- Wave equations and fluid dynamics -- Electricity and magnetism -- Quantum mechanics -- Thermodynamics and statistical physics -- Biological models: population dynamics and plant growth -- Additional entry-level problems.

Summary: Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It's also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 5.0 (1 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Barcode
Books	IIITDM Kurnool General Stacks	Non-fiction	530.15 LAN (Browse shelf(Opens below))	Available	0003659

Computational basics for physics --
Data analytics for physics --
Classical and nonlinear dynamics --
Wave equations and fluid dynamics --
Electricity and magnetism --
Quantum mechanics --
Thermodynamics and statistical physics --
Biological models: population dynamics and plant growth --
Additional entry-level problems.

Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It's also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem

There are no comments on this title.

to post a comment.