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Computational problems for physics : with guided solutions using python / Rubin H. Landau, Manuel José Páez.

By: Contributor(s): Material type: TextTextSeries: Series in computational physicsPublisher: Boca Raton : London CRC Press, Taylor & Francis Group, [2018]Description: xix, 389 pages ; 26 cmISBN:
  • 9781138705913
Subject(s): DDC classification:
  • 530.15 LAN
Contents:
Computational basics for physics -- Data analytics for physics -- Classical & nonlinear dynamics -- Wave equations & fluid dynamics -- Electricity & magnetism -- Quantum mechanics -- Thermodynamics & statistical physics -- Biological models: population dynamics & 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"-- Provided by publisher.
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Item type Current library Collection Call number Status Date due Barcode
Books Books H.T. Parekh Library SIAS Collection 530.15 LAN (Browse shelf(Opens below)) Available K2950

GBP 92.00
S02/142

Computational basics for physics -- Data analytics for physics -- Classical & nonlinear dynamics -- Wave equations & fluid dynamics -- Electricity & magnetism -- Quantum mechanics -- Thermodynamics & statistical physics -- Biological models: population dynamics & 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"-- Provided by publisher.

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