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7.7 MB
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BC4C833E3E1E76F647002F55145F1BD071D9059C
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March 3, 2026, 9:43 a.m.
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(Last updated: March 3, 2026, 9:44 a.m.)
| File | Size |
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| Sun Q. Python for Quantum Chemistry. A Full Stack Programming Guide 2025.pdf | 7.7 MB |
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SOURCE: Sun Q. Python for Quantum Chemistry. A Full Stack Programming Guide 2025
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MEDIAINFO
Textbook in PDF format
Quantum chemistry requires ever higher computational performance, with more and more sophisticated and dedicated Python scripts being required to solve challenging problems. Although resources for basic use of Python are widely (and often freely) available online and in literature, truly cohesive materials for advanced Python programming skills are lacking.
Qiming Sun, a developer of the popular Python package PySCF, provides a comprehensive, end-to-end practical resource for researchers and engineers who have basic Python programming experiences chiefly in computational chemistry but want to take their use of the software forwards to the next level, the book provides an insightful exploration of Numpy, Pandas, and other data analysis tools. Readers will learn how to manage their Python computational projects in a professional way, with various tools and protocols for computational chemistry research and general scientific computing tasks exhibited and analysed from a technical perspective. Multiple programming paradigms including object-oriented, functional, meta-programming, dynamic, concurrent, and vector-oriented are illustrated in various technology scenarios allowing readers to properly use them to enhance their program projects. Readers will also learn how to use the presented optimization technologies to speed up their Python applications, even to the level as fast as a native C++ implementation. The applications of these technologies are then demonstrated using quantum chemistry Python applications.
Python for Quantum Chemistry: A Full Stack Programming Guide is written primarily for graduate students, researchers and software engineers working primarily in the fields of theoretical chemistry, computational chemistry, condensed matter physics, material modelling, molecular simulations, and quantum computing.
Python programming environment
Data processing
Visualization
Scientific computing tools
Meta-programming and non-numerical computation
Input and output
Working with cloud
Foreign language interfaces
Program performance optimization
Parallel computation
GPU programming
Integral evaluation
Mea-field methods
Post Hartree-Fock I: full cofiguration interaction
Post Hartree-Fock II: coupled cluster
Molecular properties
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