000 04099nam a22006015i 4500
001 978-3-031-17646-3
003 DE-He213
005 20240730164436.0
007 cr nn 008mamaa
008 230125s2023 sz | s |||| 0|eng d
020 _a9783031176463
_9978-3-031-17646-3
024 7 _a10.1007/978-3-031-17646-3
_2doi
050 4 _aQA76.73.P98
072 7 _aUMX
_2bicssc
072 7 _aCOM051360
_2bisacsh
072 7 _aUMX
_2thema
082 0 4 _a005.133
_223
100 1 _aWang, Jay.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984520
245 1 0 _aIntroduction to Computation in Physical Sciences
_h[electronic resource] :
_bInteractive Computing and Visualization with Python™ /
_cby Jay Wang, Adam Wang.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2023.
300 _aXV, 255 p. 58 illus., 51 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Computation and Analytics,
_x2766-8967
505 0 _aProgramming environments -- Python Tutorial -- Interactive computing and visualization -- Basic algorithms -- Force and motion -- Oscillations and waves -- Modern physics and quantum mechanics -- Statistical and thermal processes -- Complex Systems.
520 _aThis book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds. The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language. Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study. The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.
650 0 _aPython (Computer program language).
_96666
650 0 _aMathematics
_xData processing.
_919904
650 0 _aComputer programming.
_94169
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aMathematical physics.
_911013
650 0 _aInformation visualization.
_914255
650 1 4 _aPython.
_934340
650 2 4 _aComputational Science and Engineering.
_984527
650 2 4 _aProgramming Techniques.
_984530
650 2 4 _aMathematics of Computing.
_931875
650 2 4 _aTheoretical, Mathematical and Computational Physics.
_931560
650 2 4 _aData and Information Visualization.
_933848
700 1 _aWang, Adam.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_984532
710 2 _aSpringerLink (Online service)
_984534
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031176456
776 0 8 _iPrinted edition:
_z9783031176470
776 0 8 _iPrinted edition:
_z9783031176487
830 0 _aSynthesis Lectures on Computation and Analytics,
_x2766-8967
_984535
856 4 0 _uhttps://doi.org/10.1007/978-3-031-17646-3
912 _aZDB-2-SXSC
942 _cEBK
999 _c85679
_d85679