By Rubin H. Landau

ISBN-10: 0691131376

ISBN-13: 9780691131375

Computational physics is a quickly turning out to be subfield of computational technological know-how, largely simply because desktops can clear up formerly intractable difficulties or simulate normal methods that don't have analytic ideas. your next step past Landau's First direction in medical Computing and a follow-up to Landau and Páez's Computational Physics , this article offers a extensive survey of key subject matters in computational physics for complicated undergraduates and starting graduate scholars, together with new discussions of visualization instruments, wavelet research, molecular dynamics, and computational fluid dynamics. via treating technology, utilized arithmetic, and machine technological know-how jointly, the e-book finds how this information base will be utilized to a much broader diversity of real-world difficulties than computational physics texts often address.

Designed for a one- or two-semester path, A Survey of Computational Physics also will curiosity a person who desires a reference on or useful adventure within the fundamentals of computational physics. The textual content incorporates a CD-ROM with supplementary fabrics, together with Java, Fortran, and C courses; animations; visualizations; colour figures; interactive Java applets; codes for MPI, PVM, and OpenDX; and a PVM tutorial.

  • Accessible to complicated undergraduates
  • Real-world problem-solving process
  • Java codes and applets built-in with textual content
  • Accompanying CD-ROM includes codes, applets, animations, and visualization documents
  • Companion website contains movies of lectures

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Extra info for A Survey of Computational Physics: Introductory Computational Science

Example text

5). Normal numbers have 0 < e < 255, and with them the convention is to assume that the mantissa’s first bit is a 1, so only the fractional part f after the binary point is stored. 5. Note that the values ±INF and NaN are not numbers in the mathematical sense, that is, objects that can be manipulated or used in calculations to take limits and such. Rather, they are signals to the computer and to you that something has gone awry and that the calculation should probably stop until you straighten things out.

7). If x is smaller than 2−128 , an underflow occurs. For overflows, the resulting number xc may end up being a machine-dependent pattern, not a number (NAN), or unpredictable. For underflows, the resulting number xc is usually set to zero, although this can usually be changed via a compiler option. ) Because the only difference between the representations of positive and negative numbers on the computer is the sign bit of one for negative numbers, the same considerations hold for negative numbers.

N O T F O R U S E I N C O U R S E S . 7 The limits of single-precision floating-point numbers and the consequences of exceeding these limits. The hash marks represent the values of numbers that can be stored; storing a number in between these values leads to truncation error. The shaded areas correspond to over- and underflow. 1)]. The corresponding disadvantage is that small numbers (those for which the first string of α values are zeros) have large relative errors. Because in the real world relative errors tend to be more important than absolute ones, integers are used mainly for counting purposes and in special applications (like banking).

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A Survey of Computational Physics: Introductory Computational Science by Rubin H. Landau


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