# A Survey of Computational Physics by Rubin H. Landau

By Rubin H. Landau

Computational physics is a quickly turning out to be subfield of computational technological know-how, largely simply because pcs can remedy formerly intractable difficulties or simulate common tactics that don't have analytic strategies. the next move past Landau's First direction in medical Computing and a follow-up to Landau and Páez's Computational Physics , this article provides a huge survey of key themes in computational physics for complex undergraduates and starting graduate scholars, together with new discussions of visualization instruments, wavelet research, molecular dynamics, and computational fluid dynamics. via treating technological know-how, utilized arithmetic, and computing device technology jointly, the publication finds how this information base could be utilized to a much broader variety of real-world difficulties than computational physics texts usually address.

Designed for a one- or two-semester direction, A Survey of Computational Physics also will curiosity someone who desires a reference on or sensible event 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 complex undergraduates
- Real-world problem-solving procedure
- Java codes and applets built-in with textual content
- Accompanying CD-ROM comprises codes, applets, animations, and visualization records
- Companion site comprises video clips of lectures

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**Extra info for A Survey of Computational Physics**

**Example text**

In fact, in the past each computer operating system and each computer language contained its own standards C O P Y R I G H T 2 0 0 8 , P R I N C ETO N U N I V E R S ITY P R E S S E VA L U AT I O N C O P Y O N LY. N O T F O R U S E I N C O U R S E S . 7976931348623157 × 10+308 for ﬂoating-point numbers. Different standards meant that the same program running correctly on different computers could give different results. Even though the results usually were only slightly different, the user could never be sure if the lack of reproducibility of a test case was due to the particular computer being used or to an error in the program’s implementation.

In addition, when computers and software adhere to this standard, and most do now, you are guaranteed that your program will produce identical results on different computers. However, because the IEEE standard may not produce the most efﬁcient code or the highest accuracy for a particular computer, sometimes you may have to invoke compiler options to demand that the IEEE standard be strictly followed for your test cases. After you know that the code is okay, you may want to run with whatever gives the greatest speed and precision.

2): s Bit position 31 e 30 f 23 22 0 The sign bit s is in bit position 31, the biased exponent e is in bits 30–23, and the fractional part of the mantissa f is in bits 22–0. Since 8 bits are used to store the exponent e and since 28 = 256, e has the range 0 ≤ e ≤ 255. The values e = 0 and 255 are special cases. 4, for singles has the range −126 ≤ p ≤ 127. The mantissa f for singles is stored as the 23 bits in positions 22–0. f × 2e−127 . Subnormal numbers have e = 0, f = 0. f × 2e−126 . f used for subnormal numbers.