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Author  Title  Accn#  Year  Item Type  Claims 
1 
Edward L. Robinson 
Data analysis for scientists and engineers 
026580 
2016 
Book 

2 
Hiroshi Sugita 
Probability and random number: A First Guide to Randomness 
026255 
2014 
Book 

3 
James Gubernatis 
Quantum Monte Carlo methods: Algorithms for Lattice Models 
026078 
2016 
Book 

4 
Benjamin A. Stickler 
Basic concepts in computational physics 
025520 
2014 
Book 

5 
James E. Gentle 
Random number generation and monte carlo methods 
020341 
2005 
Book 

6 
J.M. Hammersley 
Monte Carlo methods 
007994 
1964 
Book 

7 
Malvin H. Kalos 
Monte Carlo methods. Vol. 1: Basics 
003932 
1986 
Book 

8 
Siegmund Brandt 
Data analysis : Statistical and computational methods for scientists and engineers 
016815 
1999 
Book 

9 
D.C. Khandekar 
PathIntegral methods and their applications 
016713 
1993 
Book 

10 
Gennadii A. Mikhailov 
Optimization of weighted Monte Carlo methods 
007569 
1992 
Book 


1.


Title  Data analysis for scientists and engineers 
Author(s)  Edward L. Robinson 
Publication  New Jersey, Princeton University Press, 2016. 
Description  xiii, 393p. 
Abstract Note 
Hardcover
Price:
$75.00 / £62.00
ISBN:
Published:
10/04/2016
Copyright:
2017
Pages:
408
Size:
8 x 10 in.
Illus:
96 line illus. 7 tables.
ebook
Price:
$75.00 / £62.00
ISBN:
Published:
10/04/2016
Copyright:
2017
Pages:
408
Size:
8 x 10 in.
Illus:
96 line illus. 7 tables.
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Reviews 2
Supplementary Materials
Data Analysis for Scientists and Engineers is a modern, graduatelevel text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary.
Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is selfcontained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. 
ISBN,Price  9780691169927 : $ 75.00(HB) 
Classification  519.22/.25

Keyword(s)  1. ANALYSIS OF SEQUENCES
2. BAYESIAN STATISTICS
3. FOURIER ANALYSIS
4. LEAST SQUARES ESTIMATION
5. MONTE CARLO METHODS
6. PROBABILITY

Item Type  Book 
Circulation Data
Accession#  
Call#  Status  Issued To  Return Due On  Physical Location 
026580 

519.22/.25/ROB/026580 
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2.


Title  Probability and random number: A First Guide to Randomness 
Author(s)  Hiroshi Sugita 
Publication  Singapore, World Scientific, 2014. 
Description  xi, 125p 
Abstract Note  This is a book of elementary probability theory that includes a chapter on algorithmic randomness. It rigorously presents definitions and theorems in computation theory, and explains the meanings of the theorems by comparing them with mechanisms of the computer, which is very effective in the current computer age.
Random number topics have not been treated by any books on probability theory, only some books on computation theory. However, the notion of random number is necessary for understanding the essential relation between probability and randomness. The field of probability has changed very much, thus this book will make and leave a big impact even to expert probabilists.
Readers from applied sciences will benefit from this book because it presents a very proper foundation of the Monte Carlo method with practical solutions, keeping the technical level no higher than 1st year university calculus.

ISBN,Price  9789813228252 : 48.00 
Classification  519.21

Keyword(s)  1. COMPUTATION THEORY
2. MONTE CARLO METHODS
3. PROBABILITY THEORY
4. RANDOM NUMBERS
5. RANDOMNESS

Item Type  Book 
Circulation Data
Accession#  
Call#  Status  Issued To  Return Due On  Physical Location 
026255 

519.21/SUG/026255 
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3.


Title  Quantum Monte Carlo methods: Algorithms for Lattice Models 
Author(s)  James Gubernatis;Naoki Kawashima;Philipp Werner 
Publication  Cambridge, Cambridge University Press, 2016. 
Description  xiii, 487p. 
Abstract Note  Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum manybody lattice problems at finite and zero temperature. These algorithms include continuoustime loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuoustime algorithms for quantum impurity models and their use within dynamical meanfield theory, along with algorithms for analytically continuing imaginarytime quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in quantum Monte Carlo techniques. 
ISBN,Price  9781107006423 : 49.99(HB) 
Classification  519.245:530.145

Keyword(s)  1. EBOOK
2. EBOOK  CAMBRIDGE UNIVERSITY PRESS
3. MANYBODY PROBLEM
4. MONTE CARLO METHODS
5. MONTE CARLO SIMULATIONS
6. QUANTUM MONTE CARLO METHODS

Item Type  Book 
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Circulation Data
Accession#  
Call#  Status  Issued To  Return Due On  Physical Location 
026078 

519.245:530.145/UB/026078 
On Shelf 



OB0865 

519.245:530.145/GUB/ 
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