I have uploaded a new version of the module Quantavo

It is a set of procedures (Maple module) for Quantum Optics and Quantum Information calculations in the optical Fock basis)

More can be found in this link

Any questions or feedback welcome.

Would you Try it...

http://www.mechofmat.com/examples/ex01/msetup.zip

Current Trial Serial Number
32FSXUT-BCTLFQ4-QEU3Z95-FE7ZM

Maple includes a useful StringTools:-Entropy procedure which computes the Shannon Entropy, or Information Entropy of a string.  Wikipedia has a nice article describing the measure online at http://en.wikipedia.org/wiki/Shannon_entropy.  I wanted to compute this value over a Matrix so I wrote the following procedure.  Let me know if you have any comments or improvements on the implementation.

We are pleased to announce that the winner of the first quarterly Maple Mentor Award is Robert Israel.  The recipient of the monthly award for January is John Fredsted. Robert and John will receive a prize of their choice to thank them for their involvement with the MaplePrimes community.

Congratulations and keep up the good work!!

To those who are interested:

New version of FourierTrigSeries package was released. This release fixes a bug in ExploreFourierSeriesCoefficients procedure.

FourierTrigSeries package provides new data structure for the representation of trigonometric series and also several procedures to manipulate with trigonometric series and to compute Fourier series.

Visit the homepage and see some examples. Try also the online Fourier series calculator.

Hi everyone,

I need help with solving my integrals

Please see attached file

Download 7055_integrals.pdf
View file details

Using MAPLE V, Release 11, a creep curve has been formulated, which represents the mechanical behavior of metals, polymers, and ceramics, for instance.

The most trivial task in option pricing is to compute values through the Black-Scholes formula: type in the formula, feed Maple with data, done. The same in computational environments like C programs or Excel (assuming a good implementation of the cumulative normal function). Really? And the limiting cases? Or coming close to them? How about small volatility (say below 10% like in FX trading?) or short expiry times (say some weeks)? No problem to back-out volatility from prices to fit models?

First I give an example that using the common formula even Maple quickly runs into numerical errors. That can be avoided by decomposing calls and puts into their so-called intrinsic value (the discounted pay-off) and their premium (that's wht has to be payed beyond that, the actual 'speculation').

Using MAPLE V, Release 10, Elliptic Integrals have been presented. Furthermore, the author proposes approximations based on both FOURIER and TAYLOR series.

Dear Sir:

I am still a novice to use the maple. Please give some advice for the
following code. Expecially, I try to construct the final P(3x3) matrix.
In the for-loop, normalized vectors are generated. Then, those are
converted into a matrix. But, I do not know how to write a code.

restart:
with(LinearAlgebra):
interface(displayprecision=4):
mass:=Matrix([[m[1],0,0],[0,m[2],0],[0,0,m[3]]]);
stif:=Matrix([[k[1]+k[2],-k[1],0],[-k[1],k[1]+k[2],-k[2]],[0,-k[2],k[2]]]);
m[1],m[2],m[3],k[1],k[2],k[3]:=4,4,4,4,4,4;
msri:=simplify(MatrixFunction(mass,sqrt(x),x)^(-1));
mass2:=msri.mass.msri; stif2:=msri.stif.msri;