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As usual happens in symbolic calculations - small change of input parameters leads to drammatical change in consuptions. I had talk about many other partial issues in  this forum. Many other issues i just tried myself without any success (for example try convert(exp(x)+x, FormalPowerSeries)) and now i must take decision: wheather or not to continue work with maple at all. It's totally clear for me that others (like Wolfram mathematica) not much better. Only one other...

I have a solution containing many exponentail terms, some of which are in the denominators of rational terms. I would like to be able to have the solution given to me in a manner where there are no exponentials in denominators but only in the numerators. The simplify command in maple does it, however for the shear number of terms (just shy of 400,000 terms and maple saying it's million plus) i am looking at, that particular command is just taking too long (15 hours!). Is there...

In Maple boolean evaluation returns the values 'true' or 'false'.

Is there any canonical way of getting evalb to produce values in {0,1}? This is of some use when testing conjectures on  hudge lists of items...

Of course: you can always define a script like

###########################
evalbb:=proc(PP)
if evalb(PP)='true' then eps:=1:
else eps:=0:
fi:
eps;
end:
###########################

but I think there should be...

Answering to that question, I posted several procedures finding minimal polynomials for the elements of finite fields. The best one was the following,

alias(a=RootOf(T^100+T^97+T^96+T^93+T^91+T^89+T^87+T^86+T^82+T^81+T^71+T^70+T^67+T^61+
T^60+T^57+T^54+T^53+T^52+T^49+T^48+T^45+T^44+T^42+T^39+T^36+T^33+T^32+T^31+T^29+T^28+T^27+
T^26+T^24+T^23+T^22+T^18+T^17+T^16+T^14+T^13+T^12+T^10+T^8+T^7+T^6+T^3+T+1)):

F:=GF(2,100,op(a)):
z:=F:-input(2):

MinPolyGF:=proc(x,y:=_X)
local A, i;
A:=Matrix(100,...

restart:
with(LinearAlgebra):
with(ArrayTools):
with(Statistics):
randomize():
with(plots):
with(combinat):

n := 100:
nstock := 7:
corr := .8:

R := Matrix(nstock, nstock, proc (i, j) options operator, arrow; `if`(i = j, 1, corr) end proc):
CD := Matrix(LUDecomposition(evalf(R), 'method' = 'Cholesky'), datatype = float[8]):

ev := [seq((1/5)*(rand(-3 .. 4))(), i = 1 .. nstock)]:
st := [seq((rand(1 .. 2))(), i = 1 .. nstock)]: