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power series method pade(m,n) off by 1?

asked 2020-11-25 17:46:27 -0600

Daniel Friedan gravatar image

If p = 1+ x + O(x^2) is a power series, then then the method p.pade(0,1) should give p.pade(0,1) = 1/(1-x) but instead it gives an error

ValueError: the precision of the series is not large enough

The documentation says that p should be given up through O(x^(m+n+1)).

Isn't this wrong? Shouldn't it be up through O(x^(m+n)) ?

The Padé approximant P_m(x)/Q_n(x) contains m+n+1 unknown coefficients, so m+n+1 terms should be included in the power series: x^0 ... x^(m+n).

I'm working with a power series that I generate numerically, term by term. I'm using the pade method to estimate the region of analyticity in order to make a conformal transformation that will accelerate the convergence. I want to use pade(n-1,n) when I have 2n terms in the power series. But the pade(m,n) throws the above error. It does not seem possible to get a Padé approximation with the same number of coefficients as in the power series.

thanks for taking a look at this. Daniel Friedan

Daniel Friedan

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Please look at the code and tell us where it is wrong. Open-source, we are.

FrédéricC gravatar imageFrédéricC ( 2020-11-26 01:45:28 -0600 )edit
FrédéricC gravatar imageFrédéricC ( 2020-11-26 02:17:36 -0600 )edit

Thanks for the quick fix. It looks to me that the calculation of pade(m,n) was fine. It was just the error check that was off by 1. So the fix seems good to me.

I've never dared look at the code of sagemath. I came to python late in life. When I write calculations in sagemath, I spend half my time googling basic python questions.

I was a bit surprised to see that pade(m,n) is simply a wrapper around rational_reconstruct(). I had the impression that rational_reconstruct() only worked modulo a prime.

Daniel

Daniel Friedan gravatar imageDaniel Friedan ( 2020-11-26 03:39:31 -0600 )edit

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answered 2020-11-26 02:30:00 -0600

Emmanuel Charpentier gravatar image

This is a problem of convention : is the order of a development the largest explicit power or the degree of the big-Oh term ?

Sage isn't always consistent. Contrast :

sage: R1.<t>=PowerSeriesRing(QQ, default_prec=6)
sage: t.exp()
1 + t + 1/2*t^2 + 1/6*t^3 + 1/24*t^4 + 1/120*t^5 + O(t^6)

with :

sage: exp(x).maxima_methods().taylor(x,0,5)
1/120*x^5 + 1/24*x^4 + 1/6*x^3 + 1/2*x^2 + x + 1

And, by the way,

sage: t.tan().pade(2,2)
-3*t/(t^2 - 3)

whereas

sage: maxima.pade(maxima.taylor(tan(x),x,0,4),2,2).sage()
[-3*x/(x^2 - 3)]
sage: maxima.pade(maxima.taylor(tan(x),x,0,4),3,2).sage()
[-3*x/(x^2 - 3), 1/3*x^3 + x]
sage: maxima.pade(maxima.taylor(tan(x),x,0,4),2,3).sage()
[-3*x/(x^2 - 3)]
sage: maxima.pade(maxima.taylor(tan(x),x,0,5),3,2).sage()
[1/3*(x^3 - 15*x)/(2*x^2 - 5)]
sage: maxima.pade(maxima.taylor(tan(x),x,0,5),2,3).sage()
[]

A look at maxima.pade? shows that the conventions are different...

HTH,

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Asked: 2020-11-25 17:46:27 -0600

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Last updated: Nov 26 '20