# Power Series¶

Sage provides an implementation of dense and sparse power series over any Sage base ring. This is the base class of the implementations of univariate and multivariate power series ring elements in Sage (see also Power Series Methods, Multivariate Power Series).

AUTHORS:

• William Stein
• David Harvey (2006-09-11): added solve_linear_de() method
• Robert Bradshaw (2007-04): sqrt, rmul, lmul, shifting
• Robert Bradshaw (2007-04): Cython version
• Simon King (2012-08): use category and coercion framework, trac ticket #13412

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: TestSuite(R).run()
sage: R([1,2,3])
1 + 2*x + 3*x^2
sage: R([1,2,3], 10)
1 + 2*x + 3*x^2 + O(x^10)
sage: f = 1 + 2*x - 3*x^3 + O(x^4); f
1 + 2*x - 3*x^3 + O(x^4)
sage: f^10
1 + 20*x + 180*x^2 + 930*x^3 + O(x^4)
sage: g = 1/f; g
1 - 2*x + 4*x^2 - 5*x^3 + O(x^4)
sage: g * f
1 + O(x^4)


In Python (as opposed to Sage) create the power series ring and its generator as follows:

sage: R = PowerSeriesRing(ZZ, 'x')
sage: x = R.gen()
sage: parent(x)
Power Series Ring in x over Integer Ring


EXAMPLES:

This example illustrates that coercion for power series rings is consistent with coercion for polynomial rings.

sage: poly_ring1.<gen1> = PolynomialRing(QQ)
sage: poly_ring2.<gen2> = PolynomialRing(QQ)
sage: huge_ring.<x> = PolynomialRing(poly_ring1)


The generator of the first ring gets coerced in as itself, since it is the base ring.

sage: huge_ring(gen1)
gen1


The generator of the second ring gets mapped via the natural map sending one generator to the other.

sage: huge_ring(gen2)
x


With power series the behavior is the same.

sage: power_ring1.<gen1> = PowerSeriesRing(QQ)
sage: power_ring2.<gen2> = PowerSeriesRing(QQ)
sage: huge_power_ring.<x> = PowerSeriesRing(power_ring1)
sage: huge_power_ring(gen1)
gen1
sage: huge_power_ring(gen2)
x

class sage.rings.power_series_ring_element.PowerSeries

A power series. Base class of univariate and multivariate power series. The following methods are available with both types of objects.

O(prec)

Return this series plus $$O(x^\text{prec})$$. Does not change self.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: p = 1 + x^2 + x^10; p
1 + x^2 + x^10
sage: p.O(15)
1 + x^2 + x^10 + O(x^15)
sage: p.O(5)
1 + x^2 + O(x^5)
sage: p.O(-5)
Traceback (most recent call last):
...
ValueError: prec (= -5) must be non-negative

V(n)

If $$f = \sum a_m x^m$$, then this function returns $$\sum a_m x^{nm}$$.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: p = 1 + x^2 + x^10; p
1 + x^2 + x^10
sage: p.V(3)
1 + x^6 + x^30
sage: (p+O(x^20)).V(3)
1 + x^6 + x^30 + O(x^60)

add_bigoh(prec)

Return the power series of precision at most prec got by adding $$O(q^\text{prec})$$ to $$f$$, where $$q$$ is the variable.

EXAMPLES:

sage: R.<A> = RDF[[]]
sage: f = (1+A+O(A^5))^5; f
1.0 + 5.0*A + 10.0*A^2 + 10.0*A^3 + 5.0*A^4 + O(A^5)
1.0 + 5.0*A + 10.0*A^2 + O(A^3)
1.0 + 5.0*A + 10.0*A^2 + 10.0*A^3 + 5.0*A^4 + O(A^5)

base_extend(R)

Return a copy of this power series but with coefficients in R.

The following coercion uses base_extend implicitly:

sage: R.<t> = ZZ[['t']]
sage: (t - t^2) * Mod(1, 3)
t + 2*t^2

base_ring()

Return the base ring that this power series is defined over.

EXAMPLES:

sage: R.<t> = GF(49,'alpha')[[]]
sage: (t^2 + O(t^3)).base_ring()
Finite Field in alpha of size 7^2

change_ring(R)

Change if possible the coefficients of self to lie in R.

EXAMPLES:

sage: R.<T> = QQ[[]]; R
Power Series Ring in T over Rational Field
sage: f = 1 - 1/2*T + 1/3*T^2 + O(T^3)
sage: f.base_extend(GF(5))
Traceback (most recent call last):
...
TypeError: no base extension defined
sage: f.change_ring(GF(5))
1 + 2*T + 2*T^2 + O(T^3)
sage: f.change_ring(GF(3))
Traceback (most recent call last):
...
ZeroDivisionError: inverse of Mod(0, 3) does not exist


We can only change the ring if there is a __call__ coercion defined. The following succeeds because ZZ(K(4)) is defined.

sage: K.<a> = NumberField(cyclotomic_polynomial(3), 'a')
sage: R.<t> = K[['t']]
sage: (4*t).change_ring(ZZ)
4*t


This does not succeed because ZZ(K(a+1)) is not defined.

sage: K.<a> = NumberField(cyclotomic_polynomial(3), 'a')
sage: R.<t> = K[['t']]
sage: ((a+1)*t).change_ring(ZZ)
Traceback (most recent call last):
...
TypeError: Unable to coerce a + 1 to an integer

coefficients()

Return the nonzero coefficients of self.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)
sage: f = t + t^2 - 10/3*t^3
sage: f.coefficients()
[1, 1, -10/3]

common_prec(f)

Return minimum precision of $$f$$ and self.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)

sage: f = t + t^2 + O(t^3)
sage: g = t + t^3 + t^4 + O(t^4)
sage: f.common_prec(g)
3
sage: g.common_prec(f)
3

sage: f = t + t^2 + O(t^3)
sage: g = t^2
sage: f.common_prec(g)
3
sage: g.common_prec(f)
3

sage: f = t + t^2
sage: f = t^2
sage: f.common_prec(g)
+Infinity

cos(prec='infinity')

Apply cos to the formal power series.

INPUT:

• prec – Integer or infinity. The degree to truncate the result to.

OUTPUT:

A new power series.

EXAMPLES:

For one variable:

sage: t = PowerSeriesRing(QQ, 't').gen()
sage: f = (t + t**2).O(4)
sage: cos(f)
1 - 1/2*t^2 - t^3 + O(t^4)


For several variables:

sage: T.<a,b> = PowerSeriesRing(ZZ,2)
sage: f = a + b + a*b + T.O(3)
sage: cos(f)
1 - 1/2*a^2 - a*b - 1/2*b^2 + O(a, b)^3
sage: f.cos()
1 - 1/2*a^2 - a*b - 1/2*b^2 + O(a, b)^3
sage: f.cos(prec=2)
1 + O(a, b)^2


If the power series has a non-zero constant coefficient $$c$$, one raises an error:

sage: g = 2+f
sage: cos(g)
Traceback (most recent call last):
...
ValueError: can only apply cos to formal power series with zero constant term


If no precision is specified, the default precision is used:

sage: T.default_prec()
12
sage: cos(a)
1 - 1/2*a^2 + 1/24*a^4 - 1/720*a^6 + 1/40320*a^8 - 1/3628800*a^10 + O(a, b)^12
sage: a.cos(prec=5)
1 - 1/2*a^2 + 1/24*a^4 + O(a, b)^5
sage: cos(a + T.O(5))
1 - 1/2*a^2 + 1/24*a^4 + O(a, b)^5

degree()

Return the degree of this power series, which is by definition the degree of the underlying polynomial.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ, sparse=True)
sage: f = t^100000 + O(t^10000000)
sage: f.degree()
100000

derivative(*args)

The formal derivative of this power series, with respect to variables supplied in args.

Multiple variables and iteration counts may be supplied; see documentation for the global derivative() function for more details.

_derivative()

EXAMPLES:

sage: R.<x> = PowerSeriesRing(QQ)
sage: g = -x + x^2/2 - x^4 + O(x^6)
sage: g.derivative()
-1 + x - 4*x^3 + O(x^5)
sage: g.derivative(x)
-1 + x - 4*x^3 + O(x^5)
sage: g.derivative(x, x)
1 - 12*x^2 + O(x^4)
sage: g.derivative(x, 2)
1 - 12*x^2 + O(x^4)

egf_to_ogf()

Returns the ordinary generating function power series, assuming self is an exponential generating function power series.

This function is known as serlaplace in PARI/GP.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)
sage: f = t + t^2/factorial(2) + 2*t^3/factorial(3)
sage: f.egf_to_ogf()
t + t^2 + 2*t^3

exp(prec=None)

Return exp of this power series to the indicated precision.

INPUT:

• prec - integer; default is self.parent().default_prec

ALGORITHM: See solve_linear_de().

Note

AUTHORS:

• David Harvey (2006-09-08): rewrote to use simplest possible “lazy” algorithm.
• David Harvey (2006-09-10): rewrote to use divide-and-conquer strategy.
• David Harvey (2006-09-11): factored functionality out to solve_linear_de().
• Sourav Sen Gupta, David Harvey (2008-11): handle constant term

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ, default_prec=10)


Check that $$\exp(t)$$ is, well, $$\exp(t)$$:

sage: (t + O(t^10)).exp()
1 + t + 1/2*t^2 + 1/6*t^3 + 1/24*t^4 + 1/120*t^5 + 1/720*t^6 + 1/5040*t^7 + 1/40320*t^8 + 1/362880*t^9 + O(t^10)


Check that $$\exp(\log(1+t))$$ is $$1+t$$:

sage: (sum([-(-t)^n/n for n in range(1, 10)]) + O(t^10)).exp()
1 + t + O(t^10)


Check that $$\exp(2t + t^2 - t^5)$$ is whatever it is:

sage: (2*t + t^2 - t^5 + O(t^10)).exp()
1 + 2*t + 3*t^2 + 10/3*t^3 + 19/6*t^4 + 8/5*t^5 - 7/90*t^6 - 538/315*t^7 - 425/168*t^8 - 30629/11340*t^9 + O(t^10)


Check requesting lower precision:

sage: (t + t^2 - t^5 + O(t^10)).exp(5)
1 + t + 3/2*t^2 + 7/6*t^3 + 25/24*t^4 + O(t^5)


Can’t get more precision than the input:

sage: (t + t^2 + O(t^3)).exp(10)
1 + t + 3/2*t^2 + O(t^3)


Check some boundary cases:

sage: (t + O(t^2)).exp(1)
1 + O(t)
sage: (t + O(t^2)).exp(0)
O(t^0)


Handle nonzero constant term (fixes trac ticket #4477):

sage: R.<x> = PowerSeriesRing(RR)
sage: (1 + x + x^2 + O(x^3)).exp()
2.71828182845905 + 2.71828182845905*x + 4.07742274268857*x^2 + O(x^3)

sage: R.<x> = PowerSeriesRing(ZZ)
sage: (1 + x + O(x^2)).exp()
Traceback (most recent call last):
...
ArithmeticError: exponential of constant term does not belong to coefficient ring (consider working in a larger ring)

sage: R.<x> = PowerSeriesRing(GF(5))
sage: (1 + x + O(x^2)).exp()
Traceback (most recent call last):
...
ArithmeticError: constant term of power series does not support exponentiation

exponents()

Return the exponents appearing in self with nonzero coefficients.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)
sage: f = t + t^2 - 10/3*t^3
sage: f.exponents()
[1, 2, 3]

inverse()

Return the inverse of self, i.e., self^(-1).

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ, sparse=True)
sage: t.inverse()
t^-1
sage: type(_)
<type 'sage.rings.laurent_series_ring_element.LaurentSeries'>
sage: (1-t).inverse()
1 + t + t^2 + t^3 + t^4 + t^5 + t^6 + t^7 + t^8 + ...

is_dense()

EXAMPLES:

sage: R.<t> = PowerSeriesRing(ZZ)
sage: t.is_dense()
True
sage: R.<t> = PowerSeriesRing(ZZ, sparse=True)
sage: t.is_dense()
False

is_gen()

Return True if this is the generator (the variable) of the power series ring.

EXAMPLES:

sage: R.<t> = QQ[[]]
sage: t.is_gen()
True
sage: (1 + 2*t).is_gen()
False


Note that this only returns True on the actual generator, not on something that happens to be equal to it.

sage: (1*t).is_gen()
False
sage: 1*t == t
True

is_monomial()

Return True if this element is a monomial. That is, if self is $$x^n$$ for some non-negative integer $$n$$.

EXAMPLES:

sage: k.<z> = PowerSeriesRing(QQ, 'z')
sage: z.is_monomial()
True
sage: k(1).is_monomial()
True
sage: (z+1).is_monomial()
False
sage: (z^2909).is_monomial()
True
sage: (3*z^2909).is_monomial()
False

is_sparse()

EXAMPLES:

sage: R.<t> = PowerSeriesRing(ZZ)
sage: t.is_sparse()
False
sage: R.<t> = PowerSeriesRing(ZZ, sparse=True)
sage: t.is_sparse()
True

is_square()

Return True if this function has a square root in this ring, e.g., there is an element $$y$$ in self.parent() such that $$y^2$$ equals self.

ALGORITHM: If the base ring is a field, this is true whenever the power series has even valuation and the leading coefficient is a perfect square.

For an integral domain, it attempts the square root in the fraction field and tests whether or not the result lies in the original ring.

EXAMPLES:

sage: K.<t> = PowerSeriesRing(QQ, 't', 5)
sage: (1+t).is_square()
True
sage: (2+t).is_square()
False
sage: (2+t.change_ring(RR)).is_square()
True
sage: t.is_square()
False
sage: K.<t> = PowerSeriesRing(ZZ, 't', 5)
sage: (1+t).is_square()
False
sage: f = (1+t)^100
sage: f.is_square()
True

is_unit()

Return True if this power series is invertible.

A power series is invertible precisely when the constant term is invertible.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(ZZ)
sage: (-1 + t - t^5).is_unit()
True
sage: (3 + t - t^5).is_unit()
False


AUTHORS:

• David Harvey (2006-09-03)
laurent_series()

Return the Laurent series associated to this power series, i.e., this series considered as a Laurent series.

EXAMPLES:

sage: k.<w> = QQ[[]]
sage: f = 1+17*w+15*w^3+O(w^5)
sage: parent(f)
Power Series Ring in w over Rational Field
sage: g = f.laurent_series(); g
1 + 17*w + 15*w^3 + O(w^5)

lift_to_precision(absprec=None)

Return a congruent power series with absolute precision at least absprec.

INPUT:

• absprec – an integer or None (default: None), the absolute precision of the result. If None, lifts to an exact element.

EXAMPLES:

sage: A.<t> = PowerSeriesRing(GF(5))
sage: x = t + t^2 + O(t^5)
sage: x.lift_to_precision(10)
t + t^2 + O(t^10)
sage: x.lift_to_precision()
t + t^2

list()

See this method in derived classes:

Implementations MUST override this in the derived class.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: PowerSeries.list(1+x^2)
Traceback (most recent call last):
...
NotImplementedError

log(prec=None)

Return log of this power series to the indicated precision.

This works only if the constant term of the power series is 1 or the base ring can take the logarithm of the constant coefficient.

INPUT:

• prec – integer; default is self.parent().default_prec()

ALGORITHM: See solve_linear_de().

Warning

Screwy things can happen if the coefficient ring is not a field of characteristic zero. See solve_linear_de().

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ, default_prec=10)
sage: (1 + t + O(t^10)).log()
t - 1/2*t^2 + 1/3*t^3 - 1/4*t^4 + 1/5*t^5 - 1/6*t^6 + 1/7*t^7 - 1/8*t^8 + 1/9*t^9 + O(t^10)

sage: t.exp().log()
t + O(t^10)

sage: (1+t).log().exp()
1 + t + O(t^10)

sage: (-1 + t + O(t^10)).log()
Traceback (most recent call last):
...
ArithmeticError: constant term of power series is not 1

sage: R.<t> = PowerSeriesRing(RR)
sage: (2+t).log().exp()
2.00000000000000 + 1.00000000000000*t + O(t^20)

map_coefficients(f, new_base_ring=None)

Returns the series obtained by applying f to the non-zero coefficients of self.

If f is a sage.categories.map.Map, then the resulting series will be defined over the codomain of f. Otherwise, the resulting polynomial will be over the same ring as self. Set new_base_ring to override this behaviour.

INPUT:

• f – a callable that will be applied to the coefficients of self.
• new_base_ring (optional) – if given, the resulting polynomial will be defined over this ring.

EXAMPLES:

sage: R.<x> = SR[[]]
sage: f = (1+I)*x^2 + 3*x - I
sage: f.map_coefficients(lambda z: z.conjugate())
I + 3*x + (-I + 1)*x^2
sage: R.<x> = ZZ[[]]
sage: f = x^2 + 2
sage: f.map_coefficients(lambda a: a + 42)
44 + 43*x^2


Examples with different base ring:

sage: R.<x> = ZZ[[]]
sage: k = GF(2)
sage: residue = lambda x: k(x)
sage: f = 4*x^2+x+3
sage: g = f.map_coefficients(residue); g
1 + x
sage: g.parent()
Power Series Ring in x over Integer Ring
sage: g = f.map_coefficients(residue, new_base_ring = k); g
1 + x
sage: g.parent()
Power Series Ring in x over Finite Field of size 2
sage: residue = k.coerce_map_from(ZZ)
sage: g = f.map_coefficients(residue); g
1 + x
sage: g.parent()
Power Series Ring in x over Finite Field of size 2


Tests other implementations:

sage: R.<q> = PowerSeriesRing(GF(11), implementation='pari')
sage: f = q - q^3 + O(q^10)
sage: f.map_coefficients(lambda c: c - 2)
10*q + 8*q^3 + O(q^10)

nth_root(n, prec=None)

Return the n-th root of this power series.

INPUT:

• n – integer
• prec – integer (optional) - precision of the result. Though, if this series has finite precision, then the result can not have larger precision.

EXAMPLES:

sage: R.<x> = QQ[[]]
sage: (1+x).nth_root(5)
1 + 1/5*x - 2/25*x^2 + ... + 12039376311816/2384185791015625*x^19 + O(x^20)

sage: (1 + x + O(x^5)).nth_root(5)
1 + 1/5*x - 2/25*x^2 + 6/125*x^3 - 21/625*x^4 + O(x^5)


Check that the results are consistent with taking log and exponential:

sage: R.<x> = PowerSeriesRing(QQ, default_prec=100)
sage: p = (1 + 2*x - x^4)**200
sage: p1 = p.nth_root(1000, prec=100)
sage: p2 = (p.log()/1000).exp()
sage: p1.prec() == p2.prec() == 100
True
sage: p1.polynomial() == p2.polynomial()
True


Positive characteristic:

sage: R.<u> = GF(3)[[]]
sage: p = 1 + 2 * u^2
sage: p.nth_root(4)
1 + 2*u^2 + u^6 + 2*u^8 + u^12 + 2*u^14 + O(u^20)
sage: p.nth_root(4)**4
1 + 2*u^2 + O(u^20)

ogf_to_egf()

Returns the exponential generating function power series, assuming self is an ordinary generating function power series.

This can also be computed as serconvol(f,exp(t)) in PARI/GP.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)
sage: f = t + t^2 + 2*t^3
sage: f.ogf_to_egf()
t + 1/2*t^2 + 1/3*t^3

padded_list(n=None)

Return a list of coefficients of self up to (but not including) $$q^n$$.

Includes 0’s in the list on the right so that the list has length $$n$$.

INPUT:

• n - (optional) an integer that is at least 0. If n is not given, it will be taken to be the precision of self, unless this is +Infinity, in which case we just return self.list().

EXAMPLES:

sage: R.<q> = PowerSeriesRing(QQ)
sage: f = 1 - 17*q + 13*q^2 + 10*q^4 + O(q^7)
sage: f.list()
[1, -17, 13, 0, 10]
[1, -17, 13, 0, 10, 0, 0]
[1, -17, 13, 0, 10, 0, 0, 0, 0, 0]
[1, -17, 13]
[1, -17, 13, 0, 10, 0, 0]
sage: g = 1 - 17*q + 13*q^2 + 10*q^4
sage: g.list()
[1, -17, 13, 0, 10]
[1, -17, 13, 0, 10]
[1, -17, 13, 0, 10, 0, 0, 0, 0, 0]

polynomial()

See this method in derived classes:

Implementations MUST override this in the derived class.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: PowerSeries.polynomial(1+x^2)
Traceback (most recent call last):
...
NotImplementedError

prec()

The precision of $$...+O(x^r)$$ is by definition $$r$$.

EXAMPLES:

sage: R.<t> = ZZ[[]]
sage: (t^2 + O(t^3)).prec()
3
sage: (1 - t^2 + O(t^100)).prec()
100

precision_absolute()

Return the absolute precision of this series.

By definition, the absolute precision of $$...+O(x^r)$$ is $$r$$.

EXAMPLES:

sage: R.<t> = ZZ[[]]
sage: (t^2 + O(t^3)).precision_absolute()
3
sage: (1 - t^2 + O(t^100)).precision_absolute()
100

precision_relative()

Return the relative precision of this series, that is the difference between its absolute precision and its valuation.

By convention, the relative precision of $$0$$ (or $$O(x^r)$$ for any $$r$$) is $$0$$.

EXAMPLES:

sage: R.<t> = ZZ[[]]
sage: (t^2 + O(t^3)).precision_relative()
1
sage: (1 - t^2 + O(t^100)).precision_relative()
100
sage: O(t^4).precision_relative()
0

shift(n)

Return this power series multiplied by the power $$t^n$$. If $$n$$ is negative, terms below $$t^n$$ will be discarded. Does not change this power series.

Note

Despite the fact that higher order terms are printed to the right in a power series, right shifting decreases the powers of $$t$$, while left shifting increases them. This is to be consistent with polynomials, integers, etc.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ['y'], 't', 5)
sage: f = ~(1+t); f
1 - t + t^2 - t^3 + t^4 + O(t^5)
sage: f.shift(3)
t^3 - t^4 + t^5 - t^6 + t^7 + O(t^8)
sage: f >> 2
1 - t + t^2 + O(t^3)
sage: f << 10
t^10 - t^11 + t^12 - t^13 + t^14 + O(t^15)
sage: t << 29
t^30


AUTHORS:

sin(prec='infinity')

Apply sin to the formal power series.

INPUT:

• prec – Integer or infinity. The degree to truncate the result to.

OUTPUT:

A new power series.

EXAMPLES:

For one variable:

sage: t = PowerSeriesRing(QQ, 't').gen()
sage: f = (t + t**2).O(4)
sage: sin(f)
t + t^2 - 1/6*t^3 + O(t^4)


For several variables:

sage: T.<a,b> = PowerSeriesRing(ZZ,2)
sage: f = a + b + a*b + T.O(3)
sage: sin(f)
a + b + a*b + O(a, b)^3
sage: f.sin()
a + b + a*b + O(a, b)^3
sage: f.sin(prec=2)
a + b + O(a, b)^2


If the power series has a non-zero constant coefficient $$c$$, one raises an error:

sage: g = 2+f
sage: sin(g)
Traceback (most recent call last):
...
ValueError: can only apply sin to formal power series with zero constant term


If no precision is specified, the default precision is used:

sage: T.default_prec()
12
sage: sin(a)
a - 1/6*a^3 + 1/120*a^5 - 1/5040*a^7 + 1/362880*a^9 - 1/39916800*a^11 + O(a, b)^12
sage: a.sin(prec=5)
a - 1/6*a^3 + O(a, b)^5
sage: sin(a + T.O(5))
a - 1/6*a^3 + O(a, b)^5

solve_linear_de(prec='infinity', b=None, f0=None)

Obtain a power series solution to an inhomogeneous linear differential equation of the form:

$f'(t) = a(t) f(t) + b(t).$

INPUT:

• self - the power series $$a(t)$$
• b - the power series $$b(t)$$ (default is zero)
• f0 - the constant term of $$f$$ (“initial condition”) (default is 1)
• prec - desired precision of result (this will be reduced if either a or b have less precision available)

OUTPUT: the power series $$f$$, to indicated precision

ALGORITHM: A divide-and-conquer strategy; see the source code. Running time is approximately $$M(n) \log n$$, where $$M(n)$$ is the time required for a polynomial multiplication of length $$n$$ over the coefficient ring. (If you’re working over something like $$\QQ$$, running time analysis can be a little complicated because the coefficients tend to explode.)

Note

• If the coefficient ring is a field of characteristic zero, then the solution will exist and is unique.
• For other coefficient rings, things are more complicated. A solution may not exist, and if it does it may not be unique. Generally, by the time the nth term has been computed, the algorithm will have attempted divisions by $$n!$$ in the coefficient ring. So if your coefficient ring has enough ‘precision’, and if your coefficient ring can perform divisions even when the answer is not unique, and if you know in advance that a solution exists, then this function will find a solution (otherwise it will probably crash).

AUTHORS:

• David Harvey (2006-09-11): factored functionality out from exp() function, cleaned up precision tests a bit

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ, default_prec=10)

sage: a = 2 - 3*t + 4*t^2 + O(t^10)
sage: b = 3 - 4*t^2 + O(t^7)
sage: f = a.solve_linear_de(prec=5, b=b, f0=3/5)
sage: f
3/5 + 21/5*t + 33/10*t^2 - 38/15*t^3 + 11/24*t^4 + O(t^5)
sage: f.derivative() - a*f - b
O(t^4)

sage: a = 2 - 3*t + 4*t^2
sage: b = b = 3 - 4*t^2
sage: f = a.solve_linear_de(b=b, f0=3/5)
Traceback (most recent call last):
...
ValueError: cannot solve differential equation to infinite precision

sage: a.solve_linear_de(prec=5, b=b, f0=3/5)
3/5 + 21/5*t + 33/10*t^2 - 38/15*t^3 + 11/24*t^4 + O(t^5)

sqrt(prec=None, extend=False, all=False, name=None)

Return a square root of self.

INPUT:

• prec - integer (default: None): if not None and the series has infinite precision, truncates series at precision prec.
• extend - bool (default: False); if True, return a square root in an extension ring, if necessary. Otherwise, raise a ValueError if the square root is not in the base power series ring. For example, if extend is True the square root of a power series with odd degree leading coefficient is defined as an element of a formal extension ring.
• name - string; if extend is True, you must also specify the print name of the formal square root.
• all - bool (default: False); if True, return all square roots of self, instead of just one.

ALGORITHM: Newton’s method

$x_{i+1} = \frac{1}{2}( x_i + \mathrm{self}/x_i )$

EXAMPLES:

sage: K.<t> = PowerSeriesRing(QQ, 't', 5)
sage: sqrt(t^2)
t
sage: sqrt(1+t)
1 + 1/2*t - 1/8*t^2 + 1/16*t^3 - 5/128*t^4 + O(t^5)
sage: sqrt(4+t)
2 + 1/4*t - 1/64*t^2 + 1/512*t^3 - 5/16384*t^4 + O(t^5)
sage: u = sqrt(2+t, prec=2, extend=True, name = 'alpha'); u
alpha
sage: u^2
2 + t
sage: u.parent()
Univariate Quotient Polynomial Ring in alpha over Power Series Ring in t over Rational Field with modulus x^2 - 2 - t
sage: K.<t> = PowerSeriesRing(QQ, 't', 50)
sage: sqrt(1+2*t+t^2)
1 + t
sage: sqrt(t^2 +2*t^4 + t^6)
t + t^3
sage: sqrt(1 + t + t^2 + 7*t^3)^2
1 + t + t^2 + 7*t^3 + O(t^50)
sage: sqrt(K(0))
0
sage: sqrt(t^2)
t

sage: K.<t> = PowerSeriesRing(CDF, 5)
sage: v = sqrt(-1 + t + t^3, all=True); v
[1.0*I - 0.5*I*t - 0.125*I*t^2 - 0.5625*I*t^3 - 0.2890625*I*t^4 + O(t^5),
-1.0*I + 0.5*I*t + 0.125*I*t^2 + 0.5625*I*t^3 + 0.2890625*I*t^4 + O(t^5)]
sage: [a^2 for a in v]
[-1.0 + 1.0*t + 0.0*t^2 + 1.0*t^3 + O(t^5), -1.0 + 1.0*t + 0.0*t^2 + 1.0*t^3 + O(t^5)]


A formal square root:

sage: K.<t> = PowerSeriesRing(QQ, 5)
sage: f = 2*t + t^3 + O(t^4)
sage: s = f.sqrt(extend=True, name='sqrtf'); s
sqrtf
sage: s^2
2*t + t^3 + O(t^4)
sage: parent(s)
Univariate Quotient Polynomial Ring in sqrtf over Power Series Ring in t over Rational Field with modulus x^2 - 2*t - t^3 + O(t^4)


AUTHORS:

• William Stein
square_root()

Return the square root of self in this ring. If this cannot be done then an error will be raised.

This function succeeds if and only if self. is_square()

EXAMPLES:

sage: K.<t> = PowerSeriesRing(QQ, 't', 5)
sage: (1+t).square_root()
1 + 1/2*t - 1/8*t^2 + 1/16*t^3 - 5/128*t^4 + O(t^5)
sage: (2+t).square_root()
Traceback (most recent call last):
...
ValueError: Square root does not live in this ring.
sage: (2+t.change_ring(RR)).square_root()
1.41421356237309 + 0.353553390593274*t - 0.0441941738241592*t^2 + 0.0110485434560398*t^3 - 0.00345266983001244*t^4 + O(t^5)
sage: t.square_root()
Traceback (most recent call last):
...
ValueError: Square root not defined for power series of odd valuation.
sage: K.<t> = PowerSeriesRing(ZZ, 't', 5)
sage: f = (1+t)^20
sage: f.square_root()
1 + 10*t + 45*t^2 + 120*t^3 + 210*t^4 + O(t^5)
sage: f = 1+t
sage: f.square_root()
Traceback (most recent call last):
...
ValueError: Square root does not live in this ring.


AUTHORS:

tan(prec='infinity')

Apply tan to the formal power series.

INPUT:

• prec – Integer or infinity. The degree to truncate the result to.

OUTPUT:

A new power series.

EXAMPLES:

For one variable:

sage: t = PowerSeriesRing(QQ, 't').gen()
sage: f = (t + t**2).O(4)
sage: tan(f)
t + t^2 + 1/3*t^3 + O(t^4)


For several variables:

sage: T.<a,b> = PowerSeriesRing(ZZ,2)
sage: f = a + b + a*b + T.O(3)
sage: tan(f)
a + b + a*b + O(a, b)^3
sage: f.tan()
a + b + a*b + O(a, b)^3
sage: f.tan(prec=2)
a + b + O(a, b)^2


If the power series has a non-zero constant coefficient $$c$$, one raises an error:

sage: g = 2+f
sage: tan(g)
Traceback (most recent call last):
...
ValueError: can only apply tan to formal power series with zero constant term


If no precision is specified, the default precision is used:

sage: T.default_prec()
12
sage: tan(a)
a + 1/3*a^3 + 2/15*a^5 + 17/315*a^7 + 62/2835*a^9 + 1382/155925*a^11 + O(a, b)^12
sage: a.tan(prec=5)
a + 1/3*a^3 + O(a, b)^5
sage: tan(a + T.O(5))
a + 1/3*a^3 + O(a, b)^5

truncate(prec='infinity')

The polynomial obtained from power series by truncation.

EXAMPLES:

sage: R.<I> = GF(2)[[]]
sage: f = 1/(1+I+O(I^8)); f
1 + I + I^2 + I^3 + I^4 + I^5 + I^6 + I^7 + O(I^8)
sage: f.truncate(5)
I^4 + I^3 + I^2 + I + 1

valuation()

Return the valuation of this power series.

This is equal to the valuation of the underlying polynomial.

EXAMPLES:

Sparse examples:

sage: R.<t> = PowerSeriesRing(QQ, sparse=True)
sage: f = t^100000 + O(t^10000000)
sage: f.valuation()
100000
sage: R(0).valuation()
+Infinity


Dense examples:

sage: R.<t> = PowerSeriesRing(ZZ)
sage: f = 17*t^100 +O(t^110)
sage: f.valuation()
100
sage: t.valuation()
1

valuation_zero_part()

Factor self as $$q^n \cdot (a_0 + a_1 q + \cdots)$$ with $$a_0$$ nonzero. Then this function returns $$a_0 + a_1 q + \cdots$$ .

Note

This valuation zero part need not be a unit if, e.g., $$a_0$$ is not invertible in the base ring.

EXAMPLES:

sage: R.<t> = PowerSeriesRing(QQ)
sage: ((1/3)*t^5*(17-2/3*t^3)).valuation_zero_part()
17/3 - 2/9*t^3


In this example the valuation 0 part is not a unit:

sage: R.<t> = PowerSeriesRing(ZZ, sparse=True)
sage: u = (-2*t^5*(17-t^3)).valuation_zero_part(); u
-34 + 2*t^3
sage: u.is_unit()
False
sage: u.valuation()
0

variable()

Return a string with the name of the variable of this power series.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(Rationals())
sage: f = x^2 + 3*x^4 + O(x^7)
sage: f.variable()
'x'


AUTHORS:

• David Harvey (2006-08-08)
sage.rings.power_series_ring_element.is_PowerSeries(x)

Return True if x is an instance of a univariate or multivariate power series.

EXAMPLES:

sage: R.<x> = PowerSeriesRing(ZZ)
sage: from sage.rings.power_series_ring_element import is_PowerSeries
sage: is_PowerSeries(1+x^2)
True
sage: is_PowerSeries(x-x)
True
sage: is_PowerSeries(0)
False
sage: var('x')
x
sage: is_PowerSeries(1+x^2)
False

sage.rings.power_series_ring_element.make_element_from_parent_v0(parent, *args)
sage.rings.power_series_ring_element.make_powerseries_poly_v0(parent, f, prec, is_gen)