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# Multivariate Power Series Rings

Construct a multivariate power series ring (in finitely many variables) over a given (commutative) base ring.

EXAMPLES:

Construct rings and elements:

    sage: R.<t,u,v> = PowerSeriesRing(QQ); R
    Multivariate Power Series Ring in t, u, v over Rational Field
    sage: TestSuite(R).run()
    sage: p = -t + 1/2*t^3*u - 1/4*t^4*u + 2/3*v^5 + R.O(6); p
    -t + 1/2*t^3*u - 1/4*t^4*u + 2/3*v^5 + O(t, u, v)^6
    sage: p in R
    True

    sage: g = 1 + v + 3*u*t^2 - 2*v^2*t^2; g
    1 + v + 3*t^2*u - 2*t^2*v^2
    sage: g in R
    True

Add big O as with single variable power series:

    sage: g.add_bigoh(3)
    1 + v + O(t, u, v)^3
    sage: g = g.O(5); g
    1 + v + 3*t^2*u - 2*t^2*v^2 + O(t, u, v)^5

Sage keeps track of total-degree precision:

    sage: f = (g-1)^2 - g + 1; f
    -v + v^2 - 3*t^2*u + 6*t^2*u*v + 2*t^2*v^2 + O(t, u, v)^5
    sage: f in R
    True
    sage: f.prec()
    5
    sage: ((g-1-v)^2).prec()
    8

Construct multivariate power series rings over various base rings.

    sage: M = PowerSeriesRing(QQ, 4, 'k'); M
    Multivariate Power Series Ring in k0, k1, k2, k3 over Rational Field
    sage: loads(dumps(M)) is M
    True
    sage: TestSuite(M).run()

    sage: H = PowerSeriesRing(PolynomialRing(ZZ,3,'z'),4,'f'); H
    Multivariate Power Series Ring in f0, f1, f2, f3 over Multivariate
    Polynomial Ring in z0, z1, z2 over Integer Ring
    sage: TestSuite(H).run()
    sage: loads(dumps(H)) is H
    True

    sage: z = H.base_ring().gens()
    sage: f = H.gens()
    sage: h = 4*z[1]^2 + 2*z[0]*z[2] + z[1]*z[2] + z[2]^2 \
    + (-z[2]^2 - 2*z[0] + z[2])*f[0]*f[2] \
    + (-22*z[0]^2 + 2*z[1]^2 - z[0]*z[2] + z[2]^2 - 1955*z[2])*f[1]*f[2] \
    + (-z[0]*z[1] - 2*z[1]^2)*f[2]*f[3] \
    + (2*z[0]*z[1] + z[1]*z[2] - z[2]^2 - z[1] + 3*z[2])*f[3]^2 \
    + H.O(3)
    sage: h in H
    True
    sage: h
    4*z1^2 + 2*z0*z2 + z1*z2 + z2^2 + (-z2^2 - 2*z0 + z2)*f0*f2
    + (-22*z0^2 + 2*z1^2 - z0*z2 + z2^2 - 1955*z2)*f1*f2
    + (-z0*z1 - 2*z1^2)*f2*f3 + (2*z0*z1 + z1*z2 - z2^2 - z1 + 3*z2)*f3^2
    + O(f0, f1, f2, f3)^3

- Use angle-bracket notation:

      sage: S.<x,y> = PowerSeriesRing(GF(65537)); S
      Multivariate Power Series Ring in x, y over Finite Field of size 65537
      sage: s = -30077*x + 9485*x*y - 6260*y^3 + 12870*x^2*y^2 - 20289*y^4 + S.O(5); s
      -30077*x + 9485*x*y - 6260*y^3 + 12870*x^2*y^2 - 20289*y^4 + O(x, y)^5
      sage: s in S
      True
      sage: TestSuite(S).run()
      sage: loads(dumps(S)) is S
      True

- Use double square bracket notation:

      sage: ZZ[['s,t,u']]
      Multivariate Power Series Ring in s, t, u over Integer Ring
      sage: GF(127931)[['x,y']]
      Multivariate Power Series Ring in x, y over Finite Field of size 127931

Variable ordering determines how series are displayed.

    sage: T.<a,b> = PowerSeriesRing(ZZ,order='deglex'); T
    Multivariate Power Series Ring in a, b over Integer Ring
    sage: TestSuite(T).run()
    sage: loads(dumps(T)) is T
    True
    sage: T.term_order()
    Degree lexicographic term order
    sage: p = - 2*b^6 + a^5*b^2 + a^7 - b^2 - a*b^3 + T.O(9); p
    a^7 + a^5*b^2 - 2*b^6 - a*b^3 - b^2 + O(a, b)^9

    sage: U = PowerSeriesRing(ZZ,'a,b',order='negdeglex'); U
    Multivariate Power Series Ring in a, b over Integer Ring
    sage: U.term_order()
    Negative degree lexicographic term order
    sage: U(p)
    -b^2 - a*b^3 - 2*b^6 + a^7 + a^5*b^2 + O(a, b)^9

Change from one base ring to another:

    sage: R.<t,u,v> = PowerSeriesRing(QQ); R
    Multivariate Power Series Ring in t, u, v over Rational Field
    sage: R.base_extend(RR)
    Multivariate Power Series Ring in t, u, v over Real Field with 53
    bits of precision
    sage: R.change_ring(IntegerModRing(10))
    Multivariate Power Series Ring in t, u, v over Ring of integers
    modulo 10

    sage: S = PowerSeriesRing(GF(65537),2,'x,y'); S
    Multivariate Power Series Ring in x, y over Finite Field of size 65537
    sage: S.change_ring(GF(5))
    Multivariate Power Series Ring in x, y over Finite Field of size 5

Coercion from polynomial ring:

    sage: R.<t,u,v> = PowerSeriesRing(QQ); R
    Multivariate Power Series Ring in t, u, v over Rational Field
    sage: A = PolynomialRing(ZZ,3,'t,u,v')
    sage: g = A.gens()
    sage: a = 2*g[0]*g[2] - 2*g[0] - 2; a
    2*t*v - 2*t - 2
    sage: R(a)
    -2 - 2*t + 2*t*v
    sage: R(a).O(4)
    -2 - 2*t + 2*t*v + O(t, u, v)^4
    sage: a.parent()
    Multivariate Polynomial Ring in t, u, v over Integer Ring
    sage: a in R
    True

Coercion from polynomial ring in subset of variables:

    sage: R.<t,u,v> = PowerSeriesRing(QQ); R
    Multivariate Power Series Ring in t, u, v over Rational Field
    sage: A = PolynomialRing(QQ,2,'t,v')
    sage: g = A.gens()
    sage: a = -2*g[0]*g[1] - 1/27*g[1]^2 + g[0] - 1/2*g[1]; a
    -2*t*v - 1/27*v^2 + t - 1/2*v
    sage: a in R
    True

Coercion from symbolic ring:

    sage: x,y = var('x,y')
    sage: S = PowerSeriesRing(GF(11),2,'x,y'); S
    Multivariate Power Series Ring in x, y over Finite Field of size 11
    sage: type(x)
    <type 'sage.symbolic.expression.Expression'>
    sage: type(S(x))
    <class 'sage.rings.multi_power_series_ring_element.MPowerSeriesRing_generic_with_category.element_class'>

    sage: f = S(2/7 -100*x^2 + 1/3*x*y + y^2).O(3); f
    5 - x^2 + 4*x*y + y^2 + O(x, y)^3
    sage: f.parent()
    Multivariate Power Series Ring in x, y over Finite Field of size 11
    sage: f.parent() == S
    True

The implementation of the multivariate power series ring uses a combination of multivariate polynomials and univariate power series. Namely, in order to construct the multivariate power series ring \(R[[x_1, x_2, \cdots, x_n]]\), we consider the univariate power series ring \(S[[T]]\) over the multivariate polynomial ring \(S := R[x_1, x_2, \cdots, x_n]\), and in it we take the subring formed by all power series whose \(i\)-th coefficient has degree \(i\) for all \(i \geq 0\). This subring is isomorphic to \(R[[x_1, x_2, \cdots, x_n]]\). This is how \(R[[x_1, x_2, \cdots, x_n]]\) is implemented in this class. The ring \(S\) is called the foreground polynomial ring, and the ring \(S[[T]]\) is called the background univariate power series ring.

AUTHORS:

- Niles Johnson (2010-07): initial code
- Simon King (2012-08, 2013-02): Use category and coercion framework, trac ticket #13412 and trac ticket #14084

class `sage.rings.multi_power_series_ring.``MPowerSeriesRing_generic`(base_ring, num_gens, name_list, order='negdeglex', default_prec=10, sparse=False)

  Bases: `sage.rings.power_series_ring.PowerSeriesRing_generic`, `sage.structure.nonexact.Nonexact`

  A multivariate power series ring. This class is implemented as a single variable power series ring in the variable `T` over a multivariable polynomial ring in the specified generators. Each generator `g` of the multivariable polynomial ring (called the “foreground ring”) is mapped to `g*T` in the single variable power series ring (called the “background ring”). The background power series ring is used to do arithmetic and track total-degree precision. The foreground polynomial ring is used to display elements.

  For usage and examples, see above, and `PowerSeriesRing()`.

  `Element`

    alias of `MPowerSeries`

  `O`(prec)

    Return big oh with precision `prec`. This function is an alias for `bigoh`.

    EXAMPLES:

        sage: T.<a,b> = PowerSeriesRing(ZZ,2); T
        Multivariate Power Series Ring in a, b over Integer Ring
        sage: T.O(10)
        0 + O(a, b)^10
        sage: T.bigoh(10)
        0 + O(a, b)^10

  `bigoh`(prec)

    Return big oh with precision `prec`. The function `O` does the same thing.

    EXAMPLES:

        sage: T.<a,b> = PowerSeriesRing(ZZ,2); T
        Multivariate Power Series Ring in a, b over Integer Ring
        sage: T.bigoh(10)
        0 + O(a, b)^10
        sage: T.O(10)
        0 + O(a, b)^10

  `change_ring`(R)

    Returns the power series ring over R in the same variable as self. This function ignores the question of whether the base ring of self is or can extend to the base ring of R; for the latter, use base_extend.

    EXAMPLES:

        sage: R.<t,u,v> = PowerSeriesRing(QQ); R
        Multivariate Power Series Ring in t, u, v over Rational Field
        sage: R.base_extend(RR)
        Multivariate Power Series Ring in t, u, v over Real Field with
        53 bits of precision
        sage: R.change_ring(IntegerModRing(10))
        Multivariate Power Series Ring in t, u, v over Ring of integers
        modulo 10
        sage: R.base_extend(IntegerModRing(10))
        Traceback (most recent call last):
        ...
        TypeError: no base extension defined

        sage: S = PowerSeriesRing(GF(65537),2,'x,y'); S
        Multivariate Power Series Ring in x, y over Finite Field of size
        65537
        sage: S.change_ring(GF(5))
        Multivariate Power Series Ring in x, y over Finite Field of size 5

  `characteristic`()

    Return characteristic of base ring, which is characteristic of self.

    EXAMPLES:

        sage: H = PowerSeriesRing(GF(65537),4,'f'); H
        Multivariate Power Series Ring in f0, f1, f2, f3 over
        Finite Field of size 65537
        sage: H.characteristic()
        65537

  `construction`()

    Returns a functor F and base ring R such that F(R) == self.

    EXAMPLES:

        sage: M = PowerSeriesRing(QQ,4,'f'); M
        Multivariate Power Series Ring in f0, f1, f2, f3 over Rational Field

        sage: (c,R) = M.construction(); (c,R)
        (Completion[('f0', 'f1', 'f2', 'f3')],
        Multivariate Polynomial Ring in f0, f1, f2, f3 over Rational Field)
        sage: c
        Completion[('f0', 'f1', 'f2', 'f3')]
        sage: c(R)
        Multivariate Power Series Ring in f0, f1, f2, f3 over Rational Field
        sage: c(R) == M
        True

  `gen`(n=0)

    Return the nth generator of self.

    EXAMPLES:

        sage: M = PowerSeriesRing(ZZ,10,'v');
        sage: M.gen(6)
        v6

  `is_dense`()

    Is self dense? (opposite of sparse)

    EXAMPLES:

        sage: M = PowerSeriesRing(ZZ,3,'s,t,u'); M
        Multivariate Power Series Ring in s, t, u over Integer Ring
        sage: M.is_dense()
        True
        sage: N = PowerSeriesRing(ZZ,3,'s,t,u',sparse=True); N
        Sparse Multivariate Power Series Ring in s, t, u over Integer Ring
        sage: N.is_dense()
        False

  `is_integral_domain`(proof=False)

    Return True if the base ring is an integral domain; otherwise return False.

    EXAMPLES:

        sage: M = PowerSeriesRing(QQ,4,'v'); M
        Multivariate Power Series Ring in v0, v1, v2, v3 over Rational Field
        sage: M.is_integral_domain()
        True

  `is_noetherian`(proof=False)

    Power series over a Noetherian ring are Noetherian.

    EXAMPLES:

        sage: M = PowerSeriesRing(QQ,4,'v'); M
        Multivariate Power Series Ring in v0, v1, v2, v3 over Rational Field
        sage: M.is_noetherian()
        True

        sage: W = PowerSeriesRing(InfinitePolynomialRing(ZZ,'a'),2,'x,y')
        sage: W.is_noetherian()
        False

  `is_sparse`()

    Is self sparse?

    EXAMPLES:

        sage: M = PowerSeriesRing(ZZ,3,'s,t,u'); M
        Multivariate Power Series Ring in s, t, u over Integer Ring
        sage: M.is_sparse()
        False
        sage: N = PowerSeriesRing(ZZ,3,'s,t,u',sparse=True); N
        Sparse Multivariate Power Series Ring in s, t, u over Integer Ring
        sage: N.is_sparse()
        True

  `laurent_series_ring`()

    Laruent series not yet implemented for multivariate power series rings

    TESTS:

        sage: M = PowerSeriesRing(ZZ,3,'x,y,z');
        sage: M.laurent_series_ring()
        Traceback (most recent call last):
        ...
        NotImplementedError: Laurent series not implemented for
        multivariate power series.

  `ngens`()

    Return number of generators of self.

    EXAMPLES:

        sage: M = PowerSeriesRing(ZZ,10,'v');
        sage: M.ngens()
        10

  `prec_ideal`()

    Return the ideal which determines precision; this is the ideal generated by all of the generators of our background polynomial ring.

    EXAMPLES:

        sage: A.<s,t,u> = PowerSeriesRing(ZZ)
        sage: A.prec_ideal()
        Ideal (s, t, u) of Multivariate Polynomial Ring in s, t, u over
        Integer Ring

  `remove_var`(*var)

    Remove given variable or sequence of variables from self.

    EXAMPLES:

        sage: A.<s,t,u> = PowerSeriesRing(ZZ)
        sage: A.remove_var(t)
        Multivariate Power Series Ring in s, u over Integer Ring
        sage: A.remove_var(s,t)
        Power Series Ring in u over Integer Ring

        sage: M = PowerSeriesRing(GF(5),5,'t'); M
        Multivariate Power Series Ring in t0, t1, t2, t3, t4 over
        Finite Field of size 5
        sage: M.remove_var(M.gens()[3])
        Multivariate Power Series Ring in t0, t1, t2, t4 over Finite
        Field of size 5

    Removing all variables results in the base ring:

        sage: M.remove_var(*M.gens())
        Finite Field of size 5

  `term_order`()

    Print term ordering of self. Term orderings are implemented by the TermOrder class.

    EXAMPLES:

        sage: M.<x,y,z> = PowerSeriesRing(ZZ,3);
        sage: M.term_order()
        Negative degree lexicographic term order
        sage: m = y*z^12 - y^6*z^8 - x^7*y^5*z^2 + x*y^2*z + M.O(15); m
        x*y^2*z + y*z^12 - x^7*y^5*z^2 - y^6*z^8 + O(x, y, z)^15

        sage: N = PowerSeriesRing(ZZ,3,'x,y,z', order="deglex");
        sage: N.term_order()
        Degree lexicographic term order
        sage: N(m)
        -x^7*y^5*z^2 - y^6*z^8 + y*z^12 + x*y^2*z + O(x, y, z)^15

`sage.rings.multi_power_series_ring.``is_MPowerSeriesRing`(x)

  Return true if input is a multivariate power series ring.

  TESTS:

      sage: from sage.rings.power_series_ring import is_PowerSeriesRing
      sage: from sage.rings.multi_power_series_ring import is_MPowerSeriesRing
      sage: M = PowerSeriesRing(ZZ,4,'v');
      sage: is_PowerSeriesRing(M)
      False
      sage: is_MPowerSeriesRing(M)
      True
      sage: T = PowerSeriesRing(RR,'v')
      sage: is_PowerSeriesRing(T)
      True
      sage: is_MPowerSeriesRing(T)
      False

`sage.rings.multi_power_series_ring.``unpickle_multi_power_series_ring_v0`(base_ring, num_gens, names, order, default_prec, sparse)

  Unpickle (deserialize) a multivariate power series ring according to the given inputs.

  EXAMPLES:

      sage: P.<x,y> = PowerSeriesRing(QQ)
      sage: loads(dumps(P)) == P # indirect doctest
      True

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