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mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, a monomial order (sometimes called a term order or an admissible order) is a
total order In mathematics, a total or linear order is a partial order in which any two elements are comparable. That is, a total order is a binary relation \leq on some set X, which satisfies the following for all a, b and c in X: # a \leq a ( reflexive ...
on the set of all ( monic)
monomial In mathematics, a monomial is, roughly speaking, a polynomial which has only one term. Two definitions of a monomial may be encountered: # A monomial, also called power product, is a product of powers of variables with nonnegative integer expon ...
s in a given
polynomial ring In mathematics, especially in the field of algebra, a polynomial ring or polynomial algebra is a ring (which is also a commutative algebra) formed from the set of polynomials in one or more indeterminates (traditionally also called variables ...
, satisfying the property of respecting multiplication, i.e., * If u \leq v and w is any other monomial, then uw \leq vw. Monomial orderings are most commonly used with Gröbner bases and multivariate division. In particular, the property of ''being'' a Gröbner basis is always relative to a specific monomial order.


Definition, details and variations

Besides respecting multiplication, monomial orders are often required to be well-orders, since this ensures the multivariate division procedure will terminate. There are however practical applications also for multiplication-respecting order relations on the set of monomials that are not well-orders. In the case of finitely many variables, well-ordering of a monomial order is equivalent to the conjunction of the following two conditions: # The order is a
total order In mathematics, a total or linear order is a partial order in which any two elements are comparable. That is, a total order is a binary relation \leq on some set X, which satisfies the following for all a, b and c in X: # a \leq a ( reflexive ...
. # If ''u'' is any monomial then 1 \leq u. Since these conditions may be easier to verify for a monomial order defined through an explicit rule, than to directly prove it is a well-ordering, they are sometimes preferred in definitions of monomial order.


Leading monomials, terms, and coefficients

The choice of a total order on the monomials allows sorting the terms of a polynomial. The leading term of a polynomial is thus the term of the largest monomial (for the chosen monomial ordering). Concretely, let be any ring of polynomials. Then the set of the (monic) monomials in is a basis of , considered as a
vector space In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called '' vectors'', may be added together and multiplied ("scaled") by numbers called ''scalars''. Scalars are often real numbers, but can ...
over the field of the coefficients. Thus, any nonzero polynomial in has a unique expression p = \textstyle\sum_ c_u u as a linear combination of monomials, where is a finite subset of and the are all nonzero. When a monomial order has been chosen, the leading monomial is the largest in , the leading coefficient is the corresponding , and the leading term is the corresponding . ''Head'' monomial/coefficient/term is sometimes used as a synonym of "leading". Some authors use "monomial" instead of "term" and "power product" instead of "monomial". In this article, a monomial is assumed to not include a coefficient. The defining property of monomial orderings implies that the order of the terms is kept when multiplying a polynomial by a monomial. Also, the leading term of a product of polynomials is the product of the leading terms of the factors.


Examples

On the set \left\ of powers of any one variable ''x'', the only monomial orders are the natural ordering 1 < ''x'' < x2 < x3 < ... and its converse, the latter of which is not a well-ordering. Therefore, the notion of monomial order becomes interesting only in the case of multiple variables. The monomial order implies an order on the individual indeterminates. One can simplify the classification of monomial orders by assuming that the indeterminates are named ''x''1, ''x''2, ''x''3, ... in decreasing order for the monomial order considered, so that always . (If there should be infinitely many indeterminates, this convention is incompatible with the condition of being a well ordering, and one would be forced to use the opposite ordering; however the case of polynomials in infinitely many variables is rarely considered.) In the example below we use ''x'', ''y'' and ''z'' instead of ''x''1, ''x''2 and ''x''3. With this convention there are still many examples of different monomial orders.


Lexicographic order

Lexicographic order (lex) first compares exponents of ''x''1 in the monomials, and in case of equality compares exponents of ''x''2, and so forth. The name is derived from the similarity with the usual alphabetical order used in
lexicography Lexicography is the study of lexicons, and is divided into two separate academic disciplines. It is the art of compiling dictionaries. * Practical lexicography is the art or craft of compiling, writing and editing dictionaries. * Theoreti ...
for dictionaries, if monomials are represented by the sequence of the exponents of the indeterminates. If the number of indeterminates is fixed (as it is usually the case), the lexicographical order is a well-order, although this is not the case for the lexicographical order applied to sequences of various lengths (see ). For Gröbner basis computations this ordering tends to be the most costly; thus it should be avoided, as far as possible, except for very simple computations.


Graded lexicographic order

Graded lexicographic order (grlex, or deglex for degree lexicographic order) first compares the total degree (sum of all exponents), and in case of a tie applies lexicographic order. This ordering is not only a well ordering, it also has the property that any monomial is preceded only by a finite number of other monomials; this is not the case for lexicographic order, where all (infinitely many) powers of ''x'' are less than ''y'' (that lexicographic order is nevertheless a well ordering is related to the impossibility of constructing an infinite decreasing chain of monomials). Although very natural, this ordering is rarely used: the Gröbner basis for the graded reverse lexicographic order, which follows, is easier to compute and provides the same information on the input set of polynomials.


Graded reverse lexicographic order

Graded reverse lexicographic order (grevlex, or degrevlex for degree reverse lexicographic order) compares the total degree first, then uses a reverse lexicographic order as tie-breaker, but it ''reverses the outcome'' of the lexicographic comparison so that lexicographically larger monomials of the same degree are considered to be degrevlex smaller. For the final order to exhibit the conventional ordering of the indeterminates, it is furthermore necessary that the tie-breaker lexicographic order before reversal considers the ''last'' indeterminate ''x''n to be the largest, which means it must start with that indeterminate. A concrete recipe for the graded reverse lexicographic order is thus to compare by the total degree first, then compare exponents of the ''last'' indeterminate ''x''''n'' but ''reversing the outcome'' (so the monomial with smaller exponent is larger in the ordering), followed (as always only in case of a tie) by a similar comparison of ''x''''n''−1, and so forth ending with ''x''1. The differences between graded lexicographic and graded reverse lexicographic orders are subtle, since they in fact coincide for 1 and 2 indeterminates. The first difference comes for degree 2 monomials in 3 indeterminates, which are graded lexicographic ordered as x_1^2 > x_1 x_2 > x_1 x_3 > x_2^2 > x_2 x_3 > x_3^2 but graded reverse lexicographic ordered as x_1^2 > x_1 x_2 > x_2^2 > x_1 x_3 > x_2 x_3 > x_3^2 . The general trend is that the reverse order exhibits all variables among the small monomials of any given degree, whereas with the non-reverse order the intervals of smallest monomials of any given degree will only be formed from the smallest variables.


Elimination order

Block order or elimination order (lexdeg) may be defined for any number of blocks but, for sake of simplicity, we consider only the case of two blocks (however, if the number of blocks equals the number of variables, this order is simply the lexicographic order). For this ordering, the variables are divided in two blocks ''x''1,..., ''x''''h'' and ''y''1,...,''y''''k'' and a monomial ordering is chosen for each block, usually the graded reverse lexicographical order. Two monomials are compared by comparing their ''x'' part, and in case of a tie, by comparing their ''y'' part. This ordering is important as it allows ''elimination'', an operation which corresponds to projection in algebraic geometry.


Weight order

Weight order depends on a vector (a_1,\ldots,a_n)\in\R_^n called the weight vector. It first compares the
dot product In mathematics, the dot product or scalar productThe term ''scalar product'' means literally "product with a scalar as a result". It is also used sometimes for other symmetric bilinear forms, for example in a pseudo-Euclidean space. is an alg ...
of the exponent sequences of the monomials with this weight vector, and in case of a tie uses some other fixed monomial order. For instance, the graded orders above are weight orders for the "total degree" weight vector (1,1,...,1). If the ''a''''i'' are rationally independent numbers (so in particular none of them are zero and all fractions \tfrac are irrational) then a tie can never occur, and the weight vector itself specifies a monomial ordering. In the contrary case, one could use another weight vector to break ties, and so on; after using ''n'' linearly independent weight vectors, there cannot be any remaining ties. One can in fact define ''any'' monomial ordering by a sequence of weight vectors ( Cox et al. pp. 72–73), for instance (1,0,0,...,0), (0,1,0,...,0), ... (0,0,...,1) for lex, or (1,1,1,...,1), (1,1,..., 1,0), ... (1,0,...,0) for grevlex. For example, consider the monomials xy^2z, z^2, x^3, and x^2z^2; the monomial orders above would order these four monomials as follows: * Lex: x^3 > x^2z^2 > xy^2z > z^2 (power of x dominates). * Grlex: x^2z^2 > xy^2z > x^3 > z^2 (total degree dominates; higher power of x broke tie among the first two). * Grevlex: xy^2z > x^2z^2 > x^3 > z^2 (total degree dominates; lower power of z broke tie among the first two). * A weight order with weight vector (1,2,4): x^2z^2 > xy^2z > z^2 > x^3 (the dot products 10>9>8>3 do not leave any ties to be broken here).


Related notions

* An elimination order guarantees that a monomial involving any of a set of indeterminates will always be greater than a monomial not involving any of them. * A product order is the easier example of an elimination order. It consists in combining monomial orders on disjoint sets of indeterminates into a monomial order on their union. It simply compares the exponents of the indeterminates in the first set using the first monomial order, then breaks ties using the other monomial ordering on the indeterminates of the second set. This method obviously generalizes to any disjoint union of sets of indeterminates; the lexicographic order can be so obtained from the singleton sets , , , ... (with the unique monomial ordering for each singleton). When using monomial orderings to compute Gröbner bases, different orders can lead to different results, and the difficulty of the computation may vary dramatically. For example, graded reverse lexicographic order has a reputation for producing, almost always, the Gröbner bases that are the easiest to compute (this is enforced by the fact that, under rather common conditions on the ideal, the polynomials in the Gröbner basis have a degree that is at most exponential in the number of variables; no such complexity result exists for any other ordering). On the other hand, elimination orders are required for elimination and relative problems.


References

* {{cite book , author1=David Cox , author2=John Little , author3=Donal O'Shea , year=2007 , title=Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra , publisher=Springer , isbn=978-0-387-35650-1, ref=cox Order theory Polynomials