Geometry of numbers
geometric number theory
The branch of number theory that studies number-theoretical problems by the use of geometric methods. Geometry of numbers in its proper sense was formulated by H. Minkowski in 1896 in his fundamental monograph . The starting point of this science, which subsequently became an independent branch of number theory, is the fact (already noted by Minkowski) that certain assertions which seem evident in the context of figures in an -dimensional Euclidean space have far-reaching consequences in number theory.
A fundamental and typical task of the geometry of numbers is the problem to determine the arithmetical minimum of some real function
Here is the infimum of the values of when runs through all the integral points (i.e. points with integer coordinates) that satisfy some supplementary condition (e.g. ). In the most important special cases information on can be obtained from Minkowski's convex-body theorem, which may be formulated as follows. Let be an -dimensional convex body of volume and let and for ; then
The quantity is useful in considering conditions of existence of solutions of the Diophantine inequality (cf. Diophantine approximations)
This is a problem to which many problems in number theory can be reduced. The geometry of quadratic forms (cf. Quadratic form) forms a separate chapter in the geometry of numbers.
Two general types of problems are distinguished in the geometry of numbers: the homogeneous and the inhomogeneous problem.
The homogeneous problem, which forms the subject of most studies in the geometry of numbers, deals with the homogeneous minima of a distance function (cf. Ray function) on a lattice of points . The concept of a lattice (of points) is a fundamental one in the geometry of numbers. Let be linearly independent vectors in an -dimensional Euclidean space. The set of points
when each run through all the integers in an independent manner, is known as the lattice (of points) with basis and determinant
Let a distance function and a lattice with determinant be given in . The greatest lower bound
of the values of over the points of is called the minimum of on (or, more accurately, the homogeneous arithmetical minimum). The greatest lower bound , which may or may not be attained, is known to be attained by a bounded star body (cf. Star-like domain), which is defined by the inequality
In order to estimate from above one must calculate (or estimate) the constant of Hermite of the distance function , defined by
where the supremum is taken over the set of all -dimensional lattices . There are relations between , the critical determinant (see below) of the set and (if is a convex symmetric distance function) the density of the densest lattice packing of the body .
Let a set and a lattice with determinant be given in . The lattice is called admissible for , or -admissible, if contains no non-zero points from . A set with at least one admissible lattice is called a set of finite type; otherwise is called a set of infinite type. Let be a set of finite type; the infimum
of the set of determinants of all -admissible lattices is called the critical determinant of . Any -admissible lattice that satisfies the condition
is called a critical lattice of . For a set of infinite type one defines .
The calculation of the constant of Hermite of a distance function is reduced to the computation of the critical determinant of the star body defined by :
The connection between the critical determinant and the density of the densest lattice packing is established by the following theorem of Blichfeldt. Let be an arbitrary set, let be the corresponding set of differences (i.e. the set of points , where ) and let be a lattice. For the arrangement , i.e. for the family of sets , where , to be a packing it is necessary and sufficient that be -admissible.
The density of the densest lattice packing of a bounded Lebesgue-measurable set of measure is defined by
For an arbitrary set and a Lebesgue-measurable set of measure that satisfies the condition the following inequality (another formulation of Blichfeldt's theorem) is valid:
If is a convex body that is symmetric with respect to a point , then
where is the density of the densest lattice packing of . This means that in the case of a symmetric distance function the computation of is reduced to the computation of the densest lattice packing of the body defined by .
A very important statement in the geometry of numbers is Minkowski's convex-body theorem. Let be a convex body that is symmetric with respect to the coordinate origin and of volume . Then
In other words, a lattice for which
has a point distinct from zero in .
Inequality (1) is known as the Minkowski inequality; it gives an estimate from below for the critical determinant of a convex body that is symmetric with respect to 0. In the general case this estimate cannot be improved. Equality is attained if and only if . Convex bodies that satisfy the condition are known as parallelohedra. They play an important role in the geometry of numbers and in mathematical crystallography (cf. Crystallography, mathematical).
All applications of Minkowski's convex-body theorem are based on the fact that for a convex symmetric distance function and an arbitrary lattice of determinant the following inequality is valid:
In particular, for the lattice of integral points and the distance function
Minkowski's theorem on linear homogeneous forms is valid: Let , be real numbers, ; , . If
then there exist integers , not all equal to zero, satisfying the system of linear inequalities
Geometry of numbers also studies the successive minima of a distance function on a lattice. Let be a distance function, let be a lattice and let there be given an index , ; then the infimum of the numbers for which the set contains at least linearly independent points of is said to be the -th successive minimum of on . Here
is valid. It is more difficult to estimate the magnitude
from above; to do this, one must be able to compute, or to estimate from above, the quantity
where the supremum is over all -dimensional lattices . The quantity is called the anomaly of the distance function , or the anomaly of the set . The inequality is valid. The following theorem  gives an estimate from above for . Let be an -dimensional distance function with anomaly , then
Examples have been constructed to show that this estimate cannot, generally speaking, be improved.
If is a convex symmetric distance function, it has been conjectured (the hypothesis on the anomaly of a convex body) that
Minkowski's second theorem on a convex body, making precise the first theorem, is valid. If is a convex symmetric distance function and if is a lattice, then
where the convex body is defined by the condition . Minkowski's second theorem is valid  independently of the hypothesis on the anomaly of a convex body.
The concept of successive minima and the fundamental results relevant to it (except for the last-named theorem) can be generalized from star bodies to arbitrary sets .
The following statement is an estimate from above of the critical determinant of a given set: For any Lebesgue-measurable set of measure ,
If is a star body that is symmetric with respect to zero, then
All proofs of this theorem include some averaging of some function given on the space of lattices. The most natural proof is given by Siegel's mean-value theorem (see, e.g., ). Let be a Lebesgue-integrable function on the -dimensional Euclidean space , and let be an invariant measure on the space of lattices with determinant 1. Let be the fundamental domain of this space, then
As distinct from the estimate from below (1), estimates (2) and (3) are not the best possible (for more precise estimates see ).
Estimates of the critical determinant of a given set from below and from above yield estimates of from above and from below, i.e. the solution (in a certain sense) of the homogeneous problem in the geometry of numbers. However, it is often important to know the exact value of the critical determinant for a given set (e.g., for a norm body of a given algebraic number field). If is a given bounded star body, then it is possible, in principle, to find an algorithm which permits one to reduce the problem of finding all critical lattices of (and hence as well) to a finite number of ordinary problems on the extrema of certain functions of several variables. However, this algorithm is realizable (in the present state of knowledge) only for convex bodies when the dimension .
Generally speaking, finding is much more difficult for unbounded star bodies ; this is clear by the isolation phenomenon of homogeneous arithmetical minima, which may be described as follows. Let be a distance function in , and let the functional
be given on the set of all lattices . The set of possible values of for all is called the Markov spectrum of . One says that has the isolation phenomenon if the set has isolated points. The set lies in the interval . If the star body , , is bounded, then
For this reason the isolation phenomenon is possible for unbounded star bodies only (cf. , Chapt. X). The most intensively studied case is ,
A.N. Korkin and E.I. Zolotarev  were the first to note the isolation phenomenon in this case (which was also the first case of the isolation phenomenon ever noted). A.A. Markov (see ) proved in 1879 that the part of the spectrum to the right of is discrete, and has the form
Here is an increasing sequence of positive integers with the following property: It is possible to find integers , such that
to each point of the spectrum (5) (the "Markov spectrum" in the narrow sense) there corresponds a unique (up to automorphisms ) lattice . The indefinite form , , is sometimes called the Markov form, while the sequence is called a Markov chain. It is also known that to the left of some number the spectrum coincides with the segment . The isolation phenomenon can be described in terms of admissible lattices (cf. ), which generalizes this concept somewhat.
The inhomogeneous problem comprises the inhomogeneous Diophantine problems which play an important role in number theory; it forms an important branch of the geometry of numbers.
Let be a distance function in , let be a lattice of determinant in and let be a point in . Consider the quantities
where the infimum is over all points of the form , , while the supremum is over all points . The quantity is called the inhomogeneous arithmetical minimum of on ; this "minimum" need not be attained. is the greatest lower bound of the real numbers having the following property: The arrangement of the set , where satisfies the condition , over the lattice is a covering, i.e.
For the distance function one considers the following analogues of the Hermite constant:
where the infimum (supremum) is over all -dimensional lattices . The quantity is usually trivial (cf. ); if the set , , has a finite volume, then
However, the inhomogeneous problem is connected with in one particular instance of the function which is of interest.
The hypothesis on the product of inhomogeneous linear forms may be stated as follows. Let
Studies on this hypothesis and its analogues account for more than one half of all studies on the inhomogeneous problem in the geometry of numbers (cf. Minkowski hypothesis).
In the general case, is more informative than . It is closely related to the value of the density of the most economical covering by the body , . In fact, if is a distance function and if the set is bounded, then
An important chapter of the inhomogeneous problems in the geometry of numbers is constituted by the so-called transference theorems for a given distance function , which are inequalities connecting the inhomogeneous minimum with the successive homogeneous minima (or with the minima of the reciprocal function with respect to the reciprocal lattice , etc., see ). Example. Let be a convex symmetric distance function and let for ; then, for any lattice ,
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A distance function is a non-negative real-valued function on an -dimensional Euclidean space such that for . If it is called symmetric, and if it is called convex. If is convex, it is required moreover that for only.
The critical determinant of a lattice is also called the lattice constant. An arrangement is also called a set lattice. The inequality (3) is usually called the Minkowski–Hlawka theorem.
In recent years the geometry of numbers has become more geometric in character. The covering and packing problems have been intensively studied, in particular the ball packing problem with its many relations to other areas such as coding, quantization of data, biology, metallurgy. Tilings have also attracted much interest; in particular Dirichlet–Voronoi (and Delone) tilings, which are of interest, for example, in geography, crystallography and computational geometry.
A tiling, or tesselation, of is a family of sets (called tiles) such that their union covers and their interiors are mutually disjoint. A Dirichlet–Voronoi tiling is a tiling with as tiles sets of the form
where is a discrete point set in . Cf. .
Other modern areas of the geometry of numbers are the theory of the zeta-function on lattices and (computational) reduction theory of quadratic forms and lattices.
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Geometry of numbers. Encyclopedia of Mathematics. URL: http://www.encyclopediaofmath.org/index.php?title=Geometry_of_numbers&oldid=24077