Concepts inA sieve algorithm for the shortest lattice vector problem
Lattice (group)
In mathematics, especially in geometry and group theory, a lattice in R is a discrete subgroup of R which spans the real vector space R. Every lattice in R can be generated from a basis for the vector space by forming all linear combinations with integer coefficients. A lattice may be viewed as a regular tiling of a space by a primitive cell. Lattices have many significant applications in pure mathematics, particularly in connection to Lie algebras, number theory and group theory.
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Bravais lattice
In geometry and crystallography, a Bravais lattice, studied by Auguste BravaisĀ , is an infinite array of discrete points generated by a set of discrete translation operations described by: where ni are any integers and ai are known as the primitive vectors which lie in different directions and span the lattice. This discrete set of vectors must be closed under vector addition and subtraction. For any choice of position vector R, the lattice looks exactly the same.
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Lattice problem
In computer science, lattice problems are a class of optimization problems on lattices. The conjectured intractability of such problems is central to construction of secure lattice-based cryptosystems. For applications in such cryptosystems, lattices over vector spaces (often) or free modules (often) are generally considered. For all the problems below, assume that we are given (in addition to other more specific inputs) a basis for the vector space V and a norm N.
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Exponentiation
Exponentiation is a mathematical operation, written as b, involving two numbers, the base b and the exponent (or index or power) n. When n is a positive integer, exponentiation corresponds to repeated multiplication; in other words, a product of n factors, each of which is equal to b (the product itself can also be called power): just as multiplication by a positive integer corresponds to repeated addition: The exponent is usually shown as a superscript to the right of the base.
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Time complexity
In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the size of the input to the problem. The time complexity of an algorithm is commonly expressed using big O notation, which suppresses multiplicative constants and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e. , as the input size goes to infinity.
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Rational number
In mathematics, a rational number is any number that can be expressed as the quotient or fraction a/b of two integers, with the denominator b not equal to zero. Since b may be equal to 1, every integer is a rational number. The set of all rational numbers is usually denoted by a boldface Q, which stands for quotient. The decimal expansion of a rational number always either terminates after a finite number of digits or begins to repeat the same finite sequence of digits over and over.
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