We characterize the analogues of Householder reflectors in matrix groups associated with scalar products. Examples of such groups include the symplectic and pseudounitary groups. We also precisely delimit the mapping capabilities of these Householder analogues: given a matrix group G and vectors x, y, we give necessary and sufficient conditions for the existence of a Householder-like analogue G...

8 Vectors and Quaternions 40 8.1 Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 8.2 Displacement Vectors . . . . . . . . . . . . . . . . . . . . . . . 40 8.3 The Parallelogram Law of Vector Addition . . . . . . . . . . . 41 8.4 The Length of Vectors . . . . . . . . . . . . . . . . . . . . . . 42 8.5 Scalar Multiples of Vectors . . . . . . . . . . . . . . . . . . . . 43...

In mining and integrating data from multiple sources, there are many privacy and security issues. In several different contexts, the security of the full privacy-preserving data mining protocol depends on the security of the underlying private scalar product protocol. We show that two of the private scalar product protocols, one of which was proposed in a leading data mining conference, are ins...

8 Vectors and Quaternions 145 8.1 Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 8.2 Displacement Vectors . . . . . . . . . . . . . . . . . . . . . . . 145 8.3 The Parallelogram Law of Vector Addition . . . . . . . . . . . 146 8.4 The Length of Vectors . . . . . . . . . . . . . . . . . . . . . . 147 8.5 Scalar Multiples of Vectors . . . . . . . . . . . . . . . . . . ....

9 Vectors and Quaternions 51 9.1 Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 9.2 Displacement Vectors . . . . . . . . . . . . . . . . . . . . . . . 51 9.3 The Parallelogram Law of Vector Addition . . . . . . . . . . . 52 9.4 The Length of Vectors . . . . . . . . . . . . . . . . . . . . . . 53 9.5 Scalar Multiples of Vectors . . . . . . . . . . . . . . . . . . . . 54...

4 Vectors and Quaternions 47 4.1 Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.2 Displacement Vectors . . . . . . . . . . . . . . . . . . . . . . . 47 4.3 The Parallelogram Law of Vector Addition . . . . . . . . . . . 49 4.4 The Length of Vectors . . . . . . . . . . . . . . . . . . . . . . 50 4.5 Scalar Multiples of Vectors . . . . . . . . . . . . . . . . . . . . 51...

The state space of a finite quantum system is identified with the set of positive semidefinite matrices of trace 1. The set of all strictly positive definite matrices of trace 1 becomes naturally a differentiable manifold and the Bogoliubov-Kubo-Mori scalar product defines a Riemannian structure on it. Reference [4] tells about the relation of this metric to the von Neumann entropy functional. ...

We consider certain scalar product of symmetric functions which is parameterized by a function r and an integer n. One the one hand we have a fermionic representation of this scalar product. On the other hand we get a representation of this product with the help of multi-integrals. This gives links between a theory of symmetric functions, soliton theory and models of random matrices (such as a ...