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Concept# Euclidean vector

Summary

In mathematics, physics, and engineering, a Euclidean vector or simply a vector (sometimes called a geometric vector or spatial vector) is a geometric object that has magnitude (or length) and direction. Vectors can be added to other vectors according to vector algebra. A Euclidean vector is frequently represented by a directed line segment, or graphically as an arrow connecting an initial point A with a terminal point B, and denoted by \overrightarrow{AB} .
A vector is what is needed to "carry" the point A to the point B; the Latin word vector means "carrier". It was first used by 18th century astronomers investigating planetary revolution around the Sun. The magnitude of the vector is the distance between the two points, and the direction refers to the direction of displacement from A to B. Many algebraic operations on real numbers such as addition, subtraction, multiplication, and negation have close analogues for vectors, operations which obey the familiar algebraic

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Le but du cours de physique générale est de donner à l'étudiant.e les notions de base nécessaires à la compréhension des phénomènes physiques. L'objectif est atteint lorsque l'étudiant.e est capable de prévoir quantitativement les conséquences de ces phénomènes avec des outils théoriques appropriés.

PHYS-101(g): General physics : mechanics

Le but du cours de physique générale est de donner à l'étudiant les notions de base nécessaires à la compréhension des phénomènes physiques. L'objectif est atteint lorsque l'étudiant est capable de prévoir quantitativement les conséquences de ces phénomènes avec des outils théoriques appropriés.

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Neutron diffraction with static and pulsed magnetic fields is used to directly probe the magnetic structures in LiNiPO4 up to 25 T and 42 T, respectively. By combining these results with magnetometry and electric polarization measurements under pulsed fields, the magnetic and magnetoelectric phases are investigated up to 56 T applied along the easy c axis. In addition to the already known transitions at lower fields, three new ones are reported at 37.6, 39.4, and 54 T. Ordering vectors are identified with Q(VI) = (0, 1/3, 0) in the interval 37.6 - 39.4 T and Q(VII) = (0, 0, 0) in the interval 39.4 - 54 T. A quadratic magnetoelectric effect is discovered in the Q(VII) = (0, 0, 0) phase and the field dependence of the induced electric polarization is described using a simple mean-field model. The observed magnetic structure and magnetoelectric tensor elements point to a change in the lattice symmetry in this phase. We speculate on the possible physical mechanism responsible for the magnetoelectric effect in LiNiPO4.

We explore a few algebraic and geometric structures, through certain questions posed by modern cryptography. We focus on the cases of discrete logarithms in finite fields of small characteristic, the structure of isogeny graphs of ordinary abelian varieties, and the geometry of ideals in cyclotomic rings.
The presumed difficulty of computing discrete logarithms in certain groups is essential for the security of a number of communication protocols deployed today. One of the most classic choices for the underlying group is the multiplicative group of a finite field. Yet this choice is showing its age, and particularly when the characteristic of the field is small: recent algorithms allow to compute logarithms efficiently in these groups. However, these methods are only heuristic: they seem to always work, yet we do not know how to prove it. In the first part, we propose to study these methods in the hope to get a better understanding, notably by revealing the geometric structures at play.
A more modern choice is the group of rational points of an elliptic curve defined over a finite field. There, the difficulty of the discrete logarithm problem seems at its peak. More generally, the group of rational points of an abelian variety (notably the Jacobian of a curve of small genus) could be appropriate. One of the main tools for studying discrete logarithms on such objects is the notion of isogeny: a morphism from a variety to another one, which allows, among other things, to transfer the computation of a logarithm. Whereas the theory for elliptic curves is already mature, little is known about the structures formed by these isogenies (the isogeny graphs) for varieties of higher dimension. In the second part, we study the structure of isogeny graphs of absolutely simple, ordinary abelian varieties, with a few consequences regarding discrete logarithms on Jacobians of hyperelliptic curves of genus 2, the main object of concern of so-called hyperelliptic cryptography.
The security of quite a few protocols, notably those relying on discrete logarithms, would collapse in front of an adversary equipped with a large-scale quantum computer. This perspective motivates cryptographers to study problems that would resist this technological feat. One of the major directions is cryptography based on Euclidean lattices, relying on the difficulty to find short vectors in a given lattice. For efficiency, one benefits from considering lattices endowed with more structure, such as the ideals of a cyclotomic field. In the third part, we study the geometry of these ideals, and show that a quantum computer allows to efficiently find much shorter vectors in these ideals than is currently possible in generic lattices.

We discuss some properties of generative models for word embeddings. Namely, (Arora et al., 2016) proposed a latent discourse model implying the concentration of the partition function of the word vectors. This concentration phenomenon led to an asymptotic linear relation between the pointwise mutual information (PMI) of pairs of words and the scalar product of their vectors. Here, we first revisit this concentration phenomenon and prove it under slightly weaker assumptions, for a set of random vectors symmetrically distributed around the origin. Second, we empirically evaluate the relation between PMI and scalar products of word vectors satisfying the concentration property. Our empirical results indicate that, in practice, this relation does not hold with arbitrarily small error. This observation is further supported by two theoretical results: (i) the error cannot be exactly zero because the corresponding shifted PMI matrix cannot be positive semidefinite; (ii) under mild assumptions, there exist pairs of words for which the error cannot be close to zero. We deduce that either natural language does not follow the assumptions of the considered generative model, or the current word vector generation methods do not allow the construction of the hypothesized word embeddings.