Optimisation non linéaireEn optimisation, vue comme branche des mathématiques, l'optimisation non linéaire (en anglais : nonlinear programming – NLP) s'occupe principalement des problèmes d'optimisation dont les données, i.e., les fonctions et ensembles définissant ces problèmes, sont non linéaires, mais sont aussi différentiables autant de fois que nécessaire pour l'établissement des outils théoriques, comme les conditions d'optimalité, ou pour la bonne marche des algorithmes de résolution qui y sont introduits et analysés.
Definite matrixIn mathematics, a symmetric matrix with real entries is positive-definite if the real number is positive for every nonzero real column vector where is the transpose of . More generally, a Hermitian matrix (that is, a complex matrix equal to its conjugate transpose) is positive-definite if the real number is positive for every nonzero complex column vector where denotes the conjugate transpose of Positive semi-definite matrices are defined similarly, except that the scalars and are required to be positive or zero (that is, nonnegative).
Definite quadratic formIn mathematics, a definite quadratic form is a quadratic form over some real vector space V that has the same sign (always positive or always negative) for every non-zero vector of V. According to that sign, the quadratic form is called positive-definite or negative-definite. A semidefinite (or semi-definite) quadratic form is defined in much the same way, except that "always positive" and "always negative" are replaced by "never negative" and "never positive", respectively.
Optimisation linéaire en nombres entiersL'optimisation linéaire en nombres entiers (OLNE) (ou programmation linéaire en nombres entiers (PLNE) ou integer programming (IP) ou Integer Linear Programming (ILP)) est un domaine des mathématiques et de l'informatique théorique dans lequel on considère des problèmes d'optimisation d'une forme particulière. Ces problèmes sont décrits par une fonction de coût et des contraintes linéaires, et par des variables entières.
Matrix decompositionIn the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems. In numerical analysis, different decompositions are used to implement efficient matrix algorithms. For instance, when solving a system of linear equations , the matrix A can be decomposed via the LU decomposition.
Spectrométrie de massethumb|right|Spectromètre de masse La spectrométrie de masse est une technique physique d'analyse permettant de détecter et d'identifier des molécules d’intérêt par mesure de leur masse, et de caractériser leur structure chimique. Son principe réside dans la séparation en phase gazeuse de molécules chargées (ions) en fonction de leur rapport masse/charge (m/z). Elle est utilisée dans pratiquement tous les domaines scientifiques : physique, astrophysique, chimie en phase gazeuse, chimie organique, dosages, biologie, médecine, archéologie.
Non-perturbativeIn mathematics and physics, a non-perturbative function or process is one that cannot be described by perturbation theory. An example is the function which does not have a Taylor series at x = 0. Every coefficient of the Taylor expansion around x = 0 is exactly zero, but the function is non-zero if x ≠ 0. In physics, such functions arise for phenomena which are impossible to understand by perturbation theory, at any finite order. In quantum field theory, 't Hooft–Polyakov monopoles, domain walls, flux tubes, and instantons are examples.
Central chargeIn theoretical physics, a central charge is an operator Z that commutes with all the other symmetry operators. The adjective "central" refers to the center of the symmetry group—the subgroup of elements that commute with all other elements of the original group—often embedded within a Lie algebra. In some cases, such as two-dimensional conformal field theory, a central charge may also commute with all of the other operators, including operators that are not symmetry generators.
Matrix ringIn abstract algebra, a matrix ring is a set of matrices with entries in a ring R that form a ring under matrix addition and matrix multiplication . The set of all n × n matrices with entries in R is a matrix ring denoted Mn(R) (alternative notations: Matn(R) and Rn×n). Some sets of infinite matrices form infinite matrix rings. Any subring of a matrix ring is a matrix ring. Over a rng, one can form matrix rngs. When R is a commutative ring, the matrix ring Mn(R) is an associative algebra over R, and may be called a matrix algebra.
Mass gapIn quantum field theory, the mass gap is the difference in energy between the lowest energy state, the vacuum, and the next lowest energy state. The energy of the vacuum is zero by definition, and assuming that all energy states can be thought of as particles in plane-waves, the mass gap is the mass of the lightest particle. Since the energies of exact (i.e. nonperturbative) energy eigenstates are spread out and therefore they are not technically eigenstates, a more precise definition is that the mass gap is the greatest lower bound of the energy of any state which is orthogonal to the vacuum.
