Lecture

Gradient, divergence

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In course

PHYS-105: Advanced physics II (thermodynamics)

Ce cours présente la thermodynamique en tant que théorie permettant une description d'un grand nombre de phénomènes importants en physique, chimie et ingéniere, et d'effets de transport. Une introduction à la physique statistique renforce les notions acqu ...

Description

This lecture covers the definitions of gradient and divergence, including the Cartesian coordinate system, scalar functions of position, infinitesimal displacement, and the divergence theorem. It also explores the flux of vector fields through different faces.

Instructors (2)

Jean-Philippe Ansermet

Jean-Philippe Ansermet was born March 1, 1957 in Lausanne (legal origin Vaumarcus, NE). He obtained a diploma as physics engineer of EPFL in 1980. He went on to get a PhD from the University of Illinois at Urbana-Champaign where, from 1985 to 1987, he persued as post-doc with Prof. Slichter his research on catalysis by solid state NMR studies of molecules bound to the surface of catalysts. From 1987 to 1992 he worked at the materials research center of Ciba-Geigy, on polymers for microelectronics, composites, dielectrics and organic charge transfer complexes. In March 1992, as professor of experimental physics, he developed a laboratory on the theme of nanostructured materials and turned full professor in 1995. Since 1992, he teaches classical mechanics, first to future engineering students, since 2004 to physics majors. Since 2000, he teaches thermodynamics also, to the same group of students. He offers a graduate course in spintronics, and another on spin dynamics. His research activities concern the fabrication and properties of magnetic nanostructures produced by electrodeposition. His involvement since the early days of spintronics have allowed him to gain recognition for his work on giant magnetoresistance (CPP-GMR), magnetic relaxation of single nanostructures, and was among the leading groups demonstrating magnetization reversal by spin-polarized currents. Furthermore, his group uses nuclear magnetic resonance , on the one hand as means of investigation of surfaces and electrodes, on the other hand, as a local probe of the electronic properties of complex ferromagnetic oxides.

Cécile Hébert

Cécile Hébert was born in France in 1970. She obtained her Ingeneer degree (physics) and her PhD degree (design of a new energy filter for transmission electron microscopy, under the direction of Prof. B. Jouffrey) at the Ecole Centrale in Paris. As a post doc with Prof. P. Schattschneider, she was working on the calculation of the fine structure of ionisation edges in EELS. As a research assistant at the Vienna University of Technology, she was one of the main participant to the CHIRALTEM project dealing with the measurement of magnetic circular dichroism in the electron microscope.

Official source

Ontological neighbourhood

Mathematics

Analysis: Vector analysis

Related concepts (28)

Divergence

In vector calculus, divergence is a vector operator that operates on a vector field, producing a scalar field giving the quantity of the vector field's source at each point. More technically, the divergence represents the volume density of the outward flux of a vector field from an infinitesimal volume around a given point. As an example, consider air as it is heated or cooled. The velocity of the air at each point defines a vector field. While air is heated in a region, it expands in all directions, and thus the velocity field points outward from that region.

Divergence theorem

In vector calculus, the divergence theorem, also known as Gauss's theorem or Ostrogradsky's theorem, is a theorem which relates the flux of a vector field through a closed surface to the divergence of the field in the volume enclosed. More precisely, the divergence theorem states that the surface integral of a vector field over a closed surface, which is called the "flux" through the surface, is equal to the volume integral of the divergence over the region inside the surface.

F-divergence

In probability theory, an -divergence is a function that measures the difference between two probability distributions and . Many common divergences, such as KL-divergence, Hellinger distance, and total variation distance, are special cases of -divergence. These divergences were introduced by Alfréd Rényi in the same paper where he introduced the well-known Rényi entropy. He proved that these divergences decrease in Markov processes.

Divergence (statistics)

In information geometry, a divergence is a kind of statistical distance: a binary function which establishes the separation from one probability distribution to another on a statistical manifold. The simplest divergence is squared Euclidean distance (SED), and divergences can be viewed as generalizations of SED. The other most important divergence is relative entropy (also called Kullback–Leibler divergence), which is central to information theory.

Kullback–Leibler divergence

In mathematical statistics, the Kullback–Leibler divergence (also called relative entropy and I-divergence), denoted , is a type of statistical distance: a measure of how one probability distribution P is different from a second, reference probability distribution Q. A simple interpretation of the KL divergence of P from Q is the expected excess surprise from using Q as a model when the actual distribution is P.

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