Quantum mutual informationIn quantum information theory, quantum mutual information, or von Neumann mutual information, after John von Neumann, is a measure of correlation between subsystems of quantum state. It is the quantum mechanical analog of Shannon mutual information. For simplicity, it will be assumed that all objects in the article are finite-dimensional. The definition of quantum mutual entropy is motivated by the classical case.
Correlation coefficientA correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables. The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution. Several types of correlation coefficient exist, each with their own definition and own range of usability and characteristics. They all assume values in the range from −1 to +1, where ±1 indicates the strongest possible agreement and 0 the strongest possible disagreement.
Statistical parameterIn statistics, as opposed to its general use in mathematics, a parameter is any measured quantity of a statistical population that summarises or describes an aspect of the population, such as a mean or a standard deviation. If a population exactly follows a known and defined distribution, for example the normal distribution, then a small set of parameters can be measured which completely describes the population, and can be considered to define a probability distribution for the purposes of extracting samples from this population.
Probability theoryProbability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms. Typically these axioms formalise probability in terms of a probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space.
Poisson distributionIn probability theory and statistics, the Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant mean rate and independently of the time since the last event. It is named after French mathematician Siméon Denis Poisson ('pwɑːsɒn; pwasɔ̃). The Poisson distribution can also be used for the number of events in other specified interval types such as distance, area, or volume.
Variation of informationIn probability theory and information theory, the variation of information or shared information distance is a measure of the distance between two clusterings (partitions of elements). It is closely related to mutual information; indeed, it is a simple linear expression involving the mutual information. Unlike the mutual information, however, the variation of information is a true metric, in that it obeys the triangle inequality. Suppose we have two partitions and of a set into disjoint subsets, namely and .
Dry cellA dry cell is a type of electric battery, commonly used for portable electrical devices. Unlike wet cell batteries, which have a liquid electrolyte, dry cells use an electrolyte in the form of a paste, and are thus less susceptible to leakage. The dry cell was developed in 1886 by the German scientist Carl Gassner, after development of wet zinc–carbon batteries by Georges Leclanché in 1866. A type of dry cell was also developed by the Japanese Sakizō Yai in 1887.
Cone cellCone cells, or cones, are photoreceptor cells in the retinas of vertebrates' eyes, including the human eye. They respond differently to light of different wavelengths, and the combination of their responses is responsible for color vision. Cones function best in relatively bright light, called the photopic region, as opposed to rod cells, which work better in dim light, or the scotopic region. Cone cells are densely packed in the fovea centralis, a 0.
Leclanché cellThe Leclanché cell is a battery invented and patented by the French scientist Georges Leclanché in 1866. The battery contained a conducting solution (electrolyte) of ammonium chloride, a cathode (positive terminal) of carbon, a depolarizer of manganese dioxide (oxidizer), and an anode (negative terminal) of zinc (reductant). The chemistry of this cell was later successfully adapted to manufacture a dry cell. In 1866, Georges Leclanché invented a battery that consisted of a zinc anode and a manganese dioxide cathode wrapped in a porous material, dipped in a jar of ammonium chloride solution.
