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Lecture

Quantum Mechanics: Principles and Operators

In course

CH-110: Advanced general chemistry I

Le cours comporte deux parties. Les bases de la thermodynamique des équilibres et de la cinétique des réactions sont introduites dans l'une d'elles. Les premières notions de chimie quantique sur les électrons et les liaisons chimiques, exemplifiées en chim ...

Description

This lecture introduces the principles of quantum mechanics, focusing on wave functions, electron density, and probability distributions. It covers the concept of expectation value, standard deviation, and operators in quantum mechanics, emphasizing the transition from classical to quantum descriptions of physical systems.

Instructors (7)

Marinella Mazzanti

Philippe Schwaller

Anne-Clémence Corminboeuf

Beat Fierz

Jacques-Edouard Moser

Jacques-Edouard Moser is titular professor in physical chemistry and is currently directing the Group for Photochemical Dynamics (Moser Group) of EPFL. He is a graduate of the École polytechnique fédérale de Lausanne, where he received a diploma degree (MSc) in chemical engineering in 1982. After two stays in 1984 and 1985 at Concordia University in Montréal (Canada), he earned in 1986 his Ph.D. in physical chemistry at EPFL (Michael Grätzel, thesis advisor). In 1986, he joined the Eastman Kodak Corporate Research Laboratories at Rochester (NY, USA) as a postdoctoral fellow and was later associated with the NSF Center for Photoinduced Electron Transfer at the University of Rochester. Returning to Switzerland, he was appointed as a lecturer of physical chemistry at EPFL in 1992 and was awarded the habilitation and the venia legendi in 1998. He is titular professor since 2005.His research activity focuses on the study of the dynamics of photoinduced electron transfer and charge carrier separation at donor-acceptor heterojunctions and in nanostructured semiconductors. He is the author and co-author of ca 200 scientific papers (H-index 75). He currently teaches general physical chemistry to freshmen students in chemistry. He gives two classes on general- and redox photochemistry in the MSc program in chemistry and chemical engineering and the doctoral programs in energy and photonics. Jacques-E. Moser presided the Swiss Society of Photochemistry and Photophysics (1995-1998) and chaired the jury of the Grammaticakis-Neumann international prize in photochemistry (1999-2001). He was a member of the board of the Swiss Chemical Society (2007-2012). He served as a member of the standing committee of the European Photochemistry Association (1992-2000) and of the executive committee of the division for fundamental research of the Swiss Chemical Society (1999-2014). He was the director of the Section of Chemistry and Chemical Engineering of EPFL and a member of the direction of the School of Basic Sciences from 2007 to 2015.

Jérôme Waser

Jérôme Waser biography and CV's are available on the following website: http://lcso.epfl.ch/waser

Official source

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Related concepts (32)

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter s, for the sample standard deviation.

Probability distribution

In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.

Average absolute deviation

The average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any reference value related to the given data set. AAD includes the mean absolute deviation and the median absolute deviation (both abbreviated as MAD). Several measures of statistical dispersion are defined in terms of the absolute deviation.

Deviation (statistics)

In mathematics and statistics, deviation is a measure of difference between the observed value of a variable and some other value, often that variable's mean. The sign of the deviation reports the direction of that difference (the deviation is positive when the observed value exceeds the reference value). The magnitude of the value indicates the size of the difference. Errors and residuals A deviation that is a difference between an observed value and the true value of a quantity of interest (where true value denotes the Expected Value, such as the population mean) is an error.

Median absolute deviation

In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample. For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median : that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values. Consider the data (1, 1, 2, 2, 4, 6, 9).

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