Quantum chemistry composite methods (also referred to as thermochemical recipes) are computational chemistry methods that aim for high accuracy by combining the results of several calculations. They combine methods with a high level of theory and a small basis set with methods that employ lower levels of theory with larger basis sets. They are commonly used to calculate thermodynamic quantities such as enthalpies of formation, atomization energies, ionization energies and electron affinities. They aim for chemical accuracy which is usually defined as within 1 kcal/mol of the experimental value. The first systematic model chemistry of this type with broad applicability was called Gaussian-1 (G1) introduced by John Pople. This was quickly replaced by the Gaussian-2 (G2) which has been used extensively. The Gaussian-3 (G3) was introduced later. (Wikipedia).
Quantum Theory - Full Documentary HD
Check: https://youtu.be/Hs_chZSNL9I The World of Quantum - Full Documentary HD http://www.advexon.com For more Scientific DOCUMENTARIES. Subscribe for more Videos... Quantum mechanics (QM -- also known as quantum physics, or quantum theory) is a branch of physics which deals with physica
From playlist TV Appearances
Quantum Mechanics 11a - Chemistry I
A great triumph of quantum mechanics is that it provides a quantitative description of chemical bonds. It thus forms the theoretical basis for all of chemistry. Part b: http://youtu.be/QludPcDLe1I Comments, including questions, suggestions and constructive criticism are always welcome.
From playlist Quantum Mechanics
Peter Zoller: Introduction to quantum optics - Lecture 4
Abstract: Quantum optical systems provides one of the best physical settings to engineer quantum many-body systems of atoms and photons, which can be controlled and measured on the level of single quanta. In this course we will provide an introduction to quantum optics from the perspective
From playlist Mathematical Physics
Peter Zoller: Introduction to quantum optics - Lecture 2
Abstract: Quantum optical systems provides one of the best physical settings to engineer quantum many-body systems of atoms and photons, which can be controlled and measured on the level of single quanta. In this course we will provide an introduction to quantum optics from the perspective
From playlist Mathematical Physics
Peter Zoller: Introduction to quantum optics - Lecture 1
Abstract: Quantum optical systems provides one of the best physical settings to engineer quantum many-body systems of atoms and photons, which can be controlled and measured on the level of single quanta. In this course we will provide an introduction to quantum optics from the perspective
From playlist Mathematical Physics
Peter Zoller: Introduction to quantum optics - Lecture 3
Abstract: Quantum optical systems provides one of the best physical settings to engineer quantum many-body systems of atoms and photons, which can be controlled and measured on the level of single quanta. In this course we will provide an introduction to quantum optics from the perspective
From playlist Mathematical Physics
Quantum field theory, Lecture 2
This winter semester (2016-2017) I am giving a course on quantum field theory. This course is intended for theorists with familiarity with advanced quantum mechanics and statistical physics. The main objective is introduce the building blocks of quantum electrodynamics. Here in Lecture 2
From playlist Quantum Field Theory
John HILLER - Nonperturbative light-front methods
https://indico.math.cnrs.fr/event/2435/
From playlist Workshop “Hamiltonian methods in strongly coupled Quantum Field Theory”
Unifying machine learning and quantum chemistry with a deep neural network | AISC
For slides and more information on the paper, visit https://ai.science/e/unifying-machine-learning-and-quantum-chemistry-with-a-deep-neural-network--LzeGRqxc5Sg38jE9eJjE Speaker: Reinhard J. Maurer; Discussion Moderator: Mehrshad Esfahani
From playlist ML in Chemistry
Quantized Energy Equation (Quantum Physics)
#Quantum #Physics #Engineering #tiktok #NicholasGKK #shorts
From playlist Quantum Mechanics
Quantum Machine Learning - Prof. Lilienfeld
Prof. O. Anatole von Lilienfeld of the University of Bassel presented his labs work on Quantum Machine Learning at the 2017 Conference on Neural Information Processing Systems on December 8th, 2017.
From playlist Quantum computing + AI/ML
Markus Reiher - Uncertainty Quantification of Quantum Chemical Methods - IPAM at UCLA
Recorded 06 May 2022. Markus Reiher ETH Zurich presents "Uncertainty Quantification of Quantum Chemical Methods" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-iii-large-scale-certi
From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics
Mod-04 Lec-40 Concluding Lecture
Nano structured materials-synthesis, properties, self assembly and applications by Prof. A.K. Ganguli,Department of Nanotechnology,IIT Delhi.For more details on NPTEL visit http://nptel.ac.in
Heather Kulik: "Molecular design blueprints: materials and catalysts from new simulation and mac..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop II: Interpretable Learning in Physical Sciences "Molecular design blueprints: materials and catalysts from new simulation and machine learning tools" Heather Kulik, Massachusetts Institute of Technology Abstract: Many
From playlist Machine Learning for Physics and the Physics of Learning 2019
Julia Contreras-García - Math-chimie: developing approaches for predicting new superconductors
Recorded 05 May 2022. Julia Contreras-García of Sorbonne Université presents "Math-chimie: developing approaches for predicting new superconductors" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/work
From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics
Anatole von Lilienfeld: "Quantum Machine Learning"
Machine Learning for Physics and the Physics of Learning 2019 Workshop II: Interpretable Learning in Physical Sciences "Quantum Machine Learning" Anatole von Lilienfeld, University of Basel Abstract: Many of the most relevant chemical properties of matter depend explicitly on atomistic a
From playlist Machine Learning for Physics and the Physics of Learning 2019
Frank Noe - Advancing molecular simulation with deep learning - IPAM at UCLA
Recorded 23 January 2023. Frank Noe of Freie Universität Berlin presents "Advancing molecular simulation with deep learning" at IPAM's Learning and Emergence in Molecular Systems Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/learning-and-emergence-in-molecular
From playlist 2023 Learning and Emergence in Molecular Systems
Laura Gagliardi - Localized-Wave-Function in Quantum Chemistry and Extension to Quantum Computers
Recorded 30 March 2022. Laura Gagliardi of the University of Chicago presents "Localized-Wave-Function Methods in Quantum Chemistry and Their Extension to Quantum Computers" at IPAM's Multiscale Approaches in Quantum Mechanics Workshop. Abstract: Quantum chemistry calculations of large, st
From playlist 2022 Multiscale Approaches in Quantum Mechanics Workshop
Quantum Mechanics 1.1: Introduction
In this video I provide some motivation behind the development of quantum mechanics, kicking off a new series on everything you've been wondering about quantum mechanics! Twitter: https://twitter.com/SciencePlease_
From playlist Quantum Mechanics
Xiaojie Wu: "Density matrix embedding theory for large-scale heterogeneous systems"
Theory and Computation for 2D Materials "Density matrix embedding theory for large-scale heterogeneous systems" Xiaojie Wu, University of California, Berkeley (UC Berkeley) Abstract: Density matrix embedding theory (DMET) is a quantum embedding theory for strongly correlated systems. Fro
From playlist Theory and Computation for 2D Materials 2020