Post-Hartree–Fock methods

Quantum chemistry composite methods

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 chemistry composite methods
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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

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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

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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

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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

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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

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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

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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

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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

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Quantized Energy Equation (Quantum Physics)

#Quantum #Physics #Engineering #tiktok #NicholasGKK #shorts

From playlist Quantum Mechanics

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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

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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

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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

From playlist IIT Delhi: Nano structured materials-synthesis, properties, self assembly and applications | CosmoLearning.org Materials Science

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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

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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

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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

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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

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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

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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

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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

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Zero-point energy | Hybrid functional | Møller–Plesset perturbation theory | Hamiltonian mechanics | Quadratic configuration interaction | Density functional theory | Spartan (chemistry software) | Coupled cluster