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Related Concept Videos

Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

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Related Experiment Video

Updated: Jun 7, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
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Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

Variational transcorrelated method.

Hongjun Luo1

  • 1Max-Planck-Institut für Mathematik in den Naturwissenschaften, Inselstr. 22-26, Leipzig D-04103, Germany. hluo@mis.mpg.de

The Journal of Chemical Physics
|October 26, 2010
PubMed
Summary

This study introduces a novel method for calculating electron correlations using the Jastrow ansatz, modifying the transcorrelated approach. The new technique offers a flexible way to optimize wave functions for improved accuracy in quantum chemistry calculations.

Area of Science:

  • Quantum Chemistry
  • Computational Physics

Background:

  • Electron correlation is crucial for accurate molecular simulations.
  • The transcorrelated method offers a way to include electron correlation.
  • Jastrow ansatz provides a compact representation of correlated wave functions.

Purpose of the Study:

  • To develop a new, versatile approach for calculating electron correlations.
  • To modify the Boys and Handy transcorrelated method for broader applicability.
  • To enable optimization of both single- and multi-determinant Jastrow wave functions.

Main Methods:

  • Modification of the transcorrelated method.
  • Replacement of the original transcorrelated orbital equation with a general variational equation.
  • Application to single- and multi-determinant Jastrow ansatz.

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  • Derivation of Hartree-Fock type and CI type equations for orbital optimization.
  • Main Results:

    • A new self-consistent equation for orbital optimization in the single-determinant Jastrow ansatz.
    • Successful application to the C(2) molecule.
    • Comparison of results with variational quantum Monte Carlo calculations.

    Conclusions:

    • The proposed method provides a robust framework for electron correlation calculations.
    • The approach is applicable to various Jastrow ansatz types.
    • The method shows promise for accurate molecular electronic structure studies.