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Polar Equations of Conics01:29

Polar Equations of Conics

A conic section can be defined in polar coordinates as the set of all points whose distance from a fixed point, known as the focus, bears a constant ratio to their distance from a fixed line, known as the directrix. This constant ratio is called the eccentricity. This definition unifies all types of conic sections—ellipses, parabolas, and hyperbolas—under a single framework. When the focus is positioned at the origin of the polar coordinate system, a single polar equation can describe any conic...
Fermi Level Dynamics01:12

Fermi Level Dynamics

The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
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The work...
Circular Orbits and Critical Velocity for Satellites01:16

Circular Orbits and Critical Velocity for Satellites

The Moon orbits around the Earth. In turn, the Earth (and other planets) orbit the Sun. The space directly above our atmosphere is filled with artificial satellites in orbit. One can examine the circular orbit, the simplest kind of orbit, to understand the relationship between the speed and the period of planets and satellites with respect to their positions and the bodies that they orbit.
Nicolaus Copernicus (1473-1543) first suggested that the Earth and all other planets orbit the Sun in...
Numerical Calculations01:24

Numerical Calculations

In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
The solution to a problem is obtained using different methods. While manually solving algebraic symbols is one of the most common methods, the graphical method is often preferred. Computers...
Atomic Orbitals02:44

Atomic Orbitals

An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
Euler Equations of Motion01:19

Euler Equations of Motion

Imagine a rigid body that is rotating at an angular velocity of ω within an inertial frame of reference. Along with this, picture a second rotating frame that is attached to the body itself. This frame moves along with the body and possesses an angular velocity of Ω. The total moment about the center of mass is calculated by adding the rate of change of angular momentum about the center of mass in relation to the rotating frame and the cross-product of the body's angular velocity and its...

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Related Experiment Video

Updated: May 19, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

GPGPU for orbital function evaluation with a new updating scheme.

Yutaka Uejima1, Ryo Maezono

  • 1School of Information Science, JAIST, Asahidai 1-1, Nomi, Ishikawa 923-1292, Japan.

Journal of Computational Chemistry
|September 4, 2012
PubMed
Summary
This summary is machine-generated.

We accelerated quantum Monte Carlo (QMC) calculations using graphical processing units (GPUs), achieving a 30x speedup for electronic structure simulations. A new Monte Carlo updating scheme also improved performance while maintaining high accuracy.

Related Experiment Videos

Last Updated: May 19, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Area of Science:

  • Computational Physics
  • Quantum Chemistry
  • Materials Science

Background:

  • Ab initio quantum Monte Carlo (QMC) methods are computationally intensive for electronic structure calculations.
  • Accelerating these calculations is crucial for studying complex systems like solid titanium dioxide (TiO2).

Purpose of the Study:

  • To accelerate ab initio quantum Monte Carlo electronic structure calculations using general-purpose computing on graphical processing units (GPGPU).
  • To introduce and evaluate a novel Monte Carlo updating scheme for enhanced computational efficiency.

Main Methods:

  • Implemented Compute Unified Device Architecture-GPGPU subroutine kernels to replace the bottleneck in existing QMC code.
  • Developed and integrated a quasi-simultaneous updating scheme for Monte Carlo sampling.
  • Performed simulations of solid TiO2 with 1536 electrons using single precision arithmetic.

Main Results:

  • Achieved a significant speedup factor of 30 for the bottleneck in the QMC calculation.
  • Demonstrated that the new quasi-simultaneous updating scheme is effective and balances accuracy with speed.
  • Confirmed that the energy error from single precision and the new updating scheme remains within the desired accuracy of ~10(-3) hartree per primitive cell.

Conclusions:

  • GPGPU acceleration offers a substantial performance improvement for ab initio QMC electronic structure calculations.
  • The proposed quasi-simultaneous updating scheme provides an efficient alternative for Monte Carlo sampling in QMC.
  • The combined approach enables accurate and faster electronic structure simulations for materials like TiO2.