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Related Experiment Video

Updated: May 28, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

A numerical projection technique for large-scale eigenvalue problems.

Ralf Gamillscheg1, Gundolf Haase, Wolfgang von der Linden

  • 1Institute of Theoretical Physics - Computational Physics, Graz University of Technology, Graz, Austria.

Computer Physics Communications
|October 5, 2011
PubMed
Summary
This summary is machine-generated.

We developed a novel numerical method for solving large eigenvalue problems, generalizing projection techniques. This approach converges to exact eigenvalues and applies to various scientific fields.

Related Experiment Videos

Last Updated: May 28, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Area of Science:

  • Numerical Analysis
  • Quantum Many-Body Physics

Background:

  • Large-scale eigenvalue problems are common in quantum many-body systems and other scientific domains.
  • Existing projection techniques offer approximate solutions by simplifying models.

Purpose of the Study:

  • To introduce a generalized numerical technique for solving large-scale eigenvalue problems.
  • To develop a method that converges to exact eigenvalues, unlike standard projection techniques.

Main Methods:

  • A novel numerical approach generalizing projection techniques.
  • Numerical implementation of both model construction and eigenvalue solving steps.
  • Application to two specific many-body models for validation.

Main Results:

  • The generalized technique converges in principle to exact eigenvalues.
  • Demonstrated applicability to large-scale eigenvalue problems with dominant diagonal matrices.
  • Validation through detailed studies on two many-body models.

Conclusions:

  • The presented numerical technique offers an accurate and versatile solution for large-scale eigenvalue problems.
  • This method extends beyond quantum many-body systems to other research areas requiring efficient eigenvalue solvers.