Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Methods of Obtaining Topography01:25

Methods of Obtaining Topography

446
Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
446
Three-Dimensional Analysis of Strain01:29

Three-Dimensional Analysis of Strain

722
Three-dimensional strain analysis is crucial for understanding how materials deform under stress, particularly in elastic, homogeneous materials. This method employs principal stress axes to simplify complex stress states into more understandable forms. Subjected to stress, a small cubic element within a material either expands or contracts along these axes, transforming into a rectangular parallelepiped. This transformation effectively illustrates the material's deformation. The principal...
722
DNA Topoisomerases02:02

DNA Topoisomerases

37.4K
Topoisomerases are enzymes that relax overwound DNA molecules during various cell processes, including DNA replication and transcription. These enzymes regulate positive and negative DNA supercoiling without changing the nucleotide sequence. DNA overwinding in a clockwise direction results in positively supercoiled DNA, whereas underwinding in a counterclockwise direction produces negatively supercoiled DNA.
Types and Mechanism of action
Topoisomerases are divided into two main types. ...
37.4K
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

18.6K
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...
18.6K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

715
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
715
Coordination Number and Geometry02:57

Coordination Number and Geometry

19.7K
For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
19.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Retrocausal Capacity of a Quantum Channel: Communicating through Noisy Closed Timelike Curves.

Physical review letters·2026
Same author

Quantum Stroboscopy for Time Measurements.

Physical review letters·2026
Same author

Maximizing Free Energy Gain.

Entropy (Basel, Switzerland)·2025
Same author

Author Correction: Quantum computational finance for martingale asset pricing in incomplete markets.

Scientific reports·2024
Same author

Quantum computational finance for martingale asset pricing in incomplete markets.

Scientific reports·2024
Same author

Unscrambling Quantum Information with Clifford Decoders.

Physical review letters·2024

Related Experiment Video

Updated: Mar 26, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.2K

Quantum algorithms for topological and geometric analysis of data.

Seth Lloyd1, Silvano Garnerone2, Paolo Zanardi3

  • 1Department of Mechanical Engineering, Research Lab for Electronics, Massachusetts Institute of Technology, MIT 3-160, Cambridge, Massachusetts 02139, USA.

Nature Communications
|January 26, 2016
PubMed
Summary

Quantum machine learning algorithms accelerate topological data analysis by efficiently calculating Betti numbers and Laplacian eigenvectors/eigenvalues. This offers an exponential speed-up for extracting insights from large datasets using persistent homology.

More Related Videos

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
12:45

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Published on: August 31, 2022

3.8K
Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser
09:00

Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser

Published on: June 28, 2018

10.6K

Related Experiment Videos

Last Updated: Mar 26, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.2K
Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
12:45

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Published on: August 31, 2022

3.8K
Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser
09:00

Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser

Published on: June 28, 2018

10.6K

Area of Science:

  • Computational topology
  • Quantum computing
  • Data science

Background:

  • Extracting meaningful information from large datasets is challenging.
  • Topological data analysis (TDA) offers powerful methods for feature identification.
  • Persistent homology is a key TDA technique for analyzing data at multiple scales.

Purpose of the Study:

  • To develop quantum machine learning algorithms for TDA.
  • To compute Betti numbers and combinatorial Laplacian eigenvalues/eigenvectors.
  • To achieve significant speed-ups over classical TDA algorithms.

Main Methods:

  • Quantum machine learning algorithms.
  • Persistent homology computations.
  • Calculation of Betti numbers and Laplacian spectra.

Main Results:

  • Development of quantum algorithms for Betti number calculation.
  • Quantum algorithms for finding Laplacian eigenvectors and eigenvalues.
  • Demonstrated exponential speed-up compared to classical TDA algorithms.

Conclusions:

  • Quantum machine learning provides a powerful new approach for topological data analysis.
  • The developed algorithms significantly enhance the efficiency of TDA.
  • This work paves the way for faster and more scalable data analysis.