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

Quantum Numbers02:43

Quantum Numbers

52.1K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
52.1K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

59.5K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
59.5K
Inverse Trigonometric Functions01:29

Inverse Trigonometric Functions

305
Inverse trigonometric functions are fundamental mathematical tools that reverse the actions of standard trigonometric functions. While trigonometric functions map angles to ratios, inverse trigonometric functions perform the opposite operation by mapping a ratio back to its corresponding angle. These functions are essential in various applications, particularly in determining angles when given specific distances, such as calculating elevation angles in navigation and engineering.For a function...
305
Inverse Hyperbolic Functions and Their Derivatives01:25

Inverse Hyperbolic Functions and Their Derivatives

81
The shape of a suspension bridge cable hanging under its own weight is described by a catenary curve, which is modeled using the hyperbolic cosine function. This mathematical model accurately captures the balance between gravity and tension acting along the cable. When a particular vertical position on the cable is known, the corresponding horizontal position can be determined using the inverse hyperbolic cosine function, allowing for a detailed analysis of the cable's geometry.Inverse...
81
Derivatives of Inverse Trigonometric Functions01:30

Derivatives of Inverse Trigonometric Functions

434
A ship tracking an approaching aircraft relies on geometric measurements to find out the aircraft’s position relative to the observer. By measuring the slant distance to the aircraft and the angle of elevation, the horizontal and vertical components of the distance can be obtained using trigonometric relationships. This geometric approach provides a basis for analyzing how the observed angle changes as the aircraft moves closer to the ship.To examine the mathematical behavior of the angle...
434
Hyperbolic and Inverse Hyperbolic Functions: Problem Solving01:30

Hyperbolic and Inverse Hyperbolic Functions: Problem Solving

131
An arched gate can be effectively modeled using a hyperbolic cosine profile because this type of function is smooth and symmetric about the vertical axis. When the arch is centered at the origin, its maximum height occurs at the center point. This symmetry ensures that any height below the crown of the arch is reached at two horizontal positions that are equal in distance from the centerline but lie on opposite sides.To determine where the gate reaches a height of five meters, the height of the...
131

You might also read

Related Articles

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

Sort by
Same author

Material Fracturing and Failure Simulation Datasets.

Scientific data·2025
Same author

Aerial imagery dataset of lost oil wells.

Scientific data·2024
Same author

Nonnegative/Binary matrix factorization with a D-Wave quantum annealer.

PloS one·2018
See all related articles

Related Experiment Video

Updated: Feb 11, 2026

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations
10:30

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Published on: September 11, 2016

11.4K

An approach to quantum-computational hydrologic inverse analysis.

Daniel O'Malley1

  • 1Computational Earth Science Group, Los Alamos National Laboratory, Los Alamos, NM, 87507, USA. omalled@lanl.gov.

Scientific Reports
|May 4, 2018
PubMed
Summary

Quantum computing is now capable of solving hydrologic inverse problems for aquifer characterization. This new method uses quantum annealers to infer subsurface properties, paving the way for quantum-computational hydrology.

More Related Videos

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
08:42

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

Published on: August 29, 2014

8.8K
Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
06:37

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

9.7K

Related Experiment Videos

Last Updated: Feb 11, 2026

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations
10:30

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Published on: September 11, 2016

11.4K
An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
08:42

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

Published on: August 29, 2014

8.8K
Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
06:37

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

9.7K

Area of Science:

  • Geosciences
  • Computational Science
  • Quantum Computing

Background:

  • Accurate aquifer flow and transport predictions depend on understanding heterogeneous properties like permeability.
  • Computational inverse analysis infers these properties from observable data, such as hydraulic head.
  • Quantum computing offers a novel approach to complex computational problems.

Purpose of the Study:

  • To present a computational inverse analysis method using a quantum annealer for hydrologic problems.
  • To demonstrate the feasibility of quantum computing for solving subsurface flow and transport problems.
  • To explore the potential of quantum-computational hydrology.

Main Methods:

  • Utilized a D-Wave 2X quantum annealer for computational inverse analysis.
  • Applied the method to solve one-dimensional (1D) and two-dimensional (2D) hydrologic inverse problems.
  • Compared the scale of quantum-solved problems to early classical computational hydrology.

Main Results:

  • Successfully solved 1D and 2D hydrologic inverse problems using a quantum annealer.
  • Demonstrated that current quantum computing technology is sufficient for certain subsurface flow applications.
  • The size of solved problems was comparable to or larger than those solved by early classical computers.

Conclusions:

  • Quantum computing, specifically quantum annealers, can be effectively applied to hydrologic inverse problems.
  • The study validates the use of quantum computation for inferring aquifer properties.
  • The findings suggest a promising future for quantum-computational hydrology as the technology advances.