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

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

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. Schrödinger...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...
Subatomic Particles03:37

Subatomic Particles

Dalton was only partially correct about the particles that make up matter. All matter is composed of atoms, and atoms are composed of three smaller subatomic particles: protons, neutrons, and electrons. These three particles account for the mass and the charge of an atom.
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Classical Mechanics01:12

Classical Mechanics

Classical mechanics provides a mathematical description of the motion of bodies under the influence of forces. A key principle within this field is the work-energy theorem, which establishes a bridge between the net work done on an object and its kinetic energy.The work-energy theorem states that the net work done on a particle by all the forces acting on it equals the change in its kinetic energy.In simple terms, the work-energy theorem is a method to analyze the effects of forces on an...

You might also read

Related Articles

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

Sort by
Same author

Mapping the crystallization landscape of rare earth MOFs: a high-throughput investigation of structure, kinetics, and selectivity.

Chemical science·2026
Same author

Quantitative prediction of siRNA complexation by ionizable drugs enables their codelivery in nanoparticles.

Science advances·2026
Same author

Lessons From Drug Discovery for Cryoprotective Agent Design: An AI-Oriented Perspective.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Photochemical post-functionalization of polystyrene enables accelerated chemical recycling.

Chemical science·2026
Same author

Adsorption Hysteresis Under Control: Tuning Host-Guest Interactions via a Genetic Algorithm.

ACS nano·2026
Same author

Discovery of tunable and soluble organic emitters for solid-state lasers with a self-driving laboratory.

Nature communications·2026

Related Experiment Video

Updated: Jul 12, 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

El Agente Cuántico: Automating quantum simulations.

Ignacio Gustin1, Luis Carlos Mantilla Calderon2, Juan B Perez-Sanchez1

  • 1Chemistry, University of Toronto - St George Campus, 80 St. George St., Toronto, Ontario, M5S 3H6, Canada.

Reports on Progress in Physics. Physical Society (Great Britain)
|July 10, 2026
PubMed
Summary

This study introduces El Agente Cuántico, an AI system that automates quantum simulations using natural language. It simplifies complex quantum computations, making quantum system exploration more accessible and efficient.

Keywords:
AI for ScienceAgentsAutonomous workflowsMulti-agent systemsQuantum simulation automationQuantum software interoperability.

Related Experiment Videos

Last Updated: Jul 12, 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

Area of Science:

  • Quantum physics and chemistry
  • Computational science

Background:

  • Quantum simulation is crucial for understanding quantum systems but faces challenges due to large Hilbert spaces and complex software.
  • Existing quantum simulation tools require specialized expertise, limiting broader accessibility.

Purpose of the Study:

  • To develop an AI system that automates quantum simulation workflows.
  • To bridge the gap between scientific intent and computational execution in quantum simulations.
  • To unify diverse quantum simulation methods under a single natural-language interface.

Main Methods:

  • Introduction of El Agente Cuántico, a multi-agent AI system.
  • The system translates natural-language scientific intent into executable quantum simulations.
  • It reasons over library documentation and APIs to dynamically assemble simulation workflows.

Main Results:

  • The AI system automates end-to-end quantum simulations, including state preparation, dynamics, tensor-network methods, and more.
  • It successfully integrates and validates computations across heterogeneous quantum-software frameworks.
  • El Agente Cuántico unifies distinct simulation paradigms through a natural-language interface.

Conclusions:

  • El Agente Cuántico significantly reduces technical barriers in quantum simulation.
  • This approach enables scalable, adaptive, and autonomous quantum simulations.
  • It accelerates the exploration of physical models and hypothesis testing in quantum science.