Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

124
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
124
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
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...
100
Conservation of Linear Momentum for a System of Particles01:28

Conservation of Linear Momentum for a System of Particles

274
In the dynamic realm of billiards, a fascinating interplay of forces governs the motion of cue balls and stationary balls. When the cue ball collides with a stationary ball, linear momentum is exchanged. The cue ball imparts a fraction of its linear momentum to the stationary ball, causing the cue ball to decelerate while initiating the motion of the stationary ball.
The impulsive force at play during this interaction is of extremely short duration, rendering its impulse negligible. When...
274
Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

501
Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
501
Euler Equations of Motion01:19

Euler Equations of Motion

321
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...
321
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

131
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
131

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Sep 10, 2025

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

657

Algoritmo cuántico de marcha en el tiempo para la simulación de la dinámica de Lorenz no lineal

Efstratios Koukoutsis1, George Vahala2, Min Soe3

  • 1School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Zographou, Greece.

Entropy (Basel, Switzerland)
|August 28, 2025
PubMed
Resumen

Este estudio presenta un algoritmo cuántico para simular el modelo no lineal de Lorenz, superando la mecánica cuántica

Palabras clave:
Producto de HadamardEl sistema de LorenzCodificación de bloque de SVDCombinación lineal de unidadesecuaciones diferenciales ordinarias no linealesestructura recurrentealgoritmo cuántico de marcha en el tiempo

Más Videos Relacionados

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.6K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.1K

Videos de Experimentos Relacionados

Last Updated: Sep 10, 2025

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

657
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.6K
Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.1K

Área de la Ciencia:

  • La computación cuántica
  • Física computacional
  • Teoría del Caos

Sus antecedentes:

  • La formulación lineal de la mecánica cuántica plantea desafíos para simular la dinámica clásica no lineal.
  • El modelo de Lorenz es un sistema fundamental en la teoría del caos, la ciencia del clima y la dinámica de fluidos.

Objetivo del estudio:

  • Desarrollar un algoritmo cuántico explícito para simular la evolución temporal del modelo de Lorenz.
  • Abordar las dificultades inherentes a la simulación de la dinámica no lineal en computadoras cuánticas.

Principales métodos:

  • Desarrolló un algoritmo cuántico que implementa un modelo de Lorenz de segundo orden.
  • El algoritmo tiene una estructura recursiva.
  • Requiere un número lineal de copias de estado inicial en relación con los pasos de tiempo.

Principales resultados:

  • El algoritmo cuántico logra una escala lineal en las copias de estado inicial, mejorando los métodos anteriores.
  • Preserva las ventajas de aceleración cuántica en la dimensionalidad del sistema.
  • La implementación clásica reprodujo con precisión los atractores del sistema Lorenz (ciclos límite y caóticos).

Conclusiones:

  • El algoritmo cuántico propuesto ofrece un método eficiente para simular sistemas clásicos no lineales como el modelo de Lorenz.
  • Demuestra el potencial de la computación cuántica para el avance de la teoría del caos y campos científicos relacionados.