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Videos de Conceptos Relacionados

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

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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.
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Fermi Level Dynamics01:12

Fermi Level Dynamics

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The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
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Biasing of Metal-Semiconductor Junctions01:27

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Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
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Biasing of FET01:22

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Biasing a Junction Field Effect Transistor (JFET) is crucial for setting operational parameters and ensuring efficient functioning in electronic circuits. JFETs are characterized by using a single carrier type in N-channel or P-channel configurations, where the channel is surrounded by PN junctions. These junctions are central to the device's ability to control current flow.
In an N-channel JFET, the structure consists of N-type material forming the channel on a P-type substrate, with the...
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Equilibrium Conditions for a Particle01:23

Equilibrium Conditions for a Particle

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When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
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Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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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
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Video Experimental Relacionado

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Montecarlo cuántico fermiónico sin sesgo con una computadora cuántica

William J Huggins1, Bryan A O'Gorman2, Nicholas C Rubin3

  • 1Google Quantum AI, Mountain View, CA, USA. whuggins@google.com.

Nature
|March 17, 2022
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce un enfoque híbrido cuántico-clásico para resolver problemas complejos de muchos electrones. Al combinar el Montecarlo cuántico restringido (QMC) con la computación cuántica, reduce los sesgos en las simulaciones de sistemas químicos.

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Área de la Ciencia:

  • Química computacional
  • La computación cuántica
  • Física cuántica de muchos cuerpos

Sus antecedentes:

  • Los problemas de muchos electrones que interactúan son computacionalmente intensivos, lo que dificulta las predicciones precisas de las propiedades del sistema cuántico.
  • Los métodos de Montecarlo cuántico fermiónico (QMC) son potentes, pero se enfrentan a sesgos debido a las limitaciones computacionales.
  • El cálculo clásico limita la flexibilidad de QMC restringido, lo que afecta a la precisión.

Objetivo del estudio:

  • Desarrollar un enfoque híbrido cuántico-clásico para mitigar los sesgos en QMC restringido.
  • Aprovechar la computación cuántica para mejorar la precisión de los cálculos de la estructura electrónica.
  • Para explorar una nueva vía para lograr ventaja cuántica en química computacional.

Principales métodos:

  • Combinando el Monte Carlo cuántico restringido (QMC) con la computación cuántica.
  • Implementación experimental utilizando hasta 16 qubits.
  • Aplicación en sistemas químicos con hasta 120 orbitales.

Principales resultados:

  • Se han reducido con éxito los sesgos en los cálculos QMC restringidos.
  • La precisión alcanzada es competitiva con los métodos clásicos de última generación.
  • Demostró las simulaciones químicas más grandes realizadas con computadoras cuánticas hasta la fecha.
  • Se han evitado técnicas de mitigación de errores onerosas.

Conclusiones:

  • El modelo híbrido cuántico-clásico propuesto ofrece una alternativa viable al solucionador cuántico variacional para problemas de estructura electrónica.
  • Este enfoque proporciona un camino hacia la ventaja cuántica práctica sin requerir una preparación y medición perfectas de la función de onda del estado fundamental.
  • El método aborda efectivamente los desafíos computacionales planteados por la interacción de sistemas de muchos electrones.