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Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The Uncertainty Principle04:08

The Uncertainty Principle

Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He mathematically...
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...
The Entropy as a State Function01:14

The Entropy as a State Function

Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
Entropy and Solvation02:05

Entropy and Solvation

The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ ≥ 15); an...

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Related Experiment Video

Updated: May 18, 2026

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

Perturbations and chaos in quantum maps.

Darío E Bullo1, Diego A Wisniacki

  • 1Departamento de Física J J Giambiagi, FCEN, Universidad de Buenos Aires, 1428 Buenos Aires, Argentina.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 26, 2012
PubMed
Summary
This summary is machine-generated.

This study validates a semiclassical theory for the local density of states (LDOS) in quantum maps. The theory accurately describes quantum distributions and LDOS width, especially for chaotic systems and strong perturbations.

Related Experiment Videos

Last Updated: May 18, 2026

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

Area of Science:

  • Quantum mechanics
  • Statistical physics
  • Chaos theory

Background:

  • The local density of states (LDOS) quantifies perturbation effects in quantum systems.
  • A recent semiclassical theory proposed a Breit-Wigner distribution for LDOS in chaotic systems.
  • This theory predicts LDOS width via a semiclassical expression, independent of perturbation strength.

Purpose of the Study:

  • To test the accuracy of the proposed semiclassical theory for LDOS in quantum maps.
  • To investigate the influence of chaoticity, perturbation location, and intensity on LDOS predictions.
  • To evaluate the theory's performance across different dynamical regimes.

Main Methods:

  • Numerical simulations of quantum maps.
  • Systematic variation of system parameters: degree of chaoticity, perturbation region, and perturbation intensity.
  • Comparison of quantum mechanical LDOS with semiclassical predictions.

Main Results:

  • The semiclassical theory accurately describes the quantum LDOS for highly chaotic maps and strong perturbations.
  • The semiclassical expression for LDOS width is well-represented even in mixed classical dynamics.
  • The theory's validity is confirmed across tested parameter ranges.

Conclusions:

  • The semiclassical theory provides a robust framework for understanding LDOS in quantum chaotic systems.
  • The findings support the applicability of semiclassical methods for predicting quantum phenomena in complex systems.
  • This work advances the theoretical understanding of quantum chaos and its manifestations.