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Related Concept Videos

Pressure and Volume in an Adiabatic Process01:27

Pressure and Volume in an Adiabatic Process

Free expansion of a gas is an adiabatic process. However, there are few differences between free expansion and adiabatic expansion. During free expansion, no work is done, and there is no change in internal energy. But, for an adiabatic expansion, work is done, and there is a change in internal energy. During an adiabatic process, the relation between the pressure and volume is obtained from the condition for the adiabatic process, that is,
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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this particular...
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Phantom instabilities in adiabatically driven systems: dynamical sensitivity to computational precision.

Haider Hasan Jafri1, Thounaojam Umeshkanta Singh, Ramakrishna Ramaswamy

  • 1School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110 067, India.

Chaos (Woodbury, N.Y.)
|October 2, 2012
PubMed
Summary
This summary is machine-generated.

Numerical precision is crucial for studying nonlinear mappings. Low precision can lead to phantom instabilities, causing deviations from true dynamics in adiabatic systems.

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Area of Science:

  • Nonlinear dynamics
  • Dynamical systems theory
  • Computational physics

Background:

  • Adiabatically driven nonlinear mappings with skew-product structure exhibit complex dynamical phenomena.
  • Numerical simulations are essential for analyzing these systems but can be susceptible to precision errors.

Purpose of the Study:

  • To investigate the robustness of dynamical phenomena in adiabatically driven nonlinear mappings under varying numerical precision.
  • To understand how inadequate numerical precision affects the observed dynamics, particularly the emergence of instabilities.

Main Methods:

  • Analysis of nonlinear mappings with skew-product structure under adiabatic driving.
  • Simulations employing different levels of numerical precision to track orbital behavior.
  • Examination of deviations from true orbits caused by computational errors.

Main Results:

  • Inadequate numerical precision leads to deviations from true orbits for monotone, periodic, or quasiperiodic driving.
  • Slow modulation can 'freeze' orbits, but low precision introduces phantom instabilities.
  • Observed dynamics are sensitive to numerical precision, with errors building up over time.

Conclusions:

  • Finite precision computations can misrepresent the true dynamics of adiabatic nonlinear systems.
  • The minimum required numerical accuracy is linked to the system's internal timescale.
  • Careful consideration of numerical precision is essential for reliable analysis of these dynamical systems.