# FDT

(redirected from Fluctuation-dissipation theorem)
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FDTFluctuation-Dissipation Theorem (statistical physics)
FDTField Device Tool
FDTFull Duplex Transhybrid
FDTFixed Disk Table
FDTFormal Description Techniques
FDTFull Duplex Tokenring
FDTFull Duplex Transmission
FDTField Definition Table
FDTFlat Display Trinitron
FDTFast Data Transfer (computing)
FDTFrequency Doubling Technology (glaucoma test)
FDTFranking Deficit Tax (Australia)
FDTFully-Differential Transconductor (electrical engineering)
FDTFormal Description Technique
FDTFermeture de Tahiti (French fence company)
FDTFrame Due Time
FDTForce Development Test
FDTFloodway Data Table (various locations)
FDTFlow Detection Transducer (wastewater monitoring)
FDTFlash Distribution Transport (France)
FDTFirst Destination Transportation
FDTFuzzy Distance Transform (bone imaging)
FDTFlight Dynamics Team
FDTForward Distribution Team (various armed forces)
FDTForward-Deployed Trainer
FDTFormal Design Theory
FDTFlight Data Transmitter
FDTFluxo de Dados Transfronteiras (Portuguese: Transboundary Flow Data)
References in periodicals archive ?
The canonical, isothermal ensemble is obtained by applying the fluctuation-dissipation theorem [35].
The fluctuation-dissipation theorem implies in turn that
Therefore, the fluctuation-dissipation theorem fixes the diffusion matrix once the drift matrix is determined.
His additional innovative ideas during that period include the use of Monte Carlo sampling as a computationally feasible means of estimating the uncertainty of weather forecasts, and the application of the fluctuation-dissipation theorem for estimating the climate response of the atmosphere.
Their topics include fluctuating hydrodynamics and fluctuation-dissipation theorem in equilibrium systems, non-equilibrium thermodynamics for evaporation and condensation, non-equilibrium thermodynamics of interfaces between aqueous solutions and crystals, minimizing entropy production with optimal control theory, mesoscopic non-equilibrium thermodynamics in biology, and the dynamics of complex fluid-fluid interfaces.
The random force [eta](t) is zero-centered and stationary Gaussian that obeys the generalized second fluctuation-dissipation theorem [67]:
When the internal noise [eta](t) in the generalized Langevin equation (9) is fractional Gaussian noise with correlation function (5), from the fluctuation-dissipation theorem (2), we derive the power-law memory kernel K(t) presented by Hurst exponent H, 0 < H < 1:
The fluctuation-dissipation theorem determines the properties of the noise, as shown in [31, 32].
Physically such a friction term has, due to the fluctuation-dissipation theorem, its origin in a non-Ohmic thermal bath, whose influence on the dynamical system is described with a powerlaw correlated additive noise in the GLE, e.g., with fractional Gaussian noise which is closely related to fractional Brownian motion [15,17].
It can be shown that, in order to maintain a well defined temperature by way of consistency with a fluctuation-dissipation theorem [3], coefficients describing the strength of the dissipative and random forces must be coupled.
The fluctuation-dissipation theorem (FDT) is concerned with the response of a system to small changes in the forcing.
Branstator, 2007: Climate response using a three-dimensional operator based on the fluctuation-dissipation theorem. J.
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