PAR

A barnstar for your extensive contributions to articles related to statistical mechanics! --HappyCamper

Subjects I'm working on- <br style="clear:both;" />

• References {{note_label|Wood1992||}} {{ref_harvard|Wood1992|Wood, 1992|}}
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1. -
2. Australian Trilobite Jump table
3. RGB
4. -
5. Pigment-loss color blindness
6. Peach
7. -
8. Template Test
9. Template Test

• equivlist

• Principle of maximum entropy
• Principle of maximum work
• Principle of minimum energy
• Minimum total potential energy principle

• Template talk:probability distribution#Status of usage
• Template talk:Prettytable and MediaWiki talk:Common.css
• verify μ is mode of Levy distribution
• Combine Heavy tail distribution and Long tail
• Mutation-selection balance | Quasispecies model | http://www.biomedcentral.com/1471-2148/5/44

Thermodynamics

• Thermodynamic Equations
• Laws of thermodynamics
• Ideal gas
• Sackur-Tetrode equation
• Gibbs paradox

Chi-square distributions

distribution	${\displaystyle \sigma ^{2}}$	${\displaystyle \nu }$
scale-inverse-chi-square distribution	${\displaystyle \sigma ^{2}}$	${\displaystyle \nu }$
inverse-chi-square distribution 1	${\displaystyle 1/\nu }$	${\displaystyle \nu }$
inverse-chi-square distribution 2	${\displaystyle 1}$	${\displaystyle \nu }$
inverse gamma distribution	${\displaystyle \beta /\alpha }$	${\displaystyle 2\alpha }$
Levy distribution	${\displaystyle c}$	${\displaystyle 1}$

Heavy tail distributions

Heavy tail distributions

Distribution	character	${\displaystyle \alpha }$
Levy skew alpha-stable distribution	continuous, stable	${\displaystyle 0\leq \alpha <2}$
Cauchy distribution	continuous, stable	${\displaystyle 1}$
Voigt distribution	continuous	${\displaystyle 1}$
Levy distribution	continuous, stable	${\displaystyle 1/2}$
scale-inverse-chi-square distribution	continuous	${\displaystyle \nu /2>0}$
inverse-chi-square distribution	continuous	${\displaystyle \nu /2>0}$
inverse gamma distribution	continuous	${\displaystyle \alpha >0}$
Pareto distribution	continuous	${\displaystyle k>0}$
Zipf's law	discrete	${\displaystyle s-1>-1???}$
Zipf-Mandelbrot law	discrete	${\displaystyle s-1>-1???}$
Zeta distribution	discrete	${\displaystyle s-1>-1???}$
Student's t-distribution	continuous	${\displaystyle \nu >0}$
Yule-Simon distribution	discrete	${\displaystyle \rho }$
? distribution	continuous	${\displaystyle s-1>-1???}$
Log-normal distribution???	continuous	${\displaystyle \rho }$
Weibull distribution???	?	${\displaystyle ?}$
Gamma-exponential distribution???	?	${\displaystyle ?}$

Statistical Mechanics

A Table of Statistical Mechanics Articles

	Maxwell Boltzmann	Bose-Einstein	Fermi-Dirac
Particle		Boson	Fermion
Statistics	Partition function Identical particles#Statistical properties Statistical ensemble|Microcanonical ensemble | Canonical ensemble | Grand canonical ensemble
Statistics	Maxwell-Boltzmann statistics Maxwell-Boltzmann distribution Boltzmann distribution Derivation of the partition function Gibbs paradox	Bose-Einstein statistics	Fermi-Dirac statistics
Thomas-Fermi approximation	gas in a box gas in a harmonic trap
Gas	Ideal gas	Bose gas Bose-Einstein condensate Planck's law of black body radiation	Fermi gas Fermion condensate
Chemical Equilibrium	Classical Chemical equilibrium

Others:

• Entropy
• Principle of maximum entropy

Continuum mechanics

• Boltzmann equation
• Navier-Stokes equations
• Fluid mechanics

• http://online.physics.uiuc.edu/courses/phys598OS/fall04/lectures/

Work pages

To fix:

• Degenerate distribution
• Fermi-Dirac statistics - not continuous, necessarily
• Bose gas (derive critical temperature)
• Spectral density-SPD Cat:Physics = Power spectrum-Cat:signal processing

(subtract mean)	(no subtract mean)
Covariance	Correlation
Cross covariance	Cross correlation see ext
Autocovariance	Autocorrelation
Covariance matrix	Correlation matrix
Estimation of covariance matrices

Proof: Introduce an additional heat reservoir at an arbitrary temperature T₀, as well as N cycles with the following property: the j-th such cycle operates between the T₀ reservoir and the T_j reservoir, transferring energy dQ_j to the latter. From the above definition of temperature, the energy extracted from the T₀ reservoir by the j-th cycle is

${\displaystyle dQ_{0,j}=T_{0}{\frac {dQ_{j}}{T_{j}}}\,\!}$ 

Now consider one cycle of the heat engine, accompanied by one cycle of each of the smaller cycles. At the end of this process, each of the N reservoirs have zero net energy loss (since the energy extracted by the engine is replaced by the smaller cycles), and the heat engine has done an amount of work equal to the energy extracted from the T₀ reservoir,

${\displaystyle W=\sum _{j=1}^{N}dQ_{0,j}=T_{0}\sum _{j=1}^{N}{\frac {dQ_{j}}{T_{j}}}\,\!}$ 

If this quantity is positive, this process would be a perpetual motion machine of the second kind, which is impossible. Thus,

${\displaystyle \sum _{i=1}^{N}{\frac {dQ_{i}}{T_{i}}}\leq 0\,\!}$ 

Now repeat the above argument for the reverse cycle. The result is

${\displaystyle \sum _{i=1}^{N}{\frac {dQ_{i}}{T_{i}}}=0\,\!}$  (reversible cycles)

In mathematics, it is often desireable to express a functional relationship ${\displaystyle f(x)\,}$  as a different function, whose argument is the derivative of f , rather than x . If we let y=df/dx  be the argument of this new function, then this new function is written ${\displaystyle f^{\star }(y)\,}$  and is called the Legendre transform of the original function.

• Random variable
• Random sequence
• Random number
• Pseudorandom number generator
• STOCHASTIC PROCESS
• Time series
• Stationary process
• Category:Random numbers
• Category:Stochastic processes
• Category:Noise
• Category:Statistics
• Category:Probability theory</nowiki>