Editing Grand canonical Monte Carlo
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'''Grand-canonical ensemble Monte Carlo''' (GCEMC | '''Grand-canonical ensemble Monte Carlo''' (GCEMC) is a very versatile and powerful [[Monte Carlo]] technique that explicitly accounts for density fluctuations at fixed volume and [[temperature]]. This is achieved by means of trial insertion and deletion of molecules. Although this feature has made it the preferred choice for the study of [[Interface |interfacial]] phenomena, in the last decade | ||
[[grand canonical ensemble | grand-canonical ensemble]] simulations have also found widespread applications in the study of bulk properties. Such applications had been hitherto limited by the very low particle insertion and deletion probabilities, but the development of the [[Configurational bias Monte Carlo |configurational bias]] grand canonical technique has very much improved the situation. | [[grand canonical ensemble | grand-canonical ensemble]] simulations have also found widespread applications in the study of bulk properties. Such applications had been hitherto limited by the very low particle insertion and deletion probabilities, but the development of the [[Configurational bias Monte Carlo |configurational bias]] grand canonical technique has very much improved the situation. | ||
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randomly. The trial move is then accepted or rejected according to the | randomly. The trial move is then accepted or rejected according to the | ||
usual Monte Carlo lottery. | usual Monte Carlo lottery. | ||
As usual, a trial move from | As usual, a trial move from state <math>o</math> to state <math>n</math> is accepted with probability | ||
:<math> acc(o \rightarrow n) = min \left (1, q \right ) </math> | :<math> acc(o \rightarrow n) = min \left (1, q \right ) </math> | ||
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probability), while <math>f(o)</math> is the probability density of state <math>o</math>. | probability), while <math>f(o)</math> is the probability density of state <math>o</math>. | ||
As noted by | As noted by Filinov, evaluation of the proper acceptance rules requires very carefull interpretation of the (clasical) grand canonical probability density: | ||
:<math> f_L({\mathbf r}_1,{\mathbf r}_2 ..., {\mathbf r}_N) \propto \frac{\Lambda^{-3N}}{N!} e^{\beta \mu N} e^{-\beta U_N}\qquad\qquad\text{(2)} </math> | :<math> f_L({\mathbf r}_1,{\mathbf r}_2 ..., {\mathbf r}_N) \propto \frac{\Lambda^{-3N}}{N!} e^{\beta \mu N} e^{-\beta U_N}\qquad\qquad\text{(2)} </math> | ||
where <math>N</math> is the total number of particles, <math>\mu</math> is the [[chemical potential]], <math>\beta := 1/k_B T</math> and <math>\Lambda</math> is the [[De | where <math>N</math> is the total number of particles, <math>\mu</math> is the [[chemical potential]], <math>\beta := 1/k_B T</math> and <math>\Lambda</math> is the de [[De Broglie thermal wavelength]]. | ||
The sub-index ''L'' makes emphasis on a particular definition of | The sub-index ''L'' makes emphasis on a particular definition of microstate in which particles are assumed to be distinguishable. Thus, <math> f_L </math> should be interpreted as the probability density of a classical state with labelled particles, having labelled particle 1 in position <math>{\mathbf r}_1</math>, labelled particle 2 in position <math>{\mathbf r}_2</math> and so on. Since labelling of the particles has no physical significance whatsoever, there are <math>N!</math> identical states which result from permutation of the labels (this explains the <math>N!</math> term in the denominator). Hence, the probability of the significant microstate of undistinguishable particles, i.e., one with <math>N</math> particles at positions <math> {\mathbf r}_1</math>, <math> {\mathbf r}_2</math>, etc., irrespective of the labels, will be given by: | ||
:<math> f_U( \{{\mathbf r}_1,{\mathbf r}_2 ..., {\mathbf r}_N \} ) \propto \sum_P | :<math> f_U( \{{\mathbf r}_1,{\mathbf r}_2 ..., {\mathbf r}_N \} ) \propto \sum_P | ||
f({\mathbf r}_1,{\mathbf r}_2 ..., {\mathbf r}_N) = \Lambda^{-3N} e^{\beta \mu N} e^{-\beta U_N}</math> | |||
where the <math>U</math> subindex stands for ''unlabelled'', the coordinates in | where the <math>U</math> subindex stands for ''unlabelled'', the coordinates in parentheis indicate that the positions are not atributted to any particular choice of labelling and the sum runs over all posible particle label permutations. | ||
Upon trial insertion of an extra particle, one obtains: | Upon trial insertion of an extra particle, one obtains: | ||
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:<math> \frac{\alpha(n\rightarrow o)}{\alpha(o\rightarrow n)} = | :<math> \frac{\alpha(n\rightarrow o)}{\alpha(o\rightarrow n)} = | ||
\frac{\alpha( N | \frac{\alpha( N \rightarrow N+1 )}{\alpha( N+1 \rightarrow N)} = \frac{V}{N+1} \qquad\qquad\text{(4)}</math> | ||
Substitution of Eq.(3) and Eq.(4) into Eq.(1) yields the | Substitution of Eq.(3) and Eq.(4) into Eq.(1) yields the | ||
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The same acceptance rules are obtained in reference books. Usually the problem of proper counting of states is circumvented by ignoring the labelling problem and assuming that the underlying probabilities for insertion and removal are equal. | The same acceptance rules are obtained in reference books. Usually the problem of proper counting of states is circumvented by ignoring the labelling problem and assuming that the underlying probabilities for insertion and removal are equal. | ||
== References == | |||
== References == | # G. E. Norman and V. S. Filinov "Investigations of phase transitions by a Monte-Carlo method", High Temperature '''7''' pp. 216-222 (1969) | ||
#[http://dx.doi.org/10.1080/00268977400102551 D. J. Adams "Chemical potential of hard-sphere fluids by Monte Carlo methods", Molecular Physics '''28''' pp. 1241-1252 (1974)] | |||
#[http://dx.doi.org/10.1063/1.2839302 Attila Malasics, Dirk Gillespie, and Dezső Boda "Simulating prescribed particle densities in the grand canonical ensemble using iterative algorithms", Journal of Chemical Physics '''128''' 124102 (2008)] | |||
[[Category: Monte Carlo]] | [[Category: Monte Carlo]] |