Similarly to the derivation of the Gibbs-Boltzmann distribution for structureless indistinguishable particles, we consider multi-particle systems some of which are contained (or delimited) inside others (Problem 1), as well as systems of particles delimited within other particles, which, in turn, are delimited yet inside another kind of particles (Problem 2). Under the natural assumptions concerning the conservation laws, such as the conservation of the total number of particles, total energy, etc, the problem of the most probable energy distributions is studied in a combinatorial formulation, with the obtained distributions treated as externally observable. For Problem 1, the particle distributions over maximal and minimal energies are also established and shown to coincide with the ones found in the framework of the original combinatorial treatment. The results for Problems 1 and 2 can be interpreted as a sorting of lower-level particles based on their statistical mechanics behavior observed in various experiments. An effective Pauli principle arises in a non-contradictory manner in one-particle observations for the complete probabilistic Problem 1 in the combinatorial formulation as well as in the problem of distributions over maximal and minimal energies. Several of the calculated distributions describe particles having no negative energy states.
Similarly to the derivation of the Gibbs-Boltzmann distribution for structureless indistinguishable particles, we consider multi-particle systems some of which are contained (or delimited) inside others (Problem 1), as well as systems of particles delimited within other particles, which, in turn, are delimited yet inside another kind of particles (Problem 2). Under the natural assumptions concerning the conservation laws, such as the conservation of the total number of particles, total energy, etc, the problem of the most probable energy distributions is studied in a combinatorial formulation, with the obtained distributions treated as externally observable. For Problem 1, the particle distributions over maximal and minimal energies are also established and shown to coincide with the ones found in the framework of the original combinatorial treatment. The results for Problems 1 and 2 can be interpreted as a sorting of lower-level particles based on their statistical mechanics behavior observed in various experiments. An effective Pauli principle arises in a non-contradictory manner in one-particle observations for the complete probabilistic Problem 1 in the combinatorial formulation as well as in the problem of distributions over maximal and minimal energies. Several of the calculated distributions describe particles having no negative energy states.
Many-particle systems contained inside other particles (problem 1), as well as systems of particles delimited inside other particles, which, in turn, are delimited inside the third particles (problem 2), are considered. Under natural assumptions about conserved quantities such as the total number of all particles, the total energy, and a number of others, the most probable energy distributions of particles, true (internal) and external observables, are studied. The results of problems 1 and 2 can be interpreted as the separation of bottom level particles into kinds with different distributions observed in different experiments. In single-particle observations in the full probability problem 1, an effective Pauli principle arises in a consistent manner.
The statistical problem of the distribution of s quanta of equal energy ε0 and total energy E among N distinguishable particles is resolved using the conventional theory based on Boltzmann's principle of equal probabilities of configurations of particles distributed among energy levels and the concept of average state. In particular, the probability that a particle is in the \k{appa}-th energy level i.e. contains \k{appa} quanta, is given by p(κ)=(N−1N+s−1)(N−2N+s−κ−2);κ=0,1,2,⋯,s In this context, the special case (N=4, s=4) presented indicates that the alternative concept of most probable state is not valid for finite values of s and N. In the present article we derive alternatively p(κ) by distributing s quanta over N particles and by introducing a new principle of equal probability of quantum states, where the quanta are indistinguishable in agreement with the Bose statistics. Therefore, the analysis of the two approaches presented in this paper highlights the equivalence of quantum theory with classical statistical mechanics for the present system. At the limit $ε_{o} \rightarrow 0 $; $s \rightarrow \infty $; sεo=E∼ fixed, where the energy of the particles becomes continuous, p(κ) transforms to the Boltzmann law P(ε)=⟨ε⟩1e−⟨ε⟩ε;0≤ε<+∞ where ⟨ε⟩=E/N. Hence, the classical principle of equal a priori probabilities for the energy of the particles leading to the above law, is justified here by quantum mechanics.
Predicting the stationary behavior of observables in isolated many-body quantum systems is a central challenge in quantum statistical mechanics. While one can often use the Gibbs ensemble, which is simple to compute, there are many scenarios where this is not possible and one must instead use another ensemble, such as the diagonal, microcanonical or generalized Gibbs ensembles. However, these all require detailed information about the energy or other conserved quantities to be constructed. Here we propose a general and computationally easy approach to determine the stationary probability distribution of observables with few outcomes. Interpreting coarse measurements at equilibrium as noisy communication channels, we provide general analytical arguments in favor of the applicability of a maximum entropy principle for this class of observables. We show that the resulting theory accurately predicts stationary probability distributions without detailed microscopic information like the energy eigenstates. Extensive numerical experiments on 7 non-weakly interacting spin-1/2 Hamiltonians demonstrate the broad applicability and robustness of this framework in both quantum integrable and chaotic models.
The problem of constructing models for the statistical dynamics of finite-level quantum mechanical systems is considered. The maximum entropy principle formulated by E.T. Jaynes in 1957 and asserting that the entropy of any physical system increases until it attains its maximum value under constraints imposed by other physical laws is applied. In accordance with this principle, the von Neumann entropy is taken for the objective function; a dynamical equation describing the evolution of the density operator in finite-level systems is derived by using the speed gradient principle. In this case, physical constraints are the mass conservation law and the energy conservation law. The stability of the equilibrium points of the system thus obtained is investigated. By using LaSalle’s theorem, it is shown that the density function tends to a Gibbs distribution, under which the entropy attains its maximum. The method is exemplified by analyzing a finite system of identical particles distributed between cells. Results of numerical simulation are presented.
The Maxwell-Boltzmann MB distribution is often derived by maximizing the number of possible arrangements of particles with different energies subject to the constraint of a fixed number of particles and fixed energy. Using the canonical approximation that only average energy is conserved and using Stirling’s approximation for large number factorials leads to the Maxwell-Boltzmann distribution. The ln of total number of arrangements using Stirling’s approximation is linked to a math form called Shannon’s entropy i.e. - Sum over i f(ei) ln(f(ei)). Interestingly this same MB result may be obtained through reaction balance which makes no use of the idea of arrangements or entropy or maximization. It is concerned with including all possible physical reactions (for example two body reactions between all energy particles) subject to conservation of energy. In this sense it deals directly with the dynamics of the problem while the arrangement approach does not. The dynamical approach considers all possible reactions with notions of independence or lack of information and ensures the system remains unchanged. Why are they the same? We argue that it is because the “recipe” for the probability of two body reactions namely n(e1)n(e2) is of the same form as the leading factor of n(e1)! n(e2)!. In the case of quantum mechanics one may apply the dynamical approach to obtain the time-independent Schrodinger equation. In such a case one does not need to think in terms of “maximizing” any quantity although one considers all possible reactions with a potential V(x). a(p) factors in W(x) = wavefunction = Sum over p a(p)exp(ipx) are interrelated, but retain their identity after all possible interactions occur. This we argue is the idea for the eigenvalue equation. At the same time, Shannon’s entropy, which is directly linked to the notion of arrangements, is applied to a bound state and possibly linked to thermodynamics i.e. dE = TdS -PdV which may be applied to an adiabatic expansion. Shannon’s entropy is created from existing probabilities in this case which do not arise from explicitly maximizing entropy subject to constraints as the probabilities follow directly from the Schrodinger equation. One might ask why Shannon’s entropy has any relevance if it is the dynamics which determines the value of W(x) and a(p). It seems, however, that one may knock out a particle in a state p with probability P(p)= a*(p)a(p) or find a particle at x with probability P(x)=W*(x)W(x). These are classical type probabilities linked to the quantum dynamical probabilities a(p) and W(x). It seems Shannon’s entropy is only applied to P(x) and P(p) or a product P(x)P(p) which may give it physical meaning in a quantum bound state. We examine these ideas in this note.
An interesting result arises in information theory, namely that if one considers a microstate with large N trials, each representing a state i with probability p(i), then even though this is only one of many possible microstates (each being a permutation of each other) it carries information about all of the permutations based on the average occupancy number. In particular, the probability of a microstate may be written as: Product over i p(ei) [power Np(ei) ] for large N. This holds for any microstate and so all have the same probability. Given that all of the microstates are permutations in the large N case, this probability is equivalent to 1/ {number of permutations} where Number of permutations = N! / { Product over i n(ei) }. We point out the above example, because it seems there are at least two main strategies in statistical mechanics. One is to begin with a set of average occupancy numbers n(ei/T) whose specific form is unknown. The idea then seems to be to seek degeneracy in the system, possibly among the arrangement of the n(ei)’s or degeneracy within single levels ei and to maximize the number of degenerate arrangements in order to account for as little information as possible. This approach may be used to calculate the Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein distributions. In the case of the latter two, degeneracy in the single energy levels ei is key. One then maximizes the ln of the degenerate arrangements subject to constraints such as Sum over i ei n(ei) and Sum over i n(ei) = N. The degeneracies themselves are associated with momentum degeneracies yielding the same energy. A completely different approach, it seems, is to consider exp(-(E-uN)/T) as representing the probability of a state with energy E and N particles and to use either the grand canonical ensemble i.e. sum the various exp(-(E-uN)/T)’s. These may then be broken into single particle sums using E(N) = sum over i ei n(ei) for n(ei) variable or sum over i ei for N fixed. Even though momentum degeneracy still exists, it is not part of the n sum of exp(-(E-uN)/T) factors which gives a single energy level probability distribution with no maximization necessary. Thus we point out that exp(-(E-uN)/T) for microstates seems to incorporate information about degeneracies without them needing to be explicitly added. On the other hand, if one starts with average n(ei) (without knowing their form), one must explicitly consider degeneracies in order to maximize so that there is no unnecessary information in the system. Both approaches should yield the same result. We consider the Bose-Einstein example of a photon gas as an example.