Abstract
Multiplicity distributions, P(N), provide valuable information on the mechanism of the production process. We argue that the observed P(N) contain more information (located in the small N region) than expected and used so far. We demonstrate that it can be retrieved by analysing specific combinations of the experimentally measured values of P(N) which we call modified combinants, Cj, and which show distinct oscillatory behavior, not observed in the usual phenomenological forms of the P(N) used to fit data. We discuss the possible sources of these oscillations and their impact on our understanding of the multiparticle production mechanism.
Highlights
The multiplicity distribution, P(N), is an important characteristic of the multiparticle production process, one of the first observables measured in any multiparticle production experiment [1]
This observation, when taken seriously, suggests that there must be some additional information hidden in the small N region, not investigated yet [9]
In general, the period of the oscillations is equal to 2λ (i.e., in Fig. 3 (b) where λ = 10 it is equal to 20). This example shows that the choice of a Binomial Distribution (BD) as the basis of the compound distributions (CD) used is crucial to obtain the oscillatory behavior of the C j
Summary
The multiplicity distribution, P(N), is an important characteristic of the multiparticle production process, one of the first observables measured in any multiparticle production experiment [1]. This observation, when taken seriously, suggests that there must be some additional information hidden in the small N region, not investigated yet [9]. With parameters c = 20.252, a1 = 0.044, a2 = 1.04 · 10−9 and b = 11, one gets the desired flat behavior of R as a function of multiplicity N, R = 1 for all N [9] Such a choice corresponds to a rather complicated, nonlinear and non monotonic spout-like form of g(N) in the recurrence relation Eq (1) and to a non monotonic, depending on multiplicity, probability of particle emission, p = p(N), with a sharp minimum around N = 10, after which p(N) grows steadily, see Fig. 1 (c)
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