Search for the Chiral Magnetic Effect in Au+Au collisions at sNN=27\sqrt{s_{_{\rm{NN}}}}=27 GeV with the STAR forward Event Plane Detectors

A decisive experimental test of the Chiral Magnetic Effect (CME) is considered one of the major scientific goals at the Relativistic Heavy-Ion Collider (RHIC) towards understanding the nontrivial topological fluctuations of the Quantum Chromodynamics vacuum. In heavy-ion collisions, the CME is expected to result in a charge separation phenomenon across the reaction plane, whose strength could be strongly energy dependent. The previous CME searches have been focused on top RHIC energy collisions. In this Letter, we present a low energy search for the CME in Au+Au collisions at $\sqrt{s_{_{\rm{NN}}}}=27$ GeV. We measure elliptic flow scaled charge-dependent correlators relative to the event planes that are defined at both mid-rapidity $|\eta|<1.0$ and at forward rapidity $2.1 < |\eta|<5.1$. We compare the results based on the directed flow plane ($\Psi_1$) at forward rapidity and the elliptic flow plane ($\Psi_2$) at both central and forward rapidity. The CME scenario is expected to result in a larger correlation relative to $\Psi_1$ than to $\Psi_2$, while a flow driven background scenario would lead to a consistent result for both event planes[1,2]. In 10-50\% centrality, results using three different event planes are found to be consistent within experimental uncertainties, suggesting a flow driven background scenario dominating the measurement. We obtain an upper limit on the deviation from a flow driven background scenario at the 95\% confidence level. This work opens up a possible road map towards future CME search with the high statistics data from the RHIC Beam Energy Scan Phase-II.Comment: main: 8 pages, 5 figures; supplementary material: 2 pages, 1 figur

Richards growth model and viability indicators for populations subject to interventions

In this work we study the problem of modeling identification of a population employing a discrete dynamic model based on the Richards growth model. The population is subjected to interventions due to consumption, such as hunting or farming animals. The model identification allows us to estimate the probability or the average time for a population number to reach a certain level. The parameter inference for these models are obtained with the use of the likelihood profile technique as developed in this paper. The identification method here developed can be applied to evaluate the productivity of animal husbandry or to evaluate the risk of extinction of autochthon populations. It is applied to data of the Brazilian beef cattle herd population, and the the population number to reach a certain goal level is investigated.<br>Neste trabalho estudamos o problema de identificação do modelo de uma população utilizando um modelo dinâmico discreto baseado no modelo de crescimento de Richards. A população é submetida a intervenções devido ao consumo, como no caso de caça ou na criação de animais. A identificação do modelo permite-nos estimar a probabilidade ou o tempo médio de ocorrência para que se atinja um certo número populacional. A inferência paramétrica dos modelos é obtida através da técnica de perfil de máxima verossimilhança como desenvolvida neste trabalho. O método de identificação desenvolvido pode ser aplicado para avaliar a produtividade de criação animal ou o risco de extinção de uma população autóctone. Ele foi aplicado aos dados da população global de gado de corte bovino brasileiro, e é utilizado na investigação de a população atingir um certo número desejado de cabeças