Abstract

The Event Shape Engineering technique allows the selection of different event shapes for a definite centrality and colliding system. The event selection is based on the azimuthal distribution of produced particles, using the so-called flow vector. For such shape selected events, the elliptic flow coefficient (v2) is significantly different with respect to the unbiased events. Moreover, recent Monte-Carlo studies show a strong correlation between the (final state) event shape selection and the (initial state) eccentricity of the collision. This opens the opportunity to characterize events according to the initial geometry. An approach to select the eccentricity of the event with the Event Shape Engineering is presented. Then the effect of this selection on identified particle spectra, mean transverse momentum and v2 of charged particles in heavy-ion collisions at = 2.76 TeV center-of-mass energy is discussed.

Highlights

  • At present, the overlap geometry in nucleus-nucleus collisions is usually studied by fixing the collision centrality or by using colliding nuclei of different size and shape

  • The Event Shape Engineering (ESE) technique, recently proposed in [1], allows to bias the event sample by selecting events characterized by a well defined initial geometry, by means of the flow vector evaluated from the azimuthal distribution of produced particles

  • A strong positive correlation between the flow vector and the eccentricity of the collision has been observed [2]. These results suggest that the shape of the initial geometry can be constrained using the flow vector in the final state

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Summary

Introduction

The overlap geometry in nucleus-nucleus collisions is usually studied by fixing the collision centrality or by using colliding nuclei of different size and shape. The Event Shape Engineering technique allows the selection of different event shapes for a definite centrality and colliding system. The event selection is based on the azimuthal distribution of produced particles, using the so-called flow vector.

Results
Conclusion

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