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Identifying f ireball fragmentation with the Kolmogorov-Smirnov test. Boris Tomášik Univerzita Mateja Bela, Banská Bystrica, Slovakia Czech Technical University, Prague, Czech Republic NICA Round Table Workshop September 10 , 2009. rapidity distribution in a single event.
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Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test Identifying fireball fragmentation with the Kolmogorov-Smirnov test • Boris Tomášik • Univerzita Mateja Bela, Banská Bystrica, Slovakia • Czech Technical University, Prague, Czech Republic • NICA Round Table Workshop • September 10, 2009
rapidity distribution in a single event Droplets and rapidity distributions dN/dy dN/dy y y without droplets with droplets If we have droplets, each event will look differently Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
Kolmogorov–Smirnov test (general intro): Are two empirical distributions generated from the same underlying probability distribution? (null hypothesis) The measure of difference between events 1 D measures the difference of two empirical distributions D maximum distance 0 y Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
How are the D's distributed? Smirnov (1944):If we have two sets of data generated from the same underlying distribution, then D's are distributed according to This is independent from the underlying distribution! For each t=D we can calculate For events generated from the same distribution, Q's will be distributed uniformly. Kolmogorov-Smirnov: theorems Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
All events within the selected centrality class are evolve according to the same scenario and the bulk evolves smoothly from the beginning to the freeze out. (Like in hydrodynamic simulation.) Null hypothesis Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
DRAGON: MC generator of (momenta and positions of) particles [BT: Computer Physics Communications 180 (2009) 1642, arXiv:0806.4770 [nucl-th]] some particles are emitted from droplets (clusters) if no droplet formation is assumed, then similar to THERMINATOR droplets are generated from a blast-wave source (tunable parameters) tunable size of droplets: Gamma-distributed or fixed droplets decay exponentially in time (tunable time, T) no overlap of droplets also directly emitted particles (tunable amount) chemical composition: equilibrium, resonances rapidity distribution: uniform or Gaussian possible OSCAR output DRoplet and hAdron GeneratOr for Nuclear collisions Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
Results from simulation: Q histograms RHIC simulation (but similar for NICA with droplets) Droplets with average volume 5 fm3 All hadrons are produced by droplets Small signal also with no droplets due to resonance decays With identified species problems with small multiplicity droplets no droplets droplets droplets no droplets no droplets Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
Different sizes of droplets and droplet abundance The peak at Q = 0 is visible … down to average droplet size of 2.5 fm3 … also if not all hadrons come from the droplets Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
The effect of momentum conservation • Toy model simulation: • N subsystems – momentum is exactly 0 within each subsystem • This leads to a dip in the Q histogram at small Q • This generates a histogram which looks as if the events were correlated with each other with resonance decays y cut • NB: other effects which • may influence the KS test: • string fragmentation (weaker than droplets) • jets (high pt) • quantum correlations (how to simulate them) stable Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
The Kolmogorov-Smirnov test can be used to compare rapidity distributions event-by-event in order to identify non-statistical differences between the events Try KS test – if it gives no effect, then all events are the same and we have one piece of bulk matter (null hypothesis) Advantage of the KS test is no bias on any moment of the rapidity distribution. Fireball fragmentation would lead to a clear signal with this technique Other effects on the KS test to be examined Summary Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test
Backup: exact formulas for Q Boris Tomášik: Identifying fireball fragmentation with the Kolmogorov-Smirnov test