Using Spectator Matter for Centrality Determination in Nucleus-Nucleus Collisions
Round 1
Reviewer 1 Report
The authors present the method of centrality determination by using spectators at NICA.
In general, I find it is to be a nice paper. The main information is successfully delivered.
I have a few minor comments:
Figure 1 and 3, the dashed lines are somewhat hardly distinguished. Is it possible to also use solid lines with difference width?
Line 139: in the MPD experiment at NICA the installation of scintillator detectors, …
Reads not like a grammatically correct sentence.
Line 189: N_{H-2}, N{H-2}, … the second N{H-2} should be a type.
Author Response
On behalf of the authors we are thankful for your review. Please see our response to your comments below.
Q1: The authors present the method of centrality determination by using spectators at NICA. In general, I find it is to be a nice paper. The main information is successfully delivered.
A1: We would like to thank the Referee for the positive evaluation of our manuscript. As explained below, we implemented all the proposed suggestions.
Q2: Figure 1 and 3, the dashed lines are somewhat hardly distinguished. Is it possible to also use solid lines with difference width?
A2: We changed the style of histograms of these figures (now Figs. 2 and 4) in order to make the histograms easily distinguishable.
Q3: Line 139: in the MPD experiment at NICA the installation of scintillator detectors, … Reads not like a grammatically correct sentence.
A3: We changed this sentence:
"As mentioned above, in the MPD experiment at NICA the installation of scintillator detectors, in particular, scintillator hodoscopes, between the interaction point and FHCal will make possible to distinguish charged spectators (protons and nuclear fragments) from spectator neutrons."
-->
"As mentioned above, in the MPD experiment at NICA scintillator detectors are planned to be installed between the interaction point and FHCal. With these scintillator hodoscopes spectator protons and nuclear fragments can be distinguished from spectator neutrons."
Q4. Line 189: N_{H-2}, N{H-2}, … the second N{H-2} should be a type.
A4. We fixed this misprint: $N_{H-2}$ --> $N_{He-4}$
Please see attachment for the updated version of the manuscript
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The abstract is a bit unclear about what is already known and what is new. The author should clarify the main bottleneck of the field and the major contribution of this paper or emphasize the significance of this study. Discussion of “machine learning algorithms” appeared only in the last sentence of the abstract and conclusion. a. Need some introduction on machine learning and why it is needed, why conventional methods can’t help b. The authors should define what they mean by ML algorithms. AAMCC is an ML algorithm yes? c. Please expand on how the result can help future machine learning algorithms for the determination of event centrality, what are the bottlenecks. This can be the discussion section of the paper. Flowchart or diagram showing how AAMCC works will help (not present in a previous paper citing AAMCC) In 2.1, the author raised using GlauberMC and points to a reference [10]. But should add a sentence describing why GlauberMC is best/appropriate model (ie, a summary of ref.10?). Minor word corrections needed, the first use of abbreviation should be defined. For each figure, need to explain the axis and the main takeaway message Conclusion: the authors reported new discoveries but need to expand on the impact of these discoveries and how they move the field forward.Author Response
We would like to thank the Referee for the positive evaluation of our manuscript, valuable comments and suggestions to improve the text. As explained below, we implemented all the proposed suggestions.
Q1: The abstract is a bit unclear about what is already known and what is new. The author should clarify the main bottleneck of the field and the major contribution of this paper or emphasize the significance of this study.
A1: We revised the abstract to state at the very beginning that spectator neutrons are commonly used to estimate the centrality of nucleus-nucleus collision events, but because of limitation of this method we consider other spectator characteristics to improve the centrality determination. Now the abstract reads as following:
"One of the common methods to measure the centrality of nucleus-nucleus collision events consists in detecting forward spectator neutrons. Because of non-monotonic dependence of neutron numbers on centrality, other characteristics of spectator matter in $^{197}$Au--$^{197}$Au collisions at NICA have to be considered to improve the centrality determination. The numbers of spectator deuterons and $\alpha$-particles, the forward-backward asymmetry of the numbers of free spectator nucleons were calculated with the Abrasion-Ablation Monte Carlo for Colliders (AAMCC) model as functions of event centrality. It was shown that the number of charged fragments per spectator nucleon decreases monotonically with an increase of the impact parameter, and thus can be used to estimate the collision centrality. The conditional probabilities that a given event with specific spectator characteristics belongs to a certain centrality class were calculated by means of AAMCC. Such probabilities can be used as an input to Bayesian or other machine learning approaches to centrality determination in $^{197}$Au--$^{197}$Au collisions."
Q2: Discussion of “machine learning algorithms” appeared only in the last sentence of the abstract and conclusion.
a. Need some introduction on machine learning and why it is needed, why conventional methods can’t help
b. The authors should define what they mean by ML algorithms. AAMCC is an ML algorithm yes?
c. Please expand on how the result can help future machine learning algorithms for the determination of event centrality,
what are the bottlenecks. This can be the discussion section of the paper. Flowchart or diagram showing how AAMCC works will help (not present in a previous paper citing AAMCC)
A2: a. As explained in lines 42-44 of the revised text, the conventional methods of measurements of multiplicities of unbound spectator nucleons as well as intermediate mass fragments are not sufficient for unambiguous centrality determination in the whole range of b. Therefore, it is necessary to search for additional characteristics of spectator matter associated with centrality.
b. As explained in lines 50-65, in our study we use Bayes' theorem to compute the posterior probability that a detected event, say with a given multiplicity of spectators, belongs to a certain centrality interval. We briefly introduce the reader to such a simple one-dimensional Bayesian derivation of this probability. We made such a derivation individually for each of the considered characteristics and explained physics behind them. A numerical recipe to get posterior probabilities is now described in a dedicated Sec. 2.4. Multidimensional ML algorithms which are based on sets of characteristics rather than on a single one are more complicated, and beyond the scope of the present work. Their descriptions can be found in Refs.[8-10].
c. In Fig. 1 a flowchart of AAMCC is given. We also updated the conclusion (lines 236-240) to explain that the considered characteristics of spectators were evaluated as centrality indicators on the basis of AAMCC and their implementation in multidimensional machine learning algorithms is very promising for centrality determination in future experiments at NICA and at the LHC.
Q3: In 2.1, the author raised using GlauberMC and points to a reference [10]. But should add a sentence describing why GlauberMC is best/appropriate model (i.e., a summary of ref.10?).
A3: Because of the limitation on the paper volume, it is difficult to give an extended summary of the present Ref.[12] devoted to GaluberMC. We suggest that the history of the Glauber model, its theoretical background, main assumptions and Monte Carlo implementation can be found in [12]. We only add that this model is widely used for estimating the initial geometry in collisions of relativistic nuclei, see lines 87-89.
Q4: Minor word corrections needed, the first use of abbreviation should be defined. For each figure, need to explain the axis and the main takeaway message.
A4: We made several minor corrections to the wording throughout the text. The probabilities presented in Figs. 2--4 are explicitly defined now by Eq.(1).
Q5: Conclusion: the authors reported new discoveries but need to expand on the impact of these discoveries and how they move the field forward.
A5: It is explained now in the conclusion (lines 236-240):
"The considered characteristics of spectators were evaluated as centrality indicators on the basis of AAMCC. These results are model dependent and it is recommended to confirm them with other models and future measurements. However, for the moment, the considered characteristics of spectators look
promising for their implementation in multidimensional machine learning algorithms to determine centrality in future experiments at NICA and at the LHC."
Please see attachment for the updated version of the manuscript
Author Response File: Author Response.pdf
