Distance matrices calculation result explanation #20.

Author: Ilia Lazarev

CHANGELOG.md

@@ -7,3 +7,4 @@
 - Figure `qcircuit`: add stages, removed measurements and initialization.
 - Figure `distance_matrix`: single figure with marked errors. Simulators was removed.
 - Measurement result explanation
+- Explanation of error of distance matrix calculation

manuscript.tex

@@ -515,8 +515,7 @@ \section{Experimental demonstration of QASOFM}
 
 In order to check that our algorithm gives the expected results we compare it to classical calculations of the distance matrix on two data sets of binary vectors, as shown in Fig.~\ref{fig:distance_matrix}.  
 We see good agreement between the distance matrices calculated classically and on the IBM Q Experience. 
-The theoretical calculations and classical simulations show perfect agreement with each other (Fig.~\ref{fig:distance_matrix}(a)). 
-The difference between Figs.~\ref{fig:distance_matrix} (a) and (b) appears due to noise in the currently available non fault-tolerant quantum processors.
+The match is close, but not perfect, and we attribute it to noise in the currently available non fault-tolerant quantum processors.
 
 An example of the QASOFM learning process is shown in Fig.~\ref{convergence}. 
 Initially, the cluster vectors were randomly chosen (see Fig.~\ref{convergence})