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Routines and Common-Block Variables

The six routines PYSPHE, PYTHRU, PYCLUS, PYCELL, PYJMAS and PYFOWO give you the possibility to find some global event shape properties. The routine PYTABU performs a statistical analysis of a number of different quantities like particle content, factorial moments and the energy-energy correlation.

Note that, by default, all remaining partons/particles except neutrinos (and some other weakly interacting particles) are used in the analysis. Neutrinos may be included with MSTU(41) = 1. Also note that axes determined are stored in PYJETS, but are not proper four-vectors and, as a general rule (with some exceptions), should therefore not be rotated or boosted.


\fbox{\texttt{CALL PYSPHE(SPH,APL)}}

Purpose:
to diagonalize the momentum tensor, i.e. find the eigenvalues $\lambda_1 > \lambda_2 > \lambda_3$, with sum unity, and the corresponding eigenvectors.
Momentum power dependence is given by PARU(41); default corresponds to sphericity, while PARU(41) = 1. gives measures linear in momenta. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value.
SPH :
$\frac{3}{2} (\lambda_2 + \lambda_3)$, i.e. sphericity (for PARU(41) = 2.).
= -1. :
analysis not performed because event contained less than two particles (or two exactly back-to-back particles, in which case the two transverse directions would be undefined).
APL :
$\frac{3}{2} \lambda_3$, i.e. aplanarity (for PARU(41) = 2.).
= -1. :
as SPH = -1.
Remark:
the lines N + 1 through N + 3 (N - 2 through N for MSTU(43) = 2) in PYJETS will, after a call, contain the following information:
K(N+i,1) = 31;
K(N+i,2) = 95;
K(N+i,3) : $i$, the axis number, $i=1,2,3$;
K(N+i,4), K(N+i,5) = 0;
P(N+i,1) - P(N+i,3) : the $i$'th eigenvector, $x$, $y$ and $z$ components;
P(N+i,4) : $\lambda_i$, the $i$'th eigenvalue;
P(N+i,5) = 0;
V(N+i,1) - V(N+i,5) = 0.
Also, the number of particles used in the analysis is given in MSTU(62).


\fbox{\texttt{CALL PYTHRU(THR,OBL)}}

Purpose:
to find the thrust, major and minor axes and corresponding projected momentum quantities, in particular thrust and oblateness. The performance of the program is affected by MSTU(44), MSTU(45), PARU(42) and PARU(48). In particular, PARU(42) gives the momentum dependence, with the default value = 1 corresponding to linear dependence. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value.
THR :
thrust (for PARU(42) = 1.).
= -1. :
analysis not performed because event contained less than two particles.
= -2. :
remaining space in PYJETS (partly used as working area) not large enough to allow analysis.
OBL :
oblateness (for PARU(42) = 1.).
= -1., -2. :
as for THR.
Remark:
the lines N + 1 through N + 3 (N - 2 through N for MSTU(43) = 2) in PYJETS will, after a call, contain the following information:
K(N+i,1) = 31;
K(N+i,2) = 96;
K(N+i,3) : $i$, the axis number, $i=1,2,3$;
K(N+i,4), K(N+i,5) = 0;
P(N+i,1) - P(N+i,3) : the thrust, major and minor axis, respectively, for $i = 1,2$ and 3;
P(N+i,4) : corresponding thrust, major and minor value;
P(N+i,5) = 0;
V(N+i,1) - V(N+i,5) = 0.
Also, the number of particles used in the analysis is given in MSTU(62).


\fbox{\texttt{CALL PYCLUS(NJET)}}

Purpose:
to reconstruct an arbitrary number of jets using a cluster analysis method based on particle momenta.
Three different distance measures are available, see section [*]. The choice is controlled by MSTU(46). The distance scale $d_{\mathrm{join}}$, above which two clusters may not be joined, is normally given by PARU(44). In general, $d_{\mathrm{join}}$ may be varied to describe different `jet-resolution powers'; the default value, 2.5 GeV, is fairly well suited for $\mathrm{e}^+\mathrm{e}^-$ physics at 30-40 GeV. With the alternative mass distance measure, PARU(44) can be used to set the absolute maximum cluster mass, or PARU(45) to set the scaled one, i.e. in $y = m^2/E_{\mathrm{cm}}^2$, where $E_{\mathrm{cm}}$ is the total invariant mass of the particles being considered.
It is possible to continue the cluster search from the configuration already found, with a new higher $d_{\mathrm{join}}$ scale, by selecting MSTU(48) properly. In MSTU(47) one can also require a minimum number of jets to be reconstructed; combined with an artificially large $d_{\mathrm{join}}$ this can be used to reconstruct a predetermined number of jets.
Which particles (or partons) are used in the analysis is determined by the MSTU(41) value, whereas assumptions about particle masses is given by MSTU(42). The parameters PARU(43) and PARU(48) regulate more technical details (for events at high energies and large multiplicities, however, the choice of a larger PARU(43) may be necessary to obtain reasonable reconstruction times).
NJET :
the number of clusters reconstructed.
= -1 :
analysis not performed because event contained less than MSTU(47) (normally 1) particles, or analysis failed to reconstruct the requested number of jets.
= -2 :
remaining space in PYJETS (partly used as working area) not large enough to allow analysis.
Remark:
if the analysis does not fail, further information is found in MSTU(61) - MSTU(63) and PARU(61) - PARU(63). In particular, PARU(61) contains the invariant mass for the system analysed, i.e. the number used in determining the denominator of $y = m^2/E_{\mathrm{cm}}^2$. PARU(62) gives the generalized thrust, i.e. the sum of (absolute values of) cluster momenta divided by the sum of particle momenta (roughly the same as multicity [Bra79]). PARU(63) gives the minimum distance $d$ (in $p_{\perp}$ or $m$) between two clusters in the final cluster configuration, 0 in case of only one cluster.
Further, the lines N + 1 through N + NJET (N - NJET + 1 through N for MSTU(43) = 2) in PYJETS will, after a call, contain the following information:
K(N+i,1) = 31;
K(N+i,2) = 97;
K(N+i,3) : $i$, the jet number, with the jets arranged in falling order of absolute momentum;
K(N+i,4) : the number of particles assigned to jet $i$;
K(N+i,5) = 0;
P(N+i,1) - P(N+i,5) : momentum, energy and invariant mass of jet $i$;
V(N+i,1) - V(N+i,5) = 0.
Also, for a particle which was used in the analysis, K(I,4)$ = i$, where I is the particle number and $i$ the number of the jet it has been assigned to. Undecayed particles not used then have K(I,4) = 0. An exception is made for lines with K(I,1) = 3 (which anyhow are not normally interesting for cluster search), where the colour-flow information stored in K(I,4) is left intact.
MSTU(3) is only set equal to the number of jets for positive NJET and MSTU(43) = 1.


\fbox{\texttt{CALL PYCELL(NJET)}}

Purpose:
to provide a simpler cluster routine more in line with what is currently used in the study of high-$p_{\perp}$ collider events.
A detector is assumed to stretch in pseudorapidity between -PARU(51) and +PARU(51) and be segmented in MSTU(51) equally large $\eta$ (pseudorapidity) bins and MSTU(52) $\varphi$ (azimuthal) bins. Transverse energy $E_{\perp}$ for undecayed entries are summed up in each bin. For MSTU(53) non-zero, the energy is smeared by calorimetric resolution effects, cell by cell. This is done according to a Gaussian distribution; if MSTU(53) = 1 the standard deviation for the $E_{\perp}$ is PARU(55) $\times \sqrt{E_{\perp}}$, if MSTU(53) = 2 the standard deviation for the $E$ is PARU(55) $\times \sqrt{E}$, $E_{\perp}$ and $E$ expressed in GeV. The Gaussian is cut off at 0 and at a factor PARU(56) times the correct $E_{\perp}$ or $E$. Cells with an $E_{\perp}$ below a given threshold PARU(58) are removed from further consideration; by default PARU(58) = 0. and thus all cells are kept.
All bins with $E_{\perp} > $PARU(52) are taken to be possible initiators of jets, and are tried in falling $E_{\perp}$ sequence to check whether the total $E_{\perp}$ summed over cells no more distant than PARU(54) in $\sqrt{(\Delta\eta)^2 + (\Delta\varphi)^2}$ exceeds PARU(53). If so, these cells define one jet, and are removed from further consideration. Contrary to PYCLUS, not all particles need be assigned to jets. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value.
NJET :
the number of jets reconstructed (may be 0).
= -2 :
remaining space in PYJETS (partly used as working area) not large enough to allow analysis.
Remark:
the lines N + 1 through N + NJET (N - NJET + 1 through N for MSTU(43) = 2) in PYJETS will, after a call, contain the following information:
K(N+i,1) = 31;
K(N+i,2) = 98;
K(N+i,3) : $i$, the jet number, with the jets arranged in falling order in $E_{\perp}$;
K(N+i,4) : the number of particles assigned to jet $i$;
K(N+i,5) = 0;
V(N+i,1) - V(N+i,5) = 0.
Further, for MSTU(54) = 1
P(N+i,1), P(N+i,2) = position in $\eta$ and $\varphi$ of the center of the jet initiator cell, i.e. geometrical center of jet;
P(N+i,3), P(N+i,4) = position in $\eta$ and $\varphi$ of the $E_{\perp}$-weighted center of the jet, i.e. the center of gravity of the jet;
P(N+i,5) = sum $E_{\perp}$ of the jet;
while for MSTU(54) = 2
P(N+i,1) - P(N+i,5) : the jet momentum vector, constructed from the summed $E_{\perp}$ and the $\eta$ and $\varphi$ of the $E_{\perp}$-weighted center of the jet as
$(p_x, p_y, p_z, E, m) = E_{\perp} (\cos\varphi, \sin\varphi,
\sinh\eta, \cosh\eta, 0)$;
and for MSTU(54) = 3
P(N+i,1) - P(N+i,5) : the jet momentum vector, constructed by adding vectorially the momentum of each cell assigned to the jet, assuming that all the $E_{\perp}$ was deposited at the center of the cell, and with the jet mass in P(N+i,5) calculated from the summed $E$ and $\mathbf{p}$ as $m^2 = E^2 - p_x^2 - p_y^2 - p_z^2$.
Also, the number of particles used in the analysis is given in MSTU(62), and the number of cells hit in MSTU(63).
MSTU(3) is only set equal to the number of jets for positive NJET and MSTU(43) = 1.


\fbox{\texttt{CALL PYJMAS(PMH,PML)}}

Purpose:
to reconstruct high and low jet mass of an event. A simplified algorithm is used, wherein a preliminary division of the event into two hemispheres is done transversely to the sphericity axis. Then one particle at a time is reassigned to the other hemisphere if that reduces the sum of squares of the two jet masses, $m_{\mathrm{H}}^2 + m_{\mathrm{L}}^2$. The procedure is stopped when no further significant change (see PARU(48)) is obtained. Often, the original assignment is retained as it is. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value, whereas assumptions about particle masses is given by MSTU(42).
PMH :
heavy jet mass (in GeV).
= -2. :
remaining space in PYJETS (partly used as working area) not large enough to allow analysis.
PML :
light jet mass (in GeV).
= -2. :
as for PMH = -2.
Remark:
After a successful call, MSTU(62) contains the number of particles used in the analysis, and PARU(61) the invariant mass of the system analysed. The latter number is helpful in constructing scaled jet masses.


\fbox{\texttt{CALL PYFOWO(H10,H20,H30,H40)}}

Purpose:
to do an event analysis in terms of the Fox-Wolfram moments. The moments $H_i$ are normalized to the lowest one, $H_0$. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value.
H10 :
$H_1/H_0$. Is $ = 0$ if momentum is balanced.
H20 :
$H_2/H_0$.
H30 :
$H_3/H_0$.
H40 :
$H_4/H_0$.
Remark:
the number of particles used in the analysis is given in MSTU(62).


\fbox{\texttt{CALL PYTABU(MTABU)}}

Purpose:
to provide a number of event-analysis options which can be be used on each new event, with accumulated statistics to be written out on request. When errors are quoted, these refer to the uncertainty in the average value for the event sample as a whole, rather than to the spread of the individual events, i.e. errors decrease like one over the square root of the number of events analysed. For a correct use of PYTABU, it is not permissible to freely mix generation and analysis of different classes of events, since only one set of statistics counters exists. A single run may still contain sequential `subruns', between which statistics is reset. Whenever an event is analysed, the number of particles/partons used is given in MSTU(62).
MTABU :
determines which action is to be taken. Generally, a last digit equal to 0 indicates that the statistics counters for this option is to be reset; since the counters are reset (by DATA statements) at the beginning of a run, this is not used normally. Last digit 1 leads to an analysis of current event with respect to the desired properties. Note that the resulting action may depend on how the event generated has been rotated, boosted or edited before this call. The statistics accumulated is output in tabular form with last digit 2, while it is dumped in the PYJETS common block for last digit 3. The latter option may be useful for interfacing to graphics output.
Warning:
this routine cannot be used on weighted events, i.e. in the statistics calculation all events are assumed to come with the same weight.
= 10 :
statistics on parton multiplicity is reset.
= 11 :
the parton content of the current event is analysed, classified according to the flavour content of the hard interaction and the total number of partons. The flavour content is assumed given in MSTU(161) and MSTU(162); these are automatically set e.g. in PYEEVT and PYEVNT calls. Main application is for $\mathrm{e}^+\mathrm{e}^-$ annihilation events.
= 12 :
gives a table on parton multiplicity distribution.
= 13 :
stores the parton multiplicity distribution of events in PYJETS, using the following format:
N = total number of different channels found;
K(I,1) = 32;
K(I,2) = 99;
K(I,3), K(I,4) = the two flavours of the flavour content;
K(I,5) = total number of events found with flavour content of K(I,3) and K(I,4);
P(I,1) - P(I,5) = relative probability to find given flavour content and a total of 1, 2, 3, 4 or 5 partons, respectively;
V(I,1) - V(I,5) = relative probability to find given flavour content and a total of 6-7, 8-10, 11-15, 16-25 or above 25 partons, respectively.
In addition, MSTU(3) = 1 and
K(N+1,1) = 32;
K(N+1,2) = 99;
K(N+1,5) = number of events analysed.
= 20 :
statistics on particle content is reset.
= 21 :
the particle/parton content of the current event is analysed, also for particles which have subsequently decayed and partons which have fragmented (unless this has been made impossible by a preceding PYEDIT call). Particles are subdivided into primary and secondary ones, the main principle being that primary particles are those produced in the fragmentation of a string, while secondary come from decay of other particles.
= 22 :
gives a table of particle content in events.
= 23 :
stores particle content in events in PYJETS, using the following format:
N = number of different particle species found;
K(I,1) = 32;
K(I,2) = 99;
K(I,3) = particle KF code;
K(I,5) = total number of particles and antiparticles of this species;
P(I,1) = average number of primary particles per event;
P(I,2) = average number of secondary particles per event;
P(I,3) = average number of primary antiparticles per event;
P(I,4) = average number of secondary antiparticles per event;
P(I,5) = average total number of particles or antiparticles per event.
In addition, MSTU(3) = 1 and
K(N+1,1) = 32;
K(N+1,2) = 99;
K(N+1,5) = number of events analysed;
P(N+1,1) = average primary multiplicity per event;
P(N+1,2) = average final multiplicity per event;
P(N+1,3) = average charged multiplicity per event.
= 30 :
statistics on factorial moments is reset.
= 31 :
analyses the factorial moments of the multiplicity distribution in different bins of rapidity and azimuth. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value. The selection between usage of true rapidity, pion rapidity or pseudorapidity is regulated by MSTU(42). The $z$ axis is assumed to be event axis; if this is not desirable find an event axis e.g. with PYSPHE or PYTHRU and use PYEDIT(31). Maximum (pion-, pseudo-) rapidity, which sets the limit for the rapidity plateau or the experimental acceptance, is given by PARU(57).
= 32 :
prints a table of the first four factorial moments for various bins of pseudorapidity and azimuth. The moments are properly normalized so that they would be unity (up to statistical fluctuations) for uniform and uncorrelated particle production according to Poisson statistics, but increasing for decreasing bin size in case of `intermittent' behaviour. The error on the average value is based on the actual statistical sample (i.e. does not use any assumptions on the distribution to relate errors to the average values of higher moments). Note that for small bin sizes, where the average multiplicity is small and the factorial moment therefore only very rarely is non-vanishing, moment values may fluctuate wildly and the errors given may be too low.
= 33 :
stores the factorial moments in PYJETS, using the format:
N = 30, with I = $i=1$-10 corresponding to results for slicing the rapidity range in $2^{i-1}$ bins, I = $i = 11$-20 to slicing the azimuth in $2^{i-11}$ bins, and I = $i = 21$-30 to slicing both rapidity and azimuth, each in $2^{i-21}$ bins;
K(I,1) = 32;
K(I,2) = 99;
K(I,3) = number of bins in rapidity;
K(I,4) = number of bins in azimuth;
P(I,1) = rapidity bin size;
P(I,2) - P(I,5) = $\langle F_2 \rangle$- $\langle F_5 \rangle$, i.e. mean of second, third, fourth and fifth factorial moment;
V(I,1) = azimuthal bin size;
V(I,2) - V(I,5) = statistical errors on $\langle F_2 \rangle$- $\langle F_5 \rangle$.
In addition, MSTU(3) = 1 and
K(31,1) = 32;
K(31,2) = 99;
K(31,5) = number of events analysed.
= 40 :
statistics on energy-energy correlation is reset.
= 41 :
the energy-energy correlation $\mathrm{EEC}$ of the current event is analysed. Which particles (or partons) are used in the analysis is determined by the MSTU(41) value. Events are assumed given in their c.m. frame. The weight assigned to a pair $i$ and $j$ is $2 E_i E_j/E_{\mathrm{vis}}^2$, where $E_{\mathrm{vis}}$ is the sum of energies of all analysed particles in the event. Energies are determined from the momenta of particles, with mass determined according to the MSTU(42) value. Statistics is accumulated for the relative angle $\theta_{ij}$, ranging between 0 and 180 degrees, subdivided into 50 bins.
= 42 :
prints a table of the energy-energy correlation $\mathrm{EEC}$ and its asymmetry $\mathrm{EECA}$, with errors. The definition of errors is not unique. In our approach each event is viewed as one observation, i.e. an $\mathrm{EEC}$ and $\mathrm{EECA}$ distribution is obtained by summing over all particle pairs of an event, and then the average and spread of this event-distribution is calculated in the standard fashion. The quoted error is therefore inversely proportional to the square root of the number of events. It could have been possible to view each single particle pair as one observation, which would have given somewhat lower errors, but then one would also be forced to do a complicated correction procedure to account for the pairs in an event not being uncorrelated (two hard jets separated by a given angle typically corresponds to several pairs at about that angle). Note, however, that in our approach the squared error on an $\mathrm{EECA}$ bin is smaller than the sum of the squares of the errors on the corresponding $\mathrm{EEC}$ bins (as it should be). Also note that it is not possible to combine the errors of two nearby bins by hand from the information given, since nearby bins are correlated (again a trivial consequence of the presence of jets).
= 43 :
stores the $\mathrm{EEC}$ and $\mathrm{EECA}$ in PYJETS, using the format:
N = 25;
K(I,1) = 32;
K(I,2) = 99;
P(I,1) = $\mathrm{EEC}$ for angles between I-1 and I, in units of $3.6^{\circ}$;
P(I,2) = $\mathrm{EEC}$ for angles between 50-I and 51-I, in units of $3.6^{\circ}$;
P(I,3) = $\mathrm{EECA}$ for angles between I-1 and I, in units of $3.6^{\circ}$;
P(I,4), P(I,5) : lower and upper edge of angular range of bin I, expressed in radians;
V(I,1) - V(I,3) : errors on the $\mathrm{EEC}$ and $\mathrm{EECA}$ values stored in P(I,1) - P(I,3) (see = 42 for comments);
V(I,4), V(I,5) : lower and upper edge of angular range of bin I, expressed in degrees.
In addition, MSTU(3) = 1 and
K(26,1) = 32;
K(26,2) = 99;
K(26,5) = number of events analysed.
= 50 :
statistics on complete final states is reset.
= 51 :
analyses the particle content of the final state of the current event record. During the course of the run, statistics is thus accumulated on how often different final states appear. Only final states with up to 8 particles are analysed, and there is only reserved space for up to 200 different final states. Most high-energy events have multiplicities far above 8, so the main use for this tool is to study the effective branching ratios obtained with a given decay model for e.g. charm or bottom hadrons. Then PY1ENT may be used to generate one decaying particle at a time, with a subsequent analysis by PYTABU. Depending on at what level this studied is to be carried out, some particle decays may be switched off, like $\pi^0$.
= 52 :
gives a list of the (at most 200) channels with up to 8 particles in the final state, with their relative branching ratio. The ordering is according to multiplicity, and within each multiplicity according to an ascending order of KF codes. The KF codes of the particles belonging to a given channel are given in descending order.
= 53 :
stores the final states and branching ratios found in PYJETS, using the format:
N = number of different explicit final states found (at most 200);
K(I,1) = 32;
K(I,2) = 99;
K(I,5) = multiplicity of given final state, a number between 1 and 8;
P(I,1) - P(I,5), V(I,1) - V(I,3) : the KF codes of the up to 8 particles of the given final state, converted to real numbers, with trailing zeroes for positions not used;
V(I,5) : effective branching ratio for the given final state.
In addition, MSTU(3) = 1 and
K(N+1,1) = 32;
K(N+1,2) = 99;
K(N+1,5) = number of events analysed;
V(N+1,5) = summed branching ratio for finals states not given above, either because they contained more than 8 particles or because all 200 channels have been used up.


\fbox{\texttt{COMMON/PYDAT1/MSTU(200),PARU(200),MSTJ(200),PARJ(200)}}

Purpose:
to give access to a number of status codes and parameters which regulate the performance of fragmentation and event analysis routines. Most parameters are described in section [*]; here only those related to the event-analysis routines are described.


MSTU(41) :
(D = 2) partons/particles used in the event-analysis routines PYSPHE, PYTHRU, PYCLUS, PYCELL, PYJMAS, PYFOWO and PYTABU (PYTABU(11) excepted).
= 1 :
all partons/particles that have not fragmented/decayed.
= 2 :
ditto, with the exception of neutrinos and unknown particles. Also the lowest-lying neutralino $\chi_1^0 $ (code 1000022), the graviton (39) and the gravitino (1000039) are treated on an equal footing with neutrinos. Other similar but not foreseen particles would not be disregarded automatically, but would have to be put to K(I,1) > 10 by hand.
= 3 :
only charged, stable particles, plus any partons still not fragmented.

MSTU(42) :
(D = 2) assumed particle masses, used in calculating energies $E^2 = \mathbf{p}^2 + m^2$, as subsequently used in PYCLUS, PYJMAS and PYTABU (in the latter also for pseudorapidity, pion rapidity or true rapidity selection).
= 0 :
all particles are assumed massless.
= 1 :
all particles, except the photon, are assumed to have the charged pion mass.
= 2 :
the true masses are used.

MSTU(43) :
(D = 1) storing of event-analysis information (mainly jet axes), in PYSPHE, PYTHRU, PYCLUS and PYCELL.
= 1 :
stored after the event proper, in positions N + 1 through N + MSTU(3). If several of the routines are used in succession, all but the latest information is overwritten.
= 2 :
stored with the event proper, i.e. at the end of the event listing, with N updated accordingly. If several of the routines are used in succession, all the axes determined are available.

MSTU(44) :
(D = 4) is the number of the fastest (i.e. with largest momentum) particles used to construct the (at most) 10 most promising starting configurations for the thrust axis determination.

MSTU(45) :
(D = 2) is the number of different starting configurations above, which have to converge to the same (best) value before this is accepted as the correct thrust axis.

MSTU(46) :
(D = 1) distance measure used for the joining of clusters in PYCLUS.
= 1 :
$d_{ij}$, i.e. approximately relative transverse momentum. Anytime two clusters have been joined, particles are reassigned to the cluster they now are closest to. The distance cut-off $d_{\mathrm{join}}$ is stored in PARU(44).
= 2 :
distance measure as in = 1, but particles are never reassigned to new jets.
= 3 :
JADE distance measure $y_{ij}$, but with dimensions to correspond approximately to total invariant mass. Particles may never be reassigned between clusters. The distance cut-off $m_{\mathrm{min}}$ is stored in PARU(44).
= 4 :
as = 3, but a scaled JADE distance $y_{ij}$ is used instead of $m_{ij}$. The distance cut-off $y_{\mathrm{min}}$ is stored in PARU(45).
= 5 :
Durham distance measure $\tilde{y}_{ij}$, but with dimensions to correspond approximately to transverse momentum. Particles may never be reassigned between clusters. The distance cut-off $p_{\perp\mathrm{min}}$ is stored in PARU(44).
= 6 :
as = 5, but a scaled Durham distance $\tilde{y}_{ij}$ is used instead of $p_{\perp ij}$. The distance cut-off $\tilde{y}_{\mathrm{min}}$ is stored in PARU(45).

MSTU(47) :
(D = 1) the minimum number of clusters to be reconstructed by PYCLUS.

MSTU(48) :
(D = 0) mode of operation of the PYCLUS routine.
= 0 :
the cluster search is started from scratch.
= 1 :
the clusters obtained in a previous cluster search on the same event (with MSTU(48) = 0) are to be taken as the starting point for subsequent cluster joining. For this call to have any effect, the joining scale in PARU(44) or PARU(45) must have been changed. If the event record has been modified after the last PYCLUS call, or if any other cluster search parameter setting has been changed, the subsequent result is unpredictable.

MSTU(51) :
(D = 25) number of pseudorapidity bins that the range between -PARU(51) and +PARU(51) is divided into to define cell size for PYCELL.

MSTU(52) :
(D = 24) number of azimuthal bins, used to define the cell size for PYCELL.

MSTU(53) :
(D = 0) smearing of correct energy, imposed cell-by-cell in PYCELL, to simulate calorimeter resolution effects.
= 0 :
no smearing.
= 1 :
the transverse energy in a cell, $E_{\perp}$, is smeared according to a Gaussian distribution with standard deviation PARU(55) $\times \sqrt{E_{\perp}}$, where $E_{\perp}$ is given in GeV. The Gaussian is cut off so that $0 < E_{\perp \mathrm{smeared}}
< $PARU(56) $\times E_{\perp \mathrm{true}}$.
= 2 :
as = 1, but it is the energy $E$ rather than the transverse energy $E_{\perp}$ that is smeared.

MSTU(54) :
(D = 1) form for presentation of information about reconstructed clusters in PYCELL, as stored in PYJETS according to the MSTU(43) value.
= 1 :
the P vector in each line contains $\eta$ and $\varphi$ for the geometric origin of the jet, $\eta$ and $\varphi$ for the weighted center of the jet, and jet $E_{\perp}$, respectively.
= 2 :
the P vector in each line contains a massless four-vector giving the direction of the jet, obtained as
$(p_x, p_y, p_z, E, m) = E_{\perp} (\cos\varphi, \sin\varphi,
\sinh\eta, \cosh\eta, 0)$,
where $\eta$ and $\varphi$ give the weighted center of a jet and $E_{\perp}$ its transverse energy.
= 3 :
the P vector in each line contains a massive four-vector, obtained by adding the massless four-vectors of all cells that form part of the jet, and calculating the jet mass from $m^2 = E^2 - p_x^2 - p_y^2 - p_z^2$. For each cell, the total $E_{\perp}$ is summed up, and then translated into a massless four-vector assuming that all the $E_{\perp}$ was deposited in the center of the cell.

MSTU(61) :
(I) first entry for storage of event-analysis information in last event analysed with PYSPHE, PYTHRU, PYCLUS or PYCELL.

MSTU(62) :
(R) number of particles/partons used in the last event analysis with PYSPHE, PYTHRU, PYCLUS, PYCELL, PYJMAS, PYFOWO or PYTABU.

MSTU(63) :
(R) in a PYCLUS call, the number of preclusters constructed in order to speed up analysis (should be equal to MSTU(62) if PARU(43) = 0.). In a PYCELL call, the number of cells hit.

MSTU(161), MSTU(162) :
hard flavours involved in current event, as used in an analysis with PYTABU(11). Either or both may be set 0, to indicate the presence of one or none hard flavours in event. Is normally set by high-level routines, like PYEEVT or PYEVNT, but can also be set by you.


PARU(41) :
(D = 2.) power of momentum-dependence in PYSPHE, default corresponds to sphericity, = 1. to linear event measures.

PARU(42) :
(D = 1.) power of momentum-dependence in PYTHRU, default corresponds to thrust.

PARU(43) :
(D = 0.25 GeV) maximum distance $d_{\mathrm{init}}$ allowed in PYCLUS when forming starting clusters used to speed up reconstruction. The meaning of the parameter is in $p_{\perp}$ for MSTU(46) $\leq 2$ or $\geq 5$ and in $m$ else. If = 0., no preclustering is obtained. If chosen too large, more joining may be generated at this stage than is desirable. The main application is at high energies, where some speedup is imperative, and the small details are not so important anyway.

PARU(44) :
(D = 2.5 GeV) maximum distance $d_{\mathrm{join}}$, below which it is allowed to join two clusters into one in PYCLUS. Is used for MSTU(46)$\leq 3$ and = 5, i.e. both for $p_{\perp}$ and mass distance measure.

PARU(45) :
(D = 0.05) maximum distance $y_{\mathrm{join}} = m^2/E_{\mathrm{vis}}^2$ or ditto with $m^2 \to p_{\perp}^2$, below which it is allowed to join two clusters into one in PYCLUS for MSTU(46) = 4 or 6.

PARU(48) :
(D = 0.0001) convergence criterion for thrust (in PYTHRU) or generalized thrust (in PYCLUS), or relative change of $m_{\mathrm{H}}^2 + m_{\mathrm{L}}^2$ (in PYJMAS), i.e. when the value changes by less than this amount between two iterations the process is stopped.

PARU(51) :
(D = 2.5) defines maximum absolute pseudorapidity used for detector assumed in PYCELL.

PARU(52) :
(D = 1.5 GeV) gives minimum $E_{\perp}$ for a cell to be considered as a potential jet initiator by PYCELL.

PARU(53) :
(D = 7.0 GeV) gives minimum summed $E_{\perp}$ for a collection of cells to be accepted as a jet.

PARU(54) :
(D = 1.) gives the maximum distance in $R = \sqrt{(\Delta\eta)^2 + (\Delta\varphi)^2}$ from cell initiator when grouping cells to check whether they qualify as a jet.

PARU(55) :
(D = 0.5) when smearing the transverse energy (or energy, see MSTU(53)) in PYCELL, the calorimeter cell resolution is taken to be PARU(55) $\times \sqrt{E_{\perp}}$ (or PARU(55) $\times \sqrt{E}$) for $E_{\perp}$ (or $E$) in GeV.

PARU(56) :
(D = 2.) maximum factor of upward fluctuation in transverse energy or energy in a given cell when calorimeter resolution is included in PYCELL (see MSTU(53)).

PARU(57) :
(D = 3.2) maximum rapidity (or pseudorapidity or pion rapidity, depending on MSTU(42)) used in the factorial moments analysis in PYTABU.

PARU(58) :
(D = 0. GeV) in a PYCELL call, cells with a transverse energy $E_{\perp}$ below PARP(58) are removed from further consideration. This may be used to represent a threshold in an actual calorimeter, or may be chosen just to speed up the algorithm in a high-multiplicity environment.

PARU(61) :
(I) invariant mass $W$ of a system analysed with PYCLUS or PYJMAS, with energies calculated according to the MSTU(42) value.

PARU(62) :
(R) the generalized thrust obtained after a successful PYCLUS call, i.e. ratio of summed cluster momenta and summed particle momenta.

PARU(63) :
(R) the minimum distance $d$ between two clusters in the final cluster configuration after a successful PYCLUS call; is 0 if only one cluster left.


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Stephen_Mrenna 2012-10-24