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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>OPTIMIZATION OF THE COMPUTATION OF MULTIDIMENSIONAL INTEGRALS FOR ESTIMATING THE MESON LIFETIME</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>D. Goderidze</string-name>
          <email>goderidze@jinr.ru</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Yu.L. Kalinovsky</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A.V. Friesen</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Daviti Goderidze</institution>
          ,
          <addr-line>Yuri Kalinovsky, Alexandra Friesen</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Joint Institute for Nuclear Research</institution>
          ,
          <addr-line>6 Joliot-Curie, Dubna, 141980</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2021</year>
      </pub-date>
      <fpage>5</fpage>
      <lpage>9</lpage>
      <abstract>
        <p>To calculate the lifetime of mesons in hot and dense nuclear matter, it is necessary to compute multidimensional integrals with a complicated integrand function. This work presents an algorithm and methods to calculate such integrals on the basis of the Monte-Carlo method. To optimize the computation, the parallel calculation algorithm is implemented in the C++ programming language using OpenMP and NVIDIA CUDA technologies. The calculations are performed on nodes with multicore CPUs and Intel Xeon Phi coprocessors and the Nvidia Tesla K40 accelerator installed within a heterogeneous cluster of the Meshcheryakov Laboratory of Information Technologies, Joint Institute for Nuclear Research, Dubna. The code is used to calculate the pion lifetime using all possible pionpion scattering modes.</p>
      </abstract>
      <kwd-group>
        <kwd>meson lifetime</kwd>
        <kwd>pion damping</kwd>
        <kwd>Monte Carlo</kwd>
        <kwd>parallelization</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and</p>
      <p>Education" (GRID'2021), Dubna, Russia, July 5-9, 2021</p>
    </sec>
    <sec id="sec-2">
      <title>1. Meson lifetime</title>
      <p>The investigation of particles and their properties, including scattering and decay modes, the
lifetime and width of particles in critical conditions of heavy ion collisions, is an important problem in
modern physics. The theoretical description of strong-interaction matter under critical conditions is a
complicated task, and it is not always possible to find an analytical solution to the problem. Therefore,
the use of modern computer technologies plays a key role in theoretical research.</p>
      <p>This paper is devoted to the investigation of the pion damping width in a hot pion gas within
the NJL model. The main contribution to the width/lifetime comes from pion–pion collisions. To
calculate the meson lifetime in hot and dense nuclear matter, it is necessary to compute 5-dimensional
integrals with a complicated integrand function. This work presents an algorithm and methods for the
calculation of complicated integrals based on the Monte-Carlo method using the parallelization
algorithm to optimize the computation time.</p>
      <p>
        The meson lifetime  is determined by the particle self-energy [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]:
Г =  −1 =  &gt;( ) ±  &lt;( ),
(1)
where the sign depends on the type of the particles: «+» for fermions and «-» for bosons. The  &gt;
function is responsible for direct processes, when a particular state decays into other states. The  &lt;
function is responsible for inverse processes that can restore the decayed state due to the decay of
other particles to this state again. This process prolongs the lifetime of particles in the medium. The Σ
functions have a complicated form:
 &gt;(&lt;)( ) =
      </p>
      <p>1
(2 )3
∫   ∫
  ⃗1 1
2 1 8</p>
      <p>1
∫−1  (
)</p>
      <p>| ⃗3|2
| ⃗3|2(√ 2+ 1)−| ⃗1| 3
| |2  &gt;(&lt;),
(2)
where  
= 
1</p>
      <p>( 1)  3 ( 3)  4 ( 4), the spectral function is calculated in the
BreitWigner form  ( ) = 2   ((</p>
      <p>1( 3 + 1)( 4 + 1) and
 −   2)2 +   2
  2)−1
with</p>
      <p>
        =  2. The factors  &gt; =
 &lt; = ( 1 + 1) 3 4 are introduced for brevity, and   are
the particle distribution functions   = (
statistics [
        <xref ref-type="bibr" rid="ref1 ref2">1, 2</xref>
        ]. The momenta  ⃗ 3 are defined as:
      </p>
      <p>( √  +  ̅2) ± 1)−1 according to the particle
| ⃗3|1,2 =
| ⃗1| 
± √| ⃗1|2 2
2 + ((√ 2 +  1)2 − | ⃗1|2
2((√ 2 +  1)2) − | ⃗1|2
2

2 )( 2 − 4 3(√ 2 +  1)2)
(3)
with  = (√ 2 +  1)2 +  3 −  4 +  1 −  12.</p>
      <p>To calculate the meson lifetime, the scattering amplitude | | of the process under investigation
should be calculated. The amplitude | | is generally considered as an invariant amplitude and depends
on the Mandelstam variables  ,  ,  , where  +  +  =
∑  .</p>
      <p>It is seen from Eq. (2) that the structure of the integrand function is complicated and depends
on many variables. The complex structure of the integrand is due to the kinematic conditions of
physical processes and is limited by the pole in the denominator and the negative value of the radical
expression. To show the 5-dimensional integration domain for the integral (2), we transfer it to the
plane ( ⃗1,  ⃗3), since by generating the arbitrary point ( 1,  3,  4,  ⃗1, cos  ) it is possible to determine  ⃗3
for the fixed  ⃗1 (Fig. 1).</p>
    </sec>
    <sec id="sec-3">
      <title>2. Optimization of computing</title>
      <p>
        In this work, the Monte Carlo (MC) method [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] is used to calculate the integrals in Eq. (2). It
is well known that the accuracy of the MC method depends on the number of selected points, as well
as on the quality of the random number generator. Tina’s Random Number Generator (TRNG) [4] is
chosen for calculations as it has various distributions (uniform and non-uniform) and is also optimized
for using in parallel computations. Parallel calculations are required for the integrals in Eq. (2), and the
result and accuracy strongly depend on the number of selected points and the best convergence is
achieved after the number of points reaches 2∙107 (Fig. 2, left). The optimization of computations is
carried out in two directions: simplification of the functions and use of parallelization technology.
0.8
0.6
03
1
- 0
1
2
l,t
u
s
e
1
R
00
1.5
8
- 10.0
1
l,t
u
s
0.5
e
R
0.00
      </p>
      <p>
        To obtain the selected point in the integration domain of Eq. (2), it is necessary to generate 5
random numbers. Taking into account the fact that cos(α) changes in [
        <xref ref-type="bibr" rid="ref1">-1,1</xref>
        ], the reflection of the
selected cos(α) from [
        <xref ref-type="bibr" rid="ref1">0,1</xref>
        ] to [-1,0] relative to zero, while saving the other variables, reduces the
required number of generations twice. Since  &gt; and  &lt; differ by the factor  &gt;(&lt;), the positions of the
special points for these functions are the same, which allows calculating the functions Σ
simultaneously to reduce the total computation time twice. This method reduces the number of the
generated points and the total number of the required calculations by 4 times, thus accelerating the
computation process.
      </p>
      <p>According to the standard MC method, if the accuracy of the integral calculated over N
selected points is insufficient, the number of points should be increased. To optimize calculations, the
additional number of the required selected points is equal to the increase step M. The calculated results
for M points are added to the previous calculations to get the final answer, and the accuracy is checked
for N+M points.</p>
      <p>
        Parallelization is also used to accelerate the machine time for computations. For this purpose,
the number of generated points (N) is evenly distributed among all threads (P). The remainder of the
points (N mod P) is also additionally distributed over the required number of threads (instead of
sending it to one thread). The program is implemented for computations in both single-thread and
multi-thread versions. The multi-thread version uses such parallelization technologies as OpenMP and
NVIDIA CUDA [
        <xref ref-type="bibr" rid="ref4 ref5">5, 6</xref>
        ].
      </p>
      <p>Error of S&gt;
Error of S&lt;
2 4 6
Points number, 107
8
10
2 4 6
Points number, 107
8
10</p>
      <p>The tests are performed at a fixed temperature T = 0.15 GeV,   = 0.143 GeV and a fixed
amplitude |A| = 1 for a different number of selected points. Fig. 2 (left) shows the results of
calculations of Г, Σ&gt;, Σ as a function of the number of selected points. Fig. 2 (right) illustrates the
upper error bounds. As seen in Fig. 2 (left), after the limit of 3-4∙107 points, the result becomes
insensitive to an increase in the number of calculations, which is caused by a decrease of the upper
error bounds.</p>
      <p>To speed up calculations, parallelization technologies are used. Table 1 shows the computation
time with the generation of 2*107 points for a different number of threads. The calculations are also
performed on the HybriLIT heterogeneous platform of the Meshcheryakov Laboratory of Information
Technologies, JINR, Dubna [7]. As demonstrated in Table 1, the use of HybriLIT parallelization
resources extremely reduces the computation time.</p>
    </sec>
    <sec id="sec-4">
      <title>3. Pion damping</title>
      <p>The physical background of this work is the calculation of the pion lifetime in hot nuclear
matter. The amplitude of pion scattering is defined within the NJL model with meson-exchange
diagrams considered in the pole approximation, which leads to amplitudes similar to the linear sigma
model [8] with isospin amplitudes:
 0 = 5 4 +  2</p>
      <p>2
 1 =  2</p>
      <p>2
 2 = 2 4 +  2
 2</p>
      <p>3
(
  2 −</p>
      <p>1
(
  2 − 
+
−</p>
      <p>1
  2 −</p>
      <p>1
  2 − 
+
) ,</p>
      <p>1
  2 −</p>
      <p>) ,
1
(
  2 − 
+</p>
      <p>1
  2 − 
) ,
where all parameters, the meson mass   and interaction constants     ,   qq, depend on temperature,
and  4 is supposed to be a constant of the 4-pion interaction,  ,  ,  are the Mandelstam variables.
The coupling strength   is defined as   ( ,  ) = 2   2 Γ ( ,  ), where Γ ( ,  ) is
the amplitude of the triangle vertex σ → ππ.</p>
      <p>
        The temperature dependence for the masses and constants is chosen within the NJL model and
can be found, for example, in [
        <xref ref-type="bibr" rid="ref6">9</xref>
        ]. In the case of pion–pion collisions, the following processes
contribute to the total cross section:
(ππ⟶ππ) =  (π0π0⟶π0π0) +  (π0π0⟶π+π-) + 2 (π0π+⟶π0π+).
      </p>
      <p>The process π0π+⟶π0π+ occurs at the same rate as π0π-⟶π0π-, so we do not calculate them
separately; we just put the factor 2. The calculation result is given in Fig. 3. It is clearly seen, that in a
hot gas, the pion spectral function significantly broadens (due to an increase in the width) near the
critical temperature, which is about 0.17 GeV for this version of the NJL model.</p>
    </sec>
    <sec id="sec-5">
      <title>4. Conclusion</title>
      <p>An algorithm for calculating the pion lifetime as a function of temperature is presented. Since
the integrals (2) have a complicated integrand function, it is necessary to select a large number of
points, which leads to an increase in the computation time.</p>
      <p>To minimize the error, tests with a constant amplitude and a fixed temperature are performed
(Fig. 2). The goal of the tests is to identify the minimal number of points for the initial step to plot the
pion width as a function of temperature (Fig. 3). However, it cannot be argued that the test results
obtained at a fixed temperature are relevant for all temperatures and a non-constant amplitude.
Therefore, for each subsequent temperature, an additional calculation is carried out. The calculation
with an increasing number of points (with the increase step M) is performed until the error obtained in
the current iteration becomes worse than in the previous one. Nevertheless, it is difficult to obtain a
smooth behavior of the function Γ( ) near critical temperatures (Fig. 3). Fig. 3 shows a comparison
of our results with GSL-integration tools (VEGAS) [10].</p>
      <p>To optimize the computation time, integral optimization and parallelization technologies (such
as OpenMP, CUDA and their combination) are applied to the code. The use of the resources of the
HybriLIT cluster reduces the computation time and enhances code efficiency.</p>
    </sec>
    <sec id="sec-6">
      <title>5. Acknowledgement References</title>
      <p>The work was supported by the RFBR, grant No. 18-02-40137.
2021.</p>
    </sec>
  </body>
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