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--> --> -->To evaluate a two-loop five-light-parton scattering amplitude, one usually first generates an integrand, reduces all of the Feynman integrals to linear combinations of relatively simpler master integrals (MIs), and finally calculates these MIs. Because integrands can be obtained either using the unitarity method [4-9] or using the conventional Feynman diagram method, and because MIs can be calculated analytically [20-24], the bottleneck is the reduction of Feynman integrals. For example, the non-planar contribution of two-loop three-photon production at the LHC cannot be calculated, owing to the lack of such reduction for nonplanar integrals [19].
Reduction is usually achieved by integration-by-parts (IBP) identities combined with Laporta's algorithm [25-35]. Although many interesting proposals have been made recently for improving the IBP reduction [36-49], the problem of reducing multiloop multiscale integrals has not been fully solved yet. The difficulty is twofold. On the one hand, owing to the number of scales, an explicit solution of the IBP system is usually too big to be used in numerical calculations; in addition, it is very difficult to obtain [47-51]. On the other hand, although solving the IBP system numerically in a single run is feasible, one usually needs to solve it many times, for either the phase space integration or fitting analytical expressions, which is very time- and resource-consuming. For example, to reconstruct the fully analytical two-loop five-gluon all-plus helicity amplitude [17], one needs to run the numerical computation of the IBP for nearly half a million times①. If one uses the same method for reconstructing analytical one-minus or maximal-helicity-violation amplitude, many more IBP calculation runs may be needed, which becomes prohibitive.
We note that a reduction can be obtained efficiently if a system of block-triangular relations is found, which has a small expression size and can be solved numerically very efficiently. Using our proposed series representation of Feynman integrals as input [52, 53], in Ref. [52] we described an algorithm that searched for block-triangular relations and yielded some preliminary results. Although our method developed in Ref. [52] is sufficiently good for reducing integrals with integrands having only denominators, the method is very time-consuming for physical problems that contain integrands with numerators.
In this paper, by further developing the method in Ref. [52], we propose a two-step search strategy along with a reduction scheme that is suitable for physical problems. Based on this, we successfully find out block-triangular relations to reduce integrals in two-loop five-light-parton scattering amplitudes. As expected, the relations are only 148 MB in size, and can be numerically solved hundreds of times faster than using other methods. Our work constitutes an important step towards the complete NNLO QCD calculation for three-jet, photon, or hadron production at the LHC. Because our method is efficient and general, it can be straightforwardly applied to any other process, thus providing a practical solution for the bottleneck problem of reducing Feynman integrals.
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Let us consider the most complicated case, topology (a) in Fig. 1, as an example that will explain what kind of Feynman integrals do we need to reduce. There are five external momenta
$\begin{split} D_1 = &\ell_1^2,D_2 = (\ell_1+p_1)^2,\,D_3 = (\ell_1+p_1+p_2)^2,\,\\ D_4 =& \ell_2^2,\,D_5 = (\ell_2+p_3)^2, D_6 =(\ell_1+\ell_2+p_1+p_2+p_3)^2,\,\\ D_7 =& (\ell_1+\ell_2-p_4)^2,\,D_8 =(\ell_1+\ell_2)^2,\\ D_9 =& (\ell_2+p_1)^2,D_{10} = (\ell_2+p_2)^2,\\D_{11} =& (\ell_2+p_4)^2, \end{split}$ ![]() | (1) |
$ I_{\vec{\nu}}(\epsilon,\vec{s}\,) = \int\frac{{\rm{d}}^{4-2\epsilon}\ell_1\, {\rm{d}}^{4-2\epsilon}\ell_2}{({\rm{i}}\pi^{2-\epsilon})^2}\,\frac{D_9^{-\nu_9}D_{10}^{-\nu_{10}}D_{11}^{-\nu_{11}}}{D_1^{\nu_1}...\,D_8^{\nu_8}}, $ ![]() | (2) |
For later convenience, we define operators
$ \begin{split}& \hat{1}^+I_{\{1,1,1,1,1,1,1,1,-4,0,-1\}} = \{I_{\{2,1,1,1,1,1,1,1,-4,0,-1\}},\\&\quad I_{\{1,2,1,1,1,1,1,1,-4,0,-1\}}, I_{\{1,1,2,1,1,1,1,1,-4,0,-1\}},\\&\quad I_{\{1,1,1,2,1,1,1,1,-4,0,-1\}}, I_{\{1,1,1,1,2,1,1,1,-4,0,-1\}},\\ &\quad I_{\{1,1,1,1,1,2,1,1,-4,0,-1\}}, I_{\{1,1,1,1,1,1,2,1,-4,0,-1\}}, \\ &\quad I_{\{1,1,1,1,1,1,1,2,-4,0,-1\}}, I_{\{1,1,1,1,1,1,1,1,-3,0,-1\}},\\ &\quad I_{\{1,1,1,1,1,1,1,1,-4,0,0\}}\}\,, \end{split} $ ![]() | (3) |
$ \begin{split} &\hat{1}^-I_{\{1,1,1,1,1,1,1,1,-4,0,-1\}} = \{I_{\{0,1,1,1,1,1,1,1,-4,0,-1\}},\\ &\quad I_{\{1,0,1,1,1,1,1,1,-4,0,-1\}}, I_{\{1,1,0,1,1,1,1,1,-4,0,-1\}}, \\ &\quad I_{\{1,1,1,0,1,1,1,1,-4,0,-1\}}, I_{\{1,1,1,1,0,1,1,1,-4,0,-1\}},\\ &\quad I_{\{1,1,1,1,1,0,1,1,-4,0,-1\}}, I_{\{1,1,1,1,1,1,0,1,-4,0,-1\}}, \\ &\quad I_{\{1,1,1,1,1,1,1,0,-4,0,-1\}}, I_{\{1,1,1,1,1,1,1,1,-5,0,-1\}},\\ &\quad I_{\{1,1,1,1,1,1,1,1,-4,-1,-1\}},I_{\{1,1,1,1,1,1,1,1,-4,0,-2\}}\}\,. \end{split} $ ![]() | (4) |
As is well-known, the most complicated② integrals in the amplitudes are those with the highest number of propagators, i.e.,
$ S_{(a)} = {\hat 5}^\circleddash I_{\{1,1,1,1,1,1,1,1,0,0,0\}}, $ ![]() | (5) |
For topologies (b), (c), and (d) in Fig. 1, we define sets of target integrals
The advantage of a system of block-triangular relations over the explicit solution can be understood based on the integrals' singularities. If we express a complicated integral as a linear combination of simpler MIs, powers of Gram determinants will appear in the denominators of the coefficients of these MIs, which is necessary because only thus the linear combination of MIs can generate correct singularities of the target integral. Then, the numerators of these coefficients will have high mass dimensions and thus will have very long expressions. This difficulty can be nicely resolved using a system of block-triangular relations. Relations in each block can be very simple, but their solution can naturally generate Gram determinants in the denominator. Furthermore, correctly choosing the blocks may result in the solution involving only one Gram determinant.
Because reduction at the multiloop level is much more complicated than for the one-loop case, the above discussion implies that constructing a system of block-triangular relations may be the best way to reduce multiloop multiscale integrals. Unlike the one-loop case, where block-triangular systems can be achieved easily by analytically solving the IBP relations, block-triangular systems at the multiloop level are in general difficult to obtain.
In Ref. [52], based on our proposed series representation of Feynman integrals [52, 53] as input information, we constructed an algorithm that searched for block-triangular relations to reduce multiloop multiscale integrals. However, we found the method to be very time-consuming for physical problems, although it was efficient for reducing integrals with integrands containing only denominators. To deal with physical problems such as two-loop five-light-parton integrals, we propose here a two-step search strategy.
In the first step, we set up a system of relations that can numerically express all of the target integrals in terms of MIs. The system is allowed to be somewhat inefficient in numerical calculations; thus, the system is not required to be block-triangular. This system can be obtained either by using our series representation of Feynman integrals [52], or simply by using the well-known IBP system.
In the second step, we search for a system of block-triangular relations, which needs to be very efficient for numerical computations. The algorithm is the same as that proposed in Ref. [52] except that, instead of using our series representation of Feynman integrals, we use the numerical solution obtained in the first step as input information.
More details about the search strategy can be found in appendix.
Using the above method, we successfully determined systems of block-triangular relations for integrals in the four topologies in Fig. 1. The file sizes for all of these relations are acceptable, ~148 MB. To obtain these results required ~200 central processing unit (CPU) core hours to search for relations in the second step of the two-step search strategy, in addition to hundreds of CPU-core hours for generating input information by numerically solving the system obtained in the first step. Some basic information about these results is listed in Table 1.
top. | ![]() ![]() | ![]() ![]() | ![]() ![]() | ![]() ![]() | size/MB |
(a) | ![]() ![]() | ![]() ![]() | 112 | 0.17 | 66 |
(b) | ![]() ![]() | ![]() ![]() | 31 | 0.090 | 40 |
(c) | ![]() ![]() | ![]() ![]() | 56 | 0.075 | 31 |
(d) | ![]() ![]() | ![]() ![]() | 8 | 0.035 | 11 |
Table1.Main information about the obtained reduction relations.
For more intuitive understanding, we show a matrix density plot for the block-triangular system of topology (a) in Fig. 2. This system contains 3914 integrals and 108 MIs, which means we need 3806 linear relations to reduce all of the target integrals. In this plot, each line represents a relation, each column corresponds to an integral, and black points represent nonzero elements in the matrix. Integrals are ordered, from the most complicated one to the simplest one, with MIs at the end of each line. The matrix is exactly block-triangular, and the largest block contains only tens of relations.
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Analytic expressions for all of these relations are available from the website in [57]. Technical details about our reduction scheme can be found in appendix.
For each given numerical point
Compared with explicit solutions, the file sizes of our reduction relations are much smaller. The file size for explicit solutions of eight-propagator integrals with degree up to 4 in topology (a), 26 integrals overall, is ~2 GB [48]; that for the explicit solutions of eight-propagator integrals with degree up to 4 in topology (b), 32 integrals overall, is ~0.8 GB [47]; and that for the solutions of all integrals in topology (c) is in excess of 20 GB for a compressed format [49]. It can be expected that our relations should be hundreds of times smaller than the complete explicit solution in terms of the file size, which results in more than a 100-fold speedup of numerical calculations, even if there is no memory deficit for storing the huge expressions of explicit solutions.
We note that the file size of trimmed IBP relations to reduce all of the integrals considered in this work is a few GB, which is also much larger than that of our reduction relations. The reason is that, although each IBP relation is simpler than ours, the IBP system involves hundreds of times more equations. Furthermore, the time spent on numerical IBP is dominated by the latter factor, because IBP relations are coupled in a complicated way. As a result, numerical IBP should be much more inefficient than our method. Through our test, numerical IBP via
The above comparison reveals the advantage of our method. Numerical evaluation of explicit solutions spends too much time on assignments; while numerical IBP spends too much time on solving linear equations. Our method performs better on both parts, and therefore it is much more efficient. Similar to numerical evaluations over the field of prime numbers, our reduction relations should also be much more efficient for numerical evaluations with floating numbers, which enables phase-space integration to obtain physical cross-sections.
To obtain the block-triangular relations, we developed the method in Ref. [52] by proposing a two-step search strategy along with a reduction scheme. As our newly developed method is general and efficient, other more complicated problems, like two-loop integrals for
In the current application of our method, most CPU time is allocated to solving the system obtained in the first step. Although the time spent is tolerable for the current problem, improvement may be needed for more complicated applications. There are different options. Using the method in [52], better integral sets can be explored. Another possible choice is to use trimmed IBP systems obtained by solving the Syzygy equations [44-48]. These possibilities will be addressed in future studies.
We thank K.T. Chao, F. Feng, Q.J. Jin, Z. Li, X.H. Liu, H. Luo, C. Meng, J. Usovitsch and Y. Zhang for many useful communications and discussions.
A.1.Search strategy: step one
We take integrals originated from topology (a) in the main text as an example for explaining the details of our technique.We want to set up a set of relations, using which we can express all integrals in
For each given integral
$\tag{A1} G_{\vec{\nu}}^{\rm{IBP}} = \{\hat{1}^+, \hat{1}^-\hat{1}^+\} I_{\vec{\nu}}. $ ![]() | (6) |
The above IBP relations can also be found out easily using the method proposed in [52]. To this end, we introduce a parameter
The advantage of our method in [52] is that it allows to search for relations among any set of integrals. As the simplest generalization of
$\tag{A2} G_{\vec{\nu}} = \{\hat{1}^+, \hat{1}^-\hat{1}^+,\hat{1}^-\} I_{\vec{\nu}}, $ ![]() | (7) |
One can certainly explore other integral sets for each seed, to further improve the reduction efficiency. We did not do that because the efficiency of either the IBP set (6) or the generalized set (7) is sufficient for us to deal with the problem in this work.
With integral sets in hand, we generate a system of linear equations from all seeds belonging to
2
A.2.Search strategy: step two
In this step, we search linear relations to reduce the given target integrals inWe first describe how to search linear relations among the integral set
$\tag{A3} \sum\limits_{i = 1}^N Q_i(\epsilon,\vec{s}\,) I_i(\epsilon,\vec{s}\,) = 0\,, $ ![]() | (8) |
$\tag{A4} Q_i(\epsilon,\vec{s}\,) = \sum\limits_{\kappa = 0}^{\epsilon_{\rm{max}}} \sum\limits_{\vec{\lambda}\in\Omega_{d_i}} \tilde{Q}_i^{ \kappa\lambda_1\ldots \lambda_5} \,\epsilon^{\kappa}s_1^{\lambda_1}\cdots s_5^{\lambda_5}, $ ![]() | (9) |
Based on the system of equations in the first step, for a given numerical point
$\tag{A5} I_i = \{C_{i,1}, \cdots, C_{i,108}\}\,,\quad i = 1,\cdots,N\,. $ ![]() | (10) |
To reduce
2
A.3.Reduction scheme
The reduction scheme determines which integrals should be involved in each block. We generate the integrals through previously defined operatorFor example, in the first block for topology (a), we need to reduce the most complicated
After reducing the top-sector integrals, we still need to reduce the integrals in the subsectors. For example, for the seven-propagator sector
Based on the above scheme, we obtain 3801 reduction relations. By introducing additional 5 symmetry relations among MIs, we have 3806 relations in total that can express 3914 integrals in
We note that there is a way to further reduce the block size that has not been applied in this work. For example, by setting