YITP-22-123
Exact analytic expressions of real tensor eigenvalue
distributions
of Gaussian tensor model for small
We obtain exact analytic expressions of real tensor eigenvalue/vector distributions of real symmetric order-three tensors with Gaussian distributions for . This is achieved by explicitly computing the partition function of a zero-dimensional boson-fermion system with four-interactions. The distributions are expressed by combinations of polynomial, exponential and error functions as results of feasible complicated bosonic integrals which appear after fermionic integrations. By extrapolating the expressions and also using a previous result, we guess a large- expression. The expressions are compared with Monte Carlo simulations, and precise and good agreement are obtained with the exact and the large- expressions, respectively. Understanding the feasibility of the integration is left for future study, which would provide a general- analytic formula.
1 Introduction
Eigenvalue distributions are important dynamical quantities in studies of matrix models. They model energy eigenvalue distributions of complex dynamical systems [1]. They provide a major technique in solving matrix models [2]. Their topological properties differentiate phases of matrix models222For more details, see for instance [3]., providing insights into the dynamics of gauge theories [4, 5].
Recently, tensor models [6, 7, 8, 9] attract much attention in various contexts [10]. While it is important to develop efficient techniques of computing eigenvalues/vectors for certain tensors in various practical applications of tensors [11], it is also interesting to study their distributions for ensembles of tensors, because tensors are dynamical in tensor models.
While there are already some interesting results [12, 13, 14, 15, 16, 17], eigenvalue distributions in tensor models still remain largely unexplored. In our previous studies [16, 17], the problem was rewritten as computations of partition functions of zero-dimensional fermion systems. In [16], an exact formula of signed distributions of real eigenvalue/vector distributions for real symmetric order-three tensors with Gaussian distributions was obtained, where each eigenvalue/vector contributed to the distribution by , depending on the sign of a Hessian matrix associated to each eigenvalue/vector. In [17], real eigenvalue/vector distributions for the same ensemble of tensors was studied. In this study, however, only an approximate large- expression333 denotes the dimension of the index vector space of the tensor. was obtained by truncating a Schwinger-Dyson equation, though some closely related exact results were also obtained. While the functional form of the large- expression, which was a Gaussian, agreed well with Monte Carlo simulations, the overall factor did not and an improvement was expected.
In this paper, we rewrite the real eigenvalue/vector problem as a computation of a partition function of a boson-fermion system with four-interactions, instead of the fermion systems in the previous studies [16, 17]. We exactly compute the real eigenvalue/vector distributions for real symmetric order-three tensors with Gaussian distributions for , and extrapolate the expressions to guess a large- expression, including the overall factor, which was not correctly obtained by the approximation of the previous paper [17]. We compare the exact expressions for small with Monte Carlo simulations, and obtain precise agreement. We also compare the large- expression, and obtain good agreement.
Computing the real eigenvalue/vector distributions is essentially the same as the computation of complexity in the -spin spherical model of spin glasses [18, 19] (see Appendix D). By using a rotational symmetry, the problem can be mapped to a random matrix model, which can subsequently be solved by the standard matrix model methods [20, 12, 13]. In fact the results of Section 6 can be obtained from those in [20], as explained in Appendix D. However we expect that the field theoretical method employed in this paper may provide new insights and new applications in future analysis of the tensor eigenvalue/vector problems, which are still largely unexplored.
This paper is organized as follows. In Section 2, we define what we compute, the real eigenvalue/vector distributions for real symmetric order-three tensors with Gaussian distributions. In Section 3, we rewrite the problem as computation of a partition function of a zero-dimensional boson-fermion system with four-interactions. In Section 4, we determine the general form which is obtained by integrating out the fermions in the partition function. In Section 5, we perform the remaining bosonic integrals but one. In Section 6, we explicitly perform the last bosonic integral for each case of , and obtain the explicit exact expressions of the distributions. Interestingly, the apparently complicated bosonic integrals are feasible and the final results have simple expressions. In Section 7, we perform some Monte Carlo simulations, and precise agreement with the exact expressions is obtained. In Section 8, we perform an extrapolation of the exact results for small to guess a large- expression. We compare it with Monte Carlo simulations, and good agreement is obtained. The last section is devoted to a summary and future prospects.
2 Real eigenvector/value distributions of tensors
In this paper, we restrict ourselves to the real symmetric order-three tensors, i.e., , satisfying , as the simplest case. As for eigenvalues/vectors of tensors, there are a few similar but slightly different definitions in the literature [21, 22, 23]. In this paper we employ the definition that the real eigenvectors of a given are the non-zero solutions to
(1) |
where the repeated indices are assumed to be summed over, as will be assumed in the rest of this paper. Then the distribution of the eigenvectors for a given is given by
(2) |
for under the volume measure , where are all the solutions to (1), denotes the absolute value, and
(3) |
Here the absolute value of the determinant, , is the Jacobian associated to the change of the arguments of the -functions performed in (2).
When the tensor has a Gaussian distribution, the real eigenvector distribution is given by
(4) |
where , , , , and , which is the total number of the independent components of .
It is worth commenting on the eigenvalue distribution corresponding to the real eigenvector distribution above. An eigenvalue accompanied with a real eigenvector (a Z-eigenvalue in the terminology of [21]) is defined by
(5) |
where . Comparing with (1), we obtain the relation,
(6) |
Therefore, by using (6) and the fact that is actually a function of because of the rotational symmetry of the distribution, we obtain the real eigenvalue distribution,
(7) |
where in the argument abusively represents an arbitrary vector of size , and , the surface volume of a unit sphere in an -dimensional space.
Here we would like to stress that we are specifically considering real eigenvalues/vectors only. Unlike real symmetric matrices, real symmetric tensors can also have complex eigenvalues/vectors by allowing complex solutions to the equation in (1). To include such complex solutions in our analysis, the expressions in this section need to appropriately be modified. Note also that the connection to the -spin spherical model explained in Appendix D is lost in this case. Therefore the end results for the complex case may have non-trivial differences from the real case.
3 A zero-dimensional boson-fermion system
In this section, we will rewrite (4) with (2) as a partition function of a zero-dimensional boson-fermion system with four-interactions. An immediate obstacle in doing this is the presence of an absolute value in (2), which is not an analytic function. To rewrite it in an analytic form, we take
(8) |
where is an identity matrix, and the parameter is a positive small regularization parameter, which assures the convergence of the integrals below.
Determinant factors like (8) can be managed inside partition functions of zero-dimensional field theoretical systems. This technique is common in supersymmetric approaches to disorder averaging in statistical physics (see for instance [24] and references therein). The numerator can be rewritten as by introducing a fermion pair, and [25]. However, the exponent of this expression contains in a quadratic manner (see (3)) and is difficult to handle when we perform an integration over as will be done below. Therefore, as was done previously in [17], we introduce another fermion pair, , to rewrite the exponent in a form linear in :
(9) |
where the contracted indices are suppressed for brevity: , , and so on. The equality can be shown by noting that . In a similar manner we obtain
(10) |
where is a new bosonic variable, and , and so on.
By using (8), (9), (10) and a well-known formula, , (4) with (2) can be rewritten as
(11) |
where
(12) |
with a new bosonic variable to rewrite the -functions.
Next, let us perform the integrations over and in the expression (11). Let us first consider . The terms containing in (12) are
(13) |
Then we obtain
(14) |
where
(15) |
where the summation is over all the permutations of , which is necessary because is a symmetric tensor. By explicitly expanding (15), we obtain
(16) |
where
(17) |
Here , and , etc., and and are respectively the projection matrices to the parallel and transverse subspaces to .
Next let us perform the integration over . Picking up the terms containing (with no ) in (12) and (16), we obtain
(18) |
Considering that is a sum of the projection matrices as in (17), we obtain
(19) |
where from (17), and
(20) |
Here we have used , and , and so on, where denotes vector projected to the transverse subspace to . From (17) the projections of and are more explicitly given by
(21) |
The first term in the second line of (20) is a constant contribution to the potential. The second and the third terms in the same line are corrections to the kinetic terms of the parallel components of the fermions and the bosons, respectively. The other terms describe the four-interaction terms among the bosons and the fermions. Collecting the results above, we obtain the following intermediate expression,
(22) |
where
(23) |
Here contain only the fermions, only the bosons, and is a mixture. Note that the quadratic terms of the parallel components in and have been corrected by the aforementioned terms from the second line of (20).
Now we want to compute more explicitly. The computation of in (23) is essentially the same as the derivation of the four-fermi interaction terms in [17] for . By noting that two of the terms in [17] do not appear, because (for ), we obtain
(24) |
What seems surprising in this expression is that the parallel components of the fermions cancel out from the interactions after all.
As for and in (23), by using the results of the computations of and in Appendix A, we obtain
(25) |
We again find the surprising fact that no parallel components appear in and .
4 Integrations over fermions
In the expression (26) the variables projected to the transverse directions, i.e., , etc., just represent -dimensional degrees of freedom with no other restrictions. Therefore we can simply regard them as -dimensional variables from the beginning. The external variable, the vector , only appears in the coupling constants of the four-interactions through . Therefore we can simply write
(28) |
where all the variables are -dimensional, and
(29) |
Note that, for simplicity, we are abusively using the same notations of the variables as those in Section 3 with a different dimension, and, to indicate this difference, the symbol is attached to the integral symbol in (28).
To compute explicitly, we first perform the fermionic integrations. The integrand in (28) can be expanded in the fermions. A useful property in this expansion is that the expansion in stops at the fourth order:
(30) |
This can be proven as follows. The fermions in are projected to or . Therefore contains only eight independent fermions in total, i.e., . Since each term of contains two of these fermions and products of more than eight of these fermions vanish, we obtain
(31) |
We also notice that, when , only four of these fermions are independent. Therefore,
(32) |
Now we want to determine the functional forms of the fermionic integrals of each summand in (30):
(33) |
From the form of and the symmetry, should be a polynomial function of , and its order in should be . In addition, each term of the polynomial function should contain equal numbers of and , and the polynomial function should also be invariant under the interchange as a whole.
From the above considerations, we uniquely obtain for
(34) |
Here is a function of and , and all below are also so.
For , we have two possibilities,
(35) |
As for , must vanish for due to (32). Considering also the other conditions mentioned above, we uniquely obtain
(36) |
As for , we need not only (32) but also the following property: Taking the derivatives of with respect to three times or less must vanish, when . This can be proven as follows. Obviously, is proportional to the product of the eight projected fermions, . After taking the derivatives of this three times or less with respect to , each term contains at least five of the eight projected fermions. Therefore all these terms vanish for because of the same reason for (32). Now using this property, we can uniquely determine
(37) |
Collecting all the results above, we conclude that the fermionic integrations of the partition function has the following general form,
(38) |
Here are generally functions of and , but in them turn out to simply disappear in the limit in (28) without any essential roles. Therefore in the following sections we ignore it by just putting in .
5 Integrations over bosons
Assuming the form (38) of the fermionic integrations, we perform the bosonic integrations but one in this section.
Let us first generalize the bosonic kinetic term by introducing new parameters :
(39) |
where are assumed for the convergence of the bosonic integration. The original kinetic term in (29) corresponds to .
Using this new kinetic term, (28), and (38), can be expressed as
(40) |
where
(41) |
with being the following partial derivative operators,
(42) |
The bosonic integration in (41) does not seem to be fully integrable, but it has a simpler expression. Since appears at most quadratically in , the integration can be performed:
(43) |
where for brevity we have introduced
(44) |
(43) does not depend on the angular directions of , and therefore the integration over these produces the spherical volume, . Then, after applying the derivative operators in (41) and performing a replacement of variable, , we obtain
(45) |
where we have used
(46) |
to delete . As we will see in Section 6, (46) holds for all the cases we consider (namely, ). In fact this relation is essentially important, because otherwise the integrand has an extra factor , and the feasibilty of the integration over which will be performed in Section 6 would become unclear.
6 Analytic expressions
In this section, we explicitly compute the integration (45) for each case of to obtain exact analytic expressions. What is surprising is that the seemingly difficult integrations can be done explicitly. The apparent reason is that the integrand of (45) turns out to be a sum of a total derivative and a simple integrable function.
6.1
6.2
In this case, since the variables in (28) are all one-dimensional, we can ignore the indices. Then we immediately obtain
(48) |
Hence, by explicitly expanding the integrand, we obtain,
(49) |
This determines
(50) |
by comparing with (38). This indeed satisfies (46). Putting (50) into (45), we obtain
(51) |
where the lower incomplete gamma function is defined by
(52) |
and we have used its property,
(53) |
The lower incomplete gamma function with index in (51) is related to the error function by
(54) |
Therefore, from (44) and (51), is represented by a combination of polynomial, exponential, and error functions of . This is common to the other cases of shown below.
6.3
The fermionic integration of (38) seems too complicated to perform by hand. Rather, we use a Mathematica package for Grassmann variables [26]. The result is
(55) |
This indeed satisfies (46). Then, by putting this into (45), we obtain
(56) |
A surprising fact is that the integrand in (56) is actually a total derivative, and we therefore obtain
(57) |
6.4 Larger odd
The strategy taken in Section 6.3 can be generalized for larger odd in the following manner. We first compute the , which are listed for in Appendix B, by using the aforementioned Mathematica package. They indeed satisfy (46). Then, by putting them into (45), we obtain . Similarly to the case of in 6.3, what we find is that the integrand of is a total derivative of the following form for :
(58) |
where are some polynomial functions of . The explicit forms of are given in Appendix B. Therefore, we obtain
(59) |
By using the in Appendix B, the explicit expressions of for are given by
(60) |
Let us lastly comment on our equipment. The computations were done on a machine which had a Xeon W2295 (3.0GHz, 18 cores), 128GB DDR4 memory, and Ubuntu 20 as OS. The computation of quickly takes longer time as becomes larger. , which appears in the next subsection, was the largest feasible case, while we failed to obtain seemingly because of a memory shortage.
6.5 Larger even
The difference from the odd case of Section 6.4 is that the integrand of is a sum of a total derivative and a simple integrable term:
(61) |
Then, by doing the integration, we obtain
(62) |
The lists of for are given in Appendix C. indeed satisfy (46). By putting the values of we obtain the explicit forms of as
(63) |
7 Comparison with Monte Carlo simulations
In this section, we compare the results in Section 6 with Monte Carlo simulations. The procedure is basically the same as that used in [16, 17]. To make this paper self-contained, however, we review the method below.
The eigenvector equation (1) is a system of polynomial equations and it can be solved by an appropriate polynomial equation solver, unless is too large. We use Mathematica 13 for this purpose. It gives generally complex solutions to the equation (1), and we pick up only real ones, since we are only counting real eigenvectors (or Z-eigenvalues). Whether this method covers all the real solutions or not can be checked by whether the number of generally complex solutions obtained for each by a polynomial equation solver agrees with the known number [23]444In fact, for large , Mathematica 13 seems to miss a few solutions for some . We have not pursued the reason for that, but the missing portion is even for our largest case of , and is statistically irrelevant in the present study..
With the above method of solving the eigenvector equation (1), our procedure of Monte Carlo simulation is given as follows.
-
•
Randomly generate a real symmetric tensor with components, , where has a normal distribution with mean value zero and standard deviation one, and is a degeneracy factor,
(64) This random generation of corresponds to in (4), since
(65) due to being a symmetric tensor.
-
•
Compute the real eigenvectors of a generated by the aforementioned method.
-
•
Store each size of all the real eigenvectors.
-
•
Repeat the above processes.
By this procedure, we obtain a sequence of sizes of real eigenvectors, . Then the size distribution of real eigenvectors can be obtained by
(66) |
where is a bin size, is the total number of randomly generated , , and is a support function which takes 1 if the inequality of the argument is satisfied, but zero otherwise. For the comparison with the analytical results obtained in Section 6, (66) should be compared with the size distribution
(67) |
where denotes the surface volume of a unit sphere in an -dimensional space, and the vector in the argument of is an arbitrary vector of size due to the rotational symmetry.
Since a Z-eigenvalue is related with the size of an eigenvector by the relation (6), the real (or Z-) eigenvalue distribution is given by
(68) |
where is a bin size. This quantity should be compared with (7).


In Figure 1, the Monte Carlo results are compared with the analytic expressions for . They agree precisely. Similar precise agreement has been obtained for all .
8 Extrapolation to general
In this section, we point out a few patterns which exist in the expressions of the distributions derived for small in Section 6, and guess an extrapolation to general . A motivation for doing this is to improve the large- expression previously obtained by an approximation using a Schwinger-Dyson equation [17]. The issue of the previous result was that, while the functional form agreed well with the numerical simulation for large-, the overall factor did not. In this section, using the extrapolation, we will guess the overall factor for general and find good agreement with Monte Carlo simulations.
After a thought one notices that for even (namely, ) in Section 6 can be expressed by the following general form:
(69) |
where are Hermite polynomials, are some coefficients generally depending on , and specifically
(70) |
As for , we could not find reasonably simple functions of .
Let us discuss the real eigenvalue distribution for large-, assuming (69) with (70). Because of the relations (6) and (44), and the fact that the major part of the distribution is around as in Figure 1, we are interested in a expansion of (69) with (70). By explicitly doing this one obtains
(71) |
where the factorials are replaced by Gamma functions to also be applicable for odd below. By combining with the previous result in [17] that the large- eigenvalue distribution is given by a Gaussian function of , one could assume that the expansion in of (71) comes from the expression,
(72) |
Putting this into (7) using (6), (40) and (44), we obtain
(73) |
which indeed is a Gaussian distribution. While the coefficient in the exponent indeed agrees with the previous result in [17], the overall factor is different. By integrating over , one can obtain the mean total number of real eigenvalues in large- as
(74) |
In the large- limit, this expression indeed agrees with the result given in [20, 13].555 Namely, Eq.(1.2) in [13].



In Figure 2 we compare the large- expression (73) with the Monte Carlo simulations for .666With our machine power (See the last part of Section 6.4), it took one full day for the computation of the case. They agree well, and the agreement seems to become slightly better, as becomes larger.
In the above discussion, we have not used the odd cases. The reason is that we could not find simple expressions valid across all the odd cases obtained in Section 6. We merely notice
(75) |
where we do not have any simple expressions for .


Rather, we find that the large- behavior of approaches that of , as becomes larger. To see this, let us introduce the parameters of the expansion as
(76) |
As in (71), for even , we have
(77) |
In Figure 3, we plot for each , which are extracted by performing the expansions of the explicit expressions in Section 6. Indeed for odd seem to approach those for even , as becomes larger. This implies that the large- formula (73) can commonly be used for both even and odd .
9 Summary and future prospects
In this paper we have explicitly computed the real eigenvalue/vector distributions for real symmetric order-three tensors with Gaussian distributions for . This has been achieved by rewriting the problem as the computation of a partition function of a zero-dimensional boson-fermion system with four-interactions. We have extrapolated the exact expressions for to guess a large- expression. Monte Carlo simulations have been performed, and precise agreement and good agreement have been obtained for the exact small- expressions and the large- expression, respectively.
It seems surprising that the complicated integrations of the partition function can be performed exactly with the final simple results expressed by polynomial, exponential, and error functions. It is suspected that this is true for any , but deeper understanding of this aspect needed for such generalization is left for future study. Considering the final simple forms, it would be possible that there exist much easier ways to compute the distributions than what has been done in this paper.
There would exist various directions to pursue by a similar strategy of this paper. One obvious direction is the generalization of tensors to those with different orders and non-Gaussian distributions. It would also be interesting to pursue the possibility of topological changes of the distributions in tensor models as in matrix models. In fact, some tensor systems seemingly suggest such possibilities [27, 28]. It would also be possible to compute correlations among eigenvalues/vectors, and also to incorporate complex eigenvalues/vectors.
Acknowledgements
The author is supported in part by JSPS KAKENHI Grant No.19K03825.
Appendix Appendix A Computations of and
From (17),
(A1) |
with
(A2) |
By explicitly writing down the sum and noting that one of the symmetrization is not necessary, we obtain
(A3) |
where we have used , etc., and , etc..
Let us next compute
(A4) |
where
(A5) |
from (17). By explicitly expanding the sum, we obtain
(A6) |
where we have taken similar computational steps as those for .
Appendix Appendix B Lists of and for
For ,
(B1) |
and
(B2) |
For ,
(B3) |
and
(B4) |
Appendix Appendix C Lists of for
For ,
(C1) |
and
(C2) |
For ,
(C3) |
and
(C4) |
For ,
(C5) |
and
(C6) |
Appendix Appendix D Complexity of the spherical -spin model
Computing the distributions of the real tensor eigenvalues/vectors is the same as the computation of complexity777 See for example [29] for a review. of the spherical -spin model [18, 19]. In this appendix, we limit ourselves to corresponding to order-three tensors.
The Hamiltonian of the spherical -spin model (with ) is given by
(D1) |
with the continuous spin variable which has a constraint,
(D2) |
Here the real symmetric tensor is assumed to have the normal Gaussian distribution and can be identified with with in our notation. To match (D2) with our notation, we introduce the change of variable,
(D3) |
and then we have
(D4) |
The problem of computing complexity of the -spin spherical model is to count the number of local minima (and stationary points) of the above Hamiltonian. By using the method of Lagrange multiplier, counting the stationary points is equivalent to solve
(D5) |
where and . The value of is the energy of the stationary point, and can be identified with the same variable employed in [20]. Comparing with the Z-eigenvalue equation (5), we have the relation,
(D6) |
By using (D6), it can be checked that the expressions of the mean distributions of the numbers of the critical points given for general in Section 7.2 of [20] agree with our results in Section 6.
References
- [1] E. P. Wigner, “On the Distribution of the Roots of Certain Symmetric Matrices,” Annals of Mathematics 67 (2), 325-327 (1958) https://doi.org/10.2307/1970008.
- [2] E. Brezin, C. Itzykson, G. Parisi and J. B. Zuber, “Planar Diagrams,” Commun. Math. Phys. 59, 35 (1978) doi:10.1007/BF01614153
- [3] B. Eynard, Counting surfaces : CRM Aisenstadt chair lectures, Prog. Math. Phys. 70, Birkhäuser, 2016.
- [4] D. J. Gross and E. Witten, “Possible Third Order Phase Transition in the Large N Lattice Gauge Theory,” Phys. Rev. D 21, 446-453 (1980) doi:10.1103/PhysRevD.21.446
- [5] S. R. Wadia, “ = Infinity Phase Transition in a Class of Exactly Soluble Model Lattice Gauge Theories,” Phys. Lett. B 93, 403-410 (1980) doi:10.1016/0370-2693(80)90353-6
- [6] J. Ambjorn, B. Durhuus and T. Jonsson, “Three-dimensional simplicial quantum gravity and generalized matrix models,” Mod. Phys. Lett. A 6, 1133-1146 (1991) doi:10.1142/S0217732391001184
- [7] N. Sasakura, “Tensor model for gravity and orientability of manifold,” Mod. Phys. Lett. A 6, 2613-2624 (1991) doi:10.1142/S0217732391003055
- [8] N. Godfrey and M. Gross, “Simplicial quantum gravity in more than two-dimensions,” Phys. Rev. D 43, R1749(R) (1991) doi:10.1103/PhysRevD.43.R1749
- [9] R. Gurau, “Colored Group Field Theory,” Commun. Math. Phys. 304, 69-93 (2011) doi:10.1007/s00220-011-1226-9 [arXiv:0907.2582 [hep-th]].
- [10] M. Ouerfelli, V. Rivasseau and M. Tamaazousti, “The Tensor Track VII: From Quantum Gravity to Artificial Intelligence,” [arXiv:2205.10326 [hep-th]].
- [11] L. Qi, H. Chen, Y, Chen, Tensor Eigenvalues and Their Applications, Springer, Singapore, 2018.
- [12] P. Breiding, “The expected number of eigenvalues of a real gaussian tensor,” SIAM Journal on Applied Algebra and Geometry 1, 254-271 (2017).
- [13] P. Breiding, “How many eigenvalues of a random symmetric tensor are real?,” Transactions of the American Mathematical Society 372, 7857-7887 (2019).
- [14] O. Evnin, “Melonic dominance and the largest eigenvalue of a large random tensor,” Lett. Math. Phys. 111, 66 (2021) doi:10.1007/s11005-021-01407-z [arXiv:2003.11220 [math-ph]].
- [15] R. Gurau, “On the generalization of the Wigner semicircle law to real symmetric tensors,” [arXiv:2004.02660 [math-ph]].
- [16] N. Sasakura, “Signed distributions of real tensor eigenvectors of Gaussian tensor model via a four-fermi theory,” Phys. Lett. B 836, 137618 (2023) doi:10.1016/j.physletb.2022.137618 [arXiv:2208.08837 [hep-th]].
- [17] N. Sasakura, “Real tensor eigenvalue/vector distributions of the Gaussian tensor model via a four-fermi theory,” PTEP 2023, no.1, 013A02 (2023) doi:10.1093/ptep/ptac169 [arXiv:2209.07032 [hep-th]].
- [18] A. Crisanti and H.-J. Sommers, “The spherical p-spin interaction spin glass model: the statics”, Z. Phys. B 87, 341 (1992).
- [19] T. Castellani and A. Cavagna, “Spin-glass theory for pedestrians”, J. Stat. Mech.: Theo. Exp. 2005, P05012 [arXiv: cond-mat/0505032].
- [20] A. Auffinger, G.B. Arous, and J. Černý, “Random Matrices and Complexity of Spin Glasses”, Comm. Pure Appl. Math., 66, 165-201 (2013) doi.org/10.1002/cpa.21422 [arXiv:1003.1129 [math.PR]].
- [21] L. Qi, “Eigenvalues of a real supersymmetric tensor,” Journal of Symbolic Computation 40, 1302-1324 (2005).
- [22] L.H. Lim, “Singular Values and Eigenvalues of Tensors: A Variational Approach,” in Proceedings of the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP ’05), Vol. 1 (2005), pp. 129–132.
- [23] D. Cartwright and B. Sturmfels, “The number of eigenvalues of a tensor,” Linear algebra and its applications 438, 942-952 (2013).
- [24] Fyodorov, Y.V., Nock, A. “On Random Matrix Averages Involving Half-Integer Powers of GOE Characteristic Polynomials,” J. Stat. Phys. 159, 731-751 (2015). https://doi.org/10.1007/s10955-015-1209-x
- [25] J. Zinn-Justin, Quantum Field Theory and Critical Phenomena, (Clarendon Press, Oxford, 1989).
- [26] M. Headrick, J Michelson, grassmann.m, https://people.brandeis.edu/~headrick/Mathematica/.
- [27] T. Kawano and N. Sasakura, “Emergence of Lie group symmetric classical spacetimes in the canonical tensor model,” PTEP 2022, no.4, 043A01 (2022) doi:10.1093/ptep/ptac045 [arXiv:2109.09896 [hep-th]].
- [28] N. Sasakura, “Splitting-merging transitions in tensor-vectors systems in exact large-N limits,” Phys. Rev. D 106, no.12, 126016 (2022) doi:10.1103/PhysRevD.106.126016 [arXiv:2206.12017 [hep-th]].
- [29] A. Crisanti, L. Leuzzi, and T. Rizzo, “The complexity of the spherical p-spin spin glass model, revisited”, Eur. Phys. J. B 36, 129-136 (2003) doi.org/10.1140/epjb/e2003-00325-x [arXiv:cond-mat/0307586].