Skip to main content

Advertisement

Log in

Stationary stochastic Higher Spin Six Vertex Model and q-Whittaker measure

  • Published:
Probability Theory and Related Fields Aims and scope Submit manuscript

Abstract

In this paper we consider the Higher Spin Six Vertex Model on the lattice \({\mathbb {Z}}_{\ge 2} \times {\mathbb {Z}}_{\ge 1}\). We first identify a family of translation invariant measures and subsequently we study the one point distribution of the height function for the model with certain random boundary conditions. Exact formulas we obtain prove to be useful in order to establish the asymptotic of the height distribution in the long space-time limit for the stationary Higher Spin Six Vertex Model. In particular, along the characteristic line we recover Baik–Rains fluctuations with size of characteristic exponent 1/3. We also consider some of the main degenerations of the Higher Spin Six Vertex Model and we adapt our analysis to the relevant cases of the q-Hahn particle process and of the Exponential Jump Model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Notes

  1. In [18] authors consider parameters \(s_i, u_j\) which have opposite sign compared to our choice (1.8). This is just a convention and hence not a problem, as the stochastic weights \({\textsf {L}}\) depend on \(s_i u_j\) and \(s_i^2\).

  2. In (5.1), (5.2) of [18], authors think of \(s_j\) and \(\xi _j\) as infinite sequences. They require that these parameters are uniformly (in j) bounded away from the boundaries of their domain of definition. When it comes to stating formulas like (2.22) the clarification “uniformly” is redundant since only finitely many of the \(s_j, \xi _j\) are used.

  3. The notation \(\mathbb {GT}^{\ge 0}\) refers to Gelfand–Tsetlin cones of partitions. One can define the same object with generic signatures instead of partitions. We refer to the two sided Gelfand–Tsetlin cone with the notation \(\mathbb {GT}\) as in (3.4).

  4. The numbering of rows and column starts from zero rather than from one.

  5. Sometimes the equivalent expression \(K_{\text {Airy}}(\nu , \theta )=\int _0^\infty \text {Ai}(\lambda + \nu ) \text {Ai}(\lambda + \theta ) d \lambda \) is found in literature.

  6. For motivation on the choice of sets \([-L, x^{\delta / 3}]\) see Remark 6.17.

  7. For the sake of the uniform convergence over compact sets conditions 2,4 are not necessary, but we still state them as they will become useful later in Lemma 6.64.

  8. Here \({\lceil }{}{\rceil }\) is the ceiling function.

References

  1. Abramowitz, M., Stegun, I.A.: Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover, New York (1964)

    MATH  Google Scholar 

  2. Aggarwal, A.: Current fluctuations of the stationary ASEP and six-vertex model. Duke Math. J. 167(2), 269–384 (2018)

    MathSciNet  MATH  Google Scholar 

  3. Aggarwal, A.: Dynamical stochastic higher spin vertex models. Sel. Math. 24(3), 2659–2735 (2018)

    MathSciNet  MATH  Google Scholar 

  4. Amir, G., Corwin, I., Quastel, J.: Probability distribution of the free energy of the continuum directed random polymer in 1+1 dimensions. Commun. Pure Appl. Math. 64(4), 466–537 (2011)

    MathSciNet  MATH  Google Scholar 

  5. Andjel, E.: Invariant measures for the zero range process. Ann. Probab. 10(3), 525–547 (1982)

    MathSciNet  MATH  Google Scholar 

  6. Baik, J., Ferrari, P.L., Pèché, S.: Limit process of stationary TASEP near the characteristic line. Commun. Pure Appl. Math. 63(8), 1017–1070 (2010)

    MathSciNet  MATH  Google Scholar 

  7. Baik, J., Rains, E.M.: Symmetrized random permutations. Random matrix models and their applications. 1–29, (2001)

  8. Baik, J., Rains, E.M.: Limiting distributions for a polynuclear growth model with external sources. J. Stat. Phys. 100(3), 523–541 (2000)

    MathSciNet  MATH  Google Scholar 

  9. Balazs, M., Cator, E., Seppalainen, T.: Cube root fluctuations for the corner growth model associated to the exclusion process. Electron. J. Probab. 11, 1094–1132 (2006)

    MathSciNet  MATH  Google Scholar 

  10. Barraquand, G.: A phase transition for \(q\)-TASEP with a few slower particles. Stoch. Process. Appl. 125(7), 2674–2699 (2015)

    MathSciNet  MATH  Google Scholar 

  11. Baxter, R.J.: Exactly Solved Models in Statistical Mechanics. Dover Publications, Dover Books on Physics, New York (2007)

    MATH  Google Scholar 

  12. Borodin, A.: On a family of symmetric rational functions. Adv. Math. 306, 973–1018 (2017)

    MathSciNet  MATH  Google Scholar 

  13. Borodin, A., Corwin, I.: Macdonald processes. Probab. Theory Relat. Fields 158(1), 225–400 (2014)

    MathSciNet  MATH  Google Scholar 

  14. Borodin, A., Corwin, I.: Discrete time \(q\)-TASEPs. Int. Math. Res. Notices 2015(2), 499–537 (2015)

    MathSciNet  MATH  Google Scholar 

  15. Borodin, A., Corwin, I., Sasamoto, T.: From duality to determinants for \(q\)-TASEP and ASEP. Ann. Probab. 42(6), 2314–2382 (2014)

    MathSciNet  MATH  Google Scholar 

  16. Borodin, A., Ferrari, P.L., Sasamoto, T.: Transition between Airy1 and Airy2 processes and TASEP fluctuation. Commun. Pure Appl. Math. 61(11), 1603–1629 (2007)

    MATH  Google Scholar 

  17. Borodin, A., Gorin, V.: Lectures on integrable probability. Probability and Statistical Physics in St. Petersburg. In: Proceedings of Symposia in Pure Mathematics 91, pp. 155–214 (2016)

  18. Borodin, A., Petrov, L.: Higher spin six vertex model and symmetric rational functions. Sel. Math. 24, 751–874 (2018)

    MathSciNet  MATH  Google Scholar 

  19. Borodin, A., Petrov, L.: Inhomogeneous exponential jump model. Probab. Theory Relat. Fields 172, 323–385 (2018)

    MathSciNet  MATH  Google Scholar 

  20. Borodin, A., Wheeler, M.: Coloured stochastic vertex models and their spectral theory. arXiv preprint, arXiv:1808.01866 [math.PR] (2018)

  21. Borodin, A., Corwin, I., Gorin, V.: Stochastic six-vertex model. Duke Math. J. 165(3), 563–624 (2016)

    MathSciNet  MATH  Google Scholar 

  22. Borodin, A., Corwin, I., Ferrari, P., Vető, B.: Height fluctuation for the stationary KPZ equation. Math. Phys. Anal. Geom. 18, 20 (2015)

    MathSciNet  MATH  Google Scholar 

  23. Borodin, A., Corwin, I., Petrov, L., Sasamoto, T.: Spectral theory for interacting particle systems solvable by coordinate Bethe Ansatz. Commun. Math. Phys. 339(3), 1167–1245 (2015)

    MathSciNet  MATH  Google Scholar 

  24. Bufetov, A., Petrov, L.: Yang–Baxter field for spin Hall-Littlewood symmetric functions. arXiv preprint, arXiv:1712.04584 [math.PR] (2017)

  25. Bufetov, A., Mucciconi, M., Petrov, L.: Yang–Baxter random fields and stochastic vertex models. arXiv preprint, arXiv:1905.06815 [math.PR] (2019)

  26. Burke, P.J.: The output of a queuing system. Oper. Res. 4(6), 699–704 (1956)

    MathSciNet  MATH  Google Scholar 

  27. Corwin, I.: The Kardar–Parisi–Zhang equation and universality class. Random Matrices Theory Appl. 1, 1130001 (2012)

    MathSciNet  MATH  Google Scholar 

  28. Corwin, I., Tsai, L.-C.: KPZ equation limit of higher-spin exclusion processes. Ann. Probab. 45(3), 1771–1798 (2017)

    MathSciNet  MATH  Google Scholar 

  29. Corwin, I.: The \(q\)-Hahn Boson Process and \(q\)-Hahn TASEP. Int. Math. Res. Not. 2015(14), 5577–5603 (2015)

    MathSciNet  MATH  Google Scholar 

  30. Corwin, I., Petrov, L.: Stochastic higher spin vertex models on the line. Commun. Math. Phys. 343(2), 651–700 (2016)

    MathSciNet  MATH  Google Scholar 

  31. Ferrari, P.A., Fontes, L.R.G.: Current fluctuations for the asymmetric simple exclusion process. Ann. Probab. 22(2), 820–832 (1994)

    MathSciNet  MATH  Google Scholar 

  32. Ferrari, P.A., Fontes, L.R.G.: The net output process of a system with infinitely many queues. Ann. Appl. Probab. 4(4), 1129–1144 (1994)

    MathSciNet  MATH  Google Scholar 

  33. Ferrari, P.L., Spohn, H.: Scaling limit for the Space-Time covariance of the stationary totally asymmetric simple exclusion process. Commun. Math. Phys. 265(1), 1–44 (2006)

    MathSciNet  MATH  Google Scholar 

  34. Ferrari, P.L., Vető, B.: Tracy–Widom asymptotics for \(q\)-TASEP. Ann. Inst. H. Poincaré Probab. Statist. 51(4), 1465–1485 (2015)

    MathSciNet  MATH  Google Scholar 

  35. Ghosal, P.: Hall–Littlewood PushTASEP and its KPZ limit. arXiv preprint, arXiv:1701.07308 (2017)

  36. Gomez, C., Ruiz-Altaba, M., Sierra, G.: Quantum Groups in Two-Dimensional Physics. Cambridge Monographs on Mathematical Physics, Cambridge (1996)

    MATH  Google Scholar 

  37. Gwa, L.H., Spohn, H.: Six-vertex model, roughened surfaces, and an asymmetric spin Hamiltonian. Phys. Rev. Lett. 68(6), 725–728 (1992)

    MathSciNet  MATH  Google Scholar 

  38. Imamura, T., Sasamoto, T.: Stationary correlations for the 1D KPZ equation. J. Stat. Phys. 150(5), 908–939 (2013)

    MathSciNet  MATH  Google Scholar 

  39. Imamura, T., Sasamoto, T.: Fluctuations for stationary \(q\)-TASEP. arXiv preprint: arXiv:1701.05991 (2017)

  40. Imamura, T., Sasamoto, T.: Free energy distribution of the stationary O’Connell–Yor directed random polymer model. J. Phys. A Math. Theor. 50(28), 285203 (2017)

    MathSciNet  MATH  Google Scholar 

  41. Ismail, M.E.H.: Classical and quantum orthogonal polynomials in one variable. Encyclopedia of Mathematics and its Applications, Cambridge (2005)

    MATH  Google Scholar 

  42. Jimbo, M.: Yang–Baxter Equation In Integrable Systems. World Scientific, Singapore (1990)

    MATH  Google Scholar 

  43. Johansson, K.: Shape fluctuations and random matrices. Commun. Mat. Phys. 209(2), 437–476 (2000)

    MathSciNet  MATH  Google Scholar 

  44. Kardar, M., Parisi, G., Zhang, Y.C.: Dynamic scaling of growing interfaces. Phys. Rev. Lett. 56(9), 889–892 (1986)

    MATH  Google Scholar 

  45. Kirillov, A.N., Yu Reshetikhin, N.: Exact solution of the integrable XXZ Heisenberg model with arbitrary spin. I. The ground state and the excitation spectrum. J. Phys. A Math. Gen. 20(6), 1565–1585 (1987)

    MathSciNet  Google Scholar 

  46. Kuan, J.: An algebraic construction of duality functions for the stochastic \({{\cal{U}}_q( A_n^{(1)})}\) vertex model and its degenerations. Commun. Math. Phys. 359(1), 121–187 (2018)

    MathSciNet  MATH  Google Scholar 

  47. Lin, Y.: KPZ equation limit of stochastic higher spin six vertex model. Math. Phys. Anal. Geom. 23, 1 (2020). https://doi.org/10.1007/s11040-019-9325-5

    Article  MathSciNet  MATH  Google Scholar 

  48. Macdonald, I.G.: Symmetric Functions and Hall Polynomials. Oxford classic texts in the physical sciences (1998)

  49. Mangazeev, V.V.: On the Yang–Baxter equation for the six-vertex model. Nucl. Phys. B 882, 70–96 (2014)

    MathSciNet  MATH  Google Scholar 

  50. Matveev, K., Petrov, L.: \(q\)-randomized Robinson-Schensted-Knuth correspondences and random polymers. Annales de l’IHP D 4(1), 1–123 (2017)

    MathSciNet  MATH  Google Scholar 

  51. Okounkov, A.: Infinite wedge and random partitions. Sel. Math. 7(1), 57–81 (2001)

    MathSciNet  MATH  Google Scholar 

  52. Okounkov, A., Reshetikhin, N.: Correlation function of Schur process with application to local geometry of a random 3-dimensional young diagram. J. Am. Math. Soc. 16(3), 581–603 (2003)

    MathSciNet  MATH  Google Scholar 

  53. Orr, D., Petrov, L.: Stochastic higher spin six vertex model and \(q\)-TASEPs. Adv. Math. 317, 473–525 (2017)

    MathSciNet  MATH  Google Scholar 

  54. Ortmann, J., Quastel, J., Remenik, D.: A Pfaffian representation for flat ASEP. Commun. Pure Appl. Math. 70(1), 3–89 (2017)

    MathSciNet  MATH  Google Scholar 

  55. Pauling, L.: The structure and entropy of ice and of other crystals with some randomness of atomic arrangement. J. Am. Chem. Soc. 57(12), 2680–2684 (1935)

    Google Scholar 

  56. Povolotsky, A.M.: On the integrability of zero-range chipping models with factorized steady states. J. Phys. A Math. Theor. 46(46), 465205 (2013)

    MathSciNet  MATH  Google Scholar 

  57. Prähofer, M., Spohn, H.: Universal distributions for growth processes in \(1+1\) dimensions and random matrices. Phys. Rev. Lett. 84(21), 4882–4885 (2000)

    Google Scholar 

  58. Sasamoto, T.: Spatial correlations of the 1D KPZ surface on a flat substrate. J. Phys. A Math. Gen. 38(33), 549–556 (2005)

    MathSciNet  Google Scholar 

  59. Sasamoto, T., Spohn, H.: Exact height distributions for the KPZ equation with narrow wedge initial condition. Nucl. Phys. B 834(3), 523–542 (2010)

    MathSciNet  MATH  Google Scholar 

  60. Schutz, G.: Duality relations for asymmetric exclusion processes. J. Stat. Phys. 86(5), 1265–1287 (1997)

    MathSciNet  MATH  Google Scholar 

  61. T. Seppalainen, Scaling for a one-dimensional directed polymer with boundary conditions. Ann. Probab., 40.1 (Jan 2012), pp. 19–73. Corrected in Erratum to Scaling for a one-dimensional directed polymer with boundary conditions. Ann. Probab., 45(3) (May 2017), pp. 2056–2058

  62. Spitzer, F.: Interaction of Markov processes. Adv. Math. 5(2), 246–290 (1970)

    MathSciNet  MATH  Google Scholar 

  63. Spohn, H.: KPZ scaling theory and the semi-discrete directed polymer model. arXiv preprint, arXiv:1201.0645 (2013)

  64. Takeuchi, K., Sano, M.: Universal fluctuations of growing interfaces: evidence in turbulent liquid crystals. Phys. Rev. Lett. 104(23), 230601 (2010)

    Google Scholar 

  65. Takeuchi, K., Sano, M.: Evidence for geometry-dependent universal fluctuations of the Kardar–Parisi–Zhang interfaces in liquid–crystal turbulence. J. Stat. Phys. 147, 853–890 (2012)

    MATH  Google Scholar 

  66. Tracy, C.A., Widom, H.: Level-spacing distributions and the Airy kernel. Commun. Math. Phys. 159(1), 151–174 (1994)

    MathSciNet  MATH  Google Scholar 

  67. Tracy, C.A., Widom, H.: Asymptotics in ASEP with step initial condition. Commun. Math. Phys. 290, 129–154 (2009)

    MathSciNet  MATH  Google Scholar 

  68. Vető, B.: Tracy–Widom limit of q-Hahn TASEP. Electron. J. Probab. 20(102), 22 (2015)

    MathSciNet  MATH  Google Scholar 

  69. Weisstein, E.W.: \(q\)-Polygamma Function. From MathWorld—A Wolfram Web Resource

Download references

Acknowledgements

M.M. is very grateful to Patrik Ferrari and Alexander Garbali for helpful discussions. We are also grateful to the anonymous referee for suggesting a number of improvements and correcting inaccuracies that were present in the previous version of the paper. The work of T.S. is supported by JSPS KAKENHI Grant Numbers JP15K05203, JP16H06338, JP18H01141, JP18H03672. The work of T.I. is supported by JSPS KAKENHI Grant Number JP16K05192.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Matteo Mucciconi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Preliminaries on q-deformed quantities

Along the course of the paper we largely made use of q-deformed quantities, such as q-Pochhammer symbols and q-hypergeometric series. The reader might consider these as fairly common and established notions, but, for the sake of completeness, we still like to dedicate this appendix to recall their definitions.

Assuming q is a parameter in the interval [0, 1), we define the q-Pochhammer symbol

$$\begin{aligned} (z;q)_n = {\left\{ \begin{array}{ll} (1-z)(1-zq) \cdots (1-zq^{n-1}), \quad \quad &{}\text {if } n \in {\mathbb {Z}}_{>0},\\ 1, &{}\text {if } n=0,\\ (1-zq^{n})^{-1} (1-zq^{n-1})^{-1} \cdots (1-zq)^{-1}, &{} \text {if } n \in {\mathbb {Z}}_{<0}, \end{array}\right. } \end{aligned}$$
(A.1)

for every meaningful \(z \in {\mathbb {C}}\). We also denote the product of multiple q-Pochhammer symbols of the same order in the compact notation

$$\begin{aligned} (z_1;q)_n \cdots (z_k;q)_n = (z_1,\dots ,z_k;q)_n. \end{aligned}$$
(A.2)

When n is positive, the q-Pochhammer symbol (A.1) is a polynomial in z and it admits the expansion

$$\begin{aligned} (z;q)_n=\sum _{k=0}^n (-z)^k q^{\left( {\begin{array}{c}k\\ 2\end{array}}\right) } \left( {\begin{array}{c}n\\ k\end{array}}\right) _{q}, \end{aligned}$$
(A.3)

where we introduced the q-binomial

$$\begin{aligned} \left( {\begin{array}{c}n\\ k\end{array}}\right) _{q} = \frac{(q;q)_n}{(q;q)_k (q;q)_{n-k}}. \end{aligned}$$
(A.4)

The the q-binomial admits the combinatorial expansion

$$\begin{aligned} \left( {\begin{array}{c}n\\ k\end{array}}\right) _{q}= \sum _{\begin{array}{c} I \subset \{1,\dots ,n\} \\ |I|=k \end{array}} q^{\Vert I \Vert - \left( {\begin{array}{c}k+1\\ 2\end{array}}\right) }, \end{aligned}$$
(A.5)

with \(I=\{i_1,\dots , i_k\}\) and \(\Vert I \Vert = i_1+ \cdots +i_k\).

When we let the integer n grow to \(+ \infty \), we see that the product in the left hand side of (A.1) is convergent and hence we can define

$$\begin{aligned} (z;q)_{\infty } = \prod _{j \ge 0} (1- z q^{j}). \end{aligned}$$
(A.6)

An important result concerning q-Pochhammer symbols is the summation identity

$$\begin{aligned} \sum _{k \ge 0} \frac{(a;q)_k}{(q;q)_k}z^k = \frac{(za;q)_\infty }{(z;q)_\infty } \qquad \text {for } a\in {\mathbb {C}}, |z|<1, \end{aligned}$$
(A.7)

which can be found in [41], Theorem 12.2.5. and it is usually called q-binomial theorem. A slightly more general version of summation (A.7) is the so called q-Gauss summation ([41], Theorem 12.2.4)

$$\begin{aligned} \sum _{n \ge 0} \left( \frac{c}{a b} \right) ^n \frac{(a,b;q)_n}{(c,q;q)_n} = \frac{(c/a, c/b;q)_\infty }{(c, c/(ab);q)_\infty }, \quad \text {for } |c/(ab)|<1, \quad \text {or }b\in q^{{\mathbb {Z}}_{<0}} .\nonumber \\ \end{aligned}$$
(A.8)

The q-hypergeometric series

$$\begin{aligned} {}_{r+1} \phi _{r} \left( \begin{array}{llllll} &{}a_1,&{} a_2, &{} \dots , &{} a_{r+1} &{}\\ &{}b_1,&{}b_2, &{}\cdots ,&{} b_{r}&{} \end{array} \Big | q, z \right) = \sum _{k \ge 0} \frac{ (a_1 , \dots , a_{r+1};q)_k }{ (b_1, \dots , b_{r},q;q)_k }z^k, \end{aligned}$$
(A.9)

is defined for generic parameters \(a_1, \dots , a_{r+1} \in {\mathbb {C}}\), \(b_1, \dots , b_{r} \in {\mathbb {C}} \setminus q^{{\mathbb {Z}}_{<0}}\) and \(|z|<1\). In the case when at least one of the \(a_j\) is of the form \(q^{-k}\), for some non-negative integer k, the q-hypergeometric series (A.9) becomes a finite sum and its definition holds also for more general complex numbers z. The regularized terminating q-hypergeometric function is also defined as

$$\begin{aligned} {}_{r+1} {\bar{\phi }}_{r} \left( \begin{array}{llllll} &{}q^{-n},&{} a_1, &{} \dots , &{} a_r &{}\\ &{}b_1,&{}b_2, &{}\cdots ,&{} b_r &{} \end{array} \Big | q, z \right) = \sum _{k = 0}^n z^k \frac{(q^{-n};q)_k}{(q;q)_k} \prod _{j=1}^r (a_j;q)_k (q^k b_j ;q)_{n-k}.\nonumber \\ \end{aligned}$$
(A.10)

In Sect. 4 we used the q-analog of the Chu–Vandermonde identity ( [41], (12.2.17)) that we report as

$$\begin{aligned} {}_{2} {\bar{\phi }}_{1} \left( \begin{array}{l} q^{-n}, a\\ c \end{array} \Big | q, q \right) = \frac{(c/a;q)_n}{(c;q)_n}a^n. \end{aligned}$$
(A.11)

In the paper we also made use of functions , defined as

(A.12)

They are related to the more classical q-polygamma function [69]

$$\begin{aligned} \varvec{\psi }_q(\theta ) = - \log (1-q) + \log (q) \sum _{n \ge 0} \frac{q^{n+\theta }}{1- q^{n + \theta }}, \end{aligned}$$

since

(A.13)

and

(A.14)

The inverse of the infinite q-Pochhammer symbol (A.6) is often called q-exponential and through it one can define a q-deformed notion of the common Laplace transform. For a given \(f \in \ell ^1({\mathbb {Z}})\) the function

$$\begin{aligned} {\widetilde{f}}(\zeta ) = \sum _{n \in {\mathbb {Z}}} \frac{f(n)}{(q^n \zeta ;q)_\infty } \qquad \text {for }\zeta \in {\mathbb {C}} \setminus q^{{\mathbb {Z}}} \end{aligned}$$
(A.15)

is the q-Laplace transform of f. As for the usual Laplace transform, the operation \(f \mapsto {\widetilde{f}}\) admits an inverse. This is discussed, for example, in [39] and we do not report the exact form of the inverse q-Laplace transform as we do not explicitly make use of it during this paper.

Bounds for \(\phi _l, \psi _l, \Phi _x, \Psi _x\)

We collect here some useful bounds for the quantities \(\phi _l, \psi _l, \Phi _x, \Psi _x\) defined in eqs. (5.4) to (5.7). Terms \(\Phi _x,\Psi _x\) can be further decomposed as

$$\begin{aligned} \Phi _x(n)= & {} \Phi _x^{(1)}(n) + \Phi _x^{(2)}(n),\\ \Psi _x(n)= & {} \Psi _x^{(1)}(n) + \Psi _x^{(2)}(n), \end{aligned}$$

obtained separating from the integration (5.6) (resp. (5.7)) the contribution of pole (resp. \(z= v\)) from that of other poles. Their exact expression was given in eqs. (5.16) to (5.19).

Proposition B.1

Let . Then, for all fixed x, there exist constants \(\Gamma _1, \Gamma _2, \Gamma _3, \Gamma _4>0\), such that

$$\begin{aligned} |\phi _l(n)|,|\psi _l(n)|,|\Phi _x(n)|,|\Phi ^{(2)}_x(n)| < \Gamma _1 e^{-\Gamma _2 |n|} \qquad \text {for all }n \in {\mathbb {Z}} \end{aligned}$$
(B.1)

and

$$\begin{aligned} |\Psi _x(n)|< {\left\{ \begin{array}{ll} \Gamma _1 e^{-\Gamma _2 |n|} \qquad \text {if }n \in {\mathbb {Z}}_{<0}\\ \Gamma _3 e^{-\Gamma _4 |n|} \qquad \text {if }n \in {\mathbb {Z}}_{\ge 0}. \end{array}\right. } \end{aligned}$$
(B.2)

Moreover \(\Gamma _1,\Gamma _2\) can be chosen so that their relative bounds also hold for in the region (1.18) (in this case the parameter b appearing in the definition of \(\tau \) (5.8) satisfies ).

Proof

We start with the terms \(\phi _l,\Phi _x(n),\Phi _x^{(2)}\). Evaluating the complex integrals as sums of residues it is straightforward to get the inequalities

for some constants \(\Gamma _1, \Gamma _2\) depending on the integrand functions but not on n.

To obtain a similar bound for the term \(\psi _l(n)\) we distinguish two cases. When n is positive we take the contour C to be a circle of radius \(r_+\) so that \(qv< r_+ < b\). On the other hand, when n is negative we take C to be a circle of radius \(r_-\) strictly bigger than c, not containing any of the numbers \(\xi _i/s_i\) (we remark that the definition itself of \(\tau (n)\) and of numbers bc is tailor-made for these conditions to be possible). With this choices we easily get

$$\begin{aligned} |\psi _l(n)| \le \text {const.}\frac{1}{\tau (n)} \left( \mathbbm {1}_{n\ge 0} r_+^{|n|} + \mathbbm {1}_{n<0} \frac{1}{r_-^{|n|}} \right) \le \Gamma _1 e^{-\Gamma _2 |n|}. \end{aligned}$$

An argument equivalent to that used for \(\psi _l\) can be carried to show (B.2). The only difference here is that the radius \(r_+\) has to be chosen so that \(v< r_+ < b\) and hence we cannot extend this bound to the region \( qv <b \le v \). \(\square \)

Proposition B.2

Let v satisfy (1.11) and or possibly (1.18). Then, for each x, there exist constants \(\Gamma _1, \Gamma _2>0\) such that

$$\begin{aligned} |\phi _l (n) \Psi _x (n) |,|\Phi _x^{(2)}(n) \Psi _x (n) | < \Gamma _1 e^{-\Gamma _2 |n|}. \end{aligned}$$
(B.3)

Proof

From Proposition B.1 we see that we only have to prove (B.3) for positive n’s. When this is the case we see directly from the integral expression (5.7) and (5.4) that we can bound both \(|\phi _l(n) \Psi _x(n)|\) and \(|\Phi ^{(2)}_x(n) \Psi _x(n)|\) with some quantity proportional to

$$\begin{aligned} \frac{|v + \epsilon |^n}{\min _{k \ge 2} |\xi _k s_k|^n }, \end{aligned}$$
(B.4)

by simply taking the C contour as a circle of radius \(v + \epsilon \), for \(\epsilon \) being sufficiently small. Due to the condition

$$\begin{aligned} v < \min _{k \ge 2}|\xi _k s_k|, \end{aligned}$$

we see that \(\epsilon \) can be chosen so that (B.4) decays to zero and this completes the proof. \(\square \)

Proposition B.3

Let satisfy (1.18). Then, for each fixed x, there exist constants \(\Gamma _1, \Gamma _2>0\) such that

$$\begin{aligned} \Big |f(n) \Phi _x^{(1)}(n) \Psi _x^{(2)} (n) \Big | < \Gamma _1 e^{-\Gamma _2 |n|}. \end{aligned}$$

Proof

We use the integral expression (5.19). When n is positive we take the integration contour \(C_1\) to be a circle of radius \(qv + \epsilon \). A bound we can easily obtain is

On the other hand, when n is negative we chose the contour \(C_1\) as a circle of radius \(v - \epsilon \) to get a bound like

In both cases condition (1.18) allows us to select \(\epsilon \) small enough to guarantee exponential decay in |n|. \(\square \)

Construction of contours

Here we discuss the construction of the steep descent contour C and that of the steep ascent contour D which were used in the asymptotic analysis of the Stationary Higher Spin Six Vertex Model in Sect. 6.

Proposition C.1

Consider fixed real numbers

$$\begin{aligned} 0<v<\varsigma , \qquad 0<q<1 \end{aligned}$$

and assume that

$$\begin{aligned} \varsigma< \inf _{k\ge 2}\{ \xi _k s_k \} \le \sup _{k\ge 2}\{ \xi _k s_k \}< \infty \quad \text {and} \quad 0 \le s_k^2 <1, \qquad \text {for all } k\ge 2. \end{aligned}$$

Take also a number \(\rho < \varsigma \) and define the contour

$$\begin{aligned} C_{\rho } = \{ \rho e^{i \vartheta } | \vartheta \in [0,2 \pi ) \}. \end{aligned}$$

Then, for \(\rho \) sufficiently close to \(\varsigma \) we have

$$\begin{aligned} \frac{d}{d\vartheta } \mathfrak {Re}\{g(\rho e^{i \vartheta })\}< 0 \quad \text {for } 0<\vartheta <\pi , \end{aligned}$$
(C.1)

where g is given in (6.42).

Remark C.2

The result of Proposition C.1 implies that \(C_\rho \) is a steep descent contour for \(\mathfrak {Re}(g)\) and in particular

  1. 1.

    \(\max _{z \in C_\rho } \mathfrak {Re}\{g(z)\} = g(\rho )\);

  2. 2.

    \(\max _{z \in C_\rho } |z| = \rho \).

This easily follows from (C.1) and from the fact that \(g({\overline{z}}) = \overline{g(z)}\), which implies that \(\mathfrak {Re}(g)\) is symmetric with respect to the real axis.

Proof

Evaluating the derivative we have

$$\begin{aligned} \begin{aligned}&\frac{d}{d\vartheta } \mathfrak {Re}\{g(\rho e^{i \vartheta })\}\\&\quad = \sin \vartheta \, \kappa \left( \sum _{i=0}^{J-1} \frac{ q^i u \rho }{1 + q^{2i} u^2 \rho ^2 - 2 q^i u \rho \cos \vartheta } \right) \\&\qquad + \sin \vartheta \frac{1}{x} \sum _{k=2}^x \sum _{j\ge 0} \left( \frac{\frac{q^j \rho }{\xi _k s_k} }{ 1 + \left( \frac{q^j \rho }{\xi _k s_k} \right) ^2 -2\frac{q^j \rho }{\xi _k s_k} \cos \vartheta } - \frac{\frac{q^j s_k^2 \rho }{\xi _k s_k} }{ 1 + \left( \frac{q^j s_k^2 \rho }{\xi _k s_k} \right) ^2 -2\frac{q^j s_k^2 \rho }{\xi _k s_k} \cos \vartheta } \right) . \end{aligned}\nonumber \\ \end{aligned}$$
(C.2)

Each term

$$\begin{aligned} \frac{ q^i u \rho }{1 + q^{2i} u^2 \rho ^2 - 2 q^i u \rho \cos \vartheta }, \end{aligned}$$

has a maximum in \(\vartheta = 0\) due to the fact that u and \(\rho \) have opposite sign, and so does each single one of the summands in the double summation in (C.2), since the generic function

$$\begin{aligned} \frac{ a }{ 1 + a^2 -2 a \cos \vartheta } - \frac{ a \sigma }{ 1 + a^2 \sigma ^2 -2 a \sigma \cos \vartheta } \end{aligned}$$

is decreasing in \(0<\vartheta < \pi \), provided that \(0<a, \sigma <1\). Now, if \(\rho \) is taken sufficiently close to the critical point \(\varsigma \), in a neighborhood of \(\vartheta =0\), the derivative of \(\mathfrak {Re}\{g(\rho e^{i \vartheta })\}\) is negative by construction and, thanks to considerations we just made, it stays negative along the whole half circle. \(\square \)

The construction of an explicit steepest descent contour D for a general choice of parameters \(q, \Xi , {\mathbf{S}}\) becomes more complicated. Therefore we use the next Proposition both to exhibit a contour in a rather simple setting and to implicitly deduce conditions on \(q, \Xi , {\mathbf{S}}\) under which our arguments of Sect. 6 are perfectly well posed.

Proposition C.3

For each choice of

$$\begin{aligned} 0<\varsigma<a, \qquad u<0, \qquad 0<\sigma <1, \end{aligned}$$

there exist constants \(R_a, R_\sigma , R_q>0\), such that for each choice of parameters \(\{ \xi _k \}_{k\ge 2}, \{ s_k \}_{k \ge 2}\), q satisfying

$$\begin{aligned} \varsigma<\inf _{k\ge 2}\{\xi _k s_k\}, \qquad |\xi _k s_k - a|<R_a, \qquad |s_k^2 - \sigma |<R_\sigma , \qquad q<R_q, \end{aligned}$$

we are able to construct a complex contour D encircling the set \(\{\xi _k s_k\}_{k \ge 2}\), for which

  1. 1.

    \(\min _{z \in D} \mathfrak {Re}\{g(z)\} = g(\varsigma )\);

  2. 2.

    \(\min _{z \in D} |z| = \varsigma \),

where g is given in (6.42).

Proof

To show this result we essentially make use of a continuity argument. We start studying the case when

$$\begin{aligned} q=0, \qquad \xi _k, s_k=a \qquad s_k^2=\sigma \qquad \text {for all } k \ge 2. \end{aligned}$$

With this choice of parameters the function g becomes

$$\begin{aligned} g(z)=- \eta \log (z)+ \kappa \log ( 1- u z) + \log \left( \frac{a-z}{a- \sigma z} \right) + {\mathcal {O}}(x^{-1}), \end{aligned}$$
(C.3)

where we can neglect the contribution of the \({\mathcal {O}}(x^{-1})\) term as we are interested in this result only in the limiting case of \(x \rightarrow \infty \). We define the contour D to be the level curve

$$\begin{aligned} D=\left\{ z:\ \mathfrak {Re}\left\{ \log \left( \frac{a-z}{a- \sigma z} \right) \right\} = \log \left( \frac{a-\varsigma }{a- \sigma \varsigma } \right) \right\} , \end{aligned}$$

which is a circle and admit the parametrization

$$\begin{aligned} \left\{ \varsigma + \rho + \rho e^{i \vartheta } |\ \vartheta \in [0, 2 \pi ) \right\} , \end{aligned}$$

with the radius \(\rho \) being

$$\begin{aligned} \rho = \frac{a^2 - a\varsigma - a \varsigma \sigma + \varsigma ^2 \sigma }{a+ a\sigma -2 \varsigma \sigma }. \end{aligned}$$

We also report that the leftmost and rightmost extremes of the contour D are respectively \(\varsigma \) and \(\varsigma + 2 \rho \) and one can easily find that the latter satisfies the inequality

$$\begin{aligned} \varsigma + 2 \rho \le \frac{2 a}{1 + \sigma }. \end{aligned}$$
(C.4)

Along the curve D we are able to calculate

$$\begin{aligned} \frac{d}{d \vartheta } \mathfrak {Re} \left\{ g(\varsigma + \rho + \rho e^{i \vartheta }) \right\} \end{aligned}$$

and to analytically show that its only critical points are \(\theta \in {\mathbb {Z}} \pi \). More specifically, substituting in (C.3) the correct expressions of coefficients \(\eta , \kappa \) given in (1.21)

$$\begin{aligned} \eta= & {} \frac{a \varsigma ^2 (1- \sigma ) (a- a^2 u + a \sigma -2 \varsigma \sigma + \varsigma ^2 u \sigma ) }{(a- \varsigma )^2 (a- \varsigma \sigma )^2}, \end{aligned}$$
(C.5)
$$\begin{aligned} \kappa= & {} - \frac{a(1-\varsigma u)^2 (1-\sigma )(a^2 - \varsigma ^2 \sigma )}{u (a- \varsigma )^2 (a-\varsigma \sigma )^2}, \end{aligned}$$
(C.6)

we get

$$\begin{aligned} \frac{d}{d \vartheta } \mathfrak {Re} \left\{ g(\varsigma + \rho + \rho e^{i \vartheta }) \right\} = \sin \vartheta ( 1+ \cos \vartheta ) \frac{1}{P(\cos \vartheta )}. \end{aligned}$$

In the last expression P is a polynomial of degree two in the argument and we see that zeros are only achieved on the real axis for \(\theta =k\pi \) for \(k \in {\mathbb {Z}}\). We can at this point readily verify that, along D the real part of g assumes a minimum at \(z=\varsigma \) and a maximum at \(z=\varsigma + 2 \rho \) as the function

$$\begin{aligned} -\eta \log (y) + \kappa \log (1-u y) \end{aligned}$$

is increasing for \(y>\varsigma \), and one can check this by direct inspection of its first derivative, by making use of expressions (1.21) for \(\eta \) and \(\kappa \).

We can now use the fact that g is continuous in the parameters \(\Xi , {\mathbf{S}}, q\) for z belonging to D and the fact that, by construction, it will always have a critical point in \(z=\varsigma \), to state the existence of neighborhoods respectively of \(a, \sigma \) and 0 in which every choice of \(\xi _k s_k , s^2_k\) and q will preserve the steepest descent properties 1 and 2. \(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Imamura, T., Mucciconi, M. & Sasamoto, T. Stationary stochastic Higher Spin Six Vertex Model and q-Whittaker measure. Probab. Theory Relat. Fields 177, 923–1042 (2020). https://doi.org/10.1007/s00440-020-00966-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00440-020-00966-x

Mathematics Subject Classification