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Colored interacting particle systems on the ring: Stationary measures from Yang–Baxter equations

Published online by Cambridge University Press:  03 October 2025

Amol Aggarwal
Affiliation:
Columbia University, 2990 Broadway, New York, NY 10027, USA Clay Mathematics Institute, 1624 Market Street, Suite 226 #17261, Denver, CO 80202, USA amolagga@gmail.com
Matthew Nicoletti
Affiliation:
Massachusetts Institute of Technology, Cambridge MA, USA Current address: Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, CA 94720, USA mnicoletti@berkeley.edu
Leonid Petrov
Affiliation:
Department of Mathematics, University of Virginia, 141 Cabell Drive, Kerchof Hall, P.O. Box 400137, Charlottesville, VA 22904, USA lenia.petrov@gmail.com

Abstract

Recently, there has been much progress in understanding stationary measures for colored (also called multi-species or multi-type) interacting particle systems, motivated by asymptotic phenomena and rich underlying algebraic and combinatorial structures (such as nonsymmetric Macdonald polynomials). In this paper, we present a unified approach to constructing stationary measures for most of the known colored particle systems on the ring and the line, including (1) the Asymmetric Simple Exclusion Process (multi-species ASEP, or mASEP); (2) the $q$-deformed Totally Asymmetric Zero Range Process (TAZRP) also known as the $q$-Boson particle system; (3) the $q$-deformed Pushing Totally Asymmetric Simple Exclusion Process ($q$-PushTASEP). Our method is based on integrable stochastic vertex models and the Yang–Baxter equation. We express the stationary measures as partition functions of new ‘queue vertex models’ on the cylinder. The stationarity property is a direct consequence of the Yang–Baxter equation. For the mASEP on the ring, a particular case of our vertex model is equivalent to the multiline queues of Martin (Stationary distributions of the multi-type ASEP, Electron. J. Probab. 25 (2020), 1–41). For the colored $q$-Boson process and the $q$-PushTASEP on the ring, we recover and generalize known stationary measures constructed using multiline queues or other methods by Ayyer, Mandelshtam and Martin (Modified Macdonald polynomials and the multispecies zero range process: II, Algebr. Comb. 6 (2022), 243–284; Modified Macdonald polynomials and the multispecies zero-range process: I, Algebr. Comb. 6 (2023), 243–284) and Bukh and Cox (Periodic words, common subsequences and frogs, Ann. Appl. Probab. 32 (2022), 1295–1332). Our proofs of stationarity use the Yang–Baxter equation and bypass the Matrix Product Ansatz (used for the mASEP by Prolhac, Evans and Mallick (The matrix product solution of the multispecies partially asymmetric exclusion process, J. Phys. A. 42 (2009), 165004)). On the line and in a quadrant, we use the Yang–Baxter equation to establish a general colored Burke’s theorem, which implies that suitable specializations of our queue vertex models produce stationary measures for particle systems on the line. We also compute the colored particle currents in stationarity.

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Research Article
Copyright
© The Author(s), 2025. The publishing rights in this article are licensed to Foundation Compositio Mathematica under an exclusive licence

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References

Aggarwal, A., Convergence of the stochastic six-vertex model to the ASEP , Math. Phys. Anal. Geom. 20 (2017), 3.10.1007/s11040-016-9235-8CrossRefGoogle Scholar
Aggarwal, A., Current fluctuations of the stationary ASEP and six-vertex model , Duke Math. J. 167 (2018), 269384.10.1215/00127094-2017-0029CrossRefGoogle Scholar
Aggarwal, A., Nonexistence and uniqueness for pure states of ferroelectric six-vertex models , Proc. Lond. Math. Soc. 124 (2022), 387425.10.1112/plms.12430CrossRefGoogle Scholar
Aggarwal, A., Borodin, A. and Wheeler, M., Colored fermionic vertex models and symmetric functions , Commun. Am. Math. Soc. 3 (2023), 400630.10.1090/cams/24CrossRefGoogle Scholar
Amir, G., Busani, O., Gonçalves, P. and Martin, J. B., The TAZRP speed process , Ann. Inst. Henri Poincaré Probab. Stat. 57 (2021), 12811305.10.1214/20-AIHP1117CrossRefGoogle Scholar
Angel, O., The stationary measure of a 2-type totally asymmetric exclusion process , J. Combin. Theory Ser. A 113 (2006), 625635.10.1016/j.jcta.2005.05.004CrossRefGoogle Scholar
Arita, C., Ayyer, A., Mallick, K. and Prolhac, S., Generalized matrix Ansatz in the multispecies exclusion process – the partially asymmetric case , J. Phys. A 45 (2012), 195001.10.1088/1751-8113/45/19/195001CrossRefGoogle Scholar
Ayyer, A. and Linusson, S., Correlations in the multispecies TASEP and a conjecture by Lam , Trans. Amer. Math. Soc. 369 (2017), 10971125.10.1090/tran/6806CrossRefGoogle Scholar
Ayyer, A., Mandelshtam, O. and Martin, J. B., Modified Macdonald polynomials and the multispecies zero range process: II , Algebr. Comb. 6 (2022), 243284.Google Scholar
Ayyer, A., Mandelshtam, O. and Martin, J. B., Modified Macdonald polynomials and the multispecies zero-range process: I , Algebr. Comb. 6 (2023), 243284.Google Scholar
Barraquand, G., A phase transition for q-TASEP with a few slower particles , Stochastic Process. Appl. 125 (2015), 26742699.10.1016/j.spa.2015.01.009CrossRefGoogle Scholar
Basu, R., Sarkar, S. and Sly, A., Invariant measures for TASEP with a slow bond , Preprint (2017), arXiv:1704.07799.Google Scholar
Bazhanov, V., Trigonometric solutions of triangle equations and classical Lie algebras , Phys. Lett. B. 159 (1985), 321324.10.1016/0370-2693(85)90259-XCrossRefGoogle Scholar
Blythe, R. A. and Evans, M. R., Nonequilibrium steady states of matrix-product form: a solver’s guide , J. Phys. A 40 (2007), R333R441.10.1088/1751-8113/40/46/R01CrossRefGoogle Scholar
Borodin, A. and Corwin, I., Macdonald processes , Probab. Theory Related Fields 158 (2014), 225400.10.1007/s00440-013-0482-3CrossRefGoogle Scholar
Borodin, A., Corwin, I. and Gorin, V., Stochastic six-vertex model , Duke J. Math. 165 (2016), 563624.10.1215/00127094-3166843CrossRefGoogle Scholar
Borodin, A., Corwin, I., Petrov, L. and Sasamoto, T., Spectral theory for the q-Boson particle system , Compositio Math. 151 (2015), 167.10.1112/S0010437X14007532CrossRefGoogle Scholar
Borodin, A., Corwin, I. and Sasamoto, T., From duality to determinants for q-TASEP and ASEP , Ann. Probab. 42 (2014), 23142382.10.1214/13-AOP868CrossRefGoogle Scholar
Borodin, A., Gorin, V. and Wheeler, M., Shift-invariance for vertex models and polymers , Proc. Lond. Math. Soc. 124 (2022), 182299.10.1112/plms.12427CrossRefGoogle Scholar
Borodin, A. and Petrov, L., Higher spin six vertex model and symmetric rational functions , Selecta Math. (N.S.) 24 (2018), 751874.10.1007/s00029-016-0301-7CrossRefGoogle Scholar
Borodin, A. and Petrov, L., Inhomogeneous exponential jump model , Probab. Theory Related Fields 172 (2018), 323385.10.1007/s00440-017-0810-0CrossRefGoogle Scholar
Borodin, A. and Wheeler, M., Colored stochastic vertex models and their spectral theory , Astérisque, vol. 437 (2022).10.24033/ast.1180CrossRefGoogle Scholar
Borodin, A. and Wheeler, M., Nonsymmetric Macdonald polynomials via integrable vertex models , Trans. Amer. Math. Soc. 375 (2022), 83538397.10.1090/tran/8309CrossRefGoogle Scholar
Bosnjak, G. and Mangazeev, V. V., Construction of R-matrices for symmetric tensor representations related to Uqln) , J. Phys. A 49 (2016), 495204.10.1088/1751-8113/49/49/495204CrossRefGoogle Scholar
Bukh, B. and Cox, C., Periodic words, common subsequences and frogs , Ann. Appl. Probab. 32 (2022), 12951332.10.1214/21-AAP1709CrossRefGoogle Scholar
Cantini, L., de Gier, J. and Wheeler, M., Matrix product formula for Macdonald polynomials , J. Phys. A 48 (2015), 384001.10.1088/1751-8113/48/38/384001CrossRefGoogle Scholar
Corteel, S., Gitlin, A., Keating, D. and Meza, J., A vertex model for LLT polynomials , Int. Math. Res. Not. IMRN 2022 (2022), 1586915931.10.1093/imrn/rnab165CrossRefGoogle Scholar
Corteel, S., Mandelshtam, O. and Williams, L., From multiline queues to Macdonald polynomials via the exclusion process , Amer. J. Math. 144 (2022), 395436.10.1353/ajm.2022.0007CrossRefGoogle Scholar
Crampe, N., Ragoucy, E. and Vanicat, M., Integrable approach to simple exclusion processes with boundaries. Review and progress , J. Stat. Mech. 2014 (2014), P11032.10.1088/1742-5468/2014/11/P11032CrossRefGoogle Scholar
Derrida, B., Evans, M. R., Hakim, V. and Pasquier, V., Exact solution of a 1D asymmetric exclusion model using a matrix formulation , J. Phys. A 26 (1993), 14931517.10.1088/0305-4470/26/7/011CrossRefGoogle Scholar
Derrida, B., Janowsky, S. A., Lebowitz, J. L. and Speer, E. R., Exact solution of the totally asymmetric simple exclusion process: Shock profiles , J. Stat. Phys. 73 (1993), 813842.10.1007/BF01052811CrossRefGoogle Scholar
Durrett, R., Probability: theory and examples, Cambridge Series in Statistical and Probabilistic Mathematics, vol. 49 (Cambridge University Press, 2019).Google Scholar
Ferrari, P. A., Kipnis, C. and Saada, E., Microscopic structure of travelling waves in the asymmetric simple exclusion process , Ann. Probab. 19 (1991), 226244.10.1214/aop/1176990542CrossRefGoogle Scholar
Ferrari, P. A. and Martin, J. B., Multiclass processes, dual points and M/M/1 queues , Preprint (2005), arXiv:math-ph/0509045.Google Scholar
Ferrari, P. A. and Martin, J. B., Stationary distributions of multi-type totally asymmetric exclusion processes , Ann. Probab. 35 (2007), 807–832.10.1214/009117906000000944CrossRefGoogle Scholar
Ferrari, P. A. and Martin, J. B., Multiclass Hammersley-Aldous-Diaconis process and multiclass-customer queues , Ann. Inst. Henri Poincaré Probab. Stat. 45 (2009), 250265.10.1214/08-AIHP168CrossRefGoogle Scholar
Garbali, A., de Gier, J. and Wheeler, M., A new generalisation of Macdonald polynomials , Comm. Math. Phys. 352 (2017), 773804.10.1007/s00220-016-2818-1CrossRefGoogle Scholar
Garbali, A. and Wheeler, M., Modified Macdonald polynomials and integrability , Comm. Math. Phys. 374 (2020), 18091876.10.1007/s00220-020-03680-wCrossRefGoogle Scholar
Gasper, G. and Rahman, M., Basic hypergeometric series (Cambridge University Press, 2004).Google Scholar
Jimbo, M., Quantum R matrix for the generalized Toda system , Comm. Math. Phys. 102 (1986), 537547.10.1007/BF01221646CrossRefGoogle Scholar
Knizel, A., Petrov, L. and Saenz, A., Generalizations of TASEP in discrete and continuous inhomogeneous space , Comm. Math. Phys. 372 (2019), 797864.10.1007/s00220-019-03495-4CrossRefGoogle Scholar
Kuan, J., An algebraic construction of duality functions for the stochastic Uq (A(1)) vertex model and its degenerations , Comm. Math. Phys. 359 (2018), 121187.10.1007/s00220-018-3108-xCrossRefGoogle Scholar
Kulish, P., Reshetikhin, N. and Sklyanin, E., Yang-Baxter equation and representation theory: I , Lett. Math. Phys. 5 (1981), 393403.10.1007/BF02285311CrossRefGoogle Scholar
Kuniba, A., Mangazeev, V., Maruyama, S. and Okado, M., Stochastic R matrix for Uq (A(1)) , Nuclear Phys. B. 913 (2016), 248277.10.1016/j.nuclphysb.2016.09.016CrossRefGoogle Scholar
Kuniba, A., Maruyama, S. and Okado, M., Multispecies totally asymmetric zero range process: I Multiline process and combinatorial R , J. Integr. Syst. 1 (2016), xyw002.10.1093/integr/xyw002CrossRefGoogle Scholar
Lascoux, A., Leclerc, B. and Thibon, J.-Y., Ribbon tableaux, Hall–Littlewood functions, quantum affine algebras, and unipotent varieties , J. Math. Phys. 38 (1997), 10411068.10.1063/1.531807CrossRefGoogle Scholar
Liggett, T., Interacting particle systems (Springer-Verlag, Berlin, 2005).Google Scholar
Liu, Z., Saenz, A. and Wang, D., Integral formulas of ASEP and q-TAZRP on a Ring , Comm. Math. Phys. 379 (2020), 261325.10.1007/s00220-020-03837-7CrossRefGoogle Scholar
Macdonald, I. G., Symmetric functions and Hall polynomials, second edition (Oxford University Press, 1995).Google Scholar
Mallick, K., Mallick, S. and Rajewsky, N., Exact solution of an exclusion process with three classes of particles and vacancies , J. Phys. A 32 (1999), 83998410.10.1088/0305-4470/32/48/303CrossRefGoogle Scholar
Marshall, D., Symmetric and nonsymmetric Macdonald polynomials , Ann. Comb. 3 (1999), 385415.10.1007/BF01608794CrossRefGoogle Scholar
Martin, J. B., Stationary distributions of the multi-type ASEP , Electron. J. Probab. 25 (2020), 141.10.1214/20-EJP421CrossRefGoogle Scholar
Neergard, J. and den Nijs, M., Crossover scaling functions in one dimensional dynamic growth crystals , Phys. Rev. Lett. 74 (1995), 730.10.1103/PhysRevLett.74.730CrossRefGoogle Scholar
O’Connell, N. and Yor, M., Brownian analogues of Burke’s theorem , Stochastic Process. Appl. 96 (2001), 285304.10.1016/S0304-4149(01)00119-3CrossRefGoogle Scholar
Pahuja, N., Correlations in the multispecies PASEP on a ring , Electron. Commun. Prob. 30 (2025), 1–12.Google Scholar
Petrov, L., PushTASEP in inhomogeneous space , Electron. J. Probab. 25 (2020), 125.10.1214/20-EJP517CrossRefGoogle Scholar
Petrov, L. and Saenz, A., Rewriting history in integrable stochastic particle systems , Comm. Math. Phys. 405 (2024), 1–75.10.1007/s00220-024-05189-yCrossRefGoogle ScholarPubMed
Prolhac, S., Evans, M. R. and Mallick, K., The matrix product solution of the multispecies partially asymmetric exclusion process , J. Phys. A 42 (2009), 165004.10.1088/1751-8113/42/16/165004CrossRefGoogle Scholar
Sasamoto, T. and Wadati, M., Exact results for one-dimensional totally asymmetric diffusion models , J. Phys. A 31 (1998), 60576071.10.1088/0305-4470/31/28/019CrossRefGoogle Scholar
Seppäläinen, T., Scaling for a one-dimensional directed polymer with boundary conditions , Ann. Probab. 40 (2012), 1973.10.1214/10-AOP617CrossRefGoogle Scholar
Takeyama, Y., Algebraic construction of multi-species q-Boson system , Preprint (2015), arXiv:1507.02033.Google Scholar
Wang, D. and Waugh, D., The transition probability of the q-TAZRP (q-Bosons) with inhomogeneous jump rates , SIGMA Symmetry Integrability Geom. Methods Appl. 12 (2016), 1–16.Google Scholar