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Markov duality for stochastic six vertex model. (English) Zbl 1431.82018
Summary: We prove that Schütz’s ASEP Markov duality functional is also a Markov duality functional for the stochastic six vertex model. We introduce a new method that uses induction on the number of particles to prove the Markov duality.

MSC:
82C22 Interacting particle systems in time-dependent statistical mechanics
82B23 Exactly solvable models; Bethe ansatz
82B20 Lattice systems (Ising, dimer, Potts, etc.) and systems on graphs arising in equilibrium statistical mechanics
60H15 Stochastic partial differential equations (aspects of stochastic analysis)
60J20 Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.)
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