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We consider a recently proposed model to understand the rigidity transitionin confluent tissues and we derive the dynamical mean field theory (DMFT)equations that describes several types of dynamics of the model in thethermodynamic limit: gradient descent, thermal Langevin noise and active drive.In particular we focus on gradient descent dynamics and we integratenumerically the corresponding DMFT equations. In this case we show thatgradient descent is blind to the zero temperature replica symmetry breaking(RSB) transition point. This means that, even if the Gibbs measure in the zerotemperature limit displays RSB, this algorithm is able to find its way to azero energy configuration. We include a discussion on possible extensions ofthe DMFT derivation to study problems rooted in high-dimensional regression andoptimization via the square loss function.

Dynamical mean field theory for models of confluent tissues and beyond