A mean-field stochastic linear-quadratic optimal control problem with jumps under partial information

In this article, the stochastic linear-quadratic optimal control problem of mean-field type with jumps under partial information is discussed. The state equation contains affine terms is a SDE with jumps driven by a multidimensional Brownian motion and a Poisson random martingale measure, the cost function containing cross terms is quadratic, in addition, the state and the control as well as their expectations are contained both in the state equation and the cost functional. Firstly, we prove the existence and uniqueness of the optimal control, and by using Pontryagin’s maximum principle we get the dual characterization of optimal control; Secondly, by introducing the adjoint processes of the state equation, establishing a stochastic Hamiltonian system and using decoupling technology, we deduce two integro-differential  Riccati equations and get the feedback representation of the optimal control under partial information; Thirdly, the existence and uniqueness of the solutions of the two associated integro-differential Riccati equations are proved; Finally, we discuss a special case, and by means of  filtering technique, establish the corresponding the filtering state feedback representation of the optimal control.