In this talk, we shortly introduce the emerging field quantum software (quantum programming and quantum machine learning), and then we discuss how we can be involved and then shape the field. We explain why education is our primary focus and how we can use pedagogical tools to attract new generation and people to the field. We share our own experiences, our ongoing projects, and also our upcoming projects. At the end, we discuss possible collaborations.

We introduce a novel approach to simulate dynamical (linear) systems (quantum or otherwise) parallel in time using quantum annealers. In particular,  we describe how the solution state vector can be found by solving a specifically crafted system of linear equations. Moreover, we demonstrate that such systems can, in fact, be effectively solved (up to a given precision) with Quadratic Unconstrained Binary Optimization. This naturally leads to a class of hybrid classical-quantum algorithms that can be implemented and executed on near-term quantum annealers.

In this presentation I am goin to show models, algorithms and computational results of CFA (Capacity and Flow Assignment) problem in multi-layer networks. The idea of multilayer, based on MPLS over DWDM architecture, is as follows. The logical links given by paths allocated to demands of the upper layer are constructed using light-paths of the lower layer. In the upper layer we introduce two kinds of traffics: uni-cast (one-to-one) and any cast (one-to-one-of-many).

We conduct experimental simulations of many-body quantum systems using a hybrid classical-quantum algorithm. In our setup, the wave function of the transverse field quantum Ising model is represented by a restricted Boltzmann machine.