The novel field of quantum technology is being promoted by academia, governments and industry. Quantum technologies offer new means for carrying out fast computation as well as secure communication, using primitives that exploit peculiar characteristics of quantum physics. While building quantum computing devices remains a challenge, the area of quantum communication and cryptography has been successful in reaching industrial applications. In particular, recently, plans for building quantum internet have been put into action and expected to be launched by 2020 in the Netherlands. Quantum internet uses quantum communication as well as quantum entanglement along with classical communication. This makes design of software platform for quantum networks very challenging and a daunting task. Seamless design and testing of platforms for quantum software, thus, becomes a necessity to develop complex simulators for this kind of networks. In this short paper, we argue that using coordination models such as Reo can significantly simplify the development of software applications for quantum internet. Moreover, formal verification of such quantum software becomes possible, thanks to the separation of concerns, compositionality, and reusability of Reo models. This paper introduces an extension of a recently developed simulator for quantum internet (SimulaQron) by incorporating Reo models extended with quantum data and operations, along with classical data. We explain the main concepts and our plan for implementing this extension as a new tool: SimulaQ(reo)n.

Additional Metadata
Keywords Quantum communication, Quantum information, Quantum networks, Reo Coordination Model
Persistent URL dx.doi.org/10.1007/978-3-030-04771-9_23
Series Lecture Notes in Computer Science
Conference International Conference on Software Technologies: Applications and Foundations
Citation
Ardeshir-Larijani, E, & Arbab, F. (2018). Reo coordination model for simulation of quantum internet software. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 311–319). doi:10.1007/978-3-030-04771-9_23