Abstract. Quantum Information Processing (QIP) is an emerging area at the intersection of physics and computer science. It aims to establish the principles of communication and computation for systems based on the theory of quantum mechanics. Interesting QIP protocols such as quantum error correction, teleportation, and blind quantum computation have already been realised in the laboratory and are now in the realm of mainstream industrial applications. The complexity of these protocols, along with possible inaccuracies in implementation, demands systematic and formal analysis. In this paper, we present a new technique and a tool, with a high-level interface, for verification of quantum protocols using equivalence checking. Previous work by Gay, Nagarajan and Papanikolaou used model-checking to verify quantum protocols represented in the stabilizer formalism, a restricted model which can be simulated efficiently on classical computers. Here, we are able to go beyond stabilizer states and verify protocols efficiently on all input states.

Abstract. We present a tool which uses a concurrent language for describing quantum systems, and performs verification by checking equivalence between specification and implementation. In general, simulation of quantum systems using current computing technology is infeasible. We restrict ourselves to the stabilizer formalism, in which there are efficient simulation algorithms. In particular, we consider concurrent quantum protocols that behave functionally in the sense of computing a deterministic input-output relation for all interleavings of the concurrent system. Crucially, these input-output relations can be abstracted by superoperators, enabling us to take advantage of linearity. This allows us to analyse the behaviour of protocols with arbitrary input, by simulating their operation on a finite basis set consisting of stabilizer states. Despite the limitations of the stabilizer formalism and also the range of protocols that can be analysed using this approach, we have applied our equivalence checking tool to specify and verify interesting and practical quantum protocols from teleportation to secret sharing.

<div>Artificial Neural networks are one of the most widely applied approaches for classification problems. However, developing an errorless artificial neural network is in practice impossible, due to the statistical nature of such networks. The employment of artificial neural networks in critical applications has rendered any such emerging errors, in these systems, incredibly more significant. Nevertheless, the real consequences of such errors have not been addressed, especially due to lacking verification approaches. This study aims to develop a verification method that eliminates errors through the integration of multiple artificial neural networks. In order to do this, first of all, a special property has been defined, by the authors, to extract the knowledge of these artificial neural networks. </div><div>Furthermore, a multi-agent system has been designed, itself comprised of multiple artificial neural networks, in order to check whether the aforementioned special property has been satisfied, or not. Also, in order to help examine the reasoning concerning the aggregation of the distributed knowledge, itself gained through the combined effort of separate artificial neural networks and acquired external information sources, a dynamic epistemic logic-based method has been proposed.</div><div>Finally, we believe aggregated knowledge may lead to self-awareness for the system. As a result, our model shall be capable of verifying specific inputs, if the cumulative knowledge of the entire system proves its correctness. </div><div>In conclusion, and formulated for multi-agent systems, a knowledge-sharing algorithm (Abbr. MASKS) has been developed. Which after being applied on the MNIST dataset successfully reduced the error rate to roughly one-eighth of previous runs on individual artificial neural network in the same model. </div>

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