QRev: migrating quantum code towards hybrid information systems

Quantum computing is now a reality, and its incomparable computational power has led companies to show a great interest in being able to work with quantum software in order to support part of their current and future business operations. However, the quantum computing paradigm differs significantly from its classical counterparts, which has brought about the need to revolutionise how the future software is designed, built, and operated in order to work with quantum computers. Since companies cannot discard all their current (and probably mission-critical) information systems, they must adapt their classical information systems to new specific quantum applications, thus evolving towards hybrid information systems. Unfortunately, there are no specific methods with which to deal with this challenge. We believe that reengineering, and more specifically, software modernisation using model-driven engineering principles, could be useful as regard migrating classical systems and existing quantum programs towards hybrid information systems. This paper, therefore, presents QRev, a reverse engineering tool that analyses quantum programs developed in Q# in order to identify its components and interrelationships, and then generates abstract models that can be used in software modernisation processes. The platform-independent models are generated according to the Knowledge Discovery Metamodel (KDM) standard. QRev is validated in a case study involving five quantum programs in order to demonstrate its effectiveness and scalability. The main implication of the study is that QRev can be used in order to attain KDM models, which can subsequently be employed to restructure or add new quantum functionality at a higher abstraction level, i.e. independently of the specific quantum technology.

Dissipative encoding of quantum information

We formalize the problem of dissipative quantum encoding, and explore the advantages of using Markovian evolution to prepare a quantum code in the desired logical space, with emphasis on discrete-time dynamics and the possibility of exact finite-time convergence. In particular, we investigate robustness of the encoding dynamics and their ability to tolerate initialization errors, thanks to the existence of non-trivial basins of attraction. As a key application, we show that for stabilizer quantum codes on qubits, a finite-time dissipative encoder may always be constructed, by using at most a number of quantum maps determined by the number of stabilizer generators. We find that even in situations where the target code lacks gauge degrees of freedom in its subsystem form, dissipative encoders afford nontrivial robustness against initialization errors, thus overcoming a limitation of purely unitary encoding procedures. Our general results are illustrated in a number of relevant examples, including Kitaev's toric code.

3D-Fringe Pattern Coding and Recognition Using Plasmonic Sensing Circuit

3D interference fringe pattern recognition using a plasmonic sensing circuit is proposed. The plasmonic sensing in the form of a panda ring comprises of an embedded gold grating at the microring center. WGM (whispering gallery mode) is observed at the microring center with suitable parameters. The dark soliton of 1.50µm wavelength excites the gold grating which leads to electron cloud oscillation and forms the electron densities where the trapped electrons inside the silicon microring are transported via wireless connection using WGM and cable connection. The spin-down |↓〉(|1〉) and spin-up |↑〉(|0〉) result from the electron cloud oscillation. By using the changes in gold lengths, the excited electron pattern recognition can be manipulated, where the values "0 and "1"' are useful for pattern recognition. The fringe patterns of the plasmonic interferometric sensor are recorded, which means that the novel 3D pattern recognition can be possibly implemented and used in many applications. Therefore, the plasmonic sensing circuit can be used to form the quantum code, quantum encryption, quantum sensor, and pattern recognition.

On maximum-likelihood decoding with circuit-level errors

Error probability distribution associated with a given Clifford measurement circuit is described exactly in terms of the circuit error-equivalence group, or the circuit subsystem code previously introduced by Bacon, Flammia, Harrow, and Shi. This gives a prescription for maximum-likelihood decoding with a given measurement circuit. Marginal distributions for subsets of circuit errors are also analyzed; these generate a family of related asymmetric LDPC codes of varying degeneracy. More generally, such a family is associated with any quantum code. Implications for decoding highly-degenerate quantum codes are discussed.

A novel construction for quantum stabilizer codes based on binary formalism

In this research, we propose a novel construction of quantum stabilizer code based on a binary formalism. First, from any binary vector of even length, we generate the parity-check matrix of the quantum code from a set composed of elements from this vector and its relations by shifts via subtraction and addition. We prove that the proposed matrices satisfy the condition constraint for the construction of quantum codes. Finally, we consider some constraint vectors which give us quantum stabilizer codes with various dimensions and a large minimum distance with code length from six to twelve digits.