Quantum Multiple-Valued Decision Diagrams in Graphical Calculi

Graphical calculi such as the ZH-calculus are powerful tools in the study and analysis of quantum processes, with links to other models of quantum computation such as quantum circuits, measurement-based computing, etc. A somewhat compact but systematic way to describe a quantum process is through the use of quantum multiple-valued decision diagrams (QMDDs), which have already been used for the synthesis of quantum circuits as well as for verification. We show in this paper how to turn a QMDD into an equivalent ZH-diagram, and vice-versa, and show how reducing a QMDD translates in the ZH-Calculus, hence allowing tools from one formalism to be used into the other

How to Efficiently Handle Complex Values? Implementing Decision Diagrams for Quantum Computing

Quantum computing promises substantial speedups by exploiting quantum mechanical phenomena such as superposition and entanglement. Corresponding design methods require efficient means of representation and manipulation of quantum functionality. In the classical domain, decision diagrams have been successfully employed as a powerful alternative to straightforward means such as truth tables. This motivated extensive research on whether decision diagrams provide similar potential in the quantum domain -- resulting in new types of decision diagrams capable of substantially reducing the complexity of representing quantum states and functionality. From an implementation perspective, many concepts and techniques from the classical domain can be re-used in order to implement decision diagrams packages for the quantum realm. However, new problems -- namely how to efficiently handle complex numbers -- arise. In this work, we propose a solution to overcome these problems. Experimental evaluations confirm that this yields improvements of orders of magnitude in the runtime needed to create and to utilize these decision diagrams. The resulting implementation is publicly available as a quantum DD package at http://iic.jku.at/eda/research/quantum_dd

A Verified Software Toolchain for Quantum Programming

Quantum computing is steadily moving from theory into practice, with small-scale quantum computers available for public use. Now quantum programmers are faced with a classical problem: How can they be sure that their code does what they intend it to do? I aim to show that techniques for classical program verification can be adapted to the quantum setting, allowing for the development of high-assurance quantum software, without sacrificing performance or programmability. In support of this thesis, I present several results in the application of formal methods to the domain of quantum programming, aiming to provide a high-assurance software toolchain for quantum programming. I begin by presenting SQIR, a small quantum intermediate representation deeply embedded in the Coq proof assistant, which has been used to implement and prove correct quantum algorithms such as Grover’s search and Shor’s factorization algorithm. Next, I present VOQC, a verified optimizer for quantum circuits that contains state-of-the-art SQIR program optimizations with performance on par with unverified tools. I additionally discuss VQO, a framework for specifying and verifying oracle programs, which can then be optimized with VOQC. Finally, I present exploratory work on providing high assurance for a high-level industry quantum programming language, Q#, in the F* proof assistant