Computer graphics for quantum computation

Dominic C. Horsman

Topological quantum computing (QC) is a way of allowing precise quantum computations to run on noisy and imperfect hardware. One implementation uses surface codes created by forming defects in a highly-entangled cluster state. Such a method of computing is a leading candidate for large-scale QC. However, there has been a lack of sufficiently powerful high-level languages to describe computing in this form without resorting to single-qubit operations, which quickly become prohibitively complex as the system size increases. In this paper, we apply the category-theoretic work of Abramsky and Coecke to the topological cluster-state model of QC to give a high-level graphical language that enables direct translation between quantum processes and physical patterns of measurement in a computer—a ‘compiler language’. We give the equivalence between the graphical and topological information flows, and show the applicable rewrite algebra for this computing model. We show that this gives us a native graphical language for the design and analysis of topological quantum algorithms, and finish by discussing the possibilities for automating this process on a large scale.

Feng Liang, Xiaolin Wen, Shixian Zhou +5 more

Tzvetan S. Metodi, Frederic T. Chong

Ross Duncan

Quantum computations are easily represented in the graphical notation known as the zx-calculus, also known as the red–green calculus. We demonstrate its use in reasoning about measurement-based quantum computing, where the graphical syntax directly captures the structure of the entangled states used to represent computations, and show that the notion of information flow within the entangled states gives rise to rewriting strategies for proving the correctness of quantum programs.

Norhan Nasr, Ahmed Younes, Ashraf Elsayed

Andrew S. Glassner

Computer graphics relies on computing hardware for everything from animation to rendering. An emerging new technology exploits the properties of quantum objects to offer radically new ways to think about, create, and run algorithms. For example, quantum computers can evaluate many different input values simultaneously, where "many" can be larger than the number of atoms in the visible universe. The catch is that only one output can be obtained from each run. Quantum computing may change how we think about computer graphics. For example, future quantum computers may be able to intersect astronomical numbers of rays with a similarly massive database of objects in a single execution, or evaluate enormous numbers of simulation parameters in parallel to return the one set that produces a desired result. This course describes, without advanced math, the core ideas of quantum computing. We start with the quantum version of the classical bit (called a qubit) and the basic operators that modify qubits. We introduce the four essential properties that distinguish quantum computers from familiar classical computers: superposition, interference, entanglement, and measurement. We show how these properties are orchestrated to build quantum algorithms. We conclude with a brief overview of some of the most well-known quantum algorithms, and some of their possible applications in computer graphics. Quantum computers are already here, and are increasing in size and reliability at a rapid pace. Open-source simulators abound, and small quantum computers are even available for free use on the web. Classical hardware has served computer graphics well. Quantum computing offers a fundamentally new way to design and execute algorithms, which could change our field in fundamental ways. Now is the perfect time to starting thinking about quantum computing for graphics.