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The Materials Research Society series

Topological Quantum Computing

Ray LaPierre

Published Jan 1, 2021• 2 citations
Publisher

Abstract

Quipu is an ancient Incan method of storing information in knots (Fig. 26.1). Topological quantum computing is a method of quantum information storage and processing using “topological” knots. In this chapter, we will examine topological quantum computing.
DOI
10.1007/978-3-030-69318-3_26

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In this paper, we will present some ideas to use 3D topology for quantum computing. Topological quantum computing in the usual sense works with an encoding of information as knotted quantum states of topological phases of matter, thus being locked into topology to prevent decay. Today, the basic structure is a 2D system to realize anyons with braiding operations. From the topological point of view, we have to deal with surface topology. However, usual materials are 3D objects. Possible topologies for these objects can be more complex than surfaces. From the topological point of view, Thurston’s geometrization theorem gives the main description of 3-dimensional manifolds. Here, complements of knots do play a prominent role and are in principle the main parts to understand 3-manifold topology. For that purpose, we will construct a quantum system on the complements of a knot in the 3-sphere. The whole system depends strongly on the topology of this complement, which is determined by non-contractible, closed curves. Every curve gives a contribution to the quantum states by a phase (Berry phase). Therefore, the quantum states can be manipulated by using the knot group (fundamental group of the knot complement). The universality of these operations was already showed by M. Planat et al.
In topological quantum computing, information is encoded in “knotted” quantum states of topological phases of matter, thus being locked into topology to prevent decay. Topological precision has been confirmed in quantum Hall liquids by experiments to an accuracy of 10 − 10 10^{-10} and harnessed to stabilize quantum memory. In this survey, we discuss the conceptual development of this interdisciplinary field at the juncture of mathematics, physics, and computer science. Our focus is on computing and physical motivations, basic mathematical notions and results, open problems and future directions related to and/or inspired by topological quantum computing.
In this paper, we will present some ideas to use 3D topology for quantum computing extending ideas from a previous paper. Topological quantum computing used “knotted” quantum states of topological phases of matter, called anyons. But anyons are connected with surface topology. But surfaces have (usually) abelian fundamental groups and therefore one needs non-Abelian anyons to use it for quantum computing. But usual materials are 3D objects which can admit more complicated topologies. Here, complements of knots do play a prominent role and are in principle the main parts to understand 3-manifold topology. For that purpose, we will construct a quantum system on the complements of a knot in the 3-sphere (see T. Asselmeyer-Maluga, Quantum Rep. 3 (2021) 153, arXiv:2102.04452 for previous work). The whole system is designed as knotted superconductor, where every crossing is a Josephson junction and the qubit is realized as flux qubit. We discuss the properties of this systems in particular the fluxion quantization by using the A-polynomial of the knot. Furthermore, we showed that 2-qubit operations can be realized by linked (knotted) superconductors again coupled via a Josephson junction.
Quantum information storage represents a significant challenge in quantum computing, demanding robust and efficient methods. This paper explores the potential of topological quantum information storage, leveraging the unique properties of topological phases to enhance stability and storage efficiency. We propose a novel system where quantum information is encoded within topologically protected states, utilizing the principles of topology to mitigate decoherence and improve information fidelity. The core mechanism centers around the manipulation of topological invariants to stabilize the quantum state, while the system incorporates adaptive control strategies for efficient data retrieval. This work presents a theoretical framework and preliminary design concepts, demonstrating the viability of topological approaches for advancing quantum information storage.