The realisation of large-scale quantum computing is no longer simply a hardware question. The rapid development of quantum technology has resulted in dozens of control and programming problems that should be directed towards the classical computer science and engineering community. One such problem is known as Pauli tracking. Methods for implementing quantum algorithms that are compatible with crucial error correction technology utilise extensive quantum teleportation protocols. These protocols are intrinsically probabilistic and result in correction operators that occur as byproducts of teleportation. These byproduct operators do not need to be corrected in the quantum hardware itself, but are tracked through the circuit and output results reinterpreted. This tracking is routinely ignored in quantum information as it is assumed that tracking algorithms will eventually be developed. In this work we help fill this gap and present an algorithm for tracking byproduct operators through a quantum computation.

Topological quantum computing has recently proven itself to be a powerful computational model when constructing viable architectures for large scale computation. The topological model is constructed from the foundation of a error correction code, required to correct for inevitable hardware faults that will exist for a large scale quantum device. It is also a measurement based model of quantum computation, meaning that the quantum hardware is responsible only for the construction of a large, computationally universal quantum state. This quantum state is then strategically consumed, allowing for the realisation of a fully error corrected quantum algorithm. The number of physical qubits needed by the quantum hardware and the amount of time required to implement an algorithm is dictated by the manner in which this universal quantum state is consumed. In this paper we examine the problem of algorithmic optimisation in the topological lattice and introduce the required elements that will be needed when designing a classical software package to compile and implement a large scale algorithm on a topological quantum computer.

We evaluate the performance of quantum arithmetic algorithms run on a distributed quantum computer (a quantum multicomputer). We vary the node capacity and I/O capabilities, and the network topology. The tradeoff of choosing between gates executed remotely, through “teleported gates” on entangled pairs of qubits (telegate), versus exchanging the relevant qubits via quantum teleportation, then executing the algorithm using local gates (teledata), is examined. We show that the teledata approach performs better, and that carry-ripple adders perform well when the teleportation block is decomposed so that the key quantum operations can be parallelized. A node size of only a few logical qubits performs adequately provided that the nodes have two transceiver qubits. A linear network topology performs acceptably for a broad range of system sizes and performance parameters. We therefore recommend pursuing small, high-I/O bandwidth nodes and a simple network. Such a machine will run Shor's algorithm for factoring large numbers efficiently.

Distributed quantum computation requires quantum operations that act over a distance on error correction-encoded states of logical qubits, such as the transfer of qubits via teleportation. We evaluate the performance of several quantum error correction (QEC) codes and find that teleportation failure rates of one percent or more are tolerable when two levels of the [[23, 1, 7]] code are used. We present an analysis of performing QEC on QEC-encoded states that span two quantum computers, including the creation of distributed logical zeros. The transfer of the individual qubits of a logical state may be multiplexed in time or space, moving serially across a single link or in parallel across multiple links. We show that the performance and reliability penalty for using serial links is small for a broad range of physical parameters, making serial links preferable for a large, distributed quantum multicomputer when engineering difficulties are considered. Such a multicomputer will be able to factor a 1,024-bit number using Shor's algorithm with a high probability of success.

We evaluate the performance of quantum arithmetic algorithms run on a distributed quantum computer (a quantum multicomputer). We vary the node capacity and I/O capabilities, and the network topology. The tradeoff of choosing between gates executed remotely, through "tele-ported gates" on entangled pairs of qubits (telegate), versus exchanging the relevant qubits via quantum teleportation, then executing the algorithm using local gates (tele-data), is examined. We show that the teledata approach performs better, and that carry-ripple adders perform well when the teleportation block is decomposed so that the key quantum operations can be parallelized. A node size of only a few logical qubits performs adequately provided that the nodes have two transceiver qubits. A linear network topology performs acceptably for a broad range of system sizes and performance parameters. We therefore recommend pursuing small, high-I/O bandwidth nodes and a simple network. Such a machine will run Shor's algorithm for factoring large numbers efficiently