In this paper we extend both standard fault tolerance theory and Kitaev's model for quantum computation, combining them so as to yield quantitative results that reveal the interplay between the two. Our analysis establishes a methodology that allows us to quantitatively determine design parameters for a quantum computer, the values of which ensure that an overall computation of interest yields a correct *final result* with some prescribed probability of success, as opposed to merely ensuring that the desired *final quantum state* is obtained. As a specific example of the practical application of our approach, we explicitly calculate the number of levels of error correction concatenation needed to achieve a correct final result for the overall computation with some prescribed success probability. Since our methodology allows one to determine parameters required in order to achieve the correct final result for the overall quantum computation, as opposed to merely ensuring that the desired final quantum state is produced, our method enables the determination of complete quantum computational resource requirements associated to the actual solution of practical problems.
In this paper we extend both standard fault tolerance theory and Kitaev's model for quantum computation, combining them so as to yield quantitative results that reveal the interplay between the two. Our analysis establishes a methodology that allows us to quantitatively determine design parameters for a quantum computer, the values of which ensure that an overall computation of interest yields a correct final result with some prescribed probability of success, as opposed to merely ensuring that the desired final quantum state is obtained. As a specific example of the practical application of our approach, we explicitly calculate the number of levels of error correction concatenation needed to achieve a correct final result for the overall computation with some prescribed success probability. Since our methodology allows one to determine parameters required in order to achieve the correct final result for the overall quantum computation, as opposed to merely ensuring that the desired final quantum state is produced, our method enables the determination of complete quantum computational resource requirements associated to the actual solution of practical problems.
We extend standard fault tolerance theory and Kitaev’s model for quantum computation so as to enable quantitative determination of design parameters for quantum computers that ensure that the overall computation yields a correct final result with some prescribed probability, as opposed to merely ensuring that the desired final quantum state is obtained. Our extension allows us to explicitly calculate the number of levels of error correction concatenation needed to achieve a correct final result with some prescribed success probability and demonstrate a clear connection between error correction and fault tolerance.
The model of quantum computation developed by Kitaev (1 ,∮4.1) shows that a perfect, error-free, quantum computer can lead to reliable classical outputs, despite the need to apply a necessarily probabilistic measurement. In this paper we extend the analysis to account for necessarily imperfect quantum computation. The analysis presented here is required to establish the utility of practical quantum computation even given the assumption that fault-tolerance techniques are successfully applied. This is due to the fact that the application of currently known fault-tolerance techniques does not permanently and completely remove errors. To this end we have introduced a mathematical relation that compares the accuracy of a necessarily imperfect quantum computation to a prescribed performance bound. Finally, we discuss several mathematical aspects of this bound and its usefulness in analyzing quantum computing protocols.
Due to very high projected error rates, large scale quantum computers will require substantial fault tolerance just to maintain a minimum level of reliability. We present tools to better analyze the performance of large, fault tolerant quantum computer designs. We find that current uses of quantum error correction are overly conservative in mitigating the impact of gate errors and negligent of other error sources in quantum data communication and memory.
We have developed circuit layout heuristics to generate detailed designs in trapped ion quantum computing technology. From these designs, we can extract much more accurate error models for a given application, including all gate, movement and idle errors on qubits. Using these extracted models, our flexible error simulation environment determines the overall failure probability of the design. Included in this simulation environment is a bit-parallel Monte Carlo technique that is 10 times faster than previous fault propagation simulations. This allows us to evaluate the reliability of designs that are an order of magnitude larger, in the same amount of time.
Using this analysis framework to verify reliability, we have developed a linear programming-based optimization for error correction which decreases overall circuit resources by an order of magnitude. In some cases, our optimization actually improves overall system reliability by removing error correction. We combine this optimization with judicious quantum error correcting code selection to provide efficient designs for large quantum arithmetic kernels used in Shor's factorization algorithm. We show our optimized designs perform 2x to 100x better than previous works in terms of probabilistic area-delay product. Additionally, the area of our layout of a 1024-bit factoring using Shor's algorithm is 64cm2, a substantial improvement compared to the 0.9m2 state-of-the-art design from prior work. A design size reduction by this amount will make fabricating such an application feasible much sooner.
This thesis is concerned with certain theoretical problems that arise naturally in the context of fault-tolerant quantum computation. Fault-tolerance can be defined as the art of building reliable devices from unreliable components, and is of particular importance for quantum computers that aim to precisely control the dynamics of extremely sensitive quantum systems. A model of quantum computation is a specification of the basic building blocks by which a quantum computation is implemented. The best known model is the quantum circuit model, where computations are implemented by means of unitary quantum gates that are applied to two-level quantum systems known as qubits. In a physical implementation of a quantum circuit, the gates and qubits will inevitably be affected by noise. Fault-tolerant quantum circuits are designed to be resilient against the effects of this noise, provided that it is not too strong. Fault-tolerance in the quantum circuit model is well developed thanks to the theory of quantum error-correcting codes. These codes allow for the correction of small numbers of errors introduced by a variety of noise processes. In a fault-tolerant quantum circuit, qubits are replaced with encoded qubits, and quantum gates with encoded gates that are immediately followed by special quantum circuits for error correction. Provided the rate at which errors occur is below a constant threshold value, the accumulation of errors can be checked so that the correct output of the computation correctly determined. The threshold acts as both a measure of how good the design of a quantum circuit is, and also as a target for experimenters aiming to implement quantum circuits. Much current research in quantum computation is aimed at designing quantum circuits that increase the noise threshold, hopefully to the point where it becomes within the reach of experimenters. A fault-tolerant encoded quantum gate must limit the propagation of errors so that the code’s corrective capabilities are not overwhelmed. It is not so easy to design encoded gates that satisfy this property, and to date only a finite handful of such gates are known. In a faulttolerant quantum circuit, all quantum gates must be decomposed or compiled in terms of those that may be implemented fault-tolerantly. In the first part of this thesis, we present two results that may be applied to this problem of gate compilation. The first is a generic method based on the Solovay-Kitaev theorem that may be applied to all quantum gates, but is most effective for those that act on single qubits. We present the Solovay-Kitaev theorem in its simples known form as an algorithm, together with novel constructions that can be used to implement it. Following this we give a two specialized methods for two-qubit gate decomposition, based on the Cartan decomposition of the Lie group SU(4). The cluster-state model of computation is an alternative to the quantum circuit model, and makes use of quantum measurements and highly entangled cluster-states to implement a quantum computation. The fault-tolerant techniques developed for quantum circuits are not immediately applicable in this model, so in order for it to be a realistic candidate for performing computations we prove that such techniques are possible. In the second part of the thesis we prove that constant fault-tolerance thresholds may be achieved in the cluster-state model, and in particular in an adaption to an optical implementation. Following this we design a complete error correction scheme for optical cluster-state computation, and numerically determine the threshold of this model in the face of the dominant noise models likely to affect such an implementation.
This paper presents a novel approach to designing fault-tolerant quantum circuits utilizing quantum error-correcting codes. The core claim is to develop a method capable of significantly reducing error rates within quantum circuits while achieving high reliability for quantum computation. This is achieved through the integration of theoretical concepts from quantum error-correcting codes with practical circuit design considerations. The proposed methodology focuses on designing quantum circuit architectures that effectively correct errors and enhance overall circuit resilience. The primary innovation lies in extending the application of quantum error-correcting codes, traditionally utilized in quantum communication, to the domain of quantum circuit design, thereby bolstering the inherent error correction capabilities of quantum computing. The presented framework outlines a systematic approach to constructing robust quantum circuits, paving the way for more reliable and scalable quantum computation. This work provides a foundational understanding of how error-correcting codes can be strategically employed to mitigate the detrimental effects of noise in quantum systems.
To ascertain the feasibility of large-scale quantum computing, the performance and quantum resource of a practical quantum-computing situation needs to be analyzed. However, most of the analyses reported so far have focused on the statistical examination that simply calculates the performance and resource based on individual quantum-computing components. In this work, we propose an integrated analysis methodology that models a large-scale fault-tolerant quantum-computing system based on three components: algorithm, error correction, and device. Furthermore, to implement the proposed methodology, we develop a quantum-computing software platform composed of three functional layers: compile, system, and building block. By using our platform, we observe that it takes $8.78\ifmmode\times\else\texttimes\fi{}{10}^{5}\phantom{\rule{0.2em}{0ex}}\mathrm{h}$, which is much longer than previous estimations, for factoring a 512-bit integer with Shor's factoring algorithm. We also discuss whether the proposed platform can play a significant role in finding an optimal concatenation level and/or code distance of quantum error-correcting code.