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Quantum Information and Computation

Turning gate synthesis errors into incoherent errors

Matthew B. Hastings

Published Apr 1, 2017• 12 citations
Publisher

Abstract

Using error correcting codes and fault tolerant techniques, it is possible, at least in theory, to produce logical qubits with significantly lower error rates than the underlying physical qubits. Suppose, however, that the gates that act on these logical qubits are only approximation of the desired gate. This can arise, for example, in synthesizing a single qubit unitary from a set of Clifford and T gates; for a generic such unitary, any finite sequence of gates only approximates the desired target. In this case, errors in the gate can add coherently so that, roughly, the error epsilon in the unitary of each gate must scale as epsilon < 1/N, where N is the number of gates. If, however, one has the option of synthesizing one of several unitaries near the desired target, and if an average of these options is closer to the target, we give some elementary bounds showing cases in which the errors can be made to add incoherently by averaging over random choices, so that, roughly, one needs epsilon < 1/ √ N. We remark on one particular application to distilling magic states where this effect happens automatically in the usual circuits.

DOI
10.26421/qic17.5-6-7

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Using error correcting codes and fault tolerant techniques, it is possible, at least in theory, to produce logical qubits with significantly lower error rates than the underlying physical qubits. Suppose, however, that the gates that act on these logical qubits are only approximation of the desired gate. This can arise, for example, in synthesizing a single qubit unitary from a set of Clifford and $T$ gates; for a generic such unitary, any finite sequence of gates only approximates the desired target. In this case, errors in the gate can add coherently so that, roughly, the error $ε$ in the unitary of each gate must scale as $ε\lesssim 1/N$, where $N$ is the number of gates. If, however, one has the option of synthesizing one of several unitaries near the desired target, and if an average of these options is closer to the target, we give some elementary bounds showing cases in which the errors can be made to add incoherently by averaging over random choices, so that, roughly, one needs $ε\lesssim 1/\sqrt{N}$. We remark on one particular application to distilling magic states where this effect happens automatically in the usual circuits.

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Using error correcting codes and fault tolerant techniques, it is possible, at least in theory, to produce logical qubits with significantly lower error rates than the underlying physical qubits. Suppose, however, that the gates that act on these logical qubits are only approximation of the desired gate. This can arise, for example, in synthesizing a single qubit unitary from a set of Clifford and T gates; for a generic such unitary, any finite sequence of gates only approximates the desired target. In this case, errors in the gate can add coherently so that, roughly, the error epsilon in the unitary of each gate must scale as epsilon < 1/N, where N is the number of gates. If, however, one has the option of synthesizing one of several unitaries near the desired target, and if an average of these options is closer to the target, we give some elementary bounds showing cases in which the errors can be made to add incoherently by averaging over random choices, so that, roughly, one needs epsilon < 1/ √ N. We remark on one particular application to distilling magic states where this effect happens automatically in the usual circuits.
Using error correcting codes and fault tolerant techniques, it is possible, at least in theory, to produce logical qubits with significantly lower error rates than the underlying physical qubits. Suppose, however, that the gates that act on these logical qubits are only approximation of the desired gate. This can arise, for example, in synthesizing a single qubit unitary from a set of Clifford and TTT gates; for a generic such unitary, any finite sequence of gates only approximates the desired target. In this case, errors in the gate can add coherently so that, roughly, the error εεε in the unitary of each gate must scale as ε≲1/Nε\lesssim 1/Nε≲1/N, where NNN is the number of gates. If, however, one has the option of synthesizing one of several unitaries near the desired target, and if an average of these options is closer to the target, we give some elementary bounds showing cases in which the errors can be made to add incoherently by averaging over random choices, so that, roughly, one needs ε≲1/Nε\lesssim 1/\sqrt{N}ε≲1/N​. We remark on one particular application to distilling magic states where this effect happens automatically in the usual circuits.
For universal quantum computation, a major challenge to overcome for practical implementation is the large amount of resources required for fault-tolerant quantum information processing. An important aspect is implementing arbitrary unitary operators built from logical gates within the quantum error correction code. A synthesis algorithm can be used to approximate any unitary gate up to arbitrary precision by assembling sequences of logical gates chosen from a small set of universal gates that are fault-tolerantly performable while encoded in a quantum error-correction code. However, current procedures do not yet support individual assignment of base gate costs and many do not support extended sets of universal base gates. We analysed cost-optimal sequences using an exhaustive search based on Dijkstra’s pathfinding algorithm for the canonical Clifford+ T set of base gates and compared them to when additionally including Z -rotations from higher orders of the Clifford hierarchy. Two approaches of assigning base gate costs were used. First, costs were reduced to T -counts by recursively applying a Z -rotation catalyst circuit. Second, costs were assigned as the average numbers of raw (i.e. physical level) magic states required to directly distil and implement the gates fault-tolerantly. We found that the average sequence cost decreases by up to 54±3% when using the Z -rotation catalyst circuit approach and by up to 33±2% when using the magic state distillation approach. In addition, we investigated observed limitations of certain assignments of base gate costs by developing an analytic model to estimate the proportion of sets of Z -rotation gates from higher orders of the Clifford hierarchy that are found within sequences approximating random target gates.
This thesis is concerned with fault-tolerant quantum information processing using quantum error-correcting codes. It contains two major pieces of work. The first is a study of coherent noise in the context of stabilizer error-correcting codes. The second is a proposed scheme for a universal set of fault-tolerant logical gates in a particular code family built out of the 3D toric code. Chapter 1 provides an introduction to quantum computation and fault tolerance. Many basic concepts in error-correcting codes are defined. Special attention is paid to the set of code properties that are most likely to determine how easily a given fault-tolerant scheme might be implemented on a physical device. These include the fault-tolerant noise threshold and the overhead. In Chapters 2 and 3 we study the effectiveness of quantum error correction against coherent noise. Coherent errors (for example, unitary noise) can interfere constructively, so that in some cases the average infidelity of a quantum circuit subjected to coherent errors may increase quadratically with the circuit size; in contrast, when errors are incoherent (for example, depolarizing noise), the average infidelity increases at worst linearly with circuit size. We consider the performance of quantum stabilizer codes against a noise model in which a unitary rotation is applied to each qubit, where the axes and angles of rotation are nearly the same for all qubits. In Chapter 2 we introduce coherent noise and incoherent noise and a number of methods that are useful for the study of coherent noise. We study the repetition code as a basic example, and we also study a correlated noise model. In Chapter 3 we show that for the toric code subject to such independent coherent noise, and for minimal-weight decoding, the logical channel after error correction becomes increasingly incoherent as the length of the code increases, provided the noise strength decays inversely with the code distance. A similar conclusion holds for weakly correlated coherent noise. Our methods can also be used for analyzing the performance of other codes and fault-tolerant protocols against coherent noise. However, our result does not show that the coherence of the logical channel is suppressed in the more physically relevant case where the noise strength is held constant as the code block grows, and we recount the difficulties that prevented us from extending the result to that case. Nevertheless our work supports the idea that fault-tolerant quantum computing schemes will work effectively against coherent noise, providing encouraging news for quantum hardware builders who worry about the damaging effects of control errors and coherent interactions with the environment. Chapter 4 is connected to another aspect of fault tolerance, fault-tolerant logical gates. The toric code is a promising candidate for fault-tolerant quantum computation because of its high threshold and low-weight stabilizers. A universal gate set in the toric code generally requires magic state distillation, which can incur a significant qubit overhead. In this work we construct an error-correcting code in three dimensions based on the toric code that features a fault-tolerant T gate with no magic state distillation required. We further describe a subsystem version of our code which supports a universal set of fault-tolerant gates. This code can be converted into the stabilizer version using gauge-fixing. We also argue that our code can be converted to a (2+1)-D protocol, where a 2D lattice undergoes a measurement-based protocol over time. In this way, a fault-tolerant logical T gate can be realized in a 2D toric code structure.
We present a method for constructing optimal fault-tolerant approximations of arbitrary unitary gates using an arbtrary discrete universal gate set. The method presented is numerical and scales exponentially with the number of gates used in the approximation, however, for the specific case of arbitrary single-qubit gates and the fault-tolerant gates permitted by the 7-qubit Steane code, it is shown that the longest practical gates sequences can be found. We also analyse the practicality of the fault-tolerant approximations of the phase rotation gates used in Shor’s algorithm and find that simple non-fault-tolerant phase rotations are more robust for realistic error rates. A general scaling law of how rapidly these fault-tolerant approximations converge to arbitrary single-qubit gates is also determined. In large-scale quantum computation, every qubit of data is encoded across multiple physical qubits to form a logical qubit permitting quantum error correction
The leading paradigm for performing a computation on quantum memories can be encapsulated as distill-then-synthesize. Initially, one performs several rounds of distillation to create high-fidelity magic states that provide one good T gate, an essential quantum logic gate. Subsequently, gate synthesis intersperses many T gates with Clifford gates to realize a desired circuit. We introduce a unified framework that implements one round of distillation and multiquibit gate synthesis in a single step. Typically, our method uses the same number of T gates as conventional synthesis but with the added benefit of quadratic error suppression. Because of this, one less round of magic state distillation needs to be performed, leading to significant resource savings.
Fault-tolerant quantum computers compose elements of a discrete gate set in order to approximate a target unitary. The problem of minimizing the number of gates is known as gate synthesis. The approximation error is a form of coherent noise, which can be significantly more damaging than comparable incoherent noise. We show how mixing over different gate sequences can convert this coherent noise into an incoherent form. As measured by diamond distance, the postmixing noise is quadratically smaller than before mixing, without increasing resource cost upper bounds. Equivalently, we can look for shorter gate sequences that achieve the same precision as unitary gate synthesis. For a broad class of problems this gives a factor 1/21/21/2 reduction in worst-case resource costs.