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Design, Automation, and Test in Europe

Improved synthesis of Clifford+T quantum functionality

Philipp Niemann, Robert Wille, Rolf Drechsler

Published Mar 1, 2018• 35 citations
Publisher

Abstract

The Clifford+T library provides robust and fault-tolerant realizations for quantum computations. Consequently, (logic) synthesis of Clifford+T quantum circuits became an important research problem. However, previously proposed solutions are either only applicable to very small quantum systems or lead to circuits that are far from being optimal- mainly caused by a local, i.e. column-wise, consideration of the underlying transformation matrix to be synthesized. In this paper, we suggest an improved approach that considers the matrix globally and, by this, overcomes many of these drawbacks. Preliminary evaluations show the promises of this direction.

DOI
10.23919/date.2018.8342078

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The Clifford+T library provides robust and fault-tolerant realizations for quantum computations. Consequently, (logic) synthesis of Clifford+T quantum circuits became an important research problem. However, previously proposed solutions are either only applicable to very small quantum systems or lead to circuits that are far from being optimal- mainly caused by a local, i.e. column-wise, consideration of the underlying transformation matrix to be synthesized. In this paper, we suggest an improved approach that considers the matrix globally and, by this, overcomes many of these drawbacks. Preliminary evaluations show the promises of this direction.
In fault-tolerant quantum circuit synthesis, T gates supplied via magic states dominate space-time cost, while Clifford gates incur negligible overhead. Conventional flows minimize AND count in an {XOR, AND, NOT} basis as a proxy for T, which neglects phase cancellation and can be far from T-optimal. We instead formulate an exact T synthesis problem and canonicalize Boolean functions under Clifford equivalence. By precomputing T-optimal implementations up to seven variables and developing a customized mapper, we reduce the T count by up to 14.3% on EPFL benchmarks and improve the T counts of several cryptographic modules by up to 40%.
Abstract Quantum systems provide a new way of conducting computations based on the so-called qubits. Due to the potential for significant speed-ups, this field received significant research attention in recent years. The Clifford+T library is a very promising and popular gate library for these kinds of computations. Unlike other libraries considered so far, it consists of only a small number of gates for all of which robust, fault-tolerant realizations are known for many technologies that seem to be promising for large-scale quantum computing. As a consequence, (logic) synthesis of Clifford+T quantum circuits became an important research problem. However, previous work in this area has several drawbacks: Corresponding approaches are either only applicable to very small quantum systems or lead to circuits that are far from being optimal. The latter is mainly caused by the fact that current synthesis realizes the desired circuit by a local, i.e., column-wise, consideration of the underlying unitary transformation matrix to be synthesized. In this paper, we analyze the conceptual drawbacks of this approach and propose to overcome them by taking a global view of the matrices and perform a separation of concerns regarding individual synthesis steps. We precisely describe a corresponding algorithm as well as its efficient implementation on top of decision diagrams. Experimental results confirm the resulting benefits and show improvements of up to several orders of magnitudes in costs compared to previous work.
Circuit synthesis is the task of decomposing a given logical functionality into a sequence of elementary gates. It is (depth-)optimal if it is impossible to achieve the desired functionality with even shorter circuits. Optimal synthesis is a central problem in both quantum and classical hardware design, but also plagued by complexity-theoretic obstacles. Motivated by fault-tolerant quantum computation, we consider the special case of synthesizing blocks of Clifford unitaries. Leveraging entangling input stimuli and the stabilizer formalism allows us to reduce the Clifford synthesis problem to a family of poly-size satisfiability (SAT) problems - one for each target circuit depth. On a conceptual level, our result showcases that the Clifford synthesis problem is contained in the first level of the polynomial hierarchy (NP), while the classical synthesis problem for logical circuits is known to be complete for the second level of the polynomial hierarchy (Σp2). Based on this theoretical reduction, we formulate a SAT encoding for depth-optimal Clifford synthesis. We then employ SAT solvers to determine a satisfying assignment or to prove that no such assignment exists. From that, the shortest depth for which synthesis is still possible (optimality) as well as the actual circuit (synthesis) can be obtained. Empirical evaluations show that the optimal synthesis approach yields a substantial depth improvement for random Clifford circuits and Clifford+T circuits for Grover search.
Although with some yet severe limitations, Physical working Quantum Computers are becoming available for end users. Such devices are based on the rules of Quantum Mechanics, which state that physical systems evolve through unitary transformations. However, as in the classical case, in order to have a model of computation, such unitary evolutions are expressed/approximated inside Quantum Computers in terms of a finite set of one/two qubit operations (i.e., through a universal set of gates). Single qubit gates are fault-tolerant, while the same cannot be said for two qubit gates. Hence, unitary matrices adopted in Quantum Algorithms must be synthesized in terms of this universal set of operations to obtain a quantum circuit. In such synthesis procedure we prefer circuits with minimum number of qubits and with minimum circuit depth. Clifford+T universal set is one of the most adopted in the literature for synthesis. In such set we have 3 single qubit gates and the CNOT, which is a two qubit gate. Many efforts have been directed to devise algorithms that synthesize general unitary matrices into Clifford+T circuits. These algorithms usually tend to optimize circuit depth or eventually the number of T gates. Since two qubit gates are not fault tolerant, in this work we propose an ASP based technique to minimize the number of CNOT gates inside a Clifford+T circuit. Moreover, in real world quantum computers, qubit are usually connected to each other according to some particular topology, thus providing further constraints. Two qubit gates —hence, CNOT gate— can be directly applied only to pair of gates that are connected. Such constraint has to be taken into account during the synthesis of CNOT minimal circuits. We propose an ASP model to solve the problem of synthesizing CNOT minimal circuits under topological constraints. We provide experimental evidence of the scalability of our proposal.
To achieve large-scale fault-tolerant quantum computation, it may be easier to combine many small sets of qubits than to construct a single large set. For example via quantum error correction with block codes, or distributed quantum processors utilizing shared entanglement. In these regimes, the time or error budget of the overall quantum computation may be dominated by non-local operations. Hence, it is worthwhile to minimize the number of these operations. We consider the case where both non-local and local connectivity may be arbitrarily restricted, and give an asymptotically optimal synthesis method for distributed CNOT and Clifford circuits, based on block-matrix Gaussian elimination. We extend this to all Clifford+RZ circuits by generalizing the Pauli exponential circuit representation; this naturally integrates with existing methods for optimizing T-count. As an application, we show how to implement CNOT circuits in a CSS code encoding n logical qubits in k blocks using O(nk) inter-block transversal CNOTs and intra-block Pauli measurements.
Resource-efficient and high-precision approximate synthesis of quantum circuits expressed in the Clifford+T gate set is vital for Fault-Tolerant quantum computing.Efficient optimal methods are known for single-qubit R Z unitaries, otherwise the problem is generally intractable.Search-based methods, like simulated annealing, empirically generate low resource cost approximate implementations of general multi-qubit unitaries so long as low precision (Hilbert-Schmidt distances of ε ≥ 10 -2 ) can be tolerated.These algorithms build up circuits that directly invert target unitaries.We instead leverage search-based methods to first approximately diagonalize a unitary, then perform the inversion analytically.This lets difficult continuous rotations be bypassed and handled in a postprocessing step.Our approach improves both the implementation precision and run time of synthesis algorithms by orders of magnitude when evaluated on unitaries from real quantum algorithms.On benchmarks previously synthesizable only with analytical techniques like the Quantum Shannon Decomposition, diagonalization uses an average of 95% fewer non-Clifford gates.