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arXiv:2205.00724 · Electronic Proceedings in Theoretical Computer Science

Dynamic Qubit Routing with CNOT Circuit Synthesis for Quantum Compilation

Arianne Meijer-van de Griend, Sarah Meng Li

Published Nov 14, 2023• 8 citations
arXivHTMLPDF

Abstract

Many quantum computers have constraints regarding which two-qubit operations are locally allowed.To run a quantum circuit under those constraints, qubits need to be mapped to different quantum registers, and multi-qubit gates need to be routed accordingly.Recent developments have shown that compiling strategies based on Steiner tree provide a competitive tool to route CNOTs.However, these algorithms require the qubit map to be decided before routing.Moreover, the qubit map is fixed throughout the computation, i.e. the logical qubit will not be moved to a different physical qubit register.This is inefficient with respect to the CNOT count of the resulting circuit.In this paper, we propose the algorithm PermRowCol for routing CNOTs in a quantum circuit.It dynamically remaps logical qubits during the computation, and thus results in fewer output CNOTs than the algorithms Steiner-Gauss [14] and RowCol [27].Here we focus on circuits over CNOT only, but this method could be generalized to a routing and mapping strategy on Clifford+T circuits by slicing the quantum circuit into subcircuits composed of CNOTs and single-qubit gates.Additionally, PermRowCol can be used in place of Steiner-Gauss in the synthesis of phase polynomials as well as the extraction of quantum circuits from ZX-diagrams.

DOI
10.4204/eptcs.394.18

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Many quantum computers have constraints regarding which two-qubit operations are locally allowed.To run a quantum circuit under those constraints, qubits need to be mapped to different quantum registers, and multi-qubit gates need to be routed accordingly.Recent developments have shown that compiling strategies based on Steiner tree provide a competitive tool to route CNOTs.However, these algorithms require the qubit map to be decided before routing.Moreover, the qubit map is fixed throughout the computation, i.e. the logical qubit will not be moved to a different physical qubit register.This is inefficient with respect to the CNOT count of the resulting circuit.In this paper, we propose the algorithm PermRowCol for routing CNOTs in a quantum circuit.It dynamically remaps logical qubits during the computation, and thus results in fewer output CNOTs than the algorithms Steiner-Gauss [14] and RowCol [27].Here we focus on circuits over CNOT only, but this method could be generalized to a routing and mapping strategy on Clifford+T circuits by slicing the quantum circuit into subcircuits composed of CNOTs and single-qubit gates.Additionally, PermRowCol can be used in place of Steiner-Gauss in the synthesis of phase polynomials as well as the extraction of quantum circuits from ZX-diagrams.
Many physical implementations of quantum computers impose stringent memory constraints in which 2-qubit operations can only be performed between qubits which are nearest neighbours in a lattice or graph structure. Hence, before a computation can be run on such a device, it must be mapped onto the physical architecture. That is, logical qubits must be assigned physical locations in the quantum memory, and the circuit must be replaced by an equivalent one containing only operations between nearest neighbours. In this paper, we give a new technique for quantum circuit mapping (a.k.a. routing), based on Gaussian elimination constrained to certain optimal spanning trees called Steiner trees. We give a reference implementation of the technique for CNOT circuits and show that it significantly out-performs general-purpose routines on CNOT circuits. We then comment on how the technique can be extended straightforwardly to the synthesis of CNOT+Rz circuits and as a modification to a recently-proposed circuit simplification/extraction procedure for generic circuits based on the ZX-calculus.
In the era of noisy intermediate-scale quantum (NISQ), executing quantum algorithms on actual quantum devices faces unique challenges. One such challenge is that quantum devices in this era have restricted connectivity: quantum gates are allowed to act only on specific pairs of physical qubits. For this reason, a quantum circuit needs to go through a compiling process called qubit routing before it can be executed on a quantum computer. In this study, we propose a CNOT synthesis method called the token reduction method to solve this problem. The token reduction method works for all quantum computers whose architecture is represented by connected graphs. A major difference between our method and the existing ones is that our method synthesizes a circuit to an output qubit mapping that might be different from the input qubit mapping. The final mapping for the synthesis is determined dynamically during the synthesis process. Results showed that our algorithm consistently outperforms the best publicly accessible algorithm for all of the tested quantum architectures.
CNOT circuits are a common building block of general quantum circuits. The problem of synthesizing and optimizing such circuits has received a lot of attention in the quantum computing literature. This problem is especially challenging for quantum devices with restricted connectivity, where two-qubit gates can only be placed between adjacent qubits. The state-of-the-art algorithms for optimizing the number of CNOT gates are heuristic algorithms that are based on Gaussian elimination and that use Steiner trees to connect between different subsets of qubits. In this article, we suggest considering weighted Steiner trees, and we present a simple low-cost heuristic to compute weights. The simulated evaluation shows that the suggested heuristic is almost always beneficial and reduces the number of CNOT gates by up to 10%.
CNOT circuits are a common building block of general quantum circuits. The problem of synthesizing and optimizing such circuits has received a lot of attention in the quantum computing literature. This problem is especially challenging for quantum devices with restricted connectivity, where two-qubit gates can only be placed between adjacent qubits. The state-of-the-art algorithms for optimizing the number of CNOT gates are heuristic algorithms that are based on Gaussian elimination and that use Steiner trees to connect between different subsets of qubits. In this article, we suggest considering \emph{weighted} Steiner trees, and we present a simple low-cost heuristic to compute weights. The simulated evaluation shows that the suggested heuristic is almost always beneficial and reduces the number of CNOT gates by up to 10%.
While mapping a quantum circuit to the physical layer one has to consider the numerous constraints imposed by the underlying hardware architecture. Connectivity of the physical qubits is one such constraint that restricts two-qubit operations, such as CNOT, to “connected” qubits. SWAP gates can be used to place the logical qubits on admissible physical qubits, but they entail a significant increase in CNOT-count. In this article, we consider the problem of reducing the CNOT-count in Clifford+T circuits on connectivity-constrained architectures, like noisy intermediate-scale quantum (NISQ) computing devices. We “slice” the circuit at the position of Hadamard gates and “build” the intermediate{CNOT,T}\{\text {CNOT},{T}\}{CNOT,T}subcircuits using Steiner trees, significantly improving on previous methods. We compared the performance of our algorithms while mapping different benchmark and random circuits to some well-known architectures, such as 9-qubit square grid, 16-qubit square grid, Rigetti 16-qubit Aspen, 16-qubit IBM QX5, and 20-qubit IBM Tokyo. Our methods give less CNOT-count compared to Qiskit and TKET transpiler as well as using SWAP gates. Assuming most of the errors in an NISQ circuit implementation are due to CNOT errors, then our method would allow circuits with a few times more CNOT gates be reliably implemented than the previous methods would permit.
We propose a scalable, hierarchical qubit mapping and routing algorithm that harnesses the power of circuit synthesis. First, we decompose large circuits into subcircuits small enough to be directly resynthesized. For each block, we pre-synthesize them for all permutations of its input and output qubits. Following this offline step, we employ a permutation-aware, block-based generalization of the popular SABRE mapping algorithm. This mapping step stitches together blocks by choosing an input-output permutation that minimizes intrablock gate count and required inter-block communication (SWAP and bridge gates). Our approach has a twofold advantage: 1) circuit synthesis may eliminate more two-qubit gates than other optimizing compilers; 2) considering all permutations of input and output qubits eliminates communication operations transparently. In contrast, other mapping algorithms can only introduce communication operations. We show that we can produce better-quality circuits than commercial compilers: shorter by up to 68% (18% on average) fewer gates than Qiskit, up to 36% (9% on average) fewer gates than Tket. We outperform BQSkit, a permutation-unaware, synthesis-based compiler, by up to 67% (21% on average) fewer gates. We also exceed experimental optimal mappers such as OLSQ in quality (10.7% shorter circuits) and time to solution. Our scalable, heuristic approach can be seamlessly integrated into any quantum circuit compiler or optimization infrastructure, and it applies well to any qubit technology, such as superconducting and trapped ions.