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IEEE International Conference on Quantum Computing and Engineering (QCE)

Towards Readout-Aware Layout Synthesis for Spin Qubit Systems with Double Quantum Dot Readouts

Ritu Thombre, Marcus Edwards, Joe Salfi, Olivia Di Matteo

Published Sep 15, 2024• 2 citations
Publisher

Abstract

A quantum compiler is required to run a quantum circuit on a quantum computer, similar to how classical compilers are required to run programs on classical computers. Spin qubits are a promising candidate for scalable quantum computers. General-purpose quantum compilers can be used for spin qubit devices, however they do not consider additional constraints imposed due to Double-Quantum-Dot (DQD) readout. For DQD readout, when a qubit in an algorithm is measured, the compiler must remap and re-route it to be adjacent to a special-purpose readout qubit, which is preserved in a known state. Moreover, this should be done in a way that minimizes overhead and maximizes the fidelity, in particular, due to noise in the readout process. This work formulates readout constraints to extend SMT (Satisfiability Modulo Theory)-based layout synthesis techniques proposed in [1] to spin qubit architectures. We define a metric, readout depth, to quantify the overheads incurred. Preliminary results, obtained from benchmarking GHZ and variational quantum eigensolver circuits on architectures with grid topologies, highlight the algorithmic tradeoffs that arise. We expect ongoing work on scaling up the methods to a larger set of algorithms will help inform the decisions of spin qubit hardware designers.

DOI
10.1109/qce60285.2024.10419

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A quantum compiler is required to run a quantum circuit on a quantum computer, similar to how classical compilers are required to run programs on classical computers. Spin qubits are a promising candidate for scalable quantum computers. General-purpose quantum compilers can be used for spin qubit devices, however they do not consider additional constraints imposed due to Double-Quantum-Dot (DQD) readout. For DQD readout, when a qubit in an algorithm is measured, the compiler must remap and re-route it to be adjacent to a special-purpose readout qubit, which is preserved in a known state. Moreover, this should be done in a way that minimizes overhead and maximizes the fidelity, in particular, due to noise in the readout process. This work formulates readout constraints to extend SMT (Satisfiability Modulo Theory)-based layout synthesis techniques proposed in [1] to spin qubit architectures. We define a metric, readout depth, to quantify the overheads incurred. Preliminary results, obtained from benchmarking GHZ and variational quantum eigensolver circuits on architectures with grid topologies, highlight the algorithmic tradeoffs that arise. We expect ongoing work on scaling up the methods to a larger set of algorithms will help inform the decisions of spin qubit hardware designers.
With the announcement of the most advanced silicon spin quantum-bit (qubit) chip by Intel, silicon-based quantum circuit manufacturing technology has shown the superior potential to realize quantum computing to other technologies because of the mature semiconductor manufacturing technologies and the compatibility with electronics. Due to the bottleneck in scalability caused by interconnections in silicon-based quantum circuits, crossbar architectures serve as one of the most promising solutions for circuitry implementation. This paper proposes the first satisfiability modulo theories (SMT) formulation to optimally solve the layout synthesis problem by simultaneously performing scheduling, mapping, and routing for silicon-based quantum systems with a specific crossbar architecture. The experiments demonstrate that the proposed method can effectively generate layout synthesis results with minimal usage of swap and shuttle gates within the shortest circuit depths, and the solutions greatly outperform those derived from a state-of-the-art work.
Despite Noisy Intermediate-Scale Quantum devices being severely constrained, hardware- and algorithm-aware quantum circuit mapping techniques have been developed to enable successful algorithm executions. Not so much attention has been paid to mapping and compilation implementations for spin-qubit quantum processors due to the scarce availability of experimental devices and their small sizes. However, based on their high scalability potential and their rapid progress it is timely to start exploring solutions on such devices. In this work, we discuss the unique mapping challenges of a scalable crossbar architecture with shared control and introduce SpinQ , the first native compilation framework for scalable spin-qubit architectures. At the core of SpinQ is the Integrated Strategy that addresses the unique operational constraints of the crossbar while considering compilation scalability and obtaining a O(n) computational complexity. To evaluate the performance of SpinQ on this novel architecture, we compiled a broad set of well-defined quantum circuits and performed an in-depth analysis based on multiple metrics such as gate overhead, depth overhead, and estimated success probability, which in turn allowed us to create unique mapping and architectural insights. Finally, we propose novel mapping techniques that could increase algorithm success rates on this architecture and potentially inspire further research on quantum circuit mapping for other scalable spin-qubit architectures.
The physical qubits in current quantum computers do not all interact with each other. Therefore, in executing a quantum algorithm on an actual quantum computer, layout synthesis is a crucial step that ensures that the synthesized circuit of the quantum algorithm can run smoothly on the quantum computer. In this paper, we focus on a layout synthesis problem for quantum circuits and improve a prior work, TB-OLSQ, which adopts a transition-based satisfiability modulo theories (SMT) formulation. We present how to modify TB-OLSQ to obtain an accelerated version for runtime reduction. In addition, we extend the accelerated version by considering gate absorption for better solution quality. Our experimental results show that compared with TB-OLSQ, the accelerated version achieves 121X speedup for a set of SWAP-free circuits and 6X speedup for the other set of circuits with no increase in SWAP gates. In addition, the accelerated version with gate absorption helps reduce the number of SWAP gates by 38.9% for the circuits requiring SWAP gates, while it is also 3X faster.
Abstract Any quantum program on a realistic quantum device must be compiled into an executable form while taking into account the underlying hardware constraints. Stringent restrictions on architecture and control imposed by physical platforms make this very challenging. In this paper, based on the quantum variational algorithm, we propose a novel scheme to train an Ansatz circuit and realize high-fidelity compilation of a set of universal quantum gates for singlet-triplet qubits in semiconductor double quantum dots, a fairly heavily constrained system. Furthermore, we propose a scalable architecture for a modular implementation of quantum programs in this constrained systems and validate its performance with two representative demonstrations, the Grover’s algorithm for the database searching (static compilation) and a variant of variational quantum eigensolver for the Max-Cut optimization (dynamic compilation). Our methods are potentially applicable to a wide range of physical devices. This work constitutes an important stepping-stone for exploiting the potential for advanced and complicated quantum algorithms on near-term devices.
Layout synthesis in quantum circuits maps the logical qubits of a synthesized circuit onto the physical qubits of a hardware device (coupling graph) and complies with the hardware limitations. Existing studies on the problem usually suffer from intractable formulation complexity and thus prohibitively long runtimes. In this paper, we propose an efficient layout synthesizer by developing a satisfiability modulo theories (SMT)-based qubit mapping checker. The proposed qubit mapping checker can efficiently derive a SWAP-free solution if one exists. If no SWAP-free solution exists for a circuit, we propose a divide-and-conquer scheme that utilizes the checker to find SWAP-free sub-solutions for sub-circuits, and the overall solution is found by merging sub-solutions with SWAP insertion. Experimental results show that the proposed optimization flow can achieve more than 3000× runtime speedup over a state-of-the-art work to derive optimal solutions for a set of SWAP-free circuits. Moreover, for the other set of benchmark circuits requiring SWAP gates, our flow achieves more than 800× speedup and obtains near-optimal solutions with only 3% SWAP overhead.
Abstract Any quantum program on a realistic quantum device must be compiled into an executable form while taking into account the underlying hardware constraints. Stringent restrictions on architecture and control imposed by physical platforms make this very challenging. In this paper, based on the quantum variational algorithm, we propose a novel scheme to train an Ansatz circuit and realize high-fidelity compilation of a set of universal quantum gates for singlet-triplet qubits in semiconductor double quantum dots, a fairly heavily constrained system. Furthermore, we propose a scalable architecture for a modular implementation ofquantum programs in this constrained systems and validate its performance with two representative demonstrations, Grover's algorithm for the database searching (static compilation) and a variant of variational quantum eigensolver for the Max-Cut optimization (dynamic compilation). Our methods are potentially applicable to a wide range of physical devices. This work constitutes an important stepping-stone for exploiting the potential for advanced and complicated quantum algorithms on near-term devices.