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arXiv:2311.08742

sQueeze: Accelerated Quantum Pulse Schedules

Lilian Hunt Alan Robertson

Published Nov 15, 2023• 1 citation
arXivHTMLPDF

Abstract

Quantum devices in the Noisy Intermediate-Scale Quantum (NISQ) era are limited by high error rates and short decoherence times. Typically, compiler optimisations have provided solutions at the gate level. Alternatively, we exploit the finest level of quantum control and introduce a set of pulse level quantum compiler optimisations: sQueeze. Instead of relying on existing calibration that may be inaccurate, we provide a method for the live calibration of two new parameterised basis gates $R_{x}(θ)$ and $R_{zx}(θ)$ using an external server. We validate our techniques using the IBM quantum devices and the OpenPulse control interface over more than 8 billion shots. The $R_{x}(θ)$ gates are on average 52.7% more accurate than their current native Qiskit decompositions, while $R_{zx}(θ)$ are 22.6% more accurate on average. These more accurate pulses also provide up to a 4.1$\times$ speed-up for single-qubit operations and 3.1$\times$ speed-up for two-qubit gates. Then sQueeze demonstrates up to a 39.6% improvement in the fidelity of quantum benchmark algorithms compared to conventional approaches.

DOI
10.48550/arxiv.2311.08742

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Quantum devices in the Noisy Intermediate-Scale Quantum (NISQ) era are limited by high error rates and short decoherence times. Typically, compiler optimisations have provided solutions at the gate level. Alternatively, we exploit the finest level of quantum control and introduce a set of pulse level quantum compiler optimisations: sQueeze. Instead of relying on existing calibration that may be inaccurate, we provide a method for the live calibration of two new parameterised basis gates Rx(θ)R_{x}(θ)Rx​(θ) and Rzx(θ)R_{zx}(θ)Rzx​(θ) using an external server. We validate our techniques using the IBM quantum devices and the OpenPulse control interface over more than 8 billion shots. The Rx(θ)R_{x}(θ)Rx​(θ) gates are on average 52.7% more accurate than their current native Qiskit decompositions, while Rzx(θ)R_{zx}(θ)Rzx​(θ) are 22.6% more accurate on average. These more accurate pulses also provide up to a 4.1×\times× speed-up for single-qubit operations and 3.1×\times× speed-up for two-qubit gates. Then sQueeze demonstrates up to a 39.6% improvement in the fidelity of quantum benchmark algorithms compared to conventional approaches.
Quantum computers are traditionally operated by programmers at the granularity of a gate-based instruction set. However, the actual device-level control of a quantum computer is performed via analog pulses. We introduce a compiler that exploits direct control at this microarchitectural level to achieve significant improvements for quantum programs. Unlike quantum optimal control, our approach is bootstrapped from existing gate calibrations and the resulting pulses are simple. Our techniques are applicable to any quantum computer and realizable on current devices. We validate our techniques with millions of experimental shots on IBM quantum computers, controlled via the OpenPulse control interface. For representative benchmarks, our pulse control techniques achieve both 1.6x lower error rates and 2x faster execution time, relative to standard gate-based compilation. These improvements are critical in the near-term era of quantum computing, which is bottlenecked by error rates and qubit lifetimes.
The effective use of current Noisy Intermediate-Scale Quantum (NISQ) devices is often limited by the noise which is caused by interaction with the environment and affects the fidelity of quantum gates. In transmon qubit systems, the quantum gate fidelity can be improved by applying control pulses that can minimize the effects of the environmental noise. In this work, we employ physics-guided quantum optimal control strategies to design optimal pulses driving quantum gates on superconducting qubit systems. We test our results by conducting experiments on the IBM quantum hardware using their OpenPulse API. We compare the performance of our pulse-optimized quantum gates against the default quantum gates and show that the optimized pulses improve the fidelity of the quantum gates, in particular the single-qubit gates. We discuss the challenges we encountered in our work and point to possible future improvements.
Near-term intermediate-scale quantum (NISQ) devices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency and improve fidelity. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recent studies investigate the merged pulse generation method for customized gates through quantum optimal control (QOC). In this work, we propose PAQOC, a novel QOC framework that can (i) exploit an augmented program-aware (APA) basis gate set for the tradeoff between compilation time and circuit performance, (ii) prune the search space based on a criticality-centric analytical model and experiment observations we learned from 150 benchmarks. Evaluations using seventeen applications show that PAQOC can achieve an average 54% reduction of the circuit latency, on average 43% reduction in compilation overhead, and a 1.27× improvement in fidelity. PAQOC is available on GitHub1.
ABSTRACT: Recent research has tackled the problem of mitigating noise present in quantum computers in the Noisy Intermediate-Scale Quantum (NISQ) era to enable precise computations and to benefit from the intrinsic properties of quantum mechanics. For this matter, an important task is the characterization of qubits available in quantum devices so as to provide insights on how to reduce noise on the final output of a quantum circuit. Characterization comprises analysis of noise sources and this information can be used to reduce noise with methods such as Cycle Benchmarking, Quantum Error Mitigation, Quantum Error Correction and others. Here, we study optimization of pulses through Quantum Optimal Control (QOC) to obtain higher gate fidelity. We will explore an algorithm that performs calibration on specific quantum gates by implementing optimized pulse schedules to subsequently use the algorithm for analysis of noise sources. Using calibrated gates as input, several benchmarking protocols, including pulse noise extrapolation, leakage analysis from quantum optimal control, and machine learning based classification of qubit readout, will be tested to extract precise information on how noise influences the analyzed qubits. We will explain and discuss different techniques for obtaining properties of qubits and quantum computers. We will implement state discrimination with a Machine Learning (ML) focus to analyze readout errors caused by factors such as cross-talk and leakage into higher quantum states. We will perform noise fitting of optimized pulses and evaluate the effectiveness of important quantum algorithms at the pulse level.
The current phase of quantum computing is in the Noisy Intermediate-Scale Quantum (NISQ) era. On NISQ devices, two-qubit gates such as CNOTs are much noisier than single-qubit gates, so it is essential to minimize their count. Quantum circuit synthesis is a process of decomposing an arbitrary unitary into a sequence of quantum gates, and can be used as an optimization tool to produce shorter circuits to improve overall circuit fidelity. However, the time-to-solution of synthesis grows exponentially with the number of qubits. As a result, synthesis is intractable for circuits on a large qubit scale. In this paper, we propose a hierarchical, block-by-block optimization framework, QGo, for quantum circuit optimization. Our approach allows an exponential cost optimization to scale to large circuits. QGo uses a combination of partitioning and synthesis: 1) partition the circuit into a sequence of independent circuit blocks; 2) re-generate and optimize each block using quantum synthesis; and 3) re-compose the final circuit by stitching all the blocks together. We perform our analysis and show the fidelity improvements in three different regimes: small-size circuits on real devices, medium-size circuits on noise simulations, and large-size circuits on analytical models. Using a set of NISQ benchmarks, we show that QGo can reduce the number of CNOT gates by 29.9% on average and up to 50% when compared with industrial compilers such as t|ket>. When executed on the IBM Athens system, shorter depth leads to higher circuit fidelity. We also demonstrate the scalability of our QGo technique to optimize circuits of 60+ qubits. Our technique is the first demonstration of successfully employing and scaling synthesis in the compilation toolchain for large circuits. Overall, our approach is robust for direct incorporation in production compiler toolchains.
In the current era of Noisy Intermediate-Scale Quantum (NISQ) technology, the practical use of quantum computers remains inhibited by our inability to aptly decouple qubits from their environment to mitigate computational errors. In this work, we introduce an approach by which knowledge of a qubit's initial quantum state and the standard parameters describing its decoherence can be leveraged to mitigate the noise present during the execution of a single-qubit gate. We benchmark our protocol using cloud-based access to IBM quantum processors. On ibmq_rome, we demonstrate a reduction of the single-qubit error rate by 38%38\%38%, from 1.6×10−31.6 \times 10 ^{-3}1.6×10−3 to 1.0×10−31.0 \times 10 ^{-3}1.0×10−3, provided the initial state of the input qubit is known. On ibmq_bogota, we prove that our protocol will never decrease gate fidelity, provided the system's T1T_1T1​ and T2T_2T2​ times have not drifted above 100100100 times their assumed values. The protocol can be used to reduce quantum state preparation errors, as well as to improve the fidelity of quantum circuits for which some knowledge of the qubits' intermediate states can be inferred. This work presents a pathway to using information about noise levels and quantum state distributions to significantly reduce error rates associated with quantum gates via optimized decomposition into native gates.