As scaling becomes a key issue for large-scale quantum computing, hardware control systems will become increasingly costly in resources. This article presents a compact direct digital synthesis architecture for signal generation adapted for spin qubits that is scalable in terms of waveform accuracy and the number of synchronized channels. The architecture can produce programmable combinations of ramps, frequency combs, and arbitrary waveform generation (AWG) at 5 GS/s, with a worst-case digital feedback latency of 76.8 ns. The field-programmable gate array (FPGA)-based system is highly configurable and takes advantage of bitstream switching to achieve the high flexibility required for scalable calibration. The architecture also provides GHz rate, multiplexed, in-phase and quadrature component, single-side band modulation for scalable reflectometry. This architecture has been validated in hardware on a Xilinx ZCU111 FPGA demonstrating the mixing of complex signals and the quality of the frequency comb generation for multiplexed control and measurement. The key benefits of this design are the increase of controllability of ramps at the digital-to-analog converter (DAC) frequency and the reduction in memory requirements by several orders of magnitude compared with existing AWG-based architectures. The hardware for a single channel is very compact, 2% of ZCU111 logic resources for one DAC lane in the default configuration, leaving significant circuit resources for integrated feedback, calibration, and quantum error correction.
{"title":"FASQuiC: Flexible Architecture for Scalable Spin Qubit Control","authors":"Mathieu Toubeix;Eric Guthmuller;Adrian Evans;Antoine Faurie;Tristan Meunier","doi":"10.1109/TQE.2024.3409811","DOIUrl":"https://doi.org/10.1109/TQE.2024.3409811","url":null,"abstract":"As scaling becomes a key issue for large-scale quantum computing, hardware control systems will become increasingly costly in resources. This article presents a compact direct digital synthesis architecture for signal generation adapted for spin qubits that is scalable in terms of waveform accuracy and the number of synchronized channels. The architecture can produce programmable combinations of ramps, frequency combs, and arbitrary waveform generation (AWG) at 5 GS/s, with a worst-case digital feedback latency of 76.8 ns. The field-programmable gate array (FPGA)-based system is highly configurable and takes advantage of bitstream switching to achieve the high flexibility required for scalable calibration. The architecture also provides GHz rate, multiplexed, in-phase and quadrature component, single-side band modulation for scalable reflectometry. This architecture has been validated in hardware on a Xilinx ZCU111 FPGA demonstrating the mixing of complex signals and the quality of the frequency comb generation for multiplexed control and measurement. The key benefits of this design are the increase of controllability of ramps at the digital-to-analog converter (DAC) frequency and the reduction in memory requirements by several orders of magnitude compared with existing AWG-based architectures. The hardware for a single channel is very compact, 2% of ZCU111 logic resources for one DAC lane in the default configuration, leaving significant circuit resources for integrated feedback, calibration, and quantum error correction.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10549805","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141453369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1109/TQE.2024.3409309
Zichang He;Bo Peng;Yuri Alexeev;Zheng Zhang
Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is that quantum noise is highly unstable and thus it is likely to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the quantum approximate optimization algorithm and the variational quantum eigensolver with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step toward improving the reliability of VQAs influenced by shifted noise from the parameter optimization perspective.
{"title":"Distributionally Robust Variational Quantum Algorithms With Shifted Noise","authors":"Zichang He;Bo Peng;Yuri Alexeev;Zheng Zhang","doi":"10.1109/TQE.2024.3409309","DOIUrl":"https://doi.org/10.1109/TQE.2024.3409309","url":null,"abstract":"Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is that quantum noise is highly unstable and thus it is likely to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the quantum approximate optimization algorithm and the variational quantum eigensolver with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step toward improving the reliability of VQAs influenced by shifted noise from the parameter optimization perspective.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10547365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141430031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1109/TQE.2024.3408757
Weining Dai;Kevin A. Brown;Thomas G. Robertazzi
Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.
{"title":"Advanced Shuttle Strategies for Parallel QCCD Architectures","authors":"Weining Dai;Kevin A. Brown;Thomas G. Robertazzi","doi":"10.1109/TQE.2024.3408757","DOIUrl":"https://doi.org/10.1109/TQE.2024.3408757","url":null,"abstract":"Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10546265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141474918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this article, we propose higher order binary formulations that can simultaneously reduce the numbers of qubits and gates required for GAS. Specifically, we consider two novel strategies: one that reduces the number of gates through polynomial factorization, and the other that halves the order of the objective function, subsequently decreasing circuit runtime and implementation cost. Our analysis demonstrates that the proposed higher order formulations improve the convergence performance of GAS by reducing both the search space size and the number of quantum gates. Our strategies are also beneficial for general combinatorial optimization problems using one-hot encoding.
格罗弗自适应搜索（GAS）是一种量子穷举搜索算法，旨在解决二进制优化问题。在本文中，我们提出了能同时减少 GAS 所需的量子比特和门数量的高阶二进制公式。具体来说，我们考虑了两种新策略：一种是通过多项式因式分解减少门的数量，另一种是将目标函数的阶数减半，从而减少电路运行时间和实现成本。我们的分析表明，通过减少搜索空间大小和量子门数量，所提出的高阶公式改善了 GAS 的收敛性能。我们的策略也适用于使用单次编码的一般组合优化问题。
{"title":"Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies With Higher Order Formulations","authors":"Yuki Sano;Kosuke Mitarai;Naoki Yamamoto;Naoki Ishikawa","doi":"10.1109/TQE.2024.3393437","DOIUrl":"https://doi.org/10.1109/TQE.2024.3393437","url":null,"abstract":"Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this article, we propose higher order binary formulations that can simultaneously reduce the numbers of qubits and gates required for GAS. Specifically, we consider two novel strategies: one that reduces the number of gates through polynomial factorization, and the other that halves the order of the objective function, subsequently decreasing circuit runtime and implementation cost. Our analysis demonstrates that the proposed higher order formulations improve the convergence performance of GAS by reducing both the search space size and the number of quantum gates. Our strategies are also beneficial for general combinatorial optimization problems using one-hot encoding.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10508492","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141068947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.1109/TQE.2024.3393416
Leonardo Oleynik;Junaid Ur Rehman;Hayder Al-Hraishawi;Symeon Chatzinotas
This article explores the performance of quantum communication systems in the presence of noise and focuses on finding the optimal encoding for maximizing the classical communication rate, approaching the classical capacity in some scenarios. Instead of theoretically bounding the ultimate capacity of the channel, we adopt a signal processing perspective to estimate the achievable performance of a physically available but otherwise unknown quantum channel. By employing a variational algorithm to estimate the trace distance between quantum states, we numerically determine the optimal encoding protocol for the amplitude damping and Pauli channels. Our simulations demonstrate the convergence and accuracy of the method with a few iterations, confirming that optimal conditions for binary quantum communication systems can be variationally determined with minimal computation. Furthermore, since the channel knowledge is not required at the transmitter or at the receiver, these results can be employed in arbitrary quantum communication systems, including satellite-based communication systems, a particularly relevant platform for the quantum Internet.
{"title":"Variational Estimation of Optimal Signal States for Quantum Channels","authors":"Leonardo Oleynik;Junaid Ur Rehman;Hayder Al-Hraishawi;Symeon Chatzinotas","doi":"10.1109/TQE.2024.3393416","DOIUrl":"https://doi.org/10.1109/TQE.2024.3393416","url":null,"abstract":"This article explores the performance of quantum communication systems in the presence of noise and focuses on finding the optimal encoding for maximizing the classical communication rate, approaching the classical capacity in some scenarios. Instead of theoretically bounding the ultimate capacity of the channel, we adopt a signal processing perspective to estimate the achievable performance of a physically available but otherwise unknown quantum channel. By employing a variational algorithm to estimate the trace distance between quantum states, we numerically determine the optimal encoding protocol for the amplitude damping and Pauli channels. Our simulations demonstrate the convergence and accuracy of the method with a few iterations, confirming that optimal conditions for binary quantum communication systems can be variationally determined with minimal computation. Furthermore, since the channel knowledge is not required at the transmitter or at the receiver, these results can be employed in arbitrary quantum communication systems, including satellite-based communication systems, a particularly relevant platform for the quantum Internet.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10508490","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140844526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1109/TQE.2024.3392834
David Winderl;Nicola Franco;Jeanette Miriam Lorenz
Variational quantum optimization algorithms, such as the variational quantum eigensolver (VQE) or the quantum approximate optimization algorithm (QAOA), are among the most studied quantum algorithms. In our work, we evaluate and improve an algorithm based on the VQE, which uses exponentially fewer qubits compared to the QAOA. We highlight the numerical instabilities generated by encoding the problem into the variational ansatz and propose a classical optimization procedure to find the ground state of the ansatz in fewer iterations with a better or similar objective. In addition, we propose a method to embed the linear interpolation of the MaxCut problem on a quantum device. Furthermore, we compare classical optimizers for this variational ansatz on quadratic unconstrained binary optimization and graph partitioning problems.
{"title":"A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits","authors":"David Winderl;Nicola Franco;Jeanette Miriam Lorenz","doi":"10.1109/TQE.2024.3392834","DOIUrl":"https://doi.org/10.1109/TQE.2024.3392834","url":null,"abstract":"Variational quantum optimization algorithms, such as the variational quantum eigensolver (VQE) or the quantum approximate optimization algorithm (QAOA), are among the most studied quantum algorithms. In our work, we evaluate and improve an algorithm based on the VQE, which uses exponentially fewer qubits compared to the QAOA. We highlight the numerical instabilities generated by encoding the problem into the variational ansatz and propose a classical optimization procedure to find the ground state of the ansatz in fewer iterations with a better or similar objective. In addition, we propose a method to embed the linear interpolation of the MaxCut problem on a quantum device. Furthermore, we compare classical optimizers for this variational ansatz on quadratic unconstrained binary optimization and graph partitioning problems.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10506971","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140902538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Quantum information cannot be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typically referred to as quantum cloning, and quantum teleportation. Quantum telecloning allows approximate copies of quantum information to be constructed by separate parties, using the classical results of a Bell measurement made on a prepared quantum telecloning state. Quantum telecloning can be implemented as a circuit on quantum computers using a classical coprocessor to compute classical feedforward instructions using if statements based on the results of a midcircuit Bell measurement in real time. We present universal symmetric optimal $1 rightarrow M$ telecloning circuits and experimentally demonstrate these quantum telecloning circuits for $M=2$ up to $M=10$ , natively executed with real-time classical control systems on IBM Quantum superconducting processors, known as dynamic circuits. We perform the cloning procedure on many different message states across the Bloch sphere, on seven IBM Quantum processors, optionally using the error suppression technique X–X sequence digital dynamical decoupling. Two circuit optimizations are utilized: one that removes ancilla qubits for $M=2, 3$ , and one that reduces the total number of gates in the circuit but still uses ancilla qubits. Parallel single-qubit tomography with maximum likelihood estimation density matrix reconstruction is used in order to compute the mixed-state density matrices of the clone qubits, and clone quality is measured using quantum fidelity. These results present one of the largest and most comprehensive noisy intermediate-scale quantum computer experimental analyses on (single qubit) quantum telecloning to date. The clone fidelity sharply decreases to 0.5 for $M > 5$ , but for $M=2$ , we are able to achieve a mean clone fidelity of up to 0.79 using dynamical decoupling.
量子信息无法完美克隆，但可以生成量子信息的近似副本。量子远程克隆结合了近似量子克隆（通常称为量子克隆）和量子远程传输。量子远距克隆可以利用对准备好的量子远距克隆状态进行贝尔测量的经典结果，由不同的当事人构建量子信息的近似副本。量子远程克隆可以在量子计算机上以电路的形式实现，使用经典协处理器，根据电路中段贝尔测量的结果，使用 if 语句实时计算经典前馈指令。我们提出了通用对称最优1美元/rightarrow M美元远程克隆电路，并在实验中演示了这些M=2美元到M=10美元的量子远程克隆电路，在IBM量子超导处理器（称为动态电路）上使用实时经典控制系统原生执行。我们在七台 IBM 量子处理器上对布洛赫球上的许多不同信息状态执行克隆程序，可选择使用误差抑制技术 X-X 序列数字动态解耦。我们采用了两种电路优化方法：一种是在 $M=2、3$ 时移除辅助量子比特，另一种是减少电路中的门总数，但仍使用辅助量子比特。为了计算克隆量子比特的混合态密度矩阵，我们使用了并行单量子比特层析技术和最大似然估计密度矩阵重构技术，并使用量子保真度来测量克隆质量。这些结果展示了迄今为止对（单量子比特）量子远程克隆进行的最大规模、最全面的噪声中型量子计算机实验分析之一。对于 $M > 5$，克隆保真度急剧下降至 0.5，但对于 $M=2$，我们能够利用动态解耦实现高达 0.79 的平均克隆保真度。
{"title":"Probing Quantum Telecloning on Superconducting Quantum Processors","authors":"Elijah Pelofske;Andreas Bärtschi;Stephan Eidenbenz;Bryan Garcia;Boris Kiefer","doi":"10.1109/TQE.2024.3391654","DOIUrl":"https://doi.org/10.1109/TQE.2024.3391654","url":null,"abstract":"Quantum information cannot be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typically referred to as quantum cloning, and quantum teleportation. Quantum telecloning allows approximate copies of quantum information to be constructed by separate parties, using the classical results of a Bell measurement made on a prepared quantum telecloning state. Quantum telecloning can be implemented as a circuit on quantum computers using a classical coprocessor to compute classical feedforward instructions using if statements based on the results of a midcircuit Bell measurement in real time. We present universal symmetric optimal \u0000<inline-formula><tex-math>$1 rightarrow M$</tex-math></inline-formula>\u0000 telecloning circuits and experimentally demonstrate these quantum telecloning circuits for \u0000<inline-formula><tex-math>$M=2$</tex-math></inline-formula>\u0000 up to \u0000<inline-formula><tex-math>$M=10$</tex-math></inline-formula>\u0000, natively executed with real-time classical control systems on IBM Quantum superconducting processors, known as dynamic circuits. We perform the cloning procedure on many different message states across the Bloch sphere, on seven IBM Quantum processors, optionally using the error suppression technique X–X sequence digital dynamical decoupling. Two circuit optimizations are utilized: one that removes ancilla qubits for \u0000<inline-formula><tex-math>$M=2, 3$</tex-math></inline-formula>\u0000, and one that reduces the total number of gates in the circuit but still uses ancilla qubits. Parallel single-qubit tomography with maximum likelihood estimation density matrix reconstruction is used in order to compute the mixed-state density matrices of the clone qubits, and clone quality is measured using quantum fidelity. These results present one of the largest and most comprehensive noisy intermediate-scale quantum computer experimental analyses on (single qubit) quantum telecloning to date. The clone fidelity sharply decreases to 0.5 for \u0000<inline-formula><tex-math>$M > 5$</tex-math></inline-formula>\u0000, but for \u0000<inline-formula><tex-math>$M=2$</tex-math></inline-formula>\u0000, we are able to achieve a mean clone fidelity of up to 0.79 using dynamical decoupling.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10505824","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-16DOI: 10.1109/TQE.2024.3386753
Shao-Hen Chiew;Kilian Poirier;Rajesh Mishra;Ulrike Bornheimer;Ewan Munro;Si Han Foon;Christopher Wanru Chen;Wei Sheng Lim;Chee Wei Nga
Multiobjective optimization is a ubiquitous problem that arises naturally in many scientific and industrial areas. Network routing optimization with multiobjective performance demands falls into this problem class, and finding good quality solutions at large scales is generally challenging. In this work, we develop a scheme with which near-term quantum computers can be applied to solve multiobjective combinatorial optimization problems. We study the application of this scheme to the network routing problem in detail, by first mapping it to the multiobjective shortest-path problem. Focusing on an implementation based on the quantum approximate optimization algorithm (QAOA)—the go-to approach for tackling optimization problems on near-term quantum computers—we examine the Pareto plot that results from the scheme and qualitatively analyze its ability to produce Pareto-optimal solutions. We further provide theoretical and numerical scaling analyses of the resource requirements and performance of QAOA and identify key challenges associated with this approach. Finally, through Amazon Braket, we execute small-scale implementations of our scheme on the IonQ Harmony 11-qubit quantum computer.
{"title":"Multiobjective Optimization and Network Routing With Near-Term Quantum Computers","authors":"Shao-Hen Chiew;Kilian Poirier;Rajesh Mishra;Ulrike Bornheimer;Ewan Munro;Si Han Foon;Christopher Wanru Chen;Wei Sheng Lim;Chee Wei Nga","doi":"10.1109/TQE.2024.3386753","DOIUrl":"https://doi.org/10.1109/TQE.2024.3386753","url":null,"abstract":"Multiobjective optimization is a ubiquitous problem that arises naturally in many scientific and industrial areas. Network routing optimization with multiobjective performance demands falls into this problem class, and finding good quality solutions at large scales is generally challenging. In this work, we develop a scheme with which near-term quantum computers can be applied to solve multiobjective combinatorial optimization problems. We study the application of this scheme to the network routing problem in detail, by first mapping it to the multiobjective shortest-path problem. Focusing on an implementation based on the quantum approximate optimization algorithm (QAOA)—the go-to approach for tackling optimization problems on near-term quantum computers—we examine the Pareto plot that results from the scheme and qualitatively analyze its ability to produce Pareto-optimal solutions. We further provide theoretical and numerical scaling analyses of the resource requirements and performance of QAOA and identify key challenges associated with this approach. Finally, through Amazon Braket, we execute small-scale implementations of our scheme on the IonQ Harmony 11-qubit quantum computer.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502334","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140844432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-05DOI: 10.1109/TQE.2024.3385673
Bagas Prabowo;Jurgen Dijkema;Xiao Xue;Fabio Sebastiano;Lieven M. K. Vandersypen;Masoud Babaie
In semiconductor spin quantum bits (qubits), the radio-frequency (RF) gate-based readout is a promising solution for future large-scale integration, as it allows for a fast, frequency-multiplexed readout architecture, enabling multiple qubits to be read out simultaneously. This article introduces a theoretical framework to evaluate the effect of various parameters, such as the readout probe power, readout chain's noise performance, and integration time on the intrinsic readout signal-to-noise ratio, and thus readout fidelity of RF gate-based readout systems. By analyzing the underlying physics of spin qubits during readout, this work proposes a qubit readout model that takes into account the qubit's quantum mechanical properties, providing a way to evaluate the tradeoffs among the aforementioned parameters. The validity of the proposed model is evaluated by comparing the simulation and experimental results. The proposed analytical approach, the developed model, and the experimental results enable designers to optimize the entire readout chain effectively, thus leading to a faster, lower power readout system with integrated cryogenic electronics.
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Pub Date : 2024-04-04DOI: 10.1109/TQE.2024.3385372
Gayathree M. Vinod;Anil Shaji
We implement a simulation of a quantum field theory in 1+1 space–time dimensions on a gate-based quantum computer using the light-front formulation of the theory. The nonperturbative simulation of the Yukawa model field theory is verified on IBM's simulator and is also demonstrated on a small-scale IBM circuit-based quantum processor, on the cloud, using IBM Qiskit. The light-front formulation allows for controlling the resource requirement and complexity of the computation with commensurate tradeoffs in accuracy and detail by modulating a single parameter, namely, the harmonic resolution. Qubit operators for the Bosonic excitations were also created and were used along with the Fermionic ones already available, to simulate the theory involving all of these particles. With the restriction on the number of logical qubits available on the existent gate-based noisy intermediate-scale quantum (NISQ) devices, the Trotterization approximation is also used. We show that experimentally relevant quantities, such as cross sections for various processes and survival probabilities of various states, can be computed. We also explore the inaccuracies introduced by the bounds on achievable harmonic resolution and Trotter steps placed by the limited number of qubits and circuit depth supported by present-day NISQ devices.
我们在基于门的量子计算机上，利用量子场论的光前表述，实现了 1+1 时空维度的量子场论模拟。我们在 IBM 的模拟器上验证了汤川模型场论的非微扰模拟，并利用 IBM Qiskit 在云端的小型 IBM 电路量子处理器上进行了演示。光前公式允许通过调节单个参数（即谐波分辨率）来控制计算的资源需求和复杂性，并在精度和细节方面做出相应的权衡。我们还创建了波色子激发的 Qubit 算子，并与已有的费米子算子一起用于模拟涉及所有这些粒子的理论。由于现有的基于门的噪声中量子（NISQ）器件的逻辑量子比特数量有限，因此还使用了特罗特化近似。我们的研究表明，各种过程的截面和各种状态的存活概率等实验相关量都可以计算出来。我们还探讨了由于当今 NISQ 器件支持的量子比特数量和电路深度有限，对可实现谐波分辨率和特罗特阶数的限制所带来的不准确性。
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