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Decoding quantum color codes with MaxSAT 用 MaxSAT 解码量子色码
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-23 DOI: 10.22331/q-2024-10-23-1506
Lucas Berent, Lukas Burgholzer, Peter-Jan H.S. Derks, Jens Eisert, Robert Wille
In classical computing, error-correcting codes are well established and are ubiquitous both in theory and practical applications. For quantum computing, error-correction is essential as well, but harder to realize, coming along with substantial resource overheads and being concomitant with needs for substantial classical computing. Quantum error-correcting codes play a central role on the avenue towards fault-tolerant quantum computation beyond presumed near-term applications. Among those, color codes constitute a particularly important class of quantum codes that have gained interest in recent years due to favourable properties over other codes. As in classical computing, $decoding$ is the problem of inferring an operation to restore an uncorrupted state from a corrupted one and is central in the development of fault-tolerant quantum devices. In this work, we show how the decoding problem for color codes can be reduced to a slight variation of the well-known $texttt{LightsOut}$ puzzle. We propose a novel decoder for quantum color codes using a formulation as a MaxSAT problem based on this analogy. Furthermore, we optimize the MaxSAT construction and show numerically that the decoding performance of the proposed decoder achieves state-of-the-art decoding performance on color codes. The implementation of the decoder as well as tools to automatically conduct numerical experiments are publicly available as part of the $textit{Munich Quantum Toolkit}$ (MQT) on GitHub.
在经典计算中,纠错码已经非常成熟,在理论和实际应用中无处不在。对于量子计算来说,纠错也是必不可少的,但却更难实现,因为纠错会带来巨大的资源开销,同时还需要大量的经典计算。量子纠错码在通往容错量子计算的道路上扮演着核心角色,超越了假定的近期应用。其中,颜色代码是一类特别重要的量子代码,由于其优于其他代码的特性,近年来备受关注。与经典计算一样,"解码 "也是推断操作以从损坏状态恢复未损坏状态的问题,是容错量子设备开发的核心。在这项工作中,我们展示了如何将彩色代码的解码问题简化为著名的$texttt{LightsOut}$谜题的细微变化。基于这种类比,我们提出了一种新型量子色码解码器,并将其表述为 MaxSAT 问题。此外,我们还对 MaxSAT 结构进行了优化,并用数值证明了所提解码器的解码性能达到了最先进的色码解码性能。作为 GitHub 上 $textit{Munich Quantum Toolkit}$ (MQT) 的一部分,解码器的实现以及自动进行数值实验的工具都是公开的。
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引用次数: 0
Random Natural Gradient 随机自然渐变
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-22 DOI: 10.22331/q-2024-10-22-1503
Ioannis Kolotouros, Petros Wallden
Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. An important bottleneck is the classical optimization loop, where the multiple local minima and the emergence of barren plateaux make these approaches less appealing. To improve the optimization the Quantum Natural Gradient (QNG) method [15] was introduced – a method that uses information about the local geometry of the quantum state-space. While the QNG-based optimization is promising, in each step it requires more quantum resources, since to compute the QNG one requires $O(m^2)$ quantum state preparations, where $m$ is the number of parameters in the parameterized circuit. In this work we propose two methods that reduce the resources/state preparations required for QNG, while keeping the advantages and performance of the QNG-based optimization. Specifically, we first introduce the Random Natural Gradient (RNG) that uses random measurements and the classical Fisher information matrix (as opposed to the quantum Fisher information used in QNG). The essential quantum resources reduce to linear $O(m)$ and thus offer a quadratic "speed-up", while in our numerical simulations it matches QNG in terms of accuracy. We give some theoretical arguments for RNG and then benchmark the method with the QNG on both classical and quantum problems. Secondly, inspired by stochastic-coordinate methods, we propose a novel approximation to the QNG which we call Stochastic-Coordinate Quantum Natural Gradient that optimizes only a small (randomly sampled) fraction of the total parameters at each iteration. This method also performs equally well in our benchmarks, while it uses fewer resources than the QNG.
量子-经典混合算法似乎是近期量子应用中最有前途的方法。一个重要的瓶颈是经典优化环路,在这个环路中,多个局部最小值和贫瘠高原的出现使这些方法不那么吸引人。为了改进优化,引入了量子自然梯度法(QNG)[15]--一种利用量子态空间局部几何信息的方法。虽然基于 QNG 的优化很有前景,但每一步都需要更多量子资源,因为计算 QNG 需要 $O(m^2)$ 量子状态准备,其中 $m$ 是参数化电路中的参数数。在这项工作中,我们提出了两种方法,既能减少 QNG 所需的资源/状态准备,又能保持基于 QNG 优化的优势和性能。具体来说,我们首先引入了随机自然梯度(RNG),它使用随机测量和经典费雪信息矩阵(而非 QNG 中使用的量子费雪信息)。必要的量子资源减少到线性 $O(m)$,因此提供了二次 "提速",而在我们的数值模拟中,它在精度方面与 QNG 不相上下。我们给出了 RNG 的一些理论依据,然后将该方法与 QNG 在经典和量子问题上进行了比较。其次,受随机坐标方法的启发,我们提出了一种新的 QNG 近似方法,我们称之为随机坐标量子自然梯度法,它在每次迭代时只优化总参数的一小部分(随机抽样)。这种方法在我们的基准测试中同样表现出色,而且比 QNG 使用更少的资源。
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引用次数: 0
Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training 量子核配准的高效参数优化:变分训练中的子采样方法
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-18 DOI: 10.22331/q-2024-10-18-1502
M. Emre Sahin, Benjamin C. B. Symons, Pushpak Pati, Fayyaz Minhas, Declan Millar, Maria Gabrani, Stefano Mensa, Jan Lukas Robertus
Quantum machine learning with quantum kernels for classification problems is a growing area of research. Recently, quantum kernel alignment techniques that parameterise the kernel have been developed, allowing the kernel to be trained and therefore aligned with a specific dataset. While quantum kernel alignment is a promising technique, it has been hampered by considerable training costs because the full kernel matrix must be constructed at every training iteration. Addressing this challenge, we introduce a novel method that seeks to balance efficiency and performance. We present a sub-sampling training approach that uses a subset of the kernel matrix at each training step, thereby reducing the overall computational cost of the training. In this work, we apply the sub-sampling method to synthetic datasets and a real-world breast cancer dataset and demonstrate considerable reductions in the number of circuits required to train the quantum kernel while maintaining classification accuracy.
利用量子内核解决分类问题的量子机器学习是一个不断发展的研究领域。最近,人们开发出了量子内核对齐技术,这种技术对内核进行参数化,允许对内核进行训练,从而使其与特定数据集对齐。虽然量子内核对齐技术前景广阔,但由于每次训练迭代时都必须构建完整的内核矩阵,因此训练成本相当高。为了应对这一挑战,我们引入了一种新方法,力求在效率和性能之间取得平衡。我们提出了一种子采样训练方法,在每个训练步骤中使用内核矩阵的一个子集,从而降低了训练的总体计算成本。在这项工作中,我们将子采样方法应用于合成数据集和真实世界的乳腺癌数据集,并证明在保持分类准确性的同时,训练量子核所需的电路数量有了显著减少。
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引用次数: 0
Quantum Locally Testable Code with Constant Soundness 具有恒健性的量子局部可测试代码
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-18 DOI: 10.22331/q-2024-10-18-1501
Andrew Cross, Zhiyang He, Anand Natarajan, Mario Szegedy, Guanyu Zhu
In this paper, we present two constructions of quantum locally testable codes (QLTC) with constant soundness. In the first approach, we introduce an operation called check product, and show how this operation gives rise to QLTCs of constant soundness, constant rate, and distance scaling with locality. In the second approach, we consider hypergraph product of a quantum code and a classical repetition code, and observe a special case in which the soundness of component codes is preserved. This insight leads us to construct QLTCs of constant soundness, scalable rate and distance, and constant average locality. Our work marks a step towards constructing QLTCs of high soundness and distance, which would give a different construction to the No Low-Energy Trivial States (NLTS) theorem.
在本文中,我们提出了两种具有恒定健全性的量子局部可检验码(QLTC)的构造。在第一种方法中,我们引入了一种称为校验积的操作,并展示了这种操作如何产生具有恒定健全性、恒定速率和随局部性缩放的距离的 QLTC。在第二种方法中,我们考虑了量子密码和经典重复密码的超图积,并观察到了一种特殊情况,即分量密码的健全性得以保留。这一洞察力引导我们构建了具有恒定健全性、可扩展速率和距离以及恒定平均位置性的 QLTC。我们的工作标志着向构造高健全性和高距离的 QLTC 迈出了一步,这将为无低能三维状态(NLTS)定理提供一种不同的构造。
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引用次数: 0
Quantum lozenge tiling and entanglement phase transition 量子菱形瓦与纠缠相变
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1497
Zhao Zhang, Israel Klich
While volume violation of area law has been exhibited in several quantum spin chains, the construction of a corresponding ground state in higher dimensions, entangled in more than one direction, has been an open problem. Here we construct a 2D frustration-free Hamiltonian with maximal violation of the area law. We do so by building a quantum model of random surfaces with color degree of freedom that can be viewed as a collection of colored Dyck paths. The Hamiltonian may be viewed as a 2D generalization of the Fredkin spin chain. It relates all the colored random surface configurations subject to a Dirichlet boundary condition and hard wall constraint from below to one another, and the ground state is therefore a superposition of all such classical states and non-degenerate. Its entanglement entropy between subsystems undergoes a quantum phase transition as the deformation parameter is tuned. The area- and volume-law phases are similar to the one-dimensional model, while the critical point scales with the linear size of the system $L$ as $Llog L$. Further it is conjectured that similar models with entanglement phase transitions can be built in higher dimensions with even softer area law violations at the critical point.
虽然在一些量子自旋链中已经出现了违反面积定律的体积现象,但在更高维度上构建一个在多个方向上纠缠的相应基态,一直是一个悬而未决的问题。在这里,我们构建了一个最大程度违反面积定律的二维无挫折哈密顿。为此,我们建立了一个具有彩色自由度的随机表面量子模型,该模型可被视为彩色戴克路径的集合。哈密顿可以看作是弗雷德金自旋链的二维广义化。它将所有受制于迪里夏特边界条件和硬壁约束的彩色随机表面配置自下而上地相互联系起来,因此基态是所有这些经典状态的叠加,而且是非退化的。随着变形参数的调整,子系统之间的纠缠熵会发生量子相变。面积法和体积法阶段与一维模型类似,而临界点则随着系统的线性大小 $L$ 的增大而增大,为 $Llog L$。此外,我们还猜想可以在更高维度上建立具有纠缠相变的类似模型,其临界点的面积律违反甚至更软。
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引用次数: 0
Branching States as The Emergent Structure of a Quantum Universe 作为量子宇宙新兴结构的分支状态
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1494
Akram Touil, Fabio Anza, Sebastian Deffner, James P. Crutchfield
Quantum Darwinism builds on decoherence theory to explain the emergence of classical behavior in a fundamentally quantum universe. Within this framework we prove two crucial insights about the emergence of classical phenomenology, centered around quantum discord as the measure of quantumness of correlations. First, we show that the so-called branching structure of the joint state of the system and environment is the only one compatible with zero discord. Second, we prove that for small but nonzero discord and for good but not perfect decoherence, the structure of the globally pure state must be arbitrarily close to the branching form, with each branch exhibiting low entanglement. Our results significantly improve on previous bounds and reinforce the existing evidence that this class of branching states is the only one compatible with the emergence of classical phenomenology, as described by Quantum Darwinism.
量子达尔文主义以去相干理论为基础,解释了在一个基本量子宇宙中经典行为的出现。在这一框架内,我们证明了关于经典现象学出现的两个关键见解,其核心是量子不和谐作为相关性量子化的衡量标准。首先,我们证明了系统与环境联合状态的所谓分支结构是唯一与零不和谐兼容的结构。其次,我们证明,对于较小但非零的不和谐以及良好但非完美的退相干,全局纯态的结构必须任意接近分支形式,每个分支都表现出低纠缠。我们的结果大大改进了以前的界限,并强化了现有的证据,即这一类分支状态是唯一与量子达尔文主义所描述的经典现象学的出现相容的状态。
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引用次数: 0
Resource Efficient Boolean Function Solver on Quantum Computer 量子计算机上的资源高效布尔函数求解器
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1500
Xiang Li, Hanxiang Shen, Weiguo Gao, Yingzhou Li
Nonlinear boolean equation systems play an important role in a wide range of applications. Grover's algorithm is one of the best-known quantum search algorithms in solving the nonlinear boolean equation system on quantum computers. In this paper, we propose three novel techniques to improve the efficiency under Grover's algorithm framework. A W-cycle circuit construction introduces a recursive idea to increase the solvable number of boolean equations given a fixed number of qubits. Then, a greedy compression technique is proposed to reduce the oracle circuit depth. Finally, a randomized Grover's algorithm randomly chooses a subset of equations to form a random oracle every iteration, which further reduces the circuit depth and the number of ancilla qubits. Numerical results on boolean quadratic equations demonstrate the efficiency of the proposed techniques.
非线性布尔方程系统在广泛的应用中发挥着重要作用。格罗弗算法是在量子计算机上求解非线性布尔方程系统最著名的量子搜索算法之一。本文提出了三种新技术,以提高 Grover 算法框架下的效率。一种 W 循环电路构造引入了一种递归思想,在给定量子比特数的情况下增加布尔方程的可解数。然后,提出了一种贪婪压缩技术,以降低神谕电路深度。最后,随机格罗弗算法每次迭代都会随机选择一个方程子集来形成随机神谕,从而进一步降低了电路深度和辅助量子比特的数量。布尔二次方程的数值结果证明了所提技术的高效性。
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引用次数: 0
Implementing any Linear Combination of Unitaries on Intermediate-term Quantum Computers 在中期量子计算机上实现任意单元线性组合
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1496
Shantanav Chakraborty
We develop three new methods to implement any Linear Combination of Unitaries (LCU), a powerful quantum algorithmic tool with diverse applications. While the standard LCU procedure requires several ancilla qubits and sophisticated multi-qubit controlled operations, our methods consume significantly fewer quantum resources. The first method ($textit{Single-Ancilla LCU}$) estimates expectation values of observables with respect to any quantum state prepared by an LCU procedure while requiring only a single ancilla qubit, and no multi-qubit controlled operations. The second approach ($textit{Analog LCU}$) is a simple, physically motivated, continuous-time analogue of LCU, tailored to hybrid qubit-qumode systems. The third method ($textit{Ancilla-free LCU}$) requires no ancilla qubit at all and is useful when we are interested in the projection of a quantum state (prepared by the LCU procedure) in some subspace of interest. We apply the first two techniques to develop new quantum algorithms for a wide range of practical problems, ranging from Hamiltonian simulation, ground state preparation and property estimation, and quantum linear systems. Remarkably, despite consuming fewer quantum resources they retain a provable quantum advantage. The third technique allows us to connect discrete and continuous-time quantum walks with their classical counterparts. It also unifies the recently developed optimal quantum spatial search algorithms in both these frameworks, and leads to the development of new ones that require fewer ancilla qubits. Overall, our results are quite generic and can be readily applied to other problems, even beyond those considered here.
我们开发了三种新方法来实现任何单元线性组合(LCU),这是一种具有多种应用的强大量子算法工具。标准的 LCU 程序需要几个安其拉量子比特和复杂的多量子比特控制操作,而我们的方法消耗的量子资源要少得多。第一种方法($textit{Single-Ancilla LCU}$)只需要单个ancilla量子比特,不需要多量子比特控制操作,就能估算出通过LCU程序准备的任何量子态的观测值的期望值。第二种方法($textit{Analog LCU}$)是一种简单的、物理的、连续时间的 LCU 类似方法,是为混合量子比特-量子模型系统量身定制的。第三种方法($textit{无辅助 LCU}$)完全不需要辅助量子比特,当我们对量子态(由 LCU 过程准备)在某些感兴趣的子空间中的投影感兴趣时,这种方法就非常有用。我们应用前两种技术为一系列实际问题开发了新的量子算法,包括哈密顿模拟、基态制备和属性估计以及量子线性系统。值得注意的是,尽管消耗的量子资源较少,但它们仍保持了可证明的量子优势。第三种技术使我们能够将离散和连续时间量子行走与它们的经典对应物联系起来。它还将最近开发的最优量子空间搜索算法与这两种框架统一起来,并开发出需要更少辅助量子比特的新算法。总之,我们的结果非常通用,可以很容易地应用于其他问题,甚至超出本文所考虑的问题。
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引用次数: 0
Iteration Complexity of Variational Quantum Algorithms 变分量子算法的迭代复杂性
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1495
Vyacheslav Kungurtsev, Georgios Korpas, Jakub Marecek, Elton Yechao Zhu
There has been much recent interest in near-term applications of quantum computers, i.e., using quantum circuits that have short decoherence times due to hardware limitations. Variational quantum algorithms (VQA), wherein an optimization algorithm implemented on a classical computer evaluates a parametrized quantum circuit as an objective function, are a leading framework in this space. An enormous breadth of algorithms in this framework have been proposed for solving a range of problems in machine learning, forecasting, applied physics, and combinatorial optimization, among others.

In this paper, we analyze the iteration complexity of VQA, that is, the number of steps that VQA requires until its iterates satisfy a surrogate measure of optimality. We argue that although VQA procedures incorporate algorithms that can, in the idealized case, be modeled as classic procedures in the optimization literature, the particular nature of noise in near-term devices invalidates the claim of applicability of off-the-shelf analyses of these algorithms. Specifically, noise makes the evaluations of the objective function via quantum circuits $biased$. Commonly used optimization procedures, such as SPSA and the parameter shift rule, can thus be seen as derivative-free optimization algorithms with biased function evaluations, for which there are currently no iteration complexity guarantees in the literature. We derive the missing guarantees and find that the rate of convergence is unaffected. However, the level of bias contributes unfavorably to both the constant therein, and the asymptotic distance to stationarity, i.e., the more bias, the farther one is guaranteed, at best, to reach a stationary point of the VQA objective.
最近,人们对量子计算机的近期应用产生了浓厚兴趣,即使用因硬件限制而退相干时间较短的量子电路。变分量子算法(VQA)是这一领域的领先框架,它是在经典计算机上实施的优化算法,将参数化的量子电路作为目标函数进行评估。在这一框架下提出了大量算法,用于解决机器学习、预测、应用物理和组合优化等领域的一系列问题。在本文中,我们分析了 VQA 的迭代复杂度,即 VQA 在其迭代结果满足最优性的替代度量之前所需的步骤数。我们认为,虽然 VQA 程序包含的算法在理想化情况下可以作为优化文献中的经典程序建模,但近端设备中噪声的特殊性质使这些算法的现成分析的适用性失效。具体来说,噪声使得通过量子电路对目标函数的评估变得有失偏颇。因此,常用的优化程序,如 SPSA 和参数移动规则,可被视为具有偏差函数评估的无导数优化算法,目前文献中还没有迭代复杂度的保证。我们推导出了缺失的保证,并发现收敛速度不受影响。然而,偏差水平会对其中的常数和到静止点的渐近距离产生不利影响,也就是说,偏差越大,最多只能保证到达 VQA 目标静止点的距离越远。
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引用次数: 0
Decoding algorithms for surface codes 面码的解码算法
IF 6.4 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Pub Date : 2024-10-10 DOI: 10.22331/q-2024-10-10-1498
Antonio deMarti iOlius, Patricio Fuentes, Román Orús, Pedro M. Crespo, Josu Etxezarreta Martinez
Quantum technologies have the potential to solve certain computationally hard problems with polynomial or super-polynomial speedups when compared to classical methods. Unfortunately, the unstable nature of quantum information makes it prone to errors. For this reason, quantum error correction is an invaluable tool to make quantum information reliable and enable the ultimate goal of fault-tolerant quantum computing. Surface codes currently stand as the most promising candidates to build near term error corrected qubits given their two-dimensional architecture, the requirement of only local operations, and high tolerance to quantum noise. Decoding algorithms are an integral component of any error correction scheme, as they are tasked with producing accurate estimates of the errors that affect quantum information, so that they can subsequently be corrected. A critical aspect of decoding algorithms is their speed, since the quantum state will suffer additional errors with the passage of time. This poses a connundrum, where decoding performance is improved at the expense of complexity and viceversa. In this review, a thorough discussion of state-of-the-art decoding algorithms for surface codes is provided. The target audience of this work are both readers with an introductory understanding of the field as well as those seeking to further their knowledge of the decoding paradigm of surface codes. We describe the core principles of these decoding methods as well as existing variants that show promise for improved results. In addition, both the decoding performance, in terms of error correction capability, and decoding complexity, are compared. A review of the existing software tools regarding surface codes decoding is also provided.
与经典方法相比,量子技术有可能以多项式或超多项式的速度解决某些难以计算的问题。遗憾的是,量子信息的不稳定性使其容易出错。因此,量子纠错是使量子信息可靠并实现容错量子计算这一终极目标的宝贵工具。鉴于表面代码的二维架构、只需局部操作的要求以及对量子噪声的高容错性,表面代码目前是最有希望构建近期纠错量子比特的候选方案。解码算法是任何纠错方案不可或缺的组成部分,因为它们的任务是对影响量子信息的误差做出准确估计,以便随后对其进行纠正。解码算法的一个关键方面是速度,因为随着时间的推移,量子态会出现更多错误。这就带来了一个难题,即提高解码性能需要牺牲复杂性,反之亦然。在这篇综述中,将对最先进的表面编码解码算法进行深入讨论。本著作的目标读者既包括对该领域有入门了解的读者,也包括希望进一步了解表面码解码范例的读者。我们介绍了这些解码方法的核心原理,以及有望改进结果的现有变体。此外,我们还比较了纠错能力和解码复杂度方面的解码性能。我们还对现有的表面编码解码软件工具进行了评述。
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引用次数: 0
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