Quantum digital twins based on hardware-tailored tensor networks for computing quantum dynamics

基于硬件定制张量网络的量子数字孪生，用于计算量子动力学

• 批准号: EP/Y005007/1
• 负责人: Oleksandr Kyriienko
• 金额: $ 38.78万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY005007%2F1
• 关键词: Quantum; digital; twins; based; hardware

Quantum computing offers a promise to solve problems that cannot be addressed by classical devices, and an early access to quantum computers is vital for UK national security. The ability to solve complex problems with quantum computers relies on optimising both the hardware (quantum devices) and the software (quantum algorithms). In this project, we will design the tools for improving the quantum software, which can largely save required resources for state preparation and simulation of dynamics. We call these tools the quantum digital twins - specific programmable models that help representing quantum devices in the most efficient way, and thus enabling their optimisation.Quantum computing (QC) offers a distinct paradigm for performing calculations. Unlike classical computers that operate with bits (taking binary values 0 or 1), quantum devices rely on two-level quantum systems - qubits - that are described by states |0> and |1> that can be put in a superposition. The collection of N qubits can be efficiently evolved on specialised hardware - quantum computers - thus processing information encoded in a quantum form. Classical processing of the same amount of information will require manipulating 2^N complex numbers, a task that becomes impossible already at the size of fifty qubits. We know that in the future quantum computing can exponentially speed up factoring (having a huge impact on cryptography) and help with areas such as simulating materials and chemicals at a scale impossible before (promoting substantial steps towards green energy and sustainability).Quantum hardware is developed by various industrial and academic institutions worldwide. Qubit counts grow every year, and this makes community hopeful for achieving a practical quantum advantage in the near term. Yet, the current level of noise does not allow for running circuits of sufficient depth. Specifically designed quantum software may help to alleviate this problem if tailored algorithms are developed. This challenge calls for imaginative approaches that account for hardware capabilities and limitations.To harness benefits from near-term quantum computing, UK needs to channel an effort on developing software tools that enable the scalable prototyping of quantum algorithms and allow for benchmarking quantum devices at the increased scale. We propose to do this by designing quantum digital twins as efficient tensor network emulators of quantum devices.This project is the collaboration between quantum researchers at the University of Exeter and the National Physical Laboratory. It is built on the three pillars, each representing an open challenge for advancing quantum software and applications: 1) developing efficient tools for quantum state preparation and quantum circuit emulation; 2) developing quantum digital twins of the dynamics; 3) benchmarking quantum algorithms for solving computationally-hard problems in material science.To tackle these challenges we will address three objectives:1. We will develop compact tensor network representations for low energy states of relevant quantum Hamiltonians, and translate these tensor networks into low-depth quantum circuits for efficient initial quantum state preparation.2. We will develop scalable tensor network-based emulators of quantum dynamics as quantum digital twins, taking advantage of the knowledge of the hardware-specific Hamiltonians.3. We will benchmark the scalability of quantum digital twins for emulating quantum devices in materials simulations, and determine the threshold for potential quantum advantage.As a result of the project, we will have the efficient tools that enable the scalable prototyping and improving of quantum simulation, thus maximizing the performance of quantum computers at increasing scale.

量子计算为解决经典设备无法解决的问题提供了希望，及早访问量子计算机对英国国家安全至关重要。用量子计算机解决复杂问题的能力依赖于硬件(量子设备)和软件(量子算法)的优化。在这个项目中，我们将设计改进量子软件的工具，这样可以极大地节省状态准备和动力学模拟所需的资源。我们称这些工具为量子数字双胞胎特定的可编程模型，有助于以最有效的方式表示量子设备，从而使它们能够进行优化。量子计算(QC)提供了一种执行计算的独特范式。与比特运算的经典计算机不同(取二进制值0或1)，量子设备依赖于二能级量子系统--量子比特--它们由可以叠加在一起的态|0和|1&gt；来描述。N个量子比特的集合可以在专门的硬件-量子计算机-上高效地进化，从而处理以量子形式编码的信息。传统的处理相同数量的信息将需要处理2^N个复数，这项任务在50个量子比特的大小下已经变得不可能完成。我们知道，在未来，量子计算可以指数级地加速因式分解(对密码学产生巨大影响)，并在模拟材料和化学品等领域提供帮助，规模达到以前不可能的水平(推动朝着绿色能源和可持续发展迈出实质性步伐)。量子硬件由世界各地的各种工业和学术机构开发。量子比特数每年都在增长，这使得社区对在短期内实现实际的量子优势抱有希望。然而，目前的噪声水平不允许运行足够深度的电路。如果开发出量身定制的算法，专门设计的量子软件可能有助于缓解这一问题。这一挑战要求考虑到硬件能力和限制的富有想象力的方法。为了利用近期量子计算的好处，英国需要致力于开发软件工具，使量子算法能够进行可扩展的原型制作，并允许在更大的规模上对量子设备进行基准测试。我们建议通过设计量子数字孪生来作为量子设备的有效张量网络仿真器来实现这一点。这个项目是埃克塞特大学和国家物理实验室的量子研究人员的合作项目。它建立在三个支柱之上，每个支柱都代表着发展量子软件和应用的开放挑战：1)开发用于量子态准备和量子电路仿真的有效工具；2)开发动力学的量子数字孪生；3)基准量子算法以解决材料科学中计算困难的问题。为了解决这些挑战，我们将解决三个目标：1.我们将开发相关量子哈密顿算符的低能态的紧凑张量网络表示，并将这些张量网络转换为低深度量子电路，用于有效的初始量子态准备。我们将利用硬件特定哈密顿的知识，开发可扩展的基于张量网络的量子动力学仿真器作为量子数字孪生。我们将对量子数字孪生在材料模拟中模拟量子器件的可扩展性进行基准测试，并确定潜在量子优势的门槛。作为该项目的结果，我们将拥有高效的工具，使量子模拟的可扩展原型和改进成为可能，从而在不断扩大的规模中最大化量子计算机的性能。