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.

量子计算提供了解决经典设备无法解决的问题的承诺，而早期访问量子计算机对于英国国家安全至关重要。解决量子计算机解决复杂问题的能力依赖于优化硬件（量子设备）和软件（量子算法）。在这个项目中，我们将设计用于改进量子软件的工具，该工具可以在很大程度上节省所需的资源来进行状态准备和模拟动态。我们将这些工具称为量子数字双胞胎 - 特定的可编程模型，以最有效的方式帮助代表量子设备，从而启用其优化。QuantumComputing（QC）为执行计算提供了独特的范式。与用位运行的古典计算机（取二进制值0或1）不同，量子设备依赖于两级量子系统 - 量子量 - 量子 - 量子| 0> and | 1>可以将其放置在叠加中。可以在专用硬件 - 量子计算机上有效地进化N量子位的收集，从而以量子形式编码的处理信息。相同数量信息的经典处理将需要操纵2^n的复数，这一任务已经在五十吨的大小上变得不可能。我们知道，在将来，量子计算可以成倍地加速保理（对密码学产生巨大影响），并有助于诸如以前不可能的规模模拟材料和化学物质等领域（促进了绿色能源和可持续性的实质性步骤）。Quantum硬件是由全球各种工业和学术机构开发的。 Qubit计数每年都在增长，这使得社区希望在短期内实现实用的量子优势。但是，当前的噪声水平不允许运行足够深度的电路。如果开发了量身定制的算法，专门设计的量子软件可能有助于减轻此问题。这项挑战要求采用富有想象力的方法来解释硬件功能和局限性。要利用近期量子计算受益，英国需要引导一项努力开发软件工具，以使量子算法的可扩展原型制作，并允许以增加规模的量子设备进行基准测试。我们建议通过将Quantum Digital Twins设计为量子设备的有效张量网络模拟器来做到这一点。该项目是埃克塞特大学的量子研究人员与国家物理实验室的量子研究人员之间的合作。它建立在三个支柱上，每个支柱都代表着推进量子软件和应用的开放挑战：1）开发有效的量子状态准备和量子电路仿真的工具； 2）开发动力学的量子数字双胞胎； 3）基准测试量子算法，用于解决材料科学中的计算困难问题。为了应对这些挑战，我们将解决三个目标：1。我们将为相关量子哈密顿量的低能状态开发紧凑的张量网络表示，并将这些张量网络转换为低深度量子电路，以进行有效的初始量子态制备。2。我们将利用特定于硬件特定的汉密尔顿的知识来开发可扩展的量子网络量子动态模拟器作为量子数字双胞胎。3。我们将基准在材料模拟中模拟量子设备的量子数字双胞胎的可伸缩性，并确定潜在量子优势的阈值。由于项目的结果，我们将拥有有效的工具，可实现可扩展的原型制作和量子模拟的改进，从而最大程度地提高量子计算机的性能，从而最大程度地提高量子计算机的性能。