Harnessing CUDA-Q's MPS for Tensor Network Simulations of Large-Scale Quantum Circuits

• URL: http://arxiv.org/abs/2501.15939v1
• Date: Mon, 27 Jan 2025 10:36:05 GMT
• Title: Harnessing CUDA-Q's MPS for Tensor Network Simulations of Large-Scale Quantum Circuits
• Authors: Gabin Schieffer, Stefano Markidis, Ivy Peng,
• Abstract summary: Current largest quantum computers feature more than one thousand qubits. A more appealing approach for simulating quantum computers is adopting the network approach. We show that network-based methods provide a significant opportunity to simulate large-qubit circuits.
• Score: 0.0
• License:
• Abstract: Quantum computer simulators are an indispensable tool for prototyping quantum algorithms and verifying the functioning of existing quantum computer hardware. The current largest quantum computers feature more than one thousand qubits, challenging their classical simulators. State-vector quantum simulators are challenged by the exponential increase of representable quantum states with respect to the number of qubits, making more than fifty qubits practically unfeasible. A more appealing approach for simulating quantum computers is adopting the tensor network approach, whose memory requirements fundamentally depend on the level of entanglement in the quantum circuit, and allows simulating the current largest quantum computers. This work investigates and evaluates the CUDA-Q tensor network simulators on an Nvidia Grace Hopper system, particularly the Matrix Product State (MPS) formulation. We compare the performance of the CUDA-Q state vector implementation and validate the correctness of MPS simulations. Our results highlight that tensor network-based methods provide a significant opportunity to simulate large-qubit circuits, albeit approximately. We also show that current GPU-accelerated computation cannot fully utilize GPU efficiently in the case of MPS simulations.

Related papers

• SeQUeNCe GUI: An Extensible User Interface for Discrete Event Quantum Network Simulations [55.2480439325792]
  SeQUeNCe is an open source simulator of quantum network communication. We implement a graphical user interface which maintains the core principles of SeQUeNCe.
  arXiv  Detail & Related papers  (2025-01-15T19:36:09Z)
• Optimising Iteration Scheduling for Full-State Vector Simulation of Quantum Circuits on FPGAs [1.221089353510972]
  We present a memory access pattern to optimise the number of iterations that need to be scheduled to execute a quantum gate. We show that this approach results in a significant reduction in the time required to simulate a gate for each added control qubit.
  arXiv  Detail & Related papers  (2024-11-27T13:57:29Z)
• Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
  Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties? We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d. We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
  arXiv  Detail & Related papers  (2024-08-22T08:21:28Z)
• State of practice: evaluating GPU performance of state vector and tensor network methods [2.4851820343103035]
  This article investigates the limits of current state-of-the-art simulation techniques on a test bench made of eight widely used quantum subroutines. We highlight how to select the best simulation strategy, obtaining a speedup of up to an order of magnitude.
  arXiv  Detail & Related papers  (2024-01-11T09:22:21Z)
• QuDiet: A Classical Simulation Platform for Qubit-Qudit Hybrid Quantum Systems [7.416447177941264]
  textbfQuDiet is a python-based higher-dimensional quantum computing simulator. textbfQuDiet offers multi-valued logic operations by utilizing generalized quantum gates. textbfQuDiet provides a full qubit-qudit hybrid quantum simulator package.
  arXiv  Detail & Related papers  (2022-11-15T06:07:04Z)
• A Reorder Trick for Decision Diagram Based Quantum Circuit Simulation [0.4358626952482686]
  We study two classes of quantum circuits on which the state-of-the-art decision diagram based simulators failed to perform well in terms of simulation time. We propose a simple and powerful reorder trick to boost the simulation of such quantum circuits.
  arXiv  Detail & Related papers  (2022-11-14T04:55:25Z)
• Recompilation-enhanced simulation of electron-phonon dynamics on IBM Quantum computers [62.997667081978825]
  We consider the absolute resource cost for gate-based quantum simulation of small electron-phonon systems. We perform experiments on IBM quantum hardware for both weak and strong electron-phonon coupling. Despite significant device noise, through the use of approximate circuit recompilation we obtain electron-phonon dynamics on current quantum computers comparable to exact diagonalisation.
  arXiv  Detail & Related papers  (2022-02-16T19:00:00Z)
• Parallel Simulation of Quantum Networks with Distributed Quantum State Management [56.24769206561207]
  We identify requirements for parallel simulation of quantum networks and develop the first parallel discrete event quantum network simulator. Our contributions include the design and development of a quantum state manager that maintains shared quantum information distributed across multiple processes. We release the parallel SeQUeNCe simulator as an open-source tool alongside the existing sequential version.
  arXiv  Detail & Related papers  (2021-11-06T16:51:17Z)
• An Algebraic Quantum Circuit Compression Algorithm for Hamiltonian Simulation [55.41644538483948]
  Current generation noisy intermediate-scale quantum (NISQ) computers are severely limited in chip size and error rates. We derive localized circuit transformations to efficiently compress quantum circuits for simulation of certain spin Hamiltonians known as free fermions. The proposed numerical circuit compression algorithm behaves backward stable and scales cubically in the number of spins enabling circuit synthesis beyond $mathcalO(103)$ spins.
  arXiv  Detail & Related papers  (2021-08-06T19:38:03Z)
• Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale [57.84751206630535]
  We present a modernized version of the Quantum Virtual Machine (TNQVM) which serves as a quantum circuit simulation backend in the e-scale ACCelerator (XACC) framework. The new version is based on the general purpose, scalable network processing library, ExaTN, and provides multiple quantum circuit simulators. By combining the portable XACC quantum processors and the scalable ExaTN backend we introduce an end-to-end virtual development environment which can scale from laptops to future exascale platforms.
  arXiv  Detail & Related papers  (2021-04-21T13:26:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.