Comparing resource requirements of noisy quantum simulation algorithms for the Tavis-Cummings model

• URL: http://arxiv.org/abs/2402.16692v1
• Date: Mon, 26 Feb 2024 16:06:24 GMT
• Title: Comparing resource requirements of noisy quantum simulation algorithms for the Tavis-Cummings model
• Authors: Alisa Haukisalmi, Matti Raasakka, Ilkka Tittonen
• Abstract summary: Fault-tolerant quantum computers could facilitate the simulation of quantum systems unfeasible for classical computation. These include quantum error mitigation (QEM) for alleviating device noise, and variational quantum algorithms (VQAs) which combine classical optimization with short-depth, parameterized quantum circuits. We compare two such methods: zero-noise extrapolation (ZNE) with noise amplification by circuit folding, and incremental structural learning (ISL) We find that while ISL achieves lower error than ZNE for smaller system sizes, it fails to produce correct dynamics for 4 qubits, where ZNE is superior.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Fault-tolerant quantum computers could facilitate the simulation of quantum systems unfeasible for classical computation. However, the noisy intermediate-scale quantum (NISQ) devices of the present and near term are limited and their utilisation requires additional strategies. These include quantum error mitigation (QEM) for alleviating device noise, and variational quantum algorithms (VQAs) which combine classical optimization with short-depth, parameterized quantum circuits. We compare two such methods: zero-noise extrapolation (ZNE) with noise amplification by circuit folding, and incremental structural learning (ISL), a type of circuit recompiling VQA. These are applied to Trotterized time-evolution of the Tavis--Cummings model (TCM) under a noise simulation. Since both methods add circuit evaluation overhead, it is of interest to see how they compare both in the accuracy of the dynamics they produce, and in terms of the quantum resources used. Additionally, noisy recompilation of time-evolution circuits with ISL has not previously been explored. We find that while ISL achieves lower error than ZNE for smaller system sizes, it fails to produce correct dynamics for 4 qubits, where ZNE is superior. Diverging resource requirements for ISL and ZNE are observed, with ISL achieving low circuit depths at the cost of a large number of circuit evaluations.

Related papers

• Subspace-Based Local Compilation of Variational Quantum Circuits for Large-Scale Quantum Many-Body Simulation [0.0]
  This paper proposes a hybrid quantum-classical algorithm for compiling the time-evolution operator. It achieves a 95% reduction in circuit depth compared to Trotterization while maintaining accuracy. We estimate the gate count needed to execute the quantum simulations using the LSVQC on near-term quantum computing architectures.
  arXiv  Detail & Related papers  (2024-07-19T09:50:01Z)
• Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
  We develop a reinforcement learning-based quantum compiler for a superconducting processor. We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths. Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
  arXiv  Detail & Related papers  (2024-06-18T01:49:48Z)
• Compressed-sensing Lindbladian quantum tomography with trapped ions [44.99833362998488]
  Characterizing the dynamics of quantum systems is a central task for the development of quantum information processors. We propose two different improvements of Lindbladian quantum tomography (LQT) that alleviate previous shortcomings.
  arXiv  Detail & Related papers  (2024-03-12T09:58:37Z)
• Towards Efficient Quantum Computing for Quantum Chemistry: Reducing Circuit Complexity with Transcorrelated and Adaptive Ansatz Techniques [0.0]
  This work demonstrates how to reduce circuit depth by combining the transcorrelated (TC) approach with adaptive quantum ans"atze. Our study demonstrates that combining the TC method with adaptive ans"atze yields compact, noise-resilient, and easy-to-optimize quantum circuits.
  arXiv  Detail & Related papers  (2024-02-26T15:31:56Z)
• QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits [82.50620782471485]
  QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits. It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness. Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
  arXiv  Detail & Related papers  (2024-01-10T22:33:00Z)
• Classical simulations of noisy variational quantum circuits [0.0]
  Noisely affects quantum computations so that they not only become less accurate but also easier to simulate classically as systems scale up. We construct a classical simulation algorithm, LOWESA, for estimating expectation values of noisy parameterised quantum circuits.
  arXiv  Detail & Related papers  (2023-06-08T17:52:30Z)
• Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Coding [44.89303833148191]
  We develop a depth-controllable architecture of entangled slimmable quantum neural networks (eSQNNs) We propose an entangled slimmable QFL (eSQFL) that communicates the superposition-coded parameters of eS-QNNs. In an image classification task, extensive simulations corroborate the effectiveness of eSQFL.
  arXiv  Detail & Related papers  (2022-12-04T03:18:03Z)
• Error Mitigation-Aided Optimization of Parameterized Quantum Circuits: Convergence Analysis [42.275148861039895]
  Variational quantum algorithms (VQAs) offer the most promising path to obtaining quantum advantages via noisy processors. gate noise due to imperfections and decoherence affects the gradient estimates by introducing a bias. Quantum error mitigation (QEM) techniques can reduce the estimation bias without requiring any increase in the number of qubits. QEM can reduce the number of required iterations, but only as long as the quantum noise level is sufficiently small.
  arXiv  Detail & Related papers  (2022-09-23T10:48:04Z)
• Robust resource-efficient quantum variational ansatz through evolutionary algorithm [0.46180371154032895]
  Vari quantum algorithms (VQAsational) are promising methods to demonstrate quantum advantage on near-term devices. We show that a fixed VQA circuit design, such as the widely-used hardware efficient ansatz, is not necessarily robust against imperfections. We propose a genome-length-adjustable evolutionary algorithm to design a robust VQA circuit that is optimized over variations of both circuit ansatz and gate parameters.
  arXiv  Detail & Related papers  (2022-02-28T12:14:11Z)
• Simulating the Mott transition on a noisy digital quantum computer via Cartan-based fast-forwarding circuits [62.73367618671969]
  Dynamical mean-field theory (DMFT) maps the local Green's function of the Hubbard model to that of the Anderson impurity model. Quantum and hybrid quantum-classical algorithms have been proposed to efficiently solve impurity models. This work presents the first computation of the Mott phase transition using noisy digital quantum hardware.
  arXiv  Detail & Related papers  (2021-12-10T17:32:15Z)

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.