Efficient and precise quantum simulation of ultra-relativistic quark-nucleus scattering

• URL: http://arxiv.org/abs/2404.00819v3
• Date: Mon, 23 Sep 2024 20:40:32 GMT
• Title: Efficient and precise quantum simulation of ultra-relativistic quark-nucleus scattering
• Authors: Sihao Wu, Weijie Du, Xingbo Zhao, James P. Vary,
• Abstract summary: We present an efficient and precise framework to simulate the dynamics of the quark-nucleus scattering. Our framework can be generalized to simulate the dynamics of various scattering problems in quantumdynamics.
• Score: 0.35998666903987897
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present an efficient and precise framework to quantum simulate the dynamics of the ultra-relativistic quark-nucleus scattering. This framework employs the eigenbasis of the asymptotic scattering system and implements a compact scheme for encoding this basis upon lattice discretization. It exploits the operator structure of the light-front Hamiltonian of the scattering system, which enables the Hamiltonian input that utilizes the quantum Fourier transform for efficiency. Our framework simulates the scattering by the efficient and precise algorithm of the truncated Taylor series. The qubit cost of our framework scales logarithmically with the Hilbert space dimension of the scattering system. The gate cost has optimal scaling with the simulation error and near optimal scaling with the simulation time. These scalings make our framework advantageous for large-scale dynamics simulations on future fault-tolerant quantum computers. We demonstrate our framework with a simple scattering problem and benchmark the results with those from the Trotter algorithm and the classical calculations, where good agreement between the results is found. Our framework can be generalized to simulate the dynamics of various scattering problems in quantum chromodynamics.

Related papers

• Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation [55.88862563823878]
  In this work, we present an original algorithm to coarsen an unstructured grid based on the concepts of differentiable physics.<n>We demonstrate performance of the algorithm on two PDEs: a linear equation which governs slightly compressible fluid flow in porous media and the wave equation.<n>Our results show that in the considered scenarios, we reduced the number of grid points up to 10 times while preserving the modeled variable dynamics in the points of interest.
  arXiv  Detail & Related papers  (2025-07-24T11:02:13Z)
• Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer [0.4593579891394288]
  The Sachdev-Ye-Kitaev (SYK) model describes a strongly correlated quantum system that shows a strong signature of quantum chaos.<n>Quantum simulations of the SYK model on noisy quantum processors are severely limited by the complexity of its Hamiltonian.<n>We simulate the real-time dynamics of a sparsified version of the SYK model with 24 Majorana fermions on a trapped-ion quantum processor.
  arXiv  Detail & Related papers  (2025-07-10T08:26:08Z)
• Tighter Error Bounds for the qDRIFT Algorithm [0.0]
  We refine the qDRIFT error bound by incorporating Jensen's inequality and a careful treatment of the integral form of the error.<n>This yields an improved scaling that significantly reduces the number of steps required to reach a fixed simulation accuracy.<n>To demonstrate the practical impact of this refinement, we apply it to three settings: quantum chemistry simulations, dissipative transverse field Ising models, and Hamiltonian encoding of classical data for quantum machine learning.
  arXiv  Detail & Related papers  (2025-06-20T17:49:58Z)
• Towards robust variational quantum simulation of Lindblad dynamics via stochastic Magnus expansion [10.144001671935907]
  We introduce a novel and general framework for the variational quantum simulation of Lindblad equations. We demonstrate the effectiveness of our algorithm through numerical examples.
  arXiv  Detail & Related papers  (2025-03-28T02:37:56Z)
• Truncated Gaussian basis approach for simulating many-body dynamics [0.0]
  The approach constructs an effective Hamiltonian within a reduced subspace, spanned by fermionic Gaussian states, and diagonalizes it to obtain approximate eigenstates and eigenenergies. Symmetries can be exploited to perform parallel computation, enabling to simulate systems with much larger sizes. For quench dynamics we observe that time-evolving wave functions in the truncated subspace facilitates the simulation of long-time dynamics.
  arXiv  Detail & Related papers  (2024-10-05T15:47:01Z)
• Real-time Dynamics of the Schwinger Model as an Open Quantum System with Neural Density Operators [1.0713888959520208]
  This work develops machine learning algorithms to overcome the difficulty of approximating exact quantum states with neural network parametrisations. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1+1d lattice Schwinger Model as an open quantum system.
  arXiv  Detail & Related papers  (2024-02-09T18:36:17Z)
• Spectral chaos bounds from scaling theory of maximally efficient quantum-dynamical scrambling [44.99833362998488]
  A key conjecture about the evolution of complex quantum systems towards an ergodic steady state, known as scrambling, is that this process acquires universal features when it is most efficient. We develop a single- parameter scaling theory for the spectral statistics in this scenario, which embodies exact self-similarity of the spectral correlations along the complete scrambling dynamics. We establish that scaling predictions are matched by a privileged process and serve as bounds for other dynamical scrambling scenarios, allowing one to quantify inefficient or incomplete scrambling on all time scales.
  arXiv  Detail & Related papers  (2023-10-17T15:41:50Z)
• A hybrid quantum-classical algorithm for multichannel quantum scattering of atoms and molecules [62.997667081978825]
  We propose a hybrid quantum-classical algorithm for solving the Schr"odinger equation for atomic and molecular collisions. The algorithm is based on the $S$-matrix version of the Kohn variational principle, which computes the fundamental scattering $S$-matrix. We show how the algorithm could be scaled up to simulate collisions of large polyatomic molecules.
  arXiv  Detail & Related papers  (2023-04-12T18:10:47Z)
• Simulations of quantum dynamics with fermionic phase-space representations using numerical matrix factorizations as stochastic gauges [0.0]
  We explore the use of dynamical diffusion gauges in quantum dynamics simulations. For the physical systems with fermionic particles considered here, the numerical evaluation of the new diffusion gauges allows us to double the practical simulation time. This development may have far reaching consequences for future quantum dynamical simulations of many-body systems.
  arXiv  Detail & Related papers  (2023-04-11T11:33:55Z)
• Capturing dynamical correlations using implicit neural representations [85.66456606776552]
  We develop an artificial intelligence framework which combines a neural network trained to mimic simulated data from a model Hamiltonian with automatic differentiation to recover unknown parameters from experimental data. In doing so, we illustrate the ability to build and train a differentiable model only once, which then can be applied in real-time to multi-dimensional scattering data.
  arXiv  Detail & Related papers  (2023-04-08T07:55:36Z)
• Importance sampling for stochastic quantum simulations [68.8204255655161]
  We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients. We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage. Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
  arXiv  Detail & Related papers  (2022-12-12T15:06:32Z)
• Hybrid Physical-Neural ODEs for Fast N-body Simulations [0.22419496088582863]
  We present a new scheme to compensate for the small-scales approximations resulting from Particle-Mesh schemes for cosmological N-body simulations. We find that our approach outperforms PGD for the cross-correlation coefficients, and is more robust to changes in simulation settings.
  arXiv  Detail & Related papers  (2022-07-12T13:06:06Z)
• Quantum algorithms for quantum dynamics: A performance study on the spin-boson model [68.8204255655161]
  Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
  arXiv  Detail & Related papers  (2021-08-09T18:00:05Z)
• Fixed Depth Hamiltonian Simulation via Cartan Decomposition [59.20417091220753]
  We present a constructive algorithm for generating quantum circuits with time-independent depth. We highlight our algorithm for special classes of models, including Anderson localization in one dimensional transverse field XY model. In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.
  arXiv  Detail & Related papers  (2021-04-01T19:06:00Z)
• Continuous-time dynamics and error scaling of noisy highly-entangling quantum circuits [58.720142291102135]
  We simulate a noisy quantum Fourier transform processor with up to 21 qubits. We take into account microscopic dissipative processes rather than relying on digital error models. We show that depending on the dissipative mechanisms at play, the choice of input state has a strong impact on the performance of the quantum algorithm.
  arXiv  Detail & Related papers  (2021-02-08T14:55:44Z)

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.