Advancing quantum simulations of nuclear shell model with noise-resilient protocols
arXiv:2504.11689 · doi:10.1103/bbkf-fjxj
Abstract
Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei, is one such case with high demand for resources as the size of the Hilbert space grows exponentially with the number of particles involved. Quantum algorithms are being developed to overcome these challenges and advance such calculations. To develop quantum circuits for the nuclear shell-model, leveraging the capabilities of noisy intermediate-scale quantum (NISQ) devices. We aim to minimize resource requirements (specifically in terms of qubits and gates) and strive to reduce the impact of noise by employing relevant mitigation techniques. We achieve noise resilience by designing an optimized ansatz for the variational quantum eigensolver (VQE) based on Givens rotations and incorporating qubit-ADAPT-VQE in combination with variational quantum deflation (VQD) to compute ground and excited states incorporating the zero-noise extrapolation mitigation technique. Furthermore, the qubit requirements are significantly reduced by mapping the basis states to qubits using Gray code encoding and generalizing transformations of fermionic operators to efficiently represent manybody states. By employing the noise-resilient protocols, we achieve the ground and excited state energy levels of 38Ar and 6Li with better accuracy. These energy levels are presented for noiseless simulations, noisy conditions, and after applying noise mitigation techniques. Results are compared for Jordan Wigner and Gray code encoding using VQE, qubit-ADAPT-VQE, and VQD. Our work highlights the potential of noise-resilient protocols to leverage the full potential of NISQ devices in scaling the nuclear shell model calculations.
21 pages
References in corpus (29)
- A variational eigenvalue solver on a quantum processor
- Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
- The Shell Model as Unified View of Nuclear Structure
- An adaptive variational algorithm for exact molecular simulations on a quantum computer
- Efficient variational quantum simulator incorporating active error minimisation
- The Bravyi-Kitaev transformation for quantum computation of electronic structure
- Variational Quantum Computation of Excited States
- Evolution of shell structure in exotic nuclei
- qubit-ADAPT-VQE: An adaptive algorithm for constructing hardware-efficient ansatze on a quantum processor
- Cloud Quantum Computing of an Atomic Nucleus
- Non-Empirical Interactions for the Nuclear Shell Model: An Update
- Exploiting symmetry in variational quantum machine learning
- Resource-efficient digital quantum simulation of -level systems for photonic, vibrational, and spin- Hamiltonians
- A Lie Algebraic Theory of Barren Plateaus for Deep Parameterized Quantum Circuits
- Linear Response on a Quantum Computer
- Quantum Computing for Neutrino-nucleus Scattering
- Improving Hamiltonian encodings with the Gray code
- Quantum computing of the Li nucleus via ordered unitary coupled clusters
- Variational approaches to constructing the many-body nuclear ground state for quantum computing
- Solving Nuclear Structure Problems with the Adaptive Variational Quantum Algorithm
- Preparation of excited states for nuclear dynamics on a quantum computer
- Symmetry assisted preparation of entangled many-body states on a quantum computer
- Calculating transition amplitudes by variational quantum deflation
- Nuclear shell-model simulation in digital quantum computers
- Symmetry breaking/symmetry preserving circuits and symmetry restoration on quantum computers: A quantum many-body perspective
- Prediction of the neutron drip line in oxygen isotopes using quantum computation
- Finite-size criticality in fully connected spin models on superconducting quantum hardware
- Quantum computation of nuclear observables involving linear combination of unitary operators
- Hybrid Ground-State Quantum Algorithms based on Neural Schrödinger Forging