Fermionic Simulators for Enhanced Scalability of Variational Quantum Simulation

Abstract

Near-term quantum simulators are mostly based on qubit-based architectures. However, their imperfect nature significantly limits their practical application. The situation is even worse for simulating fermionic systems, which underlie most of material science and chemistry, as one has to adopt fermion-to-qubit encodings which create significant additional resource overhead and trainability issues. Thanks to recent advances in trapping and manipulation of neutral atoms in optical tweezers, digital fermionic quantum simulators are becoming viable. A key question is whether these emerging fermionic simulators can outperform qubit-based simulators for characterizing strongly correlated electronic systems. Here, we perform a comprehensive comparison of resource efficiency between qubit and fermionic simulators for variational ground-state emulation of fermionic systems in both condensed matter systems and quantum chemistry problems. We show that the fermionic simulators indeed outperform their qubit counterparts with respect to resources for quantum evolution (circuit depth), as well as classical optimization (number of required parameters and iterations). In addition, they show less sensitivity to the random initialization of the circuit. The relative advantage of fermionic simulators becomes even more pronounced as interaction becomes stronger, or tunneling is allowed in more than one dimension, as well as for spinful fermions. Importantly, this improvement is scalable, i.e., the performance gap between fermionic and qubit simulators only grows for bigger system sizes.

arXiv commentAccepted in Physical Review Research, 13 pages, 8 Figures, Close to published version

References in corpus (80)

• Quantum Computing in the NISQ era and beyond
• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• A variational eigenvalue solver on a quantum processor
• Variational Quantum Algorithms
• Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
• Quantum Simulation
• Quantum computational advantage using photons
• Barren plateaus in quantum neural network training landscapes
• Noisy intermediate-scale quantum (NISQ) algorithms
• Quantum Chemistry in the Age of Quantum Computing
• Integrated Photonic Quantum Technologies
• Error mitigation for short-depth quantum circuits
• Strong quantum computational advantage using a superconducting quantum processor
• Many-Body Physics with Individually-Controlled Rydberg Atoms
• An Open-System Quantum Simulator with Trapped Ions
• Cost Function Dependent Barren Plateaus in Shallow Parametrized Quantum Circuits
• The Variational Quantum Eigensolver: a review of methods and best practices
• An adaptive variational algorithm for exact molecular simulations on a quantum computer
• Fermionic quantum computation
• A Rydberg Quantum Simulator
• Programmable Quantum Simulations of Spin Systems with Trapped Ions
• Quantum algorithms for quantum chemistry and quantum materials science
• Realizing quantum Ising models in tunable two-dimensional arrays of single Rydberg atoms
• Programmable quantum simulation of 2D antiferromagnets with hundreds of Rydberg atoms
• Hartree-Fock on a superconducting qubit quantum computer
• Generation and manipulation of Schrödinger cat states in Rydberg atom arrays
• Parallel implementation of high-fidelity multi-qubit gates with neutral atoms
• Universal digital quantum simulation with trapped ions
• Self-Verifying Variational Quantum Simulation of the Lattice Schwinger Model
• Practical Quantum Error Mitigation for Near-Future Applications
• Quantum Kibble-Zurek mechanism and critical dynamics on a programmable Rydberg simulator
• Boson sampling with 20 input photons in 60-mode interferometers at $10^{14}$ state spaces
• Quantum chemistry calculations on a trapped-ion quantum simulator
• Quantum Simulation of Electronic Structure with Linear Depth and Connectivity
• Quantum simulation of a Fermi-Hubbard model using a semiconductor quantum dot array
• Classical simulation of noninteracting-fermion quantum circuits
• Observation of gauge invariance in a 71-site Bose-Hubbard quantum simulator
• Quantum walks on a programmable two-dimensional 62-qubit superconducting processor
• Quantum computing with alkaline earth atoms
• Low Depth Quantum Simulation of Electronic Structure
• Accelerated Variational Quantum Eigensolver
• Efficient Symmetry-Preserving State Preparation Circuits for the Variational Quantum Eigensolver Algorithm
• Hong-Ou-Mandel atom interferometry in tunnel-coupled optical tweezers
• Thermalization dynamics of a gauge theory on a quantum simulator
• Stochastic gradient descent for hybrid quantum-classical optimization
• Microscopic control and detection of ultracold strontium in optical-tweezer arrays
• A concise review of Rydberg atom based quantum computation and quantum simulation
• Exploiting symmetry in variational quantum machine learning
• Generalized Jordan-Wigner Transformations
• Quantum simulations of materials on near-term quantum computers
• Theory of overparametrization in quantum neural networks
• Variational Quantum Eigensolver with Fewer Qubits
• Hardware efficient quantum simulation of non-abelian gauge theories with qudits on Rydberg platforms
• Analog quantum chemistry simulation
• Towards quantum simulation with circular Rydberg atoms
• Error Mitigation by Symmetry Verification on a Variational Quantum Eigensolver
• On barren plateaus and cost function locality in variational quantum algorithms
• Machine learning of noise-resilient quantum circuits
• Observing ground-state properties of the Fermi-Hubbard model using a scalable algorithm on a quantum computer
• Lowering qubit requirements for quantum simulations of fermionic systems
• Quantum simulation of Fermi-Hubbard models in semiconductor quantum dot arrays
• Tweezer-programmable 2D quantum walks in a Hubbard-regime lattice
• Finite-range interacting Ising quantum magnets with Rydberg atoms in optical lattices - From Rydberg superatoms to crystallization
• Quantum Computing with Circular Rydberg Atoms
• A Fermi-Hubbard Optical Tweezer Array
• Fermionic quantum processing with programmable neutral atom arrays
• Symmetry-adapted variational quantum eigensolver
• Variational Quantum Eigensolver for Frustrated Quantum Systems
• Variational preparation of finite-temperature states on a quantum computer
• Scaling of variational quantum circuit depth for condensed matter systems
• A two-dimensional programmable tweezer array of fermions
• Fermion-qudit quantum processors for simulating lattice gauge theories with matter
• Universal Effectiveness of High-Depth Circuits in Variational Eigenproblems
• Robust resource-efficient quantum variational ansatz through evolutionary algorithm
• Quantum computation of molecular response properties
• Expressivity of Quantum Neural Networks
• Symmetry enhanced variational quantum spin eigensolver
• Shallow-circuit variational quantum eigensolver based on symmetry-inspired Hilbert space partitioning for quantum chemical calculations
• Accelerated variational algorithms for digital quantum simulation of many-body ground states
• Variational Approach to Quantum Spin Liquid in a Rydberg Atom Simulator

Cited by in corpus (9)

• Hubbard parameters for programmable tweezer arrays
• Simulating Chemistry with Fermionic Optical Superlattices
• Quantum Reservoir Computing for Realized Volatility Forecasting
• A recipe for local simulation of strongly-correlated fermionic matter on quantum computers: the 2D Fermi-Hubbard model
• Effective light-induced Hamiltonian for atoms with large nuclear spin
• Variational simulation of higher-spin systems on qubit-based quantum simulators
• Quantum science with arrays of metastable helium-3 atoms
• Linear differential equation approach to the Loschmidt amplitude
• Quantum reservoir computing for predicting and characterizing chaotic maps