Variational Simulation of Schwinger's Hamiltonian with Polarisation Qubits

Abstract

The numerical emulation of quantum physics and quantum chemistry often involves an intractable number of degrees of freedom and admits no known approximation in general form. In practice, representing quantum-mechanical states using available numerical methods becomes exponentially more challenging with increasing system size. Recently quantum algorithms implemented as variational models, have been proposed to accelerate such simulations. Here we study the effect of noise on the quantum phase transition in the Schwinger model, within a variational framework. The experiments are built using a free space optical scheme to realize a pair of polarization qubits and enable any two-qubit state to be experimentally prepared up to machine tolerance. We specifically exploit the possibility to engineer noise and decoherence for polarization qubits to explore the limits of variational algorithms for NISQ architectures in identifying and quantifying quantum phase transitions with noisy qubits. We find that despite the presence of noise one can detect the phase transition of the Schwinger Hamiltonian even for a two-qubit system using variational quantum algorithms.

11 pages, 8 figures

References in corpus (22)

• Quantum Machine Learning
• A variational eigenvalue solver on a quantum processor
• Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
• Barren plateaus in quantum neural network training landscapes
• Scalable Quantum Simulation of Molecular Energies
• Self-Verifying Variational Quantum Simulation of the Lattice Schwinger Model
• Experimental ten-photon entanglement
• Variational Quantum Computation of Excited States
• A wavelength-tunable fiber-coupled source of narrowband entangled photons
• Variational quantum algorithms for nonlinear problems
• Quantum Computation of Electronic Transitions using a Variational Quantum Eigensolver
• Quantum Implementation of Unitary Coupled Cluster for Simulating Molecular Electronic Structure
• Accelerated Variational Quantum Eigensolver
• From transistor to trapped-ion computers for quantum chemistry
• Reachability Deficits in Quantum Approximate Optimization
• Universal Variational Quantum Computation
• Variational Quantum Unsampling on a Quantum Photonic Processor
• On the Universality of the Quantum Approximate Optimization Algorithm
• Machine Learning Phase Transitions with a Quantum Processor
• Engineering arbitrary pure and mixed quantum states
• Scaling of variational quantum circuit depth for condensed matter systems
• Generalization of the output of variational quantum eigensolver by parameter interpolation with low-depth ansatz

Cited by in corpus (11)

• Neural Error Mitigation of Near-Term Quantum Simulations
• Training Saturation in Layerwise Quantum Approximate Optimisation
• Quantum autoencoders with enhanced data encoding
• Two-qubit quantum photonic processor manufactured by femtosecond laser writing
• Numerical hardware-efficient variational quantum simulation of a soliton solution
• Noise-Robust Detection of Quantum Phase Transitions
• Error mitigated variational algorithm on a photonic processor
• Fractal states of the Schwinger model
• Photonic variational quantum eigensolver using entanglement measurements
• Photonic variational quantum eigensolver for NISQ-compatible quantum technology
• Distributed variational quantum computing with deterministic entanglement tuning