Quantum Alternating Operator Ansatz for the Preparation and Detection of Long-Lived Singlet States in NMR

Abstract

Designing efficient and robust quantum control strategies is vital for developing quantum technologies. One recent strategy is the Quantum Alternating Operator Ansatz (QAOA) sequence that alternatively propagates under two noncommuting Hamiltonians, whose control parameters can be optimized to generate a gate or prepare a state. Here, we describe the design of a QAOA sequence to prepare long-lived singlet states (LLS) from the thermal state in NMR. With extraordinarily long lifetimes exceeding the spin-lattice relaxation time constant $T_1$, LLS have been of great interest for various applications, from spectroscopy to medical imaging. Accordingly, designing sequences for efficiently preparing LLS in a general spin system is crucial. Using numerical analysis, we study the efficiency and robustness of our QAOA sequence over a wide range of errors in the control parameters. Using a two-qubit NMR register, we conduct an experimental study to benchmark our QAOA sequence against other prominent methods of LLS preparation and observe superior performance, especially under noisy conditions. Finally, we numerically demonstrate the applicability of our QAOA sequence beyond two-qubit registers, specifically for polychromatic excitation of delocalized LLS in a six-proton system.

9+3 pages, 7+1 figures; Major revisions to method and experimental results

References in corpus (25)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Variational Quantum Algorithms
• The theory of variational hybrid quantum-classical algorithms
• A Quantum Approximate Optimization Algorithm
• Noisy intermediate-scale quantum (NISQ) algorithms
• From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
• Quantum Approximate Optimization Algorithm: Performance, Mechanism, and Implementation on Near-Term Devices
• Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor
• A Review on Quantum Approximate Optimization Algorithm and its Variants
• Quantum Approximate Optimization of the Long-Range Ising Model with a Trapped-Ion Quantum Simulator
• The Quantum Approximate Optimization Algorithm and the Sherrington-Kirkpatrick Model at Infinite Size
• Design of Strongly Modulating Pulses to Implement Precise Effective Hamiltonians for Quantum Information Processing
• Preparation of Nuclear Spin Singlet States using Spin-Lock Induced Crossing
• Optimizing Variational Quantum Algorithms using Pontryagin's Minimum Principle
• Efficient variational simulation of non-trivial quantum states
• On the Universality of the Quantum Approximate Optimization Algorithm
• Quantum approximate optimization is computationally universal
• Robust conversion of singlet spin order in coupled spin-1/2 pairs by adiabatically switched RF-fields
• Constant-adiabaticity RF-pulses for generating long-lived singlet spin states in NMR
• Quantifying the efficiency of state preparation via quantum variational eigensolvers
• Steering Quantum Dynamics via Bang-Bang Control: Implementing optimal fixed point quantum search algorithm
• Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols
• Bang-Bang Optimal Control of Large Spin Systems: Enhancement of ${}^{13}$C-${}^{13}$C Singlet-Order at Natural Abundance
• Steady state preparation of long-lived nuclear spin singlet pair at room temperature
• Long-Lived Singlet State in an Oriented Phase and its Survival across the Phase Transition Into an Isotropic Phase