Quantum annealing sampling with a bias field
arXiv:2205.15820 · doi:10.1103/PhysRevApplied.18.044036
Abstract
The presence of a bias field, encoding some information about the target state, can enhance the performance of quantum optimization methods. Here we investigate the effect of such a bias field on the outcome of quantum annealing sampling, at the example of the exact cover problem. The sampling is carried out on a D-Wave machine, and different bias configurations are benchmarked against the unbiased sampling procedure. It is found that the biased annealing algorithm works particularly well for larger problem sizes, where the Hamming distance between bias and target configuration becomes less important. This work motivates future research efforts for finding good bias configurations, either on the quantum machine itself, or in a hybrid fashion via classical algorithms.
References in corpus (54)
- Quantum Annealing in the Transverse Ising Model
- A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
- Adiabatic Quantum Computing
- Shortcuts to adiabaticity: concepts, methods, and applications
- Shortcuts to adiabaticity by counter-diabatic driving
- Perspectives of quantum annealing: Methods and implementations
- Anderson localization casts clouds over adiabatic quantum optimization
- Experimental implementation of an adiabatic quantum optimization algorithm
- First order phase transition in the Quantum Adiabatic Algorithm
- Searching for quantum speedup in quasistatic quantum annealers
- Adiabatic tracking of quantum many-body dynamics
- Quantum annealing with antiferromagnetic fluctuations
- Reverse annealing for the fully connected -spin model
- Simple Glass Models and their Quantum Annealing
- Modernizing Quantum Annealing using Local Searches
- First-order transitions and the performance of quantum algorithms in random optimization problems
- Nonstoquastic Hamiltonians and Quantum Annealing of an Ising Spin Glass
- Exponential Speedup of Quantum Annealing by Inhomogeneous Driving of the Transverse Field
- Dynamics of reverse annealing for the fully-connected -spin model
- Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits
- Different Strategies for Optimization Using the Quantum Adiabatic Algorithm
- Does Adiabatic Quantum Optimization Truly Fail for NP-complete problems?
- Reverse quantum annealing of the -spin model with relaxation
- Counterdiabatic driving in the quantum annealing of the -spin model: a variational approach
- Quantum annealing of the -spin model under inhomogeneous transverse field driving
- Role of Non-stoquastic Catalysts in Quantum Adiabatic Optimization
- Quantum annealing with longitudinal bias fields
- Quantum annealing for the number partitioning problem using a tunable spin glass of ions
- Quantum algorithm for energy matching in hard optimization problems
- Experimental demonstration of perturbative anticrossing mitigation using non-uniform driver Hamiltonians
- Algorithmic approach to adiabatic quantum optimization
- Quantum Adiabatic Algorithm Design using Reinforcement Learning
- Two-parameter counter-diabatic driving in quantum annealing
- Probing Entanglement in Adiabatic Quantum Optimization with Trapped Ions
- An energetic perspective on rapid quenches in quantum annealing
- Quantum Approximate Optimization Algorithm with Adaptive Bias Fields
- Genetic optimization of quantum annealing
- Variational optimization of the quantum annealing schedule for the Lechner-Hauke-Zoller scheme
- Inhomogeneous quasi-adiabatic driving of quantum critical dynamics in weakly disordered spin chains
- Optimal quantum annealing: A variational shortcut to adiabaticity approach
- Schedule path optimization for quantum annealing and adiabatic quantum computing
- General bound on the performance of counter-diabatic driving acting on dissipative spin systems
- Generalized transitionless quantum driving for open quantum systems
- Search range in experimental quantum annealing
- Standard quantum annealing outperforms adiabatic reverse annealing with decoherence
- Quantum phase transition with inhomogeneous driving in the Lechner-Hauke-Zoller model
- Polynomial scaling enhancement in ground-state preparation of Ising spin models via counter-diabatic driving
- Optimization by a quantum reinforcement algorithm
- Optimizing Quantum Adiabatic Algorithm
- Theoretical survey of unconventional quantum annealing methods applied to adifficult trial problem
- Semiclassical approach to finite temperature quantum annealing with trapped ions
- The quantum annealing gap and quench dynamics in the exact cover problem
- Hard instance learning for quantum adiabatic prime factorization
- Quantum walk in a reinforced free-energy landscape: Quantum annealing with reinforcement