Sampling on NISQ Devices: "Who's the Fairest One of All?"
arXiv:2107.06468 · doi:10.1109/QCE52317.2021.00038
Abstract
Modern NISQ devices are subject to a variety of biases and sources of noise that degrade the solution quality of computations carried out on these devices. A natural question that arises in the NISQ era, is how fairly do these devices sample ground state solutions. To this end, we run five fair sampling problems (each with at least three ground state solutions) that are based both on quantum annealing and on the Grover Mixer-QAOA algorithm for gate-based NISQ hardware. In particular, we use seven IBM~Q devices, the Aspen-9 Rigetti device, the IonQ device, and three D-Wave quantum annealers. For each of the fair sampling problems, we measure the ground state probability, the relative fairness of the frequency of each ground state solution with respect to the other ground state solutions, and the aggregate error as given by each hardware provider. Overall, our results show that NISQ devices do not achieve fair sampling yet. We also observe differences in the software stack with a particular focus on compilation techniques that illustrate what work will still need to be done to achieve a seamless integration of frontend (i.e. quantum circuit description) and backend compilation.
arXiv comment11 pages
References in corpus (13)
- Quantum Annealing in the Transverse Ising Model
- From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
- A practical heuristic for finding graph minors
- Fixed-point quantum search with an optimal number of queries
- A different kind of quantum search
- Reachability Deficits in Quantum Approximate Optimization
- Grover Mixers for QAOA: Shifting Complexity from Mixer Design to State Preparation
- Exponentially-Biased Ground-State Sampling of Quantum Annealing Machines with Transverse-Field Driving Hamiltonians
- Uncertain fate of fair sampling in quantum annealing
- Fair Sampling by Simulated Annealing on Quantum Annealer
- Programmable Superpositions of Ising Configurations
- Assessment of Quantum Annealing for the Construction of Satisfiability Filters
- Achieving fair sampling in quantum annealing
Cited by in corpus (7)
- Quantum Volume in Practice: What Users Can Expect from NISQ Devices
- Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer
- Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers
- High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware
- Comparing Three Generations of D-Wave Quantum Annealers for Minor Embedded Combinatorial Optimization Problems
- Multi-round QAOA and advanced mixers on a trapped-ion quantum computer
- Quantum Advantage for All