136 citations · 415 across the 14 of their papers we have counts for
11 papers · 1 filter
Trainability Barriers in Low-Depth QAOA Landscapes
Joel Rajakumar, John Golden, Andreas Bärtschi +1
The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum algorithm for solving combinatorial optimization problems. Its effectiveness depends on identifyin…
Hierarchical Multigrid Ansatz for Variational Quantum Algorithms
Christo Meriwether Keller, Stephan Eidenbenz, Andreas Bärtschi +3
Quantum computing is an emerging topic in engineering that promises to enhance supercomputing using fundamental physics. In the near term, the best candidate algorithms for achievi…
Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs
Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio +2
We show through numerical simulation that the Quantum Approximate Optimization Algorithm (QAOA) for higher-order, random-coefficient, heavy-hex compatible spin glass Ising models h…
Provable bounds for noise-free expectation values computed from noisy samples
Samantha V. Barron, Daniel J. Egger, Elijah Pelofske +4
In this paper, we explore the impact of noise on quantum computing, particularly focusing on the challenges when sampling bit strings from noisy quantum computers as well as the im…
Probing Quantum Telecloning on Superconducting Quantum Processors
Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz +2
Quantum information can not be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typi…
Lower bounds on the number of rounds of the quantum approximate optimization algorithm required for guaranteed approximation ratios
Naphan Benchasattabuse, Andreas Bärtschi, Luis Pedro García-Pintos +3
The quantum approximate optimization algorithm, also known in its generalization as the quantum alternating operator ansatz, (QAOA) is a heuristic hybrid quantum-classical algorith…
Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation
Elijah Pelofske, Vincent Russo, Ryan LaRose +5
Quantum Volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of a square circuit which can be executed on the target device with reasona…
High-Round QAOA for MAX -SAT on Trapped Ion NISQ Devices
Elijah Pelofske, Andreas Bärtschi, John Golden +1
The Quantum Alternating Operator Ansatz (QAOA) is a hybrid classical-quantum algorithm that aims to sample the optimal solution(s) of discrete combinatorial optimization problems.…
The Quantum Alternating Operator Ansatz for Satisfiability Problems
John Golden, Andreas Bärtschi, Daniel O'Malley +1
We comparatively study, through large-scale numerical simulation, the performance across a large set of Quantum Alternating Operator Ansatz (QAOA) implementations for finding appro…
Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers
Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz
Quantum annealing (QA) and Quantum Alternating Operator Ansatz (QAOA) are both heuristic quantum algorithms intended for sampling optimal solutions of combinatorial optimization pr…
Deterministic Preparation of Dicke States
Andreas Bärtschi, Stephan Eidenbenz
The Dicke state is an equal-weight superposition of all -qubit states with Hamming Weight (i.e. all strings of length with exactly ones over a binary…