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Iterative quantum optimisation with a warm-started quantum state
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Iterative quantum optimisation with a warm-started quantum state
abstract
We provide a method to prepare a warm-started quantum state from measurements with an iterative framework to enhance the quantum approximate optimisation algorithm (QAOA). The numerical simulations show the method can effectively address the "stuck issue" of the standard QAOA using a single-string warm-started initial state described in [Cain et al., 2023]. When applied to the $3$-regular MaxCut problem, our approach achieves an improved approximation ratio, with a lower bound that iteratively converges toward the best classical algorithms for $p=1$ standard QAOA. Additionally, in the context of the discrete global minimal variance portfolio (DGMVP) model, simulations reveal a more favourable scaling of identifying the global minimal compared to the QAOA standalone, the single-string warm-started QAOA and a classical constrained sampling approach.
Forward citations
Cited by 4 Pith papers
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Nonvariational quantum optimisation approaches to pangenome-guided sequence assembly
Iterative-QAOA solves pangenome assembly instances on current quantum hardware by using a fixed-ramp QAOA schedule with warm-start updates and a new HUBO encoding that cuts variables from O(N^{2}) to O(N log N).
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Constrained Quantum Optimization via Iterative Warm-Start XY-Mixers
A warm-started XY-mixer aligned to a biased W-state, iterated via sample-based probability updates, raises optimal-solution sampling rates for one-hot constrained QAOA and finds optima on 144-qubit hardware with post-...
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Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting
Bitflip-gauge warm-start QAOA that aligns the ansatz with amplitude-damping noise improves 100-qubit Ising approximation ratios over non-gauge iterative warm-start at no extra circuit cost.
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Iterative warm-start optimization with quantum imaginary time evolution
An iterative nonvariational quantum algorithm using warm-start states and classically computed imaginary time evolution circuits achieves median solutions within 95% of optimal for MaxCut on small 3-regular graphs usi...
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