Iterative orthogonal-basis interpolation constructs high-quality QAOA parameter schedules for depths exceeding 1000 layers, outperforming prior methods on SK, portfolio, and LABS benchmarks.
Evidence of scaling advantage for the quantum approxi- mate optimization algorithm on a classically intractable problem
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Systematic numerical study of QAOA parameter transfer on heavy-hex Ising models with local cubic terms shows transferred angles from small instances yield improving expectation values up to 49 layers on instances up to 156 qubits, with hardware runs confirming gains up to p=10.
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.
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Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm
Iterative orthogonal-basis interpolation constructs high-quality QAOA parameter schedules for depths exceeding 1000 layers, outperforming prior methods on SK, portfolio, and LABS benchmarks.
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Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
Systematic numerical study of QAOA parameter transfer on heavy-hex Ising models with local cubic terms shows transferred angles from small instances yield improving expectation values up to 49 layers on instances up to 156 qubits, with hardware runs confirming gains up to p=10.
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The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.