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To enhance the variational quantum eigensolver (VQE), the CAFQA method can utilize classical computational capabilities to identify a better initial state than the Hartree-Fock method.
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The randomized measurement toolbox
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Chemically aware unitary coupled cluster with ab initio calculations on an ion trap quantum computer: A refrigerant chemicals’ application
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Evidence for the utility of quantum computing before fault tolerance
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Navigating the dynamic noise landscape of variational quantum algorithms with QISMET
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Engineering a Control System for a Logical Qubit-Scalee Trapped Ion Quantum Computer
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Ever more optimized simulations of fermionic systems on a quantum computer. In 2023 60th ACM/IEEE Design Automation Conference (DAC) . IEEE, 1–6
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Enhancing the Electron Pair Approximation with Measurements on Trapped Ion Quantum Computers
Luning Zhao, Joshua Goings, Qingfeng Wang, Kyujin Shin, Woomin Kyoung, Seunghyo Noh, Young Min Rhee, and Kyungmin Kim. 2023 · 2023
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Optimal Clifford Initial States for Ising Hamiltonians
Bikrant Bhattacharyya and Gokul Subramanian Ravi. 2024 · 2024
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VarSaw: Application-tailored Measurement Error Mitigation for Variational Quantum Algorithms
Siddharth Dangwal, Gokul Subramanian Ravi, Poulami Das, Kaitlin N. Smith, Jonathan M. Baker, and Frederic T. Chong. 2024 · 2024
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Variational denoising for variational quantum eigensolver
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DISQ: Dynamic Iteration Skipping for Variational Quantum Algorithms
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Experimental error mitigation using linear rescaling for variational quantum eigensolving with up to 20 qubits
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