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Khanh Uyen Giang

Publications and source records attributed to Khanh Uyen Giang.

2 recordsLinked to original sources

Double-bracket quantum algorithms for high-fidelity ground state preparation

Ground state preparation is a central application for quantum computers but remains challenging in practice. In this work, we quantitatively investigate the performance and gate counts of double-bracket quantum algorithms (DBQAs) for ground state preparation. We propose a practical strategy in which DBQAs refine initial state preparation circuits, and we compile them for Heisenberg chains using controlled-Z and single-qubit gates. Warm-started DBQAs consistently improve both the energy and ground-state fidelity relative to the initial states provided by variational ansätze, indicating that DBQAs offer an effective unitary synthesis method. To demonstrate compatibility with near-term hardware, we executed a proof-of-concept example on IBM devices. With error mitigation, we observed a statistically significant improvement over the corresponding warm-start circuit. Furthermore, numerical emulations for the same system size indicate that executing DBQAs on Quantinuum's hardware could achieve similar cost-function gains without requiring error mitigation. These findings suggest that DBQAs are a promising approach for enhancing ground-state approximations on near-term quantum devices.

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Double-Bracket Algorithmic Cooling

Algorithmic cooling shows that it is possible to locally reduce the entropy of a qubit belonging to an isolated ensemble such as nuclear spins in molecules or nitrogen-vacancy centers in diamonds. In the same physical setting, we introduce double-bracket algorithmic cooling (DBAC), a protocol that systematically suppresses quantum coherence of pure states. DBAC achieves this by simulating quantum imaginary-time evolution through recursive unitary synthesis of Riemannian steepest-descent flows and it utilizes density-matrix exponentiation as a subroutine. This subroutine makes DBAC a concrete instance of a dynamic quantum algorithm that operates using quantum information stored in copies of the input states. Thus, the circuits of DBAC are independent of the input state, enabling the extension of algorithmic cooling from targeting entropy to quantum coherence without resorting to measurements. Akin to Nernst principle, DBAC increases the cooling performance when including more input qubits which serve as quantum instructions. Our work demonstrates that dynamic quantum algorithms are a promising route toward new protocols for foundational tasks in quantum thermodynamics.

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