Dissipative Variational Quantum Algorithms for Gibbs State Preparation

Yigal Ilin;Itai Arad
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Abstract

In recent years, variational quantum algorithms have gained significant attention due to their adaptability and efficiency on near-term quantum hardware. They have shown potential in a variety of tasks, including linear algebra, search problems, Gibbs, and ground state preparation. Nevertheless, the presence of noise in current day quantum hardware severely limits their performance. In this work, we introduce dissipative variational quantum algorithms (D-VQAs) by incorporating dissipative operations, such as qubit RESET and stochastic gates, as an intrinsic part of a variational quantum circuit. We argue that such dissipative variational algorithms possess some natural resilience to dissipative noise. We demonstrate how such algorithms can prepare Gibbs states over a wide range of quantum many-body Hamiltonians and temperatures, while significantly reducing errors due to both coherent and noncoherent noise. An additional advantage of our approach is that no ancilla qubits are need. Our results highlight the potential of D-VQAs to enhance the robustness and accuracy of variational quantum computations on noisy intermediate-scale quantum (NISQ) devices.
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