Universal compilation for quantum state preparation and tomography
- URL: http://arxiv.org/abs/2204.11635v1
- Date: Mon, 25 Apr 2022 13:10:33 GMT
- Title: Universal compilation for quantum state preparation and tomography
- Authors: Vu Tuan Hai and Le Bin Ho
- Abstract summary: We propose a universal compilation-based variational algorithm for the preparation and tomography of quantum states in low-depth quantum circuits.
We evaluate the performance of various unitary topologies and the trainability of different unitarys for getting high efficiency.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Universal compilation is a training process that compiles a trainable unitary
into a target unitary and it serves vast potential applications from quantum
dynamic simulations to optimal circuits with deep-compressing, device
benchmarking, quantum error mitigation, and so on. Here, we propose a universal
compilation-based variational algorithm for the preparation and tomography of
quantum states in low-depth quantum circuits. We apply the Fubini-Study
distance to be a trainable cost function under various gradient-based
optimizers, including the quantum natural gradient approach. We evaluate the
performance of various unitary topologies and the trainability of different
optimizers for getting high efficiency. In practice, we address different
circuit ansatzes in quantum state preparation, including the linear and
graph-based ansatzes for preparing different entanglement target states such as
representative GHZ and W states. We also discuss the effect of the circuit
depth, barren plateau, readout noise in the model, and the error mitigation
solution. We next evaluate the reconstructing efficiency in quantum state
tomography via various popular circuit ansatzes and reveal the crucial role of
the circuit depth in the robust fidelity. The results are comparable with the
shadow tomography method, a similar fashion in the field. Our work expresses
the adequate capacity of the universal compilation-based variational algorithm
to maximize the efficiency in the quantum state preparation and tomography.
Further, it promises applications in quantum metrology and sensing and is
applicable in the near-term quantum computers for verification of the circuits
fidelity and various quantum computing tasks.
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