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Trapped Ion Quantum Computing
Quantum Machine Learning
Expressibility, entangling power and quantum average causal effect for causally indefinite circuits
arXiv
Authors: Pedro C. Azado, Guilherme I. Correr, Alexandre Drinko, Ivan Medina, Askery Canabarro, Diogo O. Soares-Pinto
Year
2024
Paper ID
36820
Status
Preprint
Abstract Read
~2 min
Abstract Words
141
Citations
N/A
Abstract
Parameterized quantum circuits are the core of new technologies such as variational quantum algorithms and quantum machine learning, which makes studying its properties a valuable task. We implement parameterized circuits with definite and indefinite causal order and compare their performance under particular descriptors. One of these is the expressibility, which measures how uniformly a given quantum circuit can reach the whole Hilbert space. Another property that we focus on this work is the entanglement capability, more specifically the concurrence and the entangling power. We also find the causal relation between the qubits of our system with the quantum average causal effect measure. We have found that indefinite circuits offer expressibility advantages over definite ones while maintaining the level of entanglement generation. Our results also point to the existence of a correlation between the quantum average causal effect and the entangling power.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- Parameterized quantum circuits are the core of new technologies such as variational quantum algorithms and quantum machine learning, which makes studying its properties a...
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