3 papers
quant-ph2025
Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction
Alice Barthe, Mahtab Yaghubi Rad, Michele Grossi +1
One of the key challenges in quantum machine learning is finding relevant machine learning tasks with a provable quantum advantage. A natural candidate for this is learning unknown…
quant-ph2025
On Dequantization of Supervised Quantum Machine Learning via Random Fourier Features
Mehrad Sahebi, Alice Barthe, Yudai Suzuki +2
In the quest for quantum advantage, a central question is under what conditions can classical algorithms achieve a performance comparable to quantum algorithms--a concept known as…
quant-ph2024
Universal approximation of continuous functions with minimal quantum circuits
Adrián Pérez-Salinas, Mahtab Yaghubi Rad, Alice Barthe +1
The conventional paradigm of quantum computing is discrete: it utilizes discrete sets of gates to realize bitstring-to-bitstring mappings, some of them arguably intractable for cla…