6 papers
Grover's algorithm is an approximation of imaginary-time evolution
Yudai Suzuki, Marek Gluza, Jeongrak Son +3
We reveal the power of Grover's algorithm from thermodynamic and geometric perspectives by showing that it is a product formula approximation of imaginary-time evolution (ITE), a R…
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…
Double-bracket algorithm for quantum signal processing without post-selection
Yudai Suzuki, Bi Hong Tiang, Jeongrak Son +3
Quantum signal processing (QSP), a framework for implementing matrix-valued polynomials, is a fundamental primitive in various quantum algorithms. Despite its versatility, a potent…
Role of scrambling and noise in temporal information processing with quantum systems
Weijie Xiong, Zoë Holmes, Armando Angrisani +3
Scrambling quantum systems have attracted attention as effective substrates for temporal information processing. Here we consider a quantum reservoir processing framework that capt…
Double-bracket quantum algorithms for quantum imaginary-time evolution
Marek Gluza, Jeongrak Son, Bi Hong Tiang +5
Efficiently preparing approximate ground-states of large, strongly correlated systems on quantum hardware is challenging and yet nature is innately adept at this. This has motivate…
Light-cone feature selection for quantum machine learning
Yudai Suzuki, Rei Sakuma, Hideaki Kawaguchi
Feature selection plays an essential role in improving the predictive performance and interpretability of trained models in classical machine learning. On the other hand, the usabi…