6 papers
Arbitrary state preparation in quantum harmonic oscillators using neural networks
Nicolas Parra-A, Vladimir Vargas-Calderón, Herbert Vinck-Posada
Preparing quantum states is a fundamental task in various quantum algorithms. In particular, state preparation in quantum harmonic oscillators (HOs) is crucial for the manipulation…
Variational decision diagrams for quantum-inspired machine learning applications
Vladimir Vargas-Calderón, Santiago Acevedo-Mancera, Herbert Vinck-Posada
Decision diagrams (DDs) have emerged as an efficient tool for simulating quantum circuits due to their capacity to exploit data redundancies in quantum states and quantum operation…
Quantum generative classification with mixed states
Diego H. Useche, Sergio Quiroga-Sandoval, Sebastian L. Molina +3
Classification can be performed using either a discriminative or a generative learning approach. Discriminative learning consists of constructing the conditional probability of the…
Quantum Deep Sets and Sequences
Vladimir Vargas-Calderón
This paper introduces the quantum deep sets model, expanding the quantum machine learning tool-box by enabling the possibility of learning variadic functions using quantum systems.…
: an automated algebraic solution for high-order quantum systems
D. MartÃnez-Tibaduiza, Vladimir Vargas-Calderón, J. G. Dueñas +2
Many significant quantum physical systems are characterized by Hamiltonians expressible as a linear combination of time-independent generators of a closed Lie algebra, $\hat{H}(t)=…
MEMO-QCD: Quantum Density Estimation through Memetic Optimisation for Quantum Circuit Design
Juan E. Ardila-GarcÃa, Vladimir Vargas-Calderón, Fabio A. González +2
This paper presents a strategy for efficient quantum circuit design for density estimation. The strategy is based on a quantum-inspired algorithm for density estimation and a circu…