collaborators

6 papers

quant-ph2026

Qudit-ADAPT-VQE: an adaptive variational algorithm with counterdiabatic-inspired improvements for qudits

Joaquín Molina, Herbert Díaz-Moraga, Dardo Goyeneche +1

Variational quantum algorithms based on qudits have attracted significant attention in recent years. However, as in their qubit-based counterparts, challenges such as barren platea…

quant-ph2026

Entanglement and discord classification via deep learning

Katherine Muñoz-Mellado, Daniel Uzcátegui-Contreras, Antonio Guerra +2

In this work, we propose a deep learning-based approach for quantum entanglement and discord classification using convolutional autoencoders. We train models to distinguish entangl…

quant-ph2026

Counterdiabatic ADAPT-VQE for molecular simulation

Diego Tancara, Herbert Díaz-Moraga, Dardo Goyeneche

Among variational quantum algorithms designed for NISQ devices, ADAPT-VQE stands out for its robustness against barren plateaus, particularly in estimating molecular ground states.…

quant-ph2025

Entanglement generation in qubit-ADAPT-VQE through four-qubit algebraic classification

Diego Tancara, Herbert Díaz-Moraga, Vicente Sepúlveda-Trivelli +1

While variational quantum algorithms are among the most promising approaches for the noisy intermediate-scale quantum (NISQ) era, their scalability is often hindered by the barren…

quant-ph2025

Efficient state estimation on quantum processors

Victor Gonzalez Avella, Abraham Vega Vargas, Tomas Merlo Vergara +6

We present two scalable and entanglement-free methods for estimating the collective state of an n-qubit quantum computer. The first method consists of a fixed set of five quantum c…

quant-ph2025

Cyclic measurements and simplified quantum state tomography

Victor Gonzalez Avella, Jakub Czartowski, Dardo Goyeneche +1

Tomographic reconstruction of quantum states plays a fundamental role in benchmarking quantum systems and accessing information encoded in quantum-mechanical systems. Among the inf…