activity
20192025
most citedKernel-based quantum regressor models learn non-Markovianity

11 citations · 31 across the 8 of their papers we have counts for

collaborators

8 papers

quant-ph2025

Single excitation swap in a modified Jaynes-Cummings-Hubbard lattice

Maritza Ahumada, Natalia Valderrama-Quinteros, Diego Tancara +1

Controlling the transport and nature of quantum excitations in low-dimensional systems is a key requirement for scalable quantum devices, including communication networks and quant…

quant-ph2024

Magnetic and phonon-induced effects on the non-Markovian dynamics of a single solid-state defect

Ariel Norambuena, Diego Tancara, Vicente Chomalí-Castro +1

The electron-phonon interaction is one of the most fundamental mechanisms in condensed matter physics. Phonons can induce memory effects in solid-state platforms when localized ele…

quant-ph2023

Quantum kernels for classifying dynamical singularities in a multiqubit system

Diego Tancara, José Fredes, Ariel Norambuena

Dynamical quantum phase transition is a critical phenomenon involving out-of-equilibrium states and broken symmetries without classical analogy. However, when finite-sized systems…

quant-ph2022★ 3 cited

Engineering non-Markovianity from defect-phonon interactions

Francisco J. González, Diego Tancara, Hossein T. Dinani +2

Understanding defect-phonon interactions in solid-state devices is crucial for improving our current knowledge of quantum platforms. In this work, we develop first-principles calcu…

quant-ph2022★ 11 cited

Kernel-based quantum regressor models learn non-Markovianity

Diego Tancara, Hossein T. Dinani, Ariel Norambuena +2

Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are pa…

quant-ph2022★ 1 cited

Estimating the degree of non-Markovianity using variational quantum circuits

Hossein T. Dinani, Diego Tancara, Felipe F. Fanchini +2

Several applications of quantum machine learning (QML) rely on a quantum measurement followed by training algorithms using the measurement outcomes. However, recently developed QML…

quant-ph2020★ 5 cited

Steering Interchange of Polariton Branches via Coherent and Incoherent Dynamics

Diego Tancara, Ariel Norambuena, Rubén Peña +3

Controlling light-matter based quantum systems in the strong coupling regime allows for exploring quantum simulation of many-body physics in nowadays architectures. For instance, t…

quant-ph2019★ 11 cited

Coding closed and open quantum systems in MATLAB: applications in quantum optics and condensed matter

Ariel Norambuena, Diego Tancara, Raúl Coto

We develop a package of numerical simulations implemented in MATLAB to solve complex many-body quantum systems. We focus on widely used examples that include the calculation of the…