activity
20192026
most citedReal-Time Propagation TDDFT and Density Analysis for Exciton Couplings Calculations in Large Systems

37 citations · 52 across the 8 of their papers we have counts for

collaborators

9 papers

quant-ph2026

Toward Quantum Utility in Correlated Topological Matter: Variational Preparation of Fractional Quantum Hall Manifolds

Sergio F. Expósito, Unai Aseginolaza, Raúl Guerrero-Avilés +3

We investigate the use of variational quantum algorithms to prepare and characterize fractional quantum Hall states on near-term quantum processors. Focusing on the Laughli…

quant-ph2025

A Useful Metric for the NISQ Era: Qubit Error Probability and Its Role in Zero Noise Extrapolation

Nahual Sobrino, Unai Aseginolaza, Joaquim Jornet-Somoza +1

Accurate assessment and management of errors is indispensable for extracting useful results from noisy intermediate-scale quantum (NISQ) devices. In this work, we propose the qubit…

cond-mat.mes-hall2024

Regioselective On-Surface Synthesis of [3]Triangulene Graphene Nanoribbons

Michael C. Daugherty, Peter H. Jacobse, Jingwei Jiang +9

The integration of low-energy states into bottom-up engineered graphene nanoribbons (GNRs) is a robust strategy for realizing materials with tailored electronic band structure for…

cond-mat.mtrl-sci2023

Optical properties and exciton transfer between N-heterocyclic carbene iridium (III) complexes for blue light-emitting diode applications from first principles

Irina V. Lebedeva, Joaquim Jornet-Somoza

N-heterocyclic carbene (NHC) iridium (III) complexes are considered as promising candidates for blue emitters in organic light-emitting diodes. They can play the roles of the emitt…

quant-ph2023★ 8 cited

Error estimation in current noisy quantum computers

Unai Aseguinolaza, Nahual Sobrino, Gabriel Sobrino +2

One of the main important features of the noisy intermediate-scale quantum (NISQ) era is the correct evaluation and consideration of errors. In this paper, we analyze the main sour…

cond-mat.mtrl-sci2022

A basic electro-topological descriptor for the prediction of organic molecule geometries by simple machine learning

Carlos Manuel de Armas-Morejón, Ask Hjorth Larsen, Luis A. Montero-Cabrera +2

This paper proposes a machine learning (ML) method to predict stable molecular geometries from their chemical composition. The method is useful for generating molecular conformatio…