36 citations · 131 across the 21 of their papers we have counts for
22 papers
autotn: Automata-inspired construction of tensor-network operators from symbolic local rules
Aitor Morais, Izaskun Oregi, Iker Pastor +1
Matrix product operators (MPOs) are a standard representation for structured operators in tensor-network simulations and quantum computing applications. However, converting symboli…
Exploring the application of quantum technologies to industrial and real-world use cases
Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi
Recent advancements in quantum computing are leading to an era of practical utility, enabling the tackling of increasingly complex problems. The goal of this era is to leverage qua…
Comparative Analysis of Classical and Quantum-Inspired Solvers: A Preliminary Study on the Weighted Max-Cut Problem
Aitor Morais, Eneko Osaba, Iker Pastor +1
Combinatorial optimization is essential across numerous disciplines. Traditional metaheuristics excel at exploring complex solution spaces efficiently, yet they often struggle with…
On the Transfer of Knowledge in Quantum Algorithms
Esther Villar-Rodriguez, Eneko Osaba, Izaskun Oregi +2
Quantum computing is poised to transform computational paradigms across science and industry. As the field evolves, it can benefit from established classical methodologies, includi…
Eclipse Qrisp QAOA: description and preliminary comparison with Qiskit counterparts
Eneko Osaba, Matic Petrič, Izaskun Oregi +4
This paper focuses on the presentation and evaluation of the high-level quantum programming language Eclipse Qrisp. The presented framework, used for developing and compiling quant…
Quantum Optimization Methods for Satellite Mission Planning
Antón Makarov, Carlos Pérez-Herradón, Giacomo Franceschetto +5
Satellite mission planning for Earth observation satellites is a combinatorial optimization problem that consists of selecting the optimal subset of imaging requests, subject to co…
Hybrid Quantum Solvers in Production: how to succeed in the NISQ era?
Eneko Osaba, Esther Villar-Rodriguez, Aitor Gomez-Tejedor +1
Hybrid quantum computing is considered the present and the future within the field of quantum computing. Far from being a passing fad, this trend cannot be considered just a stopga…
A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe
Eneko Osaba, Guillaume Gelabert, Esther Villar-Rodriguez +2
One of the problems in quantitative finance that has received the most attention is the portfolio optimization problem. Regarding its solving, this problem has been approached usin…
Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing
Antón Makarov, Márcio M. Taddei, Eneko Osaba +3
Satellite image acquisition scheduling is a problem that is omnipresent in the earth observation field; its goal is to find the optimal subset of images to be taken during a given…
Digital-Analog Quantum Computation with Arbitrary Two-Body Hamiltonians
Mikel Garcia-de-Andoin, Álvaro Saiz, Pedro Pérez-Fernández +3
Digital-analog quantum computing is a computational paradigm which employs an analog Hamiltonian resource together with single-qubit gates to reach universality. Here, we design a…
Formulation of the Electric Vehicle Charging and Routing Problem for a Hybrid Quantum-Classical Search Space Reduction Heuristic
M. Garcia de Andoin, A. Bottarelli, S. Schmitt +3
Combinatorial optimization problems have attracted much interest in the quantum computing community in the recent years as a potential testbed to showcase quantum advantage. In thi…
Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers
Sebastián V. Romero, Eneko Osaba, Esther Villar-Rodriguez +2
Efficient packing of items into bins is a common daily task. Known as Bin Packing Problem, it has been intensively studied in the field of artificial intelligence, thanks to the wi…
Digital Quantum Simulation and Circuit Learning for the Generation of Coherent States
Ruilin Liu, Sebastián V. Romero, Izaskun Oregi +3
Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning,and quantum optics. In this article, two ways…
Comparative Benchmark of a Quantum Algorithm for the Bin Packing Problem
Mikel Garcia-de-Andoin, Izaskun Oregi, Esther Villar-Rodriguez +2
The Bin Packing Problem (BPP) stands out as a paradigmatic combinatorial optimization problem in logistics. Quantum and hybrid quantum-classical algorithms are expected to show an…
Analyzing the behaviour of D'WAVE quantum annealer: fine-tuning parameterization and tests with restrictive Hamiltonian formulations
Esther Villar-Rodriguez, Eneko Osaba, Izaskun Oregi
Despite being considered as the next frontier in computation, Quantum Computing is still in an early stage of development. Indeed, current commercial quantum computers suffer from…
Hybrid Quantum-Classical Heuristic for the Bin Packing Problem
Mikel Garcia de Andoin, Eneko Osaba, Izaskun Oregi +2
Optimization problems is one of the most challenging applications of quantum computers, as well as one of the most relevants. As a consequence, it has attracted huge efforts to obt…
Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem
Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi +1
Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community. Widely conceived as the next frontier of com…
Hybrid Quantum Computing -- Tabu Search Algorithm for Partitioning Problems: preliminary study on the Traveling Salesman Problem
Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi +1
Quantum Computing is considered as the next frontier in computing, and it is attracting a lot of attention from the current scientific community. This kind of computation provides…
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
Javier Del Ser, Ibai Lana, Eric L. Manibardo +5
In short-term traffic forecasting, the goal is to accurately predict future values of a traffic parameter of interest occurring shortly after the prediction is queried. The activit…
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning
Jesus L. Lobo, Izaskun Oregi, Albert Bifet +1
Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios. One of the most promising techniques in stream learning…
Real-time Electrical Power Prediction in a Combined Cycle Power Plant
Jesus L. Lobo, Igor Ballesteros, Izaskun Oregi +1
The prediction of electrical power in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power output can vary depending on envir…
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics
Antonio Benitez-Hidalgo, Antonio J. Nebro, Jose Garcia-Nieto +2
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well…