Elias Combarro

University of Oviedo | UNIOVI · Department of Computer Science

Quantum abstract detecting systems (QADS) provide a common framework to address detection problems in quantum computers. A particular QADS family, that of combinatorial QADS, has been proved to be useful for decision problems on eigenvalues or phase estimation methods. In this paper, we consider functional QADS, which not only have interesting theo...

The so-called Hamming distance measures the difference between two binary strings A and B. In simplified form, it measures the number of changes in A to get B. This type of distance is very useful in classical computing in applications such as error correction. It is also advantageous in quantum computing, being for example widely used in quantum m...

One of the strategies to reduce the complexity of N-body simulations is the computation of the neighbour list. However, this list needs to be updated from time to time, with a high computational cost. This paper focuses on the use of quantum computing to accelerate such a computation. Our proposal is based on a well-known oracular quantum algorithm...

When classifying a collection of finite algebras (for instance, in the computational classification of finite semifields), an important task is the determination of substructures such as the right, middle, and left nuclei, the nucleus, and the center. Finding these structures may become computationally expensive when there is no additional informat...

The aim of a ranking aggregation problem is to combine several rankings into a single one that best represents them. A common method for solving this problem is due to Kemeny and selects as the aggregated ranking the one that minimizes the sum of the Kendall distances to the rankings to be aggregated. Unfortunately, the identification of the said r...

Background The World Health Organization (WHO) establishes as a top priority the early detection of respiratory diseases. This detection could be performed by means of recognizing the presence of acoustic bio-markers (adventitious sounds) from auscultation because it is still the main technique applied in any health center to assess the status of t...

Current quantum computers have a limited number of resources and are heavily affected by internal and external noise. Therefore, small, noise-tolerant circuits are of great interest. With regard to circuit size, it is especially important to reduce the number of required qubits. Concerning to fault-tolerance, circuits entirely built with Clifford+T...

In an earlier work [1], we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. This paper explores the dual-PQC G...

The algorithms that best demonstrate the potential of quantum computing are Shor’s algorithm and Grover’s algorithm. To this day, new evidence continues to emerge in the form of algorithms or ingenious applications that increase the field of application of this type of computing. However, given the limited number of qubits in current quantum comput...

This chapter provides a self-contained introduction to quantum computing and quantum algorithms, focusing mainly on the models of quantum circuits and quantum adiabatic computing. The concepts of qubits, quantum gates, and measurements are introduced and illustrated with examples. Applications of quantum computing are also discussed.

Free energy-based reinforcement learning (FERL) with clamped quantum Boltzmann machines (QBM) was shown to significantly improve the learning efficiency compared to classical Q-learning with the restriction, however, to discrete state-action space environments. In this paper, the FERL approach is extended to multi-dimensional continuous state-actio...

Current quantum computers have a limited number of resources and are heavily affected by internal and external noise. Therefore, small, noise-tolerant circuits are of great interest. With regard to circuit size, it is especially important to reduce the number of required qubits. Concerning to fault-tolerance, circuits entirely built with Clifford+T...

In this paper, we introduce and study the quantum measurement detection algorithms (QMDA), whose objective is to detect whether unwanted measurements are being taken in a quantum circuit or not by applying the Zeno effect. A QMDA is a quantum circuit that includes three unitary matrices, one of them being applied numerous times consecutively, and w...

In an earlier work, we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of a quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. This paper explores the dual- PQC GA...

Quantum abstract detecting systems (QADS) were introduced as a common framework for the study and design of detecting algorithms in a quantum computing setting. In this paper, we introduce new families of such QADS, known as combinatorial and rotational, which, respectively, generalize detecting systems based on single qubit controlled gates and on...

Quantum computing (QC) is one of the most promising new technologies for High Performance Computing. Its potential use in High Energy Physics has lead CERN, one of the top world users of large-scale distributed computing, to start programmes such as the Quantum Technology Initiative (QTI) to further assess and explore the applications of QC. As a p...

A correction to this paper has been published: https://doi.org/10.1007/s11227-021-03923-0

The security of a broad family of coding based cryptographic techniques relies on the hardness of the Syndrome Decoding Problem (SDP). In this problem, the aim is to find a word with a given syndrome and of Hamming weight smaller than a prefixed bound. If this last condition is replaced by “of minimum weight”, then we have the Coset Leader Problem...

Generating random numbers is important for many real-world applications, including cryptography, statistical sampling and Monte Carlo simulations. Quantum systems subject to a measurement produce random results via Born’s rule, and thus it is natural to study the possibility of using such systems in order to generate high-quality random numbers. Ho...

In this paper, we propose a parallel source separation system designed to extract heart and lung sounds from single-channel mixtures. The proposed system is based on a non-negative matrix factorization (NMF) approach and a clustering strategy together with a soft-masking filtering. Furthermore, we propose an offline and online implementation of the...

Two of the most well-known quantum algorithms, those introduced by Deutsch–Jozsa and Bernstein–Vazirani, can solve promise problems with just one function query, showing an oracular separation with deterministic classical algorithms. In this work, we generalise those methods to study a family of quantum algorithms that can, with just one query, exa...

We have developed two quantum classifier models for the $t\bar{t}H(b\bar{b})$ classification problem, both of which fall into the category of hybrid quantum-classical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies, serve as a proof of concept that Quantum Machine Learning (QML) methods can have...

Generative models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo simulations. It has been proposed that, in certain circumstances, simulation using GANs can be sped-up by using quantum GANs (qGANs). We present a new design of qGAN, the dual-Parameterized Quantum Circuit(PQC) GAN,...

Deep Neural Networks (DNNs) come into the limelight in High Energy Physics (HEP) in order to manipulate the increasing amount of data encountered in the next generation of accelerators. Recently, the HEP community has suggested Generative Adversarial Networks (GANs) to replace traditional time-consuming Geant4 simulations based on the Monte Carlo m...

The Quantum Approximate Optimization Algorithm (QAOA) was proposed as a way of finding good, approximate solutions to hard combinatorial optimization problems. QAOA uses a hybrid approach. A parametrized quantum state is repeatedly prepared and measured on a quantum computer to estimate its average energy. Then, a classical optimizer, running in a...

Generative models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo simulations. It has been proposed that, in certain circumstances, simulation using GANs can be sped-up by using quantum GANs (qGANs). We present a new design of qGAN, the dual-Parameterized Quantum Circuit (PQC) GAN,...

We have developed two quantum classifier models for the ttH classification problem, both of which fall into the category of hybrid quantumclassical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies, serve as a proof of concept that Quantum Machine Learning (QML) methods can have similar or better...

This paper presents a parallel system for searching a digital score of classical music in a personal library. The application scenario of the system is for a musician who wants to search for a specific score in its own device by playing an excerpt of a few seconds of the composition. We propose a solution, based on audio-to-score alignment, which a...

Reversible adders are essential circuits in quantum computing systems. They are a fundamental part of the algorithms implemented for such systems, where Shor's celebrated factoring algorithm is one of the most prominent examples in which reversible arithmetic is needed. There is a wide variety of works in the existing literature which tackle the de...

In this paper, we study Quantum Abstract Detecting Systems (QADS), that generalize some key characteristics of the operators used in Grover’s algorithm, a wide variety of quantum walks and the quantum abstract search algorithm. A QADS is an algorithm that constructs a quantum state and a quantum operator that help testing whether a circuit-implemen...

The standard description of a quantum algorithm consists in three steps. First, encoding the data in a suitable initial quantum state. Second, driving such a state by a convenient sequence of unitary transformations until a final quantum state is reached. Third, measuring the final state and use such a measurement to solve the problem the quantum a...

Nonassociative algebra plays a fundamental role in the description of physical systems. Symmetry is related to the transformations of these algebras, which are controlled by their automorphisms group. Starting from the known structure of finite division rings with 64 elements, we construct some nonassociative finite division algebra of Orders 256 a...

In this work, Minimals Plus, an algorithm for the random generation of linear extensions from a poset is introduced. It improves a previously existing heuristic algorithm, Minimals, and its recent modification, Bottom-Up. Minimals Plus shares all the strengths of Bottom-Up and none of its weaknesses: it can be applied to any poset, has a fast initi...

Soundprism is a real‐time algorithm to separate polyphonic music audio into source signals, given the musical score of the audio in advance. This paper presents a framework for a Soundprism implementation. A study of the sound quality of the online score‐informed source separation is shown, although a real‐time implementation is not carried out. Th...

A quantum procedure for testing the commutativity of a finite dimensional algebra is introduced. This algorithm, based on Grover’s quantum search, is shown to provide a quadratic speed-up (when the number of queries to the algebra multiplication constants are considered) over any classical algorithm (both deterministic and randomized) with equal su...

This paper presents a real-time audio-to-score alignment system for musical applications. The aim of these systems is to synchronize a live musical performance with its symbolic representation in a music sheet. We have used as a base our previous real-time alignment system by enhancing it with a traceback stage, a stage used in offline alignment to...

This paper presents a parallel real-time sound source separation system for decomposing an audio signal captured with a single microphone in so many audio signals as the number of instruments that are really playing. This approach is usually known as Soundprism. The application scenario of the system is for a concert hall in which users, instead of...

Determining whether a given algebra is commutative or not is important in the study of these algebraic objects in general and in the classification of semifields in particular. The best classical (i.e. non‐quantum) algorithm for this task has a running time which is or order O(n³), where n is the dimension of the algebra. To reduce this cost, in th...

In order to define management and marketing strategies, farmers need adequate knowledge about future yield with the greatest possible accuracy and anticipation. In citrus orchards, greater variability and non-normality of yield distributions complicate the early estimation of fruit production. This study was conducted with the objective of developi...

Quantum walks provide a framework for the construction of quantum algorithms. Based on this approach, we consider different walks for testing the commutativity of a finite dimensional algebra. In particular, we consider Szegedy's and Santos’ quantum walks constructed from complete and torus graphs. Results of numerical experiments are presented, sh...

Substitution boxes (S-boxes) are an important part of the design of block ciphers. They provide nonlinearity and so the security of the cipher depends strongly on them. Some block ciphers use S-boxes given by lookup tables (e.g., DES) where as others use S-boxes obtained from finite field operations (e.g., AES). As a generalization of the latter, f...

Precision Agriculture entails the appropriate management of the inherent variability of soil and crops, resulting in an increase of economic benefits and a reduction of environmental impact. However, site-specific treatments require maps of the soil variability to identify areas of land that share similar properties. In order to produce these maps,...

An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) v...

In Precision Agriculture one of the basic tasks is the classification of land zones in either arable or non-arable land. Several studies have been conducted using data obtained from soil analysis or local exploration of the parcels. However, sometimes only data from satellite images are available and then the problem not only becomes more challengi...

Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodolog...

Farm-Oriented Open Data in Europe will provide specific and high-value applications and services for the support in the planning and decision-making processes of farmers and other stakeholders groups related to the agricultural and environmental domains. Specifically, smart services are based on machine learning algorithms and other artificial inte...

One of the first steps in the application of precision agriculture techniques to a particular geographical zone is the task of land delimitation: determining which regions share similar soil properties and can (and should) be treated in a uniform way. In particular, automatic land delimitation is focused on providing delimitations from different da...

The delimitation of crop land areas grouping zones that share similar soil properties is a key factor in the precision agriculture context. However automatic land delimitation is a challenging task. We propose automatically delimit the zones based on remote sensed reflectivity and we study how the temporal resolution affects to this delimitation. I...

The combined monitoring-based and modelling-based priority setting (COMMPS), provides a procedure for the identification of priority hazardous substances outlined in the Working Document (ENV/191000/01 of 16 January 2001). This procedure is based on scoring a set of criteria, which individually make substances more or less hazardous. The way scores...

This research work presents a method of daily air pollution modeling by using support vector machine (SVM) technique in Oviedo urban area (Northern Spain) at local scale. Hazardous air pollutants or toxic air contaminants refer to any substances that may cause or contribute to an increase in mortality or in serious illness, or that may pose a prese...

In this paper, a highly demanding computer-assisted classification of four-dimensional finite semifields over the field 𝔽7 is provided. The techniques considered to overcome the difficulties in the management of the large data processed are explained.

A concrete construction of a commutative semifield of order 3 5 is introduced. This semifield is proved to be not isotopic to F 35 or Albert's twisted fields of such an order. It is shown that it is equivalent up to the action of the symmetric group S 3 neither to any of those semifields nor to Coulter-Matthews or Ding-Yuan semifields with 3 5 elem...

In this paper we deal with the problem of obtaining a random procedure for generating fuzzy measures. We use the fact that the polytope of fuzzy measures is an order polytope, so that it has special properties that allow to build a uniform algorithm. First, we derive an exact procedure based on an existing procedure to generate random linear extens...

This work develops a decision-supported system based on machine learning and scoring measures to discover the kind of female urinary incontinence (FUI) of a given patient. This system has two main branches. Each patient is characterized by a set of features (age, weight, number of childbirths, etc.). The first task consists of selecting the feature...

Finite semifields (finite non-necessarily associative division rings) have traditionally been considered in the context of finite geometries (they coordinatize projective semifield planes). New applications to the coding theory, combinatorics and the graph theory have broadened the potential interest in these rings. We show recent progress in the s...

This work presents a method of monthly air pollution modelling by using support vector machine (SVM) technique in the city of Oviedo (Spain). Hazardous air pollutants or toxic air contaminants refer to any substances that may cause or contribute to an increase in mortality or in serious illness, or that may pose a present or potential hazard to hum...

In this paper we study some properties of the polytope of belief functions on a finite referential. These properties can be used in the problem of identification of a belief function from sample data. More concretely, we study the set of isometries, the set of invariant measures and the adjacency structure. From these results, we prove that the pol...

Finite nonassociative division algebras (i.e., finite semifields) with 243 elements are completely classified. Comment: 6 pages, 3 tables

In this paper we study the adjacency structure of the order polytope of a poset. For a given poset, we determine whether two vertices in the corresponding order polytope are adjacent. This is done through filters in the original poset. We also prove that checking adjacency between two vertices can be done in quadratic time on the number of elements...

In this paper we study the group of isometries over the order polytope of a poset. We provide a result that characterizes any isometry based on the order structure in the original poset. From this result we provide upper bounds for the number of isometries over the order polytope in terms of its number of connected components. Finally, as an exampl...

The family ofk-additive measures has been introduced as a midterm between probabilities and general fuzzy measures and finds a wide number of applications in practice. However, its struc- ture is different from other families of fuzzy measures and is cer- tainly more complex (for instance, its vertices are not always {0,1}- valued), so it has not b...

A finite semifield D is a finite nonassociative ring with identity such that the set D∗=D∖{0} is closed under the product. In this paper we obtain a computer-assisted description of all semifields of order 64, which completes the classification of finite semifields of order at most 125.

In this paper the performance of the Set Cover (SC) Feature Selection (FS) method for Text Categorisation (TC) and Spam Detection problems is studied. Several variants of the original method are presented either to overcome the drawback of the unbalanced problems which are usually present in TC or to increase the efficiency. The behaviour of the al...

In this paper we present some results concerning the vertices of the set of fuzzy measures being at most k-additive. We provide an algorithm to compute them. We give some examples of the results obtained with this algorithm and give lower bounds on the number of vertices for the (n−1)-additive(n−1)-additive case, proving that it grows much faster t...

In this paper we deal with the problem of studying the structure of the polytope of fuzzy measures for finite referential sets. We prove that the diameter of the polytope of fuzzy measures is 3 for referentials of 3 elements or more. We also show that the polytope is combinatorial, whence we deduce that the adjacency graph of fuzzy measures is Hami...

Text Categorisation (TC) consists of automatically assigning documents to a set of prefixed categories. It usually involves the management of a huge number of features. Some of them are irrelevant or noisy which mislead the classifiers. Thus, they are reduced to increase the efficiency and effectiveness of the classification. In this paper we propo...

A finite semifield $D$ is a finite nonassociative ring with identity such that the set $D^*=D\setminus\{0\}$ is closed under the product. In this paper we obtain a computer-assisted description of all 64-element finite semifields, which completes the classification of finite semifields of order 125 or less.

In this paper we deal with the problem of studying the structure of the polytope of non-additive measures for finite referential sets. We give a necessary and sufficient condition for two extreme points of this polytope to be adjacent. We also show that it is possible to find out in polynomial time whether two vertices are adjacent. These results c...

A finite semifield is a finite nonassociative ring with identity such that the set of its nonzero elements is closed under the product. From any finite semifield a projective plane can be constructed. In this paper we obtain new semifield planes of orders 81 by means of computational methods. These computer-assisted results yield to a complete clas...

The generation of fuzzy measures is an important question arising in the practical use of these operators. In this paper, we deal with the problem of developing a random generator of fuzzy measures. More concretely, we study some of the properties that any random generator should satisfy. These properties lead to some theoretical problems concernin...

Feature Selection is an important task within Text Categorization, where irrelevant or noisy features are usually present, causing a lost in the performance of the classifiers. Feature Selection in Text Categorization has usually been performed using a filtering approach based on selecting the features with highest score according to certain measur...

Non-additive measures are a valuable tool to model many different problems arising in real situations. However, two important difficulties appear in their practical use: the complexity of the measures and their identification from sample data. For the first problem, additional conditions are imposed, leading to different subfamilies of non-additive...

In this paper, we introduce a method for the identification of fuzzy measures from sample data. It is implemented using genetic algorithms and is flexible enough to allow the use of different subfamilies of fuzzy measures for the learning, as k-additive or p-symmetric measures. The experiments performed to test the algorithm suggest that it is robu...

Text Categorization, which consists of automatically assigning documents to a set of categories, usually involves the management of a huge number of features. Most of them are irrelevant or introduce noise which misleads the classifiers. Thus, feature reduction is often performed in order to increase the efficiency and effectiveness of the classifi...

A common way of performing Feature Selection in Text Categorization consists in keeping the features with highest score according to certain measures, like linear ones which have been successfully proposed in [1]. Its disadvantage is that they need to previously determine the parameter which defines them. Until now, this drawback has been overcome...

The generation of fuzzy measures is an important problem arising in the practical use of these operators. In this paper we deal with the problem of developing a random generator of fuzzy measures. More concretely, we study some of the properties that any random generator should satisfy. These properties lead to some the-oretical problems that we ta...

Text categorization, which consists of automatically assigning documents to a set of categories, usually involves the management of a huge number of features. Most of them are irrelevant and others introduce noise which could mislead the classifiers. Thus, feature reduction is often performed in order to increase the efficiency and effectiveness of...