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Abstract Devising an efficient exploration of the search space is one of the key challenges in the design of combinatorial optimization algorithms. Here, we introduce the Generator-Enhanced Optimization (GEO) strategy: a framework that leverages any generative model (classical, quantum, or quantum-inspired) to solve optimization problems. We focus on a quantum-inspired version of GEO relying on tensor-network Born machines, and referred to hereafter as TN-GEO. To illustrate our results, we run these benchmarks in the context of the canonical cardinality-constrained portfolio optimization problem by constructing instances from the S&P 500 and several other financial stock indexes, and demonstrate how the generalization capabilities of these quantum-inspired generative models can provide real value in the context of an industrial application. We also comprehensively compare state-of-the-art algorithms and show that TN-GEO is among the best; a remarkable outcome given the solvers used in the comparison have been fine-tuned for decades in this real-world industrial application. Also, a promising step toward a practical advantage with quantum-inspired models and, subsequently, with quantum generative models

Abstract Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in the near term. In this study, we build over an existing framework for evaluating the generalization performance of generative models, and we establish the first quantitative comparative race towards practical quantum advantage (PQA) between classical and quantum generative models, namely Quantum Circuit Born Machines (QCBMs), Transformers (TFs), Recurrent Neural Networks (RNNs), Variational Autoencoders (VAEs), and Wasserstein Generative Adversarial Networks (WGANs). After defining four types of PQAs scenarios, we focus on what we refer to as potential PQA, aiming to compare quantum models with the best-known classical algorithms for the task at hand. We let the models race on a well-defined and application-relevant competition setting, where we illustrate and demonstrate our framework on 20 variables (qubits) generative modeling task. Our results suggest that QCBMs are more efficient in the data-limited regime than the other state-of-the-art classical generative models. Such a feature is highly desirable in a wide range of real-world applications where the available data is scarce.

Abstract Parametrized quantum circuits (PQCs) represent a promising framework for using present-day quantum hardware to solve diverse problems in materials science, quantum chemistry, and machine learning. We introduce a “synergistic” approach that addresses two prominent issues with these models: the prevalence of barren plateaus in PQC optimization landscapes, and the difficulty to outperform state-of-the-art classical algorithms. This framework first uses classical resources to compute a tensor network encoding a high-quality solution, and then converts this classical output into a PQC which can be further improved using quantum resources. We provide numerical evidence that this framework effectively mitigates barren plateaus in systems of up to 100 qubits using only moderate classical resources, with overall performance improving as more classical or quantum resources are employed. We believe our results highlight that classical simulation methods are not an obstacle to overcome in demonstrating practically useful quantum advantage, but rather can help quantum methods find their way.

La pandemia de la COVID-19 ha generado una crisis global y obligado a ejercicios de investigación de coyuntura. En Colombia las microempresas son más del 90% del tejido empresarial y tienen una tasa de supervivencia de menos del 40%. Este estudio cualitativo explora cómo un grupo de microempresas del sector industrial afrontaron los desafíos de la COVID-19. El trabajo de campo se realizó aplicando una entrevista semiestructura a una muestra de 50 microempresas formalizadas mediante registro mercantil. Los datos se procesaron en el software Nvivo con cuatro categorías de análisis: impactos, apoyos estatales, estrategias para afrontar la crisis y decisiones de futuro. Los resultados evidencian cómo la COVID-19 hizo visible un dilema que parecía obsoleto: la tensión entre solidaridad y flexibilidad en el mundo del trabajo. Además, se encontró una tendencia hacia la transformación digital básica y al ajuste en los modelos de negocios con fuertes restricciones financieras y de operación por insuficiencia del apoyo estatal. Se concluye que el sector microempresarial posee lógicas de gerencia muy susceptibles a las coyunturas socioeconómicas expresadas en tensiones entre la formalidad y la informalidad.

La presente investigación tiene como objetivo interpretar los antecedentes y consecuentes de la responsabilidad social empresarial en empresas del sector industrial de Colombia. La investigación se realiza a través de una metodología cualitativa utilizando la encuesta semiestructurada a profundidad. Los datos se analizan en el software en NVivo utilizando cuatro categorías de análisis. Los resultados aportan evidencia al campo emergente de la responsabilidad social en países en desarrollo. Se encuentra que la responsabilidad social empresarial es antecedida por un sentido de deber moral y filantrópico centrado en valores de los empresarios fundadores, por la necesidad de adquirir licencias sociales para operar en territorios en conflicto, por la necesidad de fortalecer las relaciones con los principales grupos de interés primarios y por la necesidad de llenar vacíos institucionales. La responsabilidad social empresarial genera consecuentes en el diseño de modelos de negocio hacia formas hibridas y de creación de valor compartido, amplía los niveles de relacionamiento con grupos de interés secundarios como las instituciones locales, las ONGs, o el entorno medio ambiental en crisis, y modifica los modelos de gobernanza corporativa al involucrar fehacientemente el proceso de rendición de cuentas cumpliendo estándares internacionales.

Constrained combinatorial optimization problems abound in industry, from portfolio optimization to logistics. One of the major roadblocks in solving these problems is the presence of non-trivial hard constraints which limit the valid search space. In some heuristic solvers, these are typically addressed by introducing certain Lagrange multipliers in the cost function, by relaxing them in some way, or worse yet, by generating many samples and only keeping valid ones, which leads to very expensive and inefficient searches. In this work, we encode arbitrary integer-valued equality constraints of the form $A \vec{x} = \vec{b}$ , directly into U (1) symmetric tensor networks (TNs) and leverage their applicability as quantum-inspired generative models to assist in the search of solutions to combinatorial optimization problems within the generator-enhanced optimization framework of Alcazar et al (2021 arXiv: 2101.06250 ). This allows us to exploit the generalization capabilities of TN generative models while constraining them so that they only output valid samples. Our constrained TN generative model efficiently captures the constraints by reducing number of parameters and computational costs. We find that at tasks with constraints given by arbitrary equalities, symmetric matrix product states outperform their standard unconstrained counterparts at finding novel and better solutions to combinatorial optimization problems.

It is believed that one of the first useful applications for a quantum computer will be the preparation of groundstates of molecular Hamiltonians. A crucial task involving state preparation and readout is obtaining physical observables of such states, which are typically estimated using projective measurements on the qubits. At present, measurement data is costly and time-consuming to obtain on any quantum computing architecture, which has significant consequences for the statistical errors of estimators. In this paper, we adapt common neural network models (restricted Boltzmann machines and recurrent neural networks) to learn complex groundstate wavefunctions for several prototypical molecular qubit Hamiltonians from typical measurement data. By relating the accuracy ɛ of the reconstructed groundstate energy to the number of measurements, we find that using a neural network model provides a robust improvement over using single-copy measurement outcomes alone to reconstruct observables. This enhancement yields an asymptotic scaling near ɛ ^−1 for the model-based approaches, as opposed to ɛ ^−2 in the case of classical shadow tomography.

Generating high-quality data (e.g., images or video) is one of the most exciting and challenging frontiers in unsupervised machine learning. Utilizing quantum computers in such tasks to potentially enhance conventional machine-learning algorithms has emerged as a promising application but poses big challenges due to the limited number of qubits and the level of gate noise in available devices. In this work, we provide the first practical and experimental implementation of a quantum-classical generative algorithm capable of generating high-resolution images of handwritten digits with state-of-the-art gate-based quantum computers. In our quantum-assisted machine-learning framework, we implement a quantum-circuit-based generative model to learn and sample the prior distribution of a generative adversarial network. We introduce a multibasis technique which leverages the unique possibility of measuring quantum states in different bases, hence enhancing the expressivity of the prior distribution. We train this hybrid algorithm on an ion-trap device based on ^{171}Yb^{+} ion qubits to generate high-quality images and quantitatively outperform comparable classical generative adversarial networks trained on the popular MNIST dataset for handwritten digits.

La literatura en management ha revelado que hay una brecha conceptual, que deriva a la práctica empresarial, entre los conceptos de sostenibilidad organizacional (micro-dimensión) y la sostenibilidad ecológica o desarrollo sostenible (macro-dimensión). Este artículo de reflexión llama la atención sobre la brecha identificada, mostrando algunos de los desafíos que esta separación demanda a las organizaciones. Se argumenta que las alianzas intersectoriales, la innovación social, y los negocios híbridos son formas organizacionales emergentes, basadas en la colaboración, que aportan al cierre de la brecha. La discusión sobre la distancia entre los enfoques de la sostenibilidad tipo valor compartido (inside-out) y los enfoques de sostenibilidad con foco en el bien común (outside-in), se ejemplifica con formas organizacionales emergentes en el contexto colombiano, con un énfasis en organizaciones con incidencia en la construcción de paz.

This paper explores the thesis associating the adoption of Corporate Social Responsibility models with implementing Pro-Peace practices in scenarios of conflict and post-conflict. This work is carried out under qualitative focus and exploratory scope. Four interviews were applied to large companies who have adopted Corporate Social Responsibility models and two interviews to Associations promoting Corporate Social Responsibility in Colombia. Evidence supporting this thesis was found and its understanding was dug into when considering that Corporate Social Responsibility, as a concept, has migrated towards Creating Shared Value and Business Sustainability. This study bears the limitations associated to determining a theoretical sample and the bias of selection it implies. From this research is derived that if companies in Colombia wish to promote Pro-Peace practices, they must become involved in management models based on Corporate Social Responsibility.

This study explores how corporate social responsibility (CSR) managers in large companies conceive the business–society interface using a CSR paradigm heuristic model. The research applies a critical management studies perspective, adopting a qualitative approach. We analyze the speeches of 25 CSR managers from large companies representing four economic sectors of an emerging economy. The paradigmatic heuristic model proposes four perspectives regarding CSR, which include functionalist, constructivist, culturalist, and socio‐political paradigms. We validate the proposed heuristic model, revealing the existence of transition zones and overlapping CSR management discourses. We found that there is no single or paradigmatic discourse of CSR among the four economic sectors analyzed. In Colombia, an emerging country, new CSR approaches and discourses are uncovered that can contribute to future contextualized and contingent research in regions with complex business–society interfaces. [ABSTRACT FROM AUTHOR]

El diseño organizacional y la teoría basada en los recursos han sido las dos áreas de la economía de la empresa que más desarrollo e impacto en la gerencia, y en el estado del arte de la disciplina, han tenido durante los últimos 15 años. Este documento aborda desde una perspectiva comparada ambos temas y encuentra una estrecha relación de mutuo apoyo conceptual. Es importante precisar que el presente documento no es una revisión de la literatura sobre diseño o arquitectura organizacional; no obstante se soporta en un conjunto de lecturas centradas en dicha temática. En este sentido, el objetivo del documento es hacer una reflexión crítica, planteando unas hipótesis de trabajo y argumentando su elaboración. La literatura sobre dirección estratégica tiene como uno de sus soportes disciplinares la denominada teoría (visión) de la empresa basada en los recursos (The Resource-Based View of the Firm, RBV) y defiende una lógica implícita de causalidad, al considerar la estructura organizacional como una consecuencia de la estrategia empresarial. Una visión crítica de la arquitectura organizacional contrasta la causalidad estrategia → estructura y puede explicar un vacío en la RBV, cuando ésta trata de explicar el tránsito del concepto de recurso a capacidad, haciendo alusión a un necesario proceso de integración de recursos básicos. Este documento plantea, entonces, la hipótesis de que la arquitectura organizacional es una forma de explicar la conformación de capacidades empresariales y, desde su argumentación, muestra cómo la causalidad → estrategia estructura se puede entender en forma inversa.

El concepto de «consumo socialmente responsable» (CSR) tiene una importante tradición en la literatura de mercadeo y recientemente en la de responsabilidad social empresarial. Sin embargo, el carácter complejo y dinámico del concepto hace relevante un debate sobre su medición. El presente artículo aporta una revisión de la literatura de forma comprensiva sobre el CSR guiada por la pregunta sobre la medición. La metodología utilizada parte de la revisión de los artículos seminales, para progresivamente sesgar la búsqueda hacia artículos en revistas de alto impacto. Se logró identificar diferentes etapas en los modelos de medida y precisar los debates actuales centrados en el papel de la responsabilidad social, y de la incidencia del contexto socioeconómico y cultural en el consumo.

Mainstream machine-learning techniques such as deep learning and probabilistic programming rely heavily on sampling from generally intractable probability distributions. There is increasing interest in the potential advantages of using quantum computing technologies as sampling engines to speed up these tasks or to make them more effective. However, some pressing challenges in state-of-the-art quantum annealers have to be overcome before we can assess their actual performance. The sparse connectivity, resulting from the local interaction between quantum bits in physical hardware implementations, is considered the most severe limitation to the quality of constructing powerful generative unsupervised machine-learning models. Here, we use embedding techniques to add redundancy to data sets, allowing us to increase the modeling capacity of quantum annealers. We illustrate our findings by training hardware-embedded graphical models on a binarized data set of handwritten digits and two synthetic data sets in experiments with up to 940 quantum bits. Our model can be trained in quantum hardware without full knowledge of the effective parameters specifying the corresponding quantum Gibbs-like distribution; therefore, this approach avoids the need to infer the effective temperature at each iteration, speeding up learning; it also mitigates the effect of noise in the control parameters, making it robust to deviations from the reference Gibbs distribution. Our approach demonstrates the feasibility of using quantum annealers for implementing generative models, and it provides a suitable framework for benchmarking these quantum technologies on machine-learning-related tasks.

Copyright of Revista Venezolana de Gerencia (RVG) is the property of Revista de Filosofia-Universidad del Zulia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

El diseño organizacional y la teoría basada en los recursos han sido las dos áreas de la economía de la empresa que más desarrollo e impacto en la gerencia, y en el estado del arte de la disciplina, han tenido durante los últimos 15 años. Este documento aborda desde una perspectiva comparada ambos temas y encuentra una estrecha relación de mutuo apoyo conceptual. Es importante precisar que el presente documento no es una revisión de la literatura sobre diseño o arquitectura organizacional; no obstante se soporta en un conjunto de lecturas centradas en dicha temática. En este sentido, el objetivo del documento es hacer una reflexión crítica, planteando unas hipótesis de trabajo y argumentando su elaboración. La literatura sobre dirección estratégica tiene como uno de sus soportes disciplinares la denominada teoría (visión) de la empresa basada en los recursos (The Resource-Based View of the Firm, RBV) y defiende una lógica implícita de causalidad, al considerar la estructura organizacional como una consecuencia de la estrategia empresarial. Una visión crítica de la arquitectura organizacional contrasta la causalidad estrategia → estructura y puede explicar un vacío en la RBV, cuando ésta trata de explicar el tránsito del concepto de recurso a capacidad, haciendo alusión a un necesario proceso de integración de recursos básicos. Este documento plantea, entonces, la hipótesis de que la arquitectura organizacional es una forma de explicar la conformación de capacidades empresariales y, desde su argumentación, muestra cómo la causalidad → estrategia estructura se puede entender en forma inversa.

Copyright of Revista Venezolana de Gerencia (RVG) is the property of Revista de Filosofia-Universidad del Zulia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The competitive environment of universities has increased the application of managerial practices such as human resource management. However, little research exists regarding the effects of these practices on knowledge workers. The study attempts to contribute to fill this gap, examining the effect of high-performance work practices (HPWP) on academic research productivity (ARP). A survey was completed by 442 researchers and the analysis supported a positive relationship between the adoption of HPWP and ARP. Specifically, HPWP promoting education, training and autonomy, and teamwork are better antecedents of ARP than practices focusing on performance management, reward systems, and selection. [ABSTRACT FROM AUTHOR]

A conceptually appealing and computationally economical course-grained molecular-orbital (MO) theory for extended quasilinear molecular heterostructures is presented. The formalism, which is based on a straightforward adaptation, by including explicitly the vacuum, of the envelope-function approximation widely employed in solid-state physics leads to a mapping of the three-dimensional single-particle eigenvalue equations into simple one-dimensional hole and electron Schrödinger-like equations with piecewise-constant effective potentials and masses. The eigenfunctions of these equations are envelope MO's in which the short-wavelength oscillations present in the full MO's, associated with the atomistic details of the molecular potential, are smoothed out automatically. The approach is illustrated by calculating the envelope MO's of high-lying occupied and low-lying virtual π states in prototypical nanometric heterostructures constituted by oligomers of polyacetylene and polydiacetylene. Comparison with atomistic electronic-structure calculations reveals that the envelope-MO energies agree very well with the energies of the π MO's and that the envelope MO's describe precisely the long-wavelength variations of the π MO's. This envelope MO theory, which is generalizable to extended systems of any dimensionality, is seen to provide a useful tool for the qualitative interpretation and quantitative prediction of the single-particle quantum states in mesoscopic molecular structures and the design of nanometric molecular devices with tailored energy levels and wavefunctions. [ABSTRACT FROM AUTHOR]

The growing diffusion and acceptance in the business world of Total Quality Management (TQM) has attracted greater interest on the part of academia. Although fundamental questions focus on how the different dimensions of TQM can bring about better business performance, a more recent recurring issue pertains to the relationship between TQM and technological innovation and whether technological innovation might provide a source of competitive advantage. Unfortunately, from both theoretical and empirical perspectives, the relationship between TQM and technological innovation appears contradictory and complex. This paper argues that the relationship might be better understood from the contingent perspective of strategic management and thus proposes a multidimensional intervening variable in the relationship, called Business Innovation Capability (BIC). An empirical study of 105 Spanish industrial firms reveals that the effect of some business practices suggested by TQM on technological innovation can be better understood when BIC dimensions are taken into account. [ABSTRACT FROM AUTHOR]

This study constructs a measurement scale for Socially Responsible Consumption in the particular context of Colombia. It uses a mixed qualitative and quantitative methodological approach, beginning with four focus groups and ending with a quantitative validation exercise employing Exploratory Factor Analysis. The result is a Socially Responsible Consumption measurement scale consisting of four dimensions that reflect paradigms found in the existing literature. These are, however, expressed differently in Colombia. In particular, Socially Responsible Consumption involves consumer behavior that favors corporate social responsibility practices and the rational consumption of resources and products while recognizing the importance of maintaining a healthy lifestyle through healthcare. [ABSTRACT FROM AUTHOR]

The difficulty of simulating quantum systems, well known to quantum chemists, prompted the idea of quantum computation. One can avoid the steep scaling associated with the exact simulation of increasingly large quantum systems on conventional computers, by mapping the quantum system to another, more controllable one. In this review, we discuss to what extent the ideas in quantum computation, now a well-established field, have been applied to chemical problems. We describe algorithms that achieve significant advantages for the electronic-structure problem, the simulation of chemical dynamics, protein folding, and other tasks. Although theory is still ahead of experiment, we outline recent advances that have led to the first chemical calculations on small quantum information processors. [ABSTRACT FROM AUTHOR]

Innovative management models consider human resources to be a key dimension in the innovation process and its performance. In particular, the knowledge of the people making up the staff and their creativity is fundamental. However, scant study has been made of what specific type of policies and practices in human resource management fosters better knowledge, attitudes and behaviour in the staff that will lead to the best performance in innovation. This paper studies the relationship between the policies and practices of human resource management from the viewpoint of total quality management and performance in innovation. Specifically, it is argued that there is a direct relationship, as well as a possible moderating effect, of strategic orientation towards innovation. An empirical study made of 106 Spanish industrial firms found no evidence of this moderating effect, although it did find evidence of a direct relationship and, in particular, of the positive effects of teamwork on technological innovation. [ABSTRACT FROM AUTHOR]

We introduce a method for the problem of learning the structure of a Bayesian network using the quantum adiabatic algorithm. We do so by introducing an efficient reformulation of a standard posterior-probability scoring function on graphs as a pseudo-Boolean function, which is equivalent to a system of 2-body Ising spins, as well as suitable penalty terms for enforcing the constraints necessary for the reformulation; our proposed method requires (n2) qubits for n Bayesian network variables. Furthermore, we prove lower bounds on the necessary weighting of these penalty terms. The logical structure resulting from the mapping has the appealing property that it is instance-independent for a given number of Bayesian network variables, as well as being independent of the number of data cases., Chemistry and Chemical Biology

Optimization problems associated with the interaction of linked particles are at the heart of polymer science, protein folding and other important problems in the physical sciences. In this review we explain how to recast these problems as constraint satisfaction problems such as linear programming, maximum satisfiability, and pseudo-boolean optimization. By encoding problems this way, one can leverage substantial insight and powerful solvers from the computer science community which studies constraint programming for diverse applications such as logistics, scheduling, artificial intelligence, and circuit design. We demonstrate how to constrain and embed lattice heteropolymer problems using several strategies. Each strikes a unique balance between number of constraints, complexity of constraints, and number of variables. In addition, each strategy has distinct advantages and disadvantages depending on problem size and available resources. Finally, we show how to reduce the locality of couplings in these energy functions so they can be realized as Hamiltonians on existing adiabatic quantum annealing machines., Chemistry and Chemical Biology

We studied the equilibrium conformations of a zinc porphyrin tweezer composed of two carboxylphenyl-functionalized zinc tetraphenyl porphyrin subunits connected by a 1,4-butyndiol spacer, which was suspended inside the amphiphilic regions of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) liposomes. By combining phase-modulation two-dimensional fluorescence spectroscopy (2D FS) with linear absorbance and fluorimetry, we determined that the zinc porphyrin tweezer adopts a mixture of folded and extended conformations in the membrane. By fitting an exciton-coupling model to a series of data sets recorded over a range of temperatures (17–85°C) and at different laser center wavelengths, we determined that the folded form of the tweezer is stabilized by a favorable change in the entropy of the local membrane environment. Our results provide insights toward understanding the balance of thermodynamic factors that govern molecular assembly in membranes., Chemistry and Chemical Biology