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Secret key exchange relies on the creation of correlated signals, serving as the raw resource for secure communication. Thermal states exhibit Hanbury Brown and Twiss correlations, which offer a promising avenue for generating such signals. In this paper, we present an experimental implementation of a central broadcast thermal-state quantum key distribution (QKD) protocol in the microwave region. Our objective is to showcase a straightforward method of QKD utilizing readily available broadcasting equipment. Unlike conventional approaches to thermal-state QKD, we leverage displaced thermal states. These states enable us to share the output of a thermal source among Alice, Bob, and Eve via both waveguide channels and free space. Through measurement and conversion into bit strings, our protocol produces key-ready bit strings without the need for specialized equipment. By harnessing the inherent noise in thermal broadcasts, our setup facilitates the recovery of distinct bit strings by all parties involved. [ABSTRACT FROM AUTHOR]

The paper considers a strategy to decrease the error of the two-mode entanglement transformation Controlled-Z by introducing non-Gaussian nodes in the cluster. Non-Gaussian nodes are obtained by using a cubic phase gate. We have shown that this strategy can significantly decrease the transformation error. The considered implementation of the Controlled-Z operation contains a teleportation scheme with the cubic phase gate. We have shown that the correct selection of phases during measurement allows for lower errors than in the initial teleportation protocol with the cubic phase gate and the original teleportation protocol. [ABSTRACT FROM AUTHOR]

It has been demonstrated that the critical point of the phase transition in scalar quantum field theory with a quartic interaction in one space dimension can be approximated via a Gaussian Effective Potential (GEP). We discuss how this critical point can be estimated using quantum hardware. Performing quantum computations with various lattice sizes, we obtain evidence of a transition from a symmetric to a symmetry-broken phase using both discrete- and continuous-variable quantum computation. The ten-site case is implemented on IBM quantum hardware using the Variational Quantum Eigensolver algorithm to minimize the GEP and identify lattice level crossings. These are extrapolated via simulations to find the continuum critical point. [ABSTRACT FROM AUTHOR]

Secret key exchange relies on the creation of correlated signals, serving as the raw resource for secure communication. Thermal states exhibit Hanbury Brown and Twiss correlations, which offer a promising avenue for generating such signals. In this paper, we present an experimental implementation of a central broadcast thermal-state quantum key distribution (QKD) protocol in the microwave region. Our objective is to showcase a straightforward method of QKD utilizing readily available broadcasting equipment. Unlike conventional approaches to thermal-state QKD, we leverage displaced thermal states. These states enable us to share the output of a thermal source among Alice, Bob, and Eve via both waveguide channels and free space. Through measurement and conversion into bit strings, our protocol produces key-ready bit strings without the need for specialized equipment. By harnessing the inherent noise in thermal broadcasts, our setup facilitates the recovery of distinct bit strings by all parties involved.

This article argues for a gradient approach to word order, which treats word order preferences, both within and across languages, as a continuous variable. Word order variability should be regarded as a basic assumption, rather than as something exceptional. Although this approach follows naturally from the emergentist usage-based view of language, we argue that it can be beneficial for all frameworks and linguistic domains, including language acquisition, processing, typology, language contact, language evolution and change, and formal approaches. Gradient approaches have been very fruitful in some domains, such as language processing, but their potential is not fully realized yet. This may be due to practical reasons. We discuss the most pressing methodological challenges in corpus-based and experimental research of word order and propose some practical solutions.

In this paper, we continue the study of the quantum cryptographic GG02 protocol, performed using the approach based on the subcarrier waves. We modify the scheme via heterodyne detection and perform security analysis for the full trusted hardware noise model in the presence of collective attacks with finite-key effects. It is shown that the system can potentially distribute the key even if the level of losses in the channel is above 9 dB. This result is consistent with the general technical level and comply with modern standards of practical CV-QKD systems. Finally, the system under consideration fully meets the criterion of composability.

Healthcare, food, and energy are the basic needs of life in the globalizing world. Humankind's quest to maintain a healthy life and find ways to meet its needs has continued since its existence. The causal relations between the healthcare, food, and energy sectors are explored using data from the pandemic when COVID-19 was a global risk, and human health sustainability underwent a complicated process. It aims to examine the interaction between the healthcare, food, and energy sectors and model the causal relationship within the framework of probabilistic dependencies. For this purpose, the relationships between these sectors during the pandemic are modeled via Bayesian Networks (BNs). This highly successful inference method makes the complex structure of causal relationships graphically understandable. The data consists of stock returns at the end of the business day between March 11, 2020, when the pandemic was declared, and December 26, 2022. Data on 13 stocks actively traded on the Istanbul Stock Exchange (BIST) during the 700 days were obtained from tr.investing.com. Causal modeling uses Gaussian Bayesian Networks (GBNs) for continuous variables. To make the inferences drawn from the data more successful and minimize the loss of information, the GBN model is built with continuous variables. The posterior Probability Density Functions (PDFs) of the stocks in the network are constructed over the structure of the Directed Acyclic Graphs (DAG) of the BNs, and inferences are made by querying possible cases (tips). Markov Chain Monte Carlo (MCMC) simulations are performed with the posterior PDFs, and measures of the central tendency of the stocks are calculated. GBNs are used to generate daily return estimates for ULKER with the lowest MSE (1.06e-03) and RMSE (3.22e-02) values and ULUUN with the highest MSE (3.43e-03) and RMSE (5.83e-02) values.

Visualization is a key aspect of communicating the results of any study aiming to estimate causal effects. In studies with time-to-event outcomes, the most popular visualization approach is depicting survival curves stratified by the variable of interest. This approach cannot be used when the variable of interest is continuous. Simple workarounds, such as categorizing the continuous covariate and plotting survival curves for each category, can result in misleading depictions of the main effects. Instead, we propose a new graphic, the survival area plot, to directly depict the survival probability over time and as a function of a continuous covariate simultaneously. This plot utilizes g-computation based on a suitable time-to-event model to obtain the relevant estimates. Through the use of g-computation, those estimates can be adjusted for confounding without additional effort, allowing a causal interpretation under the standard causal identifiability assumptions. If those assumptions are not met, the proposed plot may still be used to depict noncausal associations. We illustrate and compare the proposed graphics to simpler alternatives using data from a large German observational study investigating the effect of the Ankle-Brachial Index on survival. To facilitate the usage of these plots, we additionally developed the contsurvplot R-package, which includes all methods discussed in this paper. [ABSTRACT FROM AUTHOR]

A new quantum private comparison protocol based on continuous-variable EPR entangled state and entanglement swapping technique is proposed. This protocol can achieve the size relation comparison of secret information between two remote parties with the help of a semi-trusted third party. At the same time, a simple linear optical communication protocol with Gaussian error correction is used to encode quantum states for reducing the impact of noise. A detailed security analysis shows that the proposed protocol can resist the external and internal attacks. [ABSTRACT FROM AUTHOR]

Continuous-variable quantum key distribution (CV-QKD) provides a theoretical unconditionally secure solution to distribute symmetric keys among users in a communication network. However, the practical devices used to implement these systems are intrinsically imperfect, and, as a result, open the door to eavesdropper attacks. In this work, we study the impact of transmitter stage imperfections on the performance and security of a Discrete Modulated (DM) CV-QKD system using M-symbol Quadrature Amplitude Modulation (M-QAM) and Amplitude and Phase Shift Keying (M-APSK) coupled with Probabilistic Constellation Shaping (PCS). Assuming two different modulation stage topologies, we first deform the constellations and then evaluate the secure key rate achievable with the deformed constellation. The presented results show that, due to the erroneously estimated channel parameters, non-monitored imbalances greatly reduce the system's performance, with situations where Bob and Alice estimate that no secure bits can be obtained while the real value of the key rate is still positive. Our results show the importance of monitoring these constellation imbalances and show that the optimal constellation may vary depending on the degree of device imperfection. [ABSTRACT FROM AUTHOR]

Gaussian unitaries play a fundamental role in the field of continuous variables. In the general n mode, they may formulated by a second-order polynomial in the bosonic operators. Another important role related to Gaussian unitaries is played by the symplectic transformations in the phase space. The paper investigates the links between the two representations: the link from Hamiltonian to symplectic, governed by an exponential, and the link from symplectic to Hamiltonian, governed by a logarithm. Thus, an answer is given to the non-trivial question: which Hamiltonian produces a given symplectic representation? The complex instead of the traditional real symplectic representation is considered, with the advantage of getting compact and elegant relations. The application to the single, two, and three modes illustrates the theory. [ABSTRACT FROM AUTHOR]

This article describes the current technical level of developments in the field of continuous-variable quantum key distribution (CV-QKD). Various classifications are described, the criteria are analyzed, and the optimal protocol is selected. The analysis is focused around device-dependent schemes with a theoretical emphasis, and therefore, a detailed analysis of device-independent CV-QKD and side-channel attacks is out of the scope of the work. However, the latter, one way or another, is taken into account when describing possible classifications. The choice of the optimal protocol was carried out, first of all, from the potential possibility of integration into existing network telecommunication infrastructures. Predominantly, the general classification is carried out in such a way that it is possible to draw up a specific protocol, depending on the task of implementation.

Entanglement and non-Gaussianity are physical resources that are essential for a large number of quantum-optics protocols. Non-Gaussian entanglement is indispensable for quantum-computing advantage and outperforms its Gaussian counterparts in a number of quantum-information protocols. The characterization of non-Gaussian entanglement is a critical matter as it is in general highly demanding in terms of resources. We propose a simple protocol based on the Fisher information for witnessing entanglement in an important class of non-Gaussian entangled states: photon-subtracted states. We demonstrate that our protocol is relevant for the detection of non-Gaussian entanglement generated by multiple photon-subtraction and that it is experimentally feasible through homodyne detection.

Quantum correlations are a vital resource in advanced information processing based on quantum phenomena. Remarkably, the vacuum state of a quantum field may act as a key element for the generation of multipartite quantum entanglement. In this work, generation of genuine tripartite entangled state and its control is achieved by the use of the phase difference between two continuous pump tones. Control of the subspaces of the covariance matrix for tripartite bisqueezed state is demonstrated. Furthermore, by optimizing the phase relationships in a three‐tone pumping scheme genuine quadripartite entanglement of a generalized H‐graph state (H∼$\mathcal {\tilde{H}}$‐graph) is explored. This scheme provides a comprehensive control toolbox for the entanglement structure and allows to demonstrate, for first time to the authors' knowledge, genuine quadripartite entanglement of microwave modes. All experimental results are verified with numerical simulations of the nonlinear quantum Langevin equation. It is envisioned that quantum resources facilitated by multi‐pump configurations offer enhanced prospects for quantum data processing using parametric microwave cavities. [ABSTRACT FROM AUTHOR]

This article describes the current technical level of developments in the field of continuousvariable quantum key distribution (CV-QKD). Various classifications are described, the criteria are analyzed, and the optimal protocol is selected. The analysis is focused around device-dependent schemes with a theoretical emphasis, and therefore, a detailed analysis of device-independent CVQKD and side-channel attacks is out of the scope of the work. However, the latter, one way or another, is taken into account when describing possible classifications. The choice of the optimal protocol was carried out, first of all, from the potential possibility of integration into existing network telecommunication infrastructures. Predominantly, the general classification is carried out in such a way that it is possible to draw up a specific protocol, depending on the task of implementation. [ABSTRACT FROM AUTHOR]

Interventions, time, and continuous-valued variables are allpotentially powerful cues to causation. Furthermore, whenobserved over time, causal processes can contain feedbackand oscillatory dynamics that make inference hard. Wepresent a generative model and framework for causal infer-ence over continuous variables in continuous time based onOrnstein-Uhlenbeck processes. Our generative model pro-duces a stochastic sequence of evolving variable values thatmanifest many dynamical properties depending on the natureof the causal relationships, and a learner’s interventions (man-ual changes to the values of variables during a trial). Ourmodel is also invertible, allowing us to benchmark participantjudgments against an optimal model. We find that when in-teracting with systems acting according to this formalism peo-ple directly compare relationships between individual variablepairs rather than considering the full space of possible models,in accordance with a local computations model of causal learn-ing (e.g., Fernbach & Sloman, 2009). The formalism presentedhere provides researchers in causal cognition with a powerfulframework for studying dynamic systems and presents oppor-tunities for other areas in cognitive psychology such as controlproblems.

We address minimization of information leakage from continuous-variable quantum channels. It is known, that regime of minimum leakage can be accessible for the modulated signal states with variance equivalent to a shot noise, i.e., vacuum fluctuations, in the case of collective attacks. Here we derive the same condition for the individual attacks and analytically study the properties of the mutual information quantities in and out of this regime. We show that in such regime a joint measurement on the modes of a two-mode entangling cloner, being the optimal individual eavesdropping attack in a noisy Gaussian channel, is no more effective that independent measurements on the modes. Varying variance of the signal out of this regime, we observe the nontrivial statistical effects of either redundancy or synergy between the measurements of two modes of the entangling cloner. The result reveals the non-optimality of entangling cloner individual attack for sub-shot-noise modulated signals. Considering the communication between the cloner modes, we show the advantage of knowing the residual noise after its interaction with the cloner and extend the result to a two-cloner scheme. [ABSTRACT FROM AUTHOR]

Functional Distributed Constraint Optimization Problems (F-DCOPs) are a constraint processing framework for continuous variables in the multi-agent system. Particle swarm optimization-based F-DCOP (PFD) is a population-based algorithm to solve F-DCOP collaboratively. Although it can significantly reduce the computational overhead and memory requirements, its solution depends on the decision of root agent in the Breadth First Search (BFS) pseudo-tree and it is easy to fall into local optimum. To solve the above problems, this paper designed an improved PFD algorithm with Local Decision named PFD-LD, which effectively reduces the dependence on root agent through local decision. In addition, a mutation operator is used to avoid falling into local optimum. It is proved that PFD-LD is an anytime algorithm and local decision can expand the search of the solution space. Finally, the extensive experiments based on four types of benchmark problems show that the proposed algorithm outperforms state-of-the-art F-DCOP solving algorithms. [ABSTRACT FROM AUTHOR]

In this study, we analyse the efficiency of a protocol with discrete modulation of continuous variable non-Gaussian states, that is, the coherent states having the addition of one photon followed by the subtraction of one photon (PASCS). We calculate lower bounds of the asymptotic key rates against Gaussian collective attacks based on the fact that for sufficiently small modulation variances we remain close to the protocol with Gaussian modulation. We compare the results of a four-state protocol (quadrature phase-shift-keying) using PASCS with the ones using coherent states, and show that under the same environmental conditions, the former always outperforms the latter, allowing to increase the maximum possible distance for secret key generation. Interestingly, we find that for the protocol using discrete-modulated PASCS, the noisier the line, the better will be its performance compared to the protocol using coherent states, showing that continuous variable non-Gaussian states can be considerably more advantageous for performing quantum key distribution in non-ideal situations. [ABSTRACT FROM AUTHOR]

Complex system design problems, such as those involved in aerospace engineering, require the use of numerically costly simulation codes in order to predict the performance of the system to be designed. In this context, these codes are often embedded into an optimization process to provide the best design while satisfying the design constraints. Recently, new approaches, called Quality-Diversity, have been proposed in order to enhance the exploration of the design space and to provide a set of optimal diversified solutions with respect to some feature functions. These functions are interesting to assess trade-offs. Furthermore, complex design problems often involve mixed continuous, discrete, and categorical design variables allowing to take into account technological choices in the optimization problem. Existing Bayesian Quality-Diversity approaches suited for intensive high-fidelity simulations are not adapted to mixed variables constrained optimization problems. In order to overcome these limitations, a new Quality-Diversity methodology based on mixed variables Bayesian optimization strategy is proposed in the context of limited simulation budget. Using adapted covariance models and dedicated enrichment strategy for the Gaussian processes in Bayesian optimization, this approach allows to reduce the computational cost up to two orders of magnitude, with respect to classical Quality-Diversity approaches while dealing with discrete choices and the presence of constraints. The performance of the proposed method is assessed on a benchmark of analytical problems as well as on two aerospace system design problems highlighting its efficiency in terms of speed of convergence. The proposed approach provides valuable trade-offs for decision-markers for complex system design. [Display omitted] • Development of a Bayesian Quality-Diversity approach involving mixed variables. • Extension of MAP-Elites algorithms to deal with mixed variables and constraints. • Application on a benchmark of analytical problems and two aerospace design problems. [ABSTRACT FROM AUTHOR]

Gaussian unitaries play a fundamental role in the field of continuous variables. In the general n mode, they may formulated by a second-order polynomial in the bosonic operators. Another important role related to Gaussian unitaries is played by the symplectic transformations in the phase space. The paper investigates the links between the two representations: the link from Hamiltonian to symplectic, governed by an exponential, and the link from symplectic to Hamiltonian, governed by a logarithm. Thus, an answer is given to the non-trivial question: which Hamiltonian produces a given symplectic representation? The complex instead of the traditional real symplectic representation is considered, with the advantage of getting compact and elegant relations. The application to the single, two, and three modes illustrates the theory.

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species‐level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity. [ABSTRACT FROM AUTHOR]

The Teaching-Learning-Based Optimization (TLBO) algorithm is a new meta-heuristic algorithm which recently received more attention in various fields of science. The TLBO algorithm divided into two phases: Teacher phase and student phase; In the first phase a teacher tries to teach the student to improve the class level, then in the second phase, students increase their level by interacting among themselves. But, due to the lack of additional parameter to calculate the distance between the teacher and the mean of students, it is easily trapped at the local optimum and make it unable to reach the best global for some difficult problems. Since the Harmony Search (HS) algorithm has a strong exploration and it can explore all unknown places in the search space, it is an appropriate complement to improve the optimization process. Thus, based on these algorithms, they are merged to improve TLBO disadvantages for solving the structural problems. The objective function of the problems is the total weight of whole members which depends on the strength and displacement limits. Indeed, to avoid violating the limits, the penalty function applied in the form of stress and displacement limits. To show the superiority of the new hybrid algorithm to previous well-known methods, several benchmark truss structures are presented. The results of the hybrid algorithm indicate that the new algorithm has shown good performance.

Continuous-variable quantum key distribution (CV-QKD) provides a theoretical unconditionally secure solution to distribute symmetric keys among users in a communication network. However, the practical devices used to implement these systems are intrinsically imperfect, and, as a result, open the door to eavesdropper attacks. In this work, we show the impact of receiver device imperfections on the estimated channel parameters, performance and security of a CV-QKD system. The presented results show that, due to the erroneously estimated channel parameters, non-monitored imbalances can pose a security risk or even reduce the system's performance. Our results show the importance of monitoring these imbalances and hint at the possibility of compensating for some receiver imbalances by tuning other components. [ABSTRACT FROM AUTHOR]

We analyse a central broadcast continuous variable quantum key distribution protocol in which a beam produced by a thermal source is used to create a secret key between two parties, Alice and Bob. A beam splitter divides the initial beam into a pair of output beams, which are sent to Alice and Bob, with Eve intercepting Bob’s beam. We investigate the protocol in detail, calculating mutual informations through a pair of analytic methods and comparing the results to the outputs of a Monte Carlo simulation of the protocol. In a lossless system, we find that a lower bound on the key rate remains positive in the protocol under a beam splitter attack, provided Bob receives a nonzero proportion of the beam initially sent to him. This suggests that the thermal state protocol could be used experimentally to produce secure keys. [ABSTRACT FROM AUTHOR]

Bipartite quantum entanglement has numerous practical applications in quantum computation and communication. Here, we study the temporal evolution of bipartite entanglement of a two-mode Gaussian state at the output of a correlated spontaneous-emission laser. The lasing medium is coupled with a strong classical field and two quantized modes of the cavity field, which are initially considered in two arbitrary single-mode Gaussian states. The influence of various parameters of the system on the bipartite entanglement of the two-mode Gaussian state is analyzed in detail. In presence of the cavity damping rates, we show that the amount and the time evolution of entanglement increases with the nonclassicality of the initial states. However, the purity of the initial states shows the absence of obvious effects on the entanglement dynamics. Further, the time interval of entanglement enhances with the Rabi frequency of the classical pump field. In addition, the photon number statistics of the two evolved modes of the cavity field is studied. [ABSTRACT FROM AUTHOR]

We address minimization of information leakage from continuous-variable quantum channels. It is known, that regime of minimum leakage can be accessible for the modulated signal states with variance equivalent to a shot noise, i.e., vacuum fluctuations, in the case of collective attacks. Here we derive the same condition for the individual attacks and analytically study the properties of the mutual information quantities in and out of this regime. We show that in such regime a joint measurement on the modes of a two-mode entangling cloner, being the optimal individual eavesdropping attack in a noisy Gaussian channel, is no more effective that independent measurements on the modes. Varying variance of the signal out of this regime, we observe the nontrivial statistical effects of either redundancy or synergy between the measurements of two modes of the entangling cloner. The result reveals the non-optimality of entangling cloner individual attack for sub-shot-noise modulated signals. Considering the communication between the cloner modes, we show the advantage of knowing the residual noise after its interaction with the cloner and extend the result to a two-cloner scheme.

The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of structural equation models that is more robust to structural misspecifications than full information estimators. Previous studies have concentrated on endogenous variables that are all continuous (MIIV-2SLS) or all ordinal. We develop a unified MIIV approach that applies to a mixture of binary, ordinal, censored, or continuous endogenous observed variables. We include estimates of factor loadings, regression coefficients, variances, and covariances along with their asymptotic standard errors. In addition, we create new goodness of fit tests of the model and overidentification tests of single equations. Our simulation study shows that the proposed MIIV approach is more robust to structural misspecifications than diagonally weighted least squares (DWLS) and that both the goodness of fit model tests and the overidentification equations tests can detect structural misspecifications. We also find that the bias in asymptotic standard errors for the MIIV estimators of factor loadings and regression coefficients are often lower than the DWLS ones, though the differences are small in large samples. Our analysis shows that scaling indicators with low reliability can adversely affect the MIIV estimators. Also, using a small subset of MIIVs reduces small sample bias of coefficient estimates, but can lower the power of overidentification tests of equations. [ABSTRACT FROM AUTHOR]

This study aimed to apply the Markovian Model (MM) to obtain optimized operating rules for a hydropower reservoir to maximize its efficiency. In this study, a Markovian Control Model with continuous state space (MCM-CSS) is presented to analyze the climatological effects through stochastic integrals. The MCM-CSS compute the optimal policies of hydropower reservoir system over the Grijalva Hydropower System (GHS). The MCM-CSS can be described as follows: a) Historical data review, b) histograms of variables studied, c) state space analysis, d) action space analysis, e) admissible decision rule, f) expected benefit analysis. As a result, the optimal policy graphs were obtained. The result obtained in this research demonstrated the advantage of having applied a continuous space in reservoir inflow and water demand with the MMC-CSS method to avoid the uncertainness and inaccuracies in simulation results with a discrete space. Modified Svanidze's Method (MSM) is also employed to investigate their capabilities to predict streamflow over the GHS and mean energy generated. The hydrological monthly simulations were calibrated and validated at GHS station for the period 1952–2018. The main objective of the study is to simulate the optimal policies obtained with the MMC-CSS for continuous states using MSM in GHS. [ABSTRACT FROM AUTHOR]

With the integration of renewable energy-based sources and demand response initiatives, the distribution network has transformed into an active network with bidirectional flows. Network Reconfiguration (NR), i.e., changing network topology, is an alternative to minimize power loss in the distribution network with sectionalizing switches (normally closed) and tie-line switches (normally open). Due to the discrete nature of switches (on or off), the NR formulation is generally a mixed-integer NP-hard nonlinear problem. This paper proposes the first NR formulation for an unbalanced active distribution network with continuous variables to indicate switches' statuses in NR while considering mutual coupling between line impedances. The obtained solution provides the optimal real power and voltage magnitude settings of dispatchable Distributed Generators (DGs) and network topology for the minimum active power loss in the network. The proposed formulation considers all practical aspects of the distribution network, i.e., mutual coupling, load unbalances, angular unbalance, and the absence of one or two phases in a line section, which, otherwise, have not been considered together in previous formulations. Further, a novel convex relaxation for bus voltage phase angles avoids explicit voltage recovery. Compared to prior formulations, numeric results for unbalanced radial distribution networks showcase the proposed formulation's effectiveness. • NR for active unbalanced mutually coupled distribution networks is formulated. • The use of continuous switch status variables reduces the problem's complexity. • A novel convex relaxation is used, where bus voltage recovery is not required. • Effect of unbalances and mutual coupling is analyzed on NR and DGs' set points. [ABSTRACT FROM AUTHOR]

When predicting a certain subject-level variable (e.g., age in years) from measured biological data (e.g., structural MRI scans), the decoding algorithm does not always preserve the distribution of the variable to predict. In such a situation, distributional transformation (DT), i.e., mapping the predicted values to the variable's distribution in the training data, might improve decoding accuracy. Here, we tested the potential of DT within the 2019 Predictive Analytics Competition (PAC) which aimed at predicting chronological age of adult human subjects from structural MRI data. In a low-dimensional setting, i.e., with less features than observations, we applied multiple linear regression, support vector regression and deep neural networks for out-of-sample prediction of subject age. We found that (i) when the number of features is low, no method outperforms linear regression; and (ii) except when using deep regression, distributional transformation increases decoding performance, reducing the mean absolute error (MAE) by about half a year. We conclude that DT can be advantageous when predicting variables that are non-controlled, but have an underlying distribution in healthy or diseased populations. [ABSTRACT FROM AUTHOR]

Optimal coordination of directional overcurrent relays (DOCRs) in interconnected power systems is a highly constrained, non‐convex and non‐linear optimisation problem. In this study, use of a series of linear programming (LP) problems in a variable neighbourhood search (VNS) framework is proposed, in which pickup current settings can be considered either as continuous or discrete variables. Therefore, the proposed hybrid algorithm (VNS–LP) is suitable for coordination problem‐solving in a network with different types of DOCRs. Furthermore, two versions of the VNS algorithm are proposed, the first of which is very easy to implement, while, the other is somewhat more sophisticated, and at the same time much faster and possibly suitable for online coordination in smart grids applications. One advantage of the second algorithm is that it relies only on elementary arithmetic and requires low RAM, which makes it implementable in any low‐level programming environment. This, in turn, can increase the interoperability, which is of crucial importance when automating tasks. The efficiency of the proposed algorithm was investigated in several test systems. Numerical results indicate that the two proposed approaches outperform the previous methods. Moreover, the coordination problem is solved in a reasonably short time using a faster approach. [ABSTRACT FROM AUTHOR]

Quantity discrimination, the ability to identify, process, and respond to differences in number, has been shown in a variety of animal species and may have fitness value. In fish, the ability to distinguish between numerically different shoals has been well studied. However, little work has been devoted to the investigation of such ability in a foraging context. Nevertheless, angelfish (Pterophyllum scalare) have been previously shown to be able to discriminate numerically different sets of food items, with variables such as size and density of the food items playing important roles in making the choice. Here, we examine the possible role of other numerical and non-numerical variables. Using a spontaneous binary choice task, we contrasted sets of food items differing in specifically controlled ways: (1) different numerical size but equal inter-item distance; (2) different numerical size and different inter-item distance; and (3) identical total contour length and area occupied but different individual food size and inter-food distance between the contrasted food sets. In Experiment 1, angelfish were found to prefer the sets with a large number of food items. In Experiment 2, they preferred the numerically smaller sets with clustered items to the numerically larger sets with scattered items, but only when the sets were in the large number range (10 vs. 5 food items). Finally, in Experiment 3 fish preferred numerically smaller sets with large-sized and scattered food items in the large number range sets. We conclude that food item number, density, and size may not be considered individually by angelfish, but instead, the fish respond to all these factors attempting to maximize energy gained from eating the food while minimizing energy expenditure collecting and/or protecting the food.

By coherently combining advantages while largely avoiding limitations of two mainstream platforms, optical hybrid entanglement involving both discrete and continuous variables has recently garnered widespread attention and emerged as a promising idea for building heterogenous quantum networks. In contrast to previous results, here we propose a new scheme to remotely generate hybrid entanglement between discrete polarization and continuous quadrature optical qubits heralded by two-photon Bell-state measurement. As a novel nonclassical light resource, we further use it to discuss two examples of ways—entanglement swapping and quantum teleportation—in which quantum information processing and communications could make use of this hybrid technique.

Methodological development of the model-implied instrumental variable (MIIV) estimation framework has proved fruitful over the last three decades. Major milestones include Bollen's (Psychometrika 61(1):109–121, 1996) original development of the MIIV estimator and its robustness properties for continuous endogenous variable SEMs, the extension of the MIIV estimator to ordered categorical endogenous variables (Bollen and Maydeu-Olivares in Psychometrika 72(3):309, 2007), and the introduction of a generalized method of moments estimator (Bollen et al., in Psychometrika 79(1):20–50, 2014). This paper furthers these developments by making several unique contributions not present in the prior literature: (1) we use matrix calculus to derive the analytic derivatives of the PIV estimator, (2) we extend the PIV estimator to apply to any mixture of binary, ordinal, and continuous variables, (3) we generalize the PIV model to include intercepts and means, (4) we devise a method to input known threshold values for ordinal observed variables, and (5) we enable a general parameterization that permits the estimation of means, variances, and covariances of the underlying variables to use as input into a SEM analysis with PIV. An empirical example illustrates a mixture of continuous variables and ordinal variables with fixed thresholds. We also include a simulation study to compare the performance of this novel estimator to WLSMV. [ABSTRACT FROM AUTHOR]

Quantity discrimination, the ability to identify, process, and respond to differences in number, has been shown in a variety of animal species and may have fitness value. In fish, the ability to distinguish between numerically different shoals has been well studied. However, little work has been devoted to the investigation of such ability in a foraging context. Nevertheless, angelfish (Pterophyllum scalare) have been previously shown to be able to discriminate numerically different sets of food items, with variables such as size and density of the food items playing important roles in making the choice. Here, we examine the possible role of other numerical and non-numerical variables. Using a spontaneous binary choice task, we contrasted sets of food items differing in specifically controlled ways: (1) different numerical size but equal inter-item distance; (2) different numerical size and different inter-item distance; and (3) identical total contour length and area occupied but different individual food size and inter-food distance between the contrasted food sets. In Experiment 1, angelfish were found to prefer the sets with a large number of food items. In Experiment 2, they preferred the numerically smaller sets with clustered items to the numerically larger sets with scattered items, but only when the sets were in the large number range (10 vs. 5 food items). Finally, in Experiment 3 fish preferred numerically smaller sets with large-sized and scattered food items in the large number range sets. We conclude that food item number, density, and size may not be considered individually by angelfish, but instead, the fish respond to all these factors attempting to maximize energy gained from eating the food while minimizing energy expenditure collecting and/or protecting the food. [ABSTRACT FROM AUTHOR]

In this somewhat pedagogical paper we revisit complementarity relations in bipartite quantum systems. Focusing on continuous-variable systems, we examine the influential class of EPR-like states through a generalization to Gaussian states and present some new quantitative relations between entanglement and local interference within symmetric and asymmetric double-double-slit scenarios. This approach is then related to ancilla-based quantum measurements, and weak measurements in particular. Finally, we tie up the notions of distinguishability, predictability, coherence and visibility while drawing some specific connections between them. [ABSTRACT FROM AUTHOR]

Resource allocation is one of the key problems in radar network. A modified particle swarm optimisation (PSO) algorithm is presented here to improve the performance of resource allocation in radar network with large baseline, where multiple tasks with multiple parameters were considered. First, the resource allocation mathematic model for radar network with large baseline was established. Second, based on modified PSO, the resource allocation algorithm is presented and it can simultaneously deal with both discrete and continuous variables. Finally, the simulation experiment is presented to verify the proposed algorithm. The simulation result suggested that the proposed algorithm is feasible and can satisfy the requirement of resource allocation in the radar network. [ABSTRACT FROM AUTHOR]

Resource allocation is one of the key problems in radar network. A modified particle swarm optimisation (PSO) algorithm is presented here to improve the performance of resource allocation in radar network with large baseline, where multiple tasks with multiple parameters were considered. First, the resource allocation mathematic model for radar network with large baseline was established. Second, based on modified PSO, the resource allocation algorithm is presented and it can simultaneously deal with both discrete and continuous variables. Finally, the simulation experiment is presented to verify the proposed algorithm. The simulation result suggested that the proposed algorithm is feasible and can satisfy the requirement of resource allocation in the radar network.

This article proposes the optimal coordination problem of protective relays within a hybrid optimisation framework which is presented based on integer coded genetic algorithm (ICGA) and non-linear programming (NLP). The optimal coordination problem of directional overcurrent relays (DOCRs) is implemented while aimed at finding the optimal plug setting multiplier (PSM) and time dial setting (TDS). In this respect, PSM is a function of the current transformer (CT) size and the tap of the relay which is discrete in nature. TDS is a function of the operating time of the relay for different short-circuit currents at different locations of the system. Here, the variables of the problem are decomposed into continuous and discrete variables. The first stage of the problem uses the ICGA to determine the size of CTs considering the permitted tap of relays while the second stage utilises the NLP method to evaluate the feasibility and optimality. The presented framework is then simulated on an 8-bus test system. The obtained results verify the effectiveness and the applicability of the optimisation technique to find the optimal settings of DOCRs.