Explicit Operator Research Articles

On the granularity of linguistic reuse

Programming languages are complex software systems integrated across an ecosystem of different applications such as language compilers or interpreters but also an integrated development environment comprehensive of syntax highlighting, code completion, error recovery, and a debugger. The complexity of language ecosystems can be faced using language workbenches—i.e., tools that tackle the development of programming languages, domain specific languages and their ecosystems in a modular way.As with any other software system, one of the priorities that developers struggle to achieve when developing programming languages is reusability. After all, the capacity to easily reuse and adapt existing components to new scenarios can dramatically improve development times. Therefore, as programming languages offer features to reuse existing code, language workbenches should offer tools to reuse existing language assets. However, reusability can be achieved in many different ways.In this work, we identify six forms of linguistic reusability, ordered by level of granularity: (i) sub-languages composition, (ii) language features composition, (iii) syntax and semantics assets composition, (iv) semantic assets composition, (v) actions composition, and. (vi) action extension. We use these mechanisms to extend the taxonomy of language composition proposed by Erdweg et al. To show a concrete application of this taxonomy, we evaluate the capabilities provided by the Neverlang language workbench with regards to our taxonomy and extend it by adding explicit support for any granularity level that was originally not supported. This is done by instantiating two levels of reusability as actual operators—desugaring, and delegation. We evaluate these operators against the clone-and-own approach, which was the only form of reuse at that level of granularity prior to the introduction of explicit operators. We show that with the clone-and-own approach the design quality of the source code is negatively affected. We conclude that language workbenches can benefit from the introduction of mechanisms to explicitly support reuse at all granularity levels.

On a generalization of time-accurate and highly-stable explicit operators for stiff problems

In this work we propose a generalization of the family of Time-Accurate and highly-Stable Explicit (TASE) operators recently introduced by Calvo, Montijano and Rández (2021). In this family the TASE operator of order p depends on p free real parameters. Here we consider operators that can also be defined by complex parameters occurring in conjugate pairs. Despite this choice the calculations continue to be done only in real arithmetic, thus not burdening the computational cost of the previous version of the family. Conversely, this generalization leads to improve both the accuracy and stability properties of explicit Runge-Kutta schemes supplemented with TASE operators. Numerical experiments showing the competitiveness of the methods proposed in this paper with respect to classical integrators for stiff problems are also presented.

Do names echo semantics? A large-scale study of identifiers used in C++’s named casts

Developers relax restrictions on a type to reuse methods with other types. While type casts are prevalent, in weakly typed languages such as C++, they are also extremely permissive. Assignments where a source expression is cast into a new type and assigned to a target variable of the new type, can lead to software bugs if performed without care. In this paper, we propose an information-theoretic approach to identify poor implementations of explicit cast operations. Our approach measures accord between the source expression and the target variable using conditional entropy. We collect casts from 34 components of the Chromium project, which collectively account for 27MLOC and random-uniformly sample this dataset to create a manually labelled dataset of 271 casts. Information-theoretic vetting of these 271 casts achieves a peak precision of 81% and a recall of 90%. We additionally present the findings of an in-depth investigation of notable explicit casts, two of which were fixed in recent releases of the Chromium project.

The Role of Reservoir Reoperation to Mitigate Climate Change Impacts on Hydropower and Environmental Water Demands

Adapting reservoir operation to a changing climate is important to improve water system performance toward benefits including water security, and energy production. However, managers still need to know if and how reoperation can also assist long-term mitigation of climate change impacts on aquatic ecosystems, creating, for example, opportunities to revert fish migration and recruitment losses. This paper investigates the operational adaptive capacity of water systems to mitigate climate change impacts on both hydropower and aquatic ecosystems, with a detailed representation of fish species recruitment response to flow regime changes. The methodology framework combines hydroclimatic modeling, explicit stochastic reservoir operation modeling, and predictive modeling of migratory fish recruitment abundance, illustrated using the large-scale hydropower system of the Paraná River Basin in Brazil. Results identified that operating policies can be adapted to improve hydropower production under a changing climate with drier conditions by 2% to 8% compared with current operating policies. Although insufficient to eliminate all energy losses that climate change may cause, the optimized operation provided flexibility to adjust flow releases and reduce the likelihood of future severe multiyear deficits, which are very harmful to fish populations. Adapting operation to climate change sacrificed fish recruitment performance over a few years of the time horizon to maintain an overall higher storage, but it also improved the chances of producing flow releases in magnitude, timing, and duration during long drier periods that prevented more severe impacts of climate change on fish recruitment and population. This indicates that it might be possible to have synergies in adapting reservoir operation to not only prevent energy losses, but also to improve fish recruitment under climate change. The ecosystem resiliency under adapted operation increased up to 2 times compared with the isolated climate change effect.

Stable attenuation-compensated reverse time migration and its application to land seismic data

Intrinsic attenuation of the earth causes energy loss and phase distortion in seismic wave propagation. To obtain high-resolution imaging results, these negative effects must be considered during reverse time migration (RTM). We can easily implement attenuation-compensated RTM using the constant Q viscoacoustic wave equation with decoupled amplitude attenuation and phase dispersion terms. However, the nonphysical amplitude-compensation process will inevitably amplify the high-frequency noise in the wavefield in an exponential form, causing the numerical simulation to become unstable. This is due to the fact that the amplitude of the compensation grows exponentially with frequency. In order to achieve stable attenuation-compensated RTM, we modify the analytic expression of the attenuation compensation extrapolation operator and make it only compensate for amplitude loss within the effective frequency band. Based on this modified analytic formula, we then derive an explicit time-space domain attenuation compensation extrapolation operator. Finally, the implementation procedure of stable attenuation-compensated RTM is presented. In addition to being simple to implement, the newly proposed attenuation-compensated extrapolation operator is superior to the conventional low-pass filter in suppressing random noise, which will further improve the imaging resolution. We use two synthetic and one land seismic datasets to verify the stability and effectiveness of the proposed attenuation-compensated RTM in improving imaging resolution in viscous media.

Hamiltonians for Polaron Models with Subcritical Ultraviolet Singularities

We treat the ultraviolet problem for polaron-type models in nonrelativistic quantum field theory. Assuming that the dispersion relations of particles and the field have the same growth at infinity, we cover all subcritical (superrenormalisable) interactions. The Hamiltonian without cutoff is exhibited as an explicit self-adjoint operator obtained by a finite iteration procedure. The cutoff Hamiltonians converge to this operator in the strong resolvent sense after subtraction of a perturbative approximation for the ground-state energy.

An explicit stable Q-compensated reverse time migration scheme for complex heterogeneous attenuation media

Prestack reverse-time migration (RTM) is a popular imaging technique for complex geological conditions, since the amplitude attenuation and velocity dispersion are common in seismic recordings. To image attenuated seismic recordings accurately, a robust migration algorithm with a stable attenuation compensation approach should be considered. In the context of the Q-compensated RTM approach based on the decoupled fractional Laplacians (DFLs) viscoacoustic wave equation, amplitude compensation can be implemented by flipping the sign of the dissipation term. However, the non-physical magnification of image amplitude could lead to a well-known numerical instability problem. The explicit stabilization operator can rectify the amplitude attenuation and suppress the numerical instability. However, limited by the inconvenient mixed-domain operator, the average Q value rather than the real Q value is often used in the compensation operator, lowering the compensated accuracy of the migration image. To overcome this problem, we propose a novel explicit Q-compensation scheme. The main advantage of the proposed compensation operator is that its order is space-invariant, making it more suitable for handling complex heterogeneous attenuation media. Several two-dimensional (2D) and three-dimensional (3D) synthetic models are used to verify the superiority of the proposed approach in terms of amplitude fidelity and image resolution. Field data further demonstrates that our approach has potential applications and can greatly enhance the resolution of seismic images.

О вычислении группы классов идеалов мнимых мультиквадратичных полей

In the paper, we extend Biasse - van Vredendaal (OBS, 2019, vol. 2) implementation and experiments of the class group computation from real to imaginary multiquadratic fields. The implementation is optimized by introducing an explicit prime ideal lift operation and by using LLL reduction instead of HNF computation. We provide examples of class group computation of the imaginary multiquadratic fields of degree 64 and 128, that has been previously unreachable.

STRUCTURE PRESERVING SPLITTING TECHNIQUES FOR EBOLA REACTION–DIFFUSION EPIDEMIC SYSTEM

In this paper, we deal with the numerical solution of the reaction–diffusion Ebola epidemic model. The diffusion which is an important phenomenon for the epidemic model is included in the model. This inclusion has made the model more comprehensive for studying the disease dynamics in the human population. The quantities linked with the model indicate the population sizes which are taken as absolute, therefore, the numerical schemes utilized to solve the underlying Ebola epidemic system should sustain the positivity. The numerical approaches used to solve the underlying epidemic models are explicit nonstandard finite difference operator splitting (ENSFD-OS) and implicit nonstandard finite difference operator splitting (INSFD-OS) techniques. These schemes preserve all the physical features of the state variables, i.e. projected schemes hold the positive solution acquired by the Ebola diffusive epidemic model. The underlying epidemic model illustrates two stable steady states, a virus-free state, and a virus existence state. The suggested approaches retain the stability of each of the steady states possessed by the assumed epidemic model. A numerical example and simulations for validation of all the characteristics of suggested techniques are also investigated.

Operational entanglement detection based on $$\Lambda $$-moments

We introduce $\Lambda$-moments with respect to any positive map $\Lambda$. We show that these $\Lambda$-moments can effectively characterize the entanglement of unknown quantum states without theirs prior reconstructions. Based on $\Lambda$-moments necessary and sufficient separability criteria, as well as necessary optimized criteria are presented, which include the ones in [\href{https://link.aps.org/doi/10.1103/PhysRevLett.127.060504}{Phys. Rev. Lett. \textbf{127}, 060504 (2021)}] as special cases. Detailed example is given to show that our criteria can detect bound entanglement that can not be identified by positive partial transpose criterion, with the explicit measurement operators to experimentally measure the corresponding $\Lambda$-moments.

Declarative Data Flow in a Graph-Based Distributed Memory Runtime System

Runtime systems can significantly reduce the cognitive complexity of scientific applications, narrowing the gap between systems engineering and domain science in HPC. One of the most important angles in this is automating data migration in a cluster. Traditional approaches require the application developer to model communication explicitly, for example through MPI primitives. Celerity, a runtime system for accelerator clusters heavily inspired by the SYCL programming model, instead provides a purely declarative approach focused around access patterns. In addition to eliminating the need for explicit data transfer operations, it provides a basis for efficient and dynamic scheduling at runtime. However, it is currently only suitable for accessing array-like data from runtime-controlled tasks, while real programs often need to interact with opaque data local to each host, such as handles or database connections, and also need a defined way of transporting data into and out of the virtualised buffers of the runtime. In this paper, we introduce a graph-based approach and declarative API for expressing side-effect dependencies between tasks and moving data from the runtime context to the application space.

Contrasting roles of measurement knowledge systems in confounding or creating sustainable change

Sustainable change initiatives are often short-circuited by failures in modelling. Unexamined assumptions about measurement and numbers push modelling into the background as a presupposition rarely articulated as an explicit operation. Even when models of system dynamics are planned components of a sustainable change effort, the key role of measurement is typically overlooked. The crux of the matter concerns the distinction between numeric counts and measured quantities. Mistaking the former for the latter confuses levels of complexity and fundamentally compromises communications. Reconceiving measurement as modelling multilevel distributed decision processes offers new alternatives aligned with historically successful efforts in creating sustainable change. Five conditions for successful sustainable change are contrasted from the perspectives of single-level vs multilevel modelling: vision, plans, skills, resources, and incentives. Omitting any one of these from efforts at creating change result, respectively, in confusion, treadmills, anxiety, frustration, and resistance. The shortcomings of typically implemented single-level approaches to measurement result in the widespread experience of these negative consequences. Results show that new potentials for creating sustainable change can be expected to follow from implementations of multilevel distributed decision processes that effectively counteract organizational amnesia by embedding new learning in an externally materialized knowledge infrastructure incorporating a shared cultural memory.

A Representation-Theoretic Approach to qq-Characters

We raise the question of whether (a slightly generalized notion of) $qq$-characters can be constructed purely representation-theoretically. In the main example of the quantum toroidal $\mathfrak{gl}_1$ algebra, geometric engineering of adjoint matter produces an explicit vertex operator $\mathsf{RR}$ which computes certain $qq$-characters, namely Hirzebruch $\chi_y$-genera, completely analogously to how the R-matrix $\mathsf{R}$ computes $q$-characters. We give a geometric proof of the independence of preferred direction for the refined vertex in this and more general non-toric settings.

Vanishing of Avramov obstructions for products of sequentially transverse ideals

Two ideals I and J are called transverse if I ∩ J = I J . We show that the obstructions defined by Avramov for products of (sequentially) transverse ideals in regular local rings are always 0. In particular, we compute an explicit free resolution and Koszul homology for all such ideals. Moreover, we construct an explicit trivial Massey operation on the associated Koszul complex and hence (by Golod's construction) a minimal free resolution of the residue field over the quotient defined by the product of transverse ideals. We conclude with questions about the existence of associative multiplicative structures on the minimal free resolution of the quotient defined by products of transverse ideals.

Symmetry operators of the asymmetric two-photon quantum Rabi model

The true level crossings in a subspace of the asymmetric two-photon quantum Rabi model (tpQRM) have been observed when the bias parameter of qubit is an even multiple of the renormalized cavity frequency. Generally, such level crossings imply the existence of the hidden symmetry because the bias term breaks the obvious symmetry exactly. In this work, we propose a Bogoliubov operator approach for the asymmetric tpQRM to derive the symmetry operators associated with the hidden symmetry hierarchically. The explicit symmetry operators consisting of Lie algebra at low biases can be easily obtained in our general scheme. We believe the present approach can be extended for other asymmetric Rabi models to find the relevant hidden symmetry.

Learning Spatial–Parallax Prior Based on Array Thermal Camera for Infrared Image Enhancement

In this article, an array thermal camera equipment is developed to capture multiple infrared images with spatial and parallax information. Based on the captured images, an end-to-end method called spatial–parallax prior network (SPPN) is proposed. Specifically, we design a spatial–parallax prior block with two symmetric branches to extract spatial and parallax features in an interactive guidance manner. Then, to effectively integrate spatial and parallax features, we introduce a channel attention mechanism to enable the network to focus on and fuse the most useful information adaptively. In this way, spatial and parallax information can be fully utilized without any explicit alignment operation. Finally, considering the scarcity and poor quality of infrared training data, we leverage transfer learning to better train the network. Extensive experimental results demonstrate that the proposed SPPN consistently outperforms the current state-of-the-art methods, providing a highly effective and scalable solution for the improvement of infrared image quality.

Enhancements to explicit stochastic reservoir operation optimization method

The Fletcher-Ponnambalam (FP) method is an explicit stochastic optimization method for design and operations management of real-world storage systems including surface water reservoir and groundwater management problems. The FP method faces no curse of dimensionality and no need for scenario generation. The paper introduces a novel implementation for the FP method, named FP-2022 here for clarity, by removing the need for nonlinear constraints and by decreasing the number of decision variables to just one third of its original value, significantly reducing solving time (∼27 times faster than the original formulation). Additionally, new expressions derived for the first and second moments of both reservoir release deficit and surplus variables and the already-derived expression for the second moments of reservoir storages are incorporated into the FP-2022 formulation enabling the method to reach an improved optimality for a nonlinear objective function. The enhanced procedure is applied to solving a reservoir operation optimization problem for a major dam in Brazil. The result comparisons made with other methods along with a thorough analysis of release operation policies prove the optimality of this highly numerically efficient and convenient-to-use FP-2022 method. Finally, a multi-reservoir application of the model is also tested with corrective simulations for improved estimates of some additional variables of interest. A specific constraint-handling approach regarding reservoir release lower and upper bounds is also presented. Satisfactory results are obtained for solving the Parambikulam-Aliyar reservoir system, a real world five-reservoir operation optimization problem from India.

Boosting ethics review capacity in public health emergency situations: Co-creation of a training model for French-speaking research ethics committees.

Ethics review preparedness is a major foundation for national effective response to public health emergencies, because it promotes pertinent research and enhances the protection of research participants and communities. In low-income countries, it can also promote equitable research partnership. However, most relevant literature is in English and not easily accessible for the members of research ethics committees in French-speaking African countries. A training module in French, addressing the issue of research ethics review during outbreaks and other public health emergencies, was designed based on a non-systematic literature review, and in order to be complementary to the Democratic Republic of Congo (DRC) national guidelines for ethics review. The module was administered to 42 members of the five ethics committees in DRC that expressed their interest for the training. This training, co-designed with local stakeholders, in the local working language and taking into account local circumstances and regulation, provided participants with up-to-date insights of research ethics (and research ethics preparedness) in public health emergencies. It resulted in rich reflection and knowledge-sharing on good practices across the ethics committees. As most participating ethics committees do not have yet explicit standard operating procedures for expedited review of protocols submitted in emergency situations, this would be a next important step to facilitate emergency reviews in the most efficient way.

HMMCF:A human-computer collaboration algorithm based on multimodal intention of reverse active fusion

This paper proposes a fusion model of an improved Hidden Markov Model (HMM) and an improved CF trust evaluation algorithm, and a human-computer collaboration mechanism embedded in the X-arm manipulator. It can correctly predict user intentions of interaction, correct erroneous intentions, and carry out human-computer collaboration under the user's multimodal fuzzy expression or wrong expression, and finally complete the intention task. It can correctly predict the user interactive intentions, correct the wrong intention, and carry out human-computer collaboration in the case of user multimodal fuzzy expression or wrong expression. The main contributions of this paper are: when humans input intentions to robots, users no longer interact strictly through discrete and explicit interactive operations, but can use non-deterministic and unclear multimodal data to express interactive intentions; When the model predicts user's intentions, it comprehensively considers modal information such as user's voice, gesture, posture, and extracts the user's intention from the user's daily habits and the context of the interactive environment. The process of trust evaluation, reverse analysis, and active acquisition of necessary information on the user's intention determines whether the intention is feasible, and then analyzes the intention through the human-computer collaboration mechanism, reasonably assigns the tasks that the human and the computer need to complete. Finally, human and computer cooperate together to achieve the user's intention. The algorithm proposed in this paper can be considered as a new method of intention understanding in human-computer interaction and a research of exploring the computational principle of natural interaction. The algorithm proposed in this paper has been verified in many daily life scenarios such as helping the elderly to drink water, take medicine, read, watch TV and so on, and it has also proposed a valuable research path for the challenging problem of human-computer interaction.

High order semi-implicit schemes for viscous compressible flows in 3D

In this article we present a high order cell-centered numerical scheme in space and time for the solution of the compressible Navier-Stokes equations. To deal with multiscale phenomena induced by the different speeds of acoustic and material waves, we propose a semi-implicit time discretization which allows the CFL-stability condition to be independent of the fast sound speed, hence improving the efficiency of the solver. This is particularly well suited for applications in the low Mach regime with a rather small fluid velocity, where the governing equations tend to the incompressible model. The momentum equation is inserted into the energy equation yielding an elliptic equation on the pressure. The class of implicit-explicit (IMEX) time integrators is then used to ensure asymptotic preserving properties of the numerical method and to improve time accuracy. High order in space is achieved relying on implicit finite difference and explicit CWENO reconstruction operators, that ultimately lead to a fully quadrature-free scheme. To relax the severe parabolic restriction on the maximum admissible time step related to viscous contributions, a novel implicit discretization of the diffusive terms is designed. A variational approach based on the discontinuous Galerkin (DG) spatial discretization is devised in order to obtain a discrete cell-centered Laplace operator. High order corner gradients of the velocity field are employed in 3D to derive the Laplace discretization, and the resulting viscous system is proven to be symmetric and positive definite. As such, it can be conveniently solved at the aid of the conjugate gradient method. Numerical results confirm the accuracy and the robustness of the novel schemes in the challenging stiff limit of the governing equations characterized by low Mach numbers.