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Although symmetricity in the converter controller is desirable for robust stability margins, a direct link between system-level asymmetricity and instability has yet to be clearly established. Converter control introduces three-phase asymmetricity through loops such as DC-link voltage control, a phase-locked loop , and a power synchronization loop. Furthermore, the inherently asymmetric topology of the two-level voltage-source converter, which converts a DC voltage into a three-phase balanced set, acts as the underlying origin of the asymmetries that propagate into the control structure. Consequently, establishing a direct relationship between system asymmetricity (rather than control asymmetricity alone) and the stability margin is essential for understanding the underlying instability mechanisms. In this work, asymmetricity is quantified using the Asymmetricity Quantification Index (AQI), derived from the sequence-domain representation of the interconnected converter-grid impedance. Within this domain, symmetricity is identified through the definition of symmetrical matrices, which serve as the benchmark against which asymmetricity is measured. A robust and generalized analysis c

In Isabelle/HOL, declarative proofs written in the Isar language are widely appreciated for their readability and robustness. However, some users may prefer writing procedural "apply-style" proof scripts since they enable rapid exploration of the search space. To get the best of both worlds, we introduce Apply2Isar, a tool for Isabelle/HOL that automatically converts apply-style scripts to declarative Isar. This allows users to write complex, possibly fragile apply-style scripts, and then automatically convert them to more readable and robust declarative Isar proofs. To demonstrate the efficacy of Apply2Isar in practice, we evaluate it on a large benchmark set consisting of apply-style proofs from the Isabelle Archive of Formal Proofs.

Integrating grid-forming converters (GFMCs) into grid-following converter (GFLC)-dominated power systems enhances the grid strength, but GFMCs' current-limiting characteristic triggers dynamic switching between constant voltage control (CVC) and current limit control (CLC). This switching feature poses critical transient stability risks to GFLCs, requiring urgent investigation. This paper first develops a mathematical model for this switched system. Then, it derives switching conditions for droop-controlled GFMCs, which are separately GFMC angle-dependent and GFLC angle-dependent. On this basis, the stability boundaries of GFLC within each subsystem are analyzed, and the impact of GFMC switching arising from GFLC angle oscillation is investigated. The findings reveal that the switched system's stability boundary coincides with that of the CLC subsystem. To enhance GFLC's transient stability and ensure GFMC converges to the CVC mode, this paper introduces a virtual fixed d-axis control (VFDC) strategy. Compared with existing methods, this method achieves decoupling and self-stabilization using only local state variables from individual converters. The conclusions are validated throu

An algorithm for simulation of switching converters is proposed in the paper. The algorithm is based on simulation of averaged circuit model applying "switching cell" concept, and construction of instantaneous values of the waveforms using quasi steady state and linear ripple approximation. Simulation covers converters operating both in the continuous and the discontinuous conduction mode. Application of the algorithm is demonstrated by simulation results of all three of the basic converters: buck, boost and buck-boost, as well as a flyback converter, which required slight generalization of the switching cell concept.

Recent advances in deep learning have established Transformer architectures as the predominant modeling paradigm. Central to the success of Transformers is the self-attention mechanism, which scores the similarity between query and key matrices to modulate a value matrix. This operation bears striking similarities to digraph convolution, prompting an investigation into whether digraph convolution could serve as an alternative to self-attention. In this study, we formalize this concept by introducing a synthetic unitary digraph convolution based on the digraph Fourier transform. The resulting model, which we term Converter, effectively converts a Transformer into a Directed Graph Neural Network (DGNN) form. We have tested Converter on Long-Range Arena benchmark, long document classification, and DNA sequence-based taxonomy classification. Our experimental results demonstrate that Converter achieves superior performance while maintaining computational efficiency and architectural simplicity, which establishes it as a lightweight yet powerful Transformer variant.

Heat engines convert thermal energy into mechanical work. We here report the experimental realization of a fully quantum engine that converts quantum coherence into work. A single solid-state spin in diamond is fueled by a coherent bath and cyclically stores energy in a spin quantum battery. We establish quantum-enhanced performance by showing that almost 200$\%$ more work is produced after a few cycle compared to the corresponding classical engine. We obtain concrete criteria for successful coherence-to-work conversion, and highlight the importance of a coherent motor-battery interaction. This device harnesses nonclassical features during all stages of its cycle, and demonstrates the functionality of a nanomachine whose parts are all quantum coherent.

The fundamental role of power converters is to efficiently manage and control the flow of electrical energy, ensuring compatibility between power sources and loads. All these applications of power converters need the design of an appropriate control law. Control of power converters is a challenging problem due to the presence of switching devices which are difficult to handle using traditional control approaches. The objective of this paper is to investigate the use of data-driven techniques, in particular the Virtual References Feedback Tuning (VRFT) method, in the context of power converters feedback control. This study considers a buck \pauline{mode} power converter circuit provided by the OwnTech foundation.

As organizations prepare for the end-of-life of Camunda 7, manual migration remains complex due to fundamental differences between the two platforms. We present Vanilla-Converter, a command-line tool that facilitates the migration of BPMN models from Camunda 7 to Camunda 8. Vanilla-Converter automates the transformation process, supports a wide range of BPMN elements, and produces a transformed model and a detailed transformation log indicating automatic changes and remaining manual conversion tasks. The tool's effectiveness is demonstrated through three case studies with real industrially used Camunda 7 models, confirming its ability to convert these models into valid and executable Camunda 8 models.

Removing carbon dioxide from the atmosphere may slow climate change and ocean acidification. My approach converts atmospheric carbon dioxide into graphite (CD2G). The net profit for this conversion is ~$381/ton CO2 removed from the atmosphere. At the gigaton scale, CD2G factories will increase the affordability and availability of graphite. Since graphite can be used to make thermal batteries and electrodes for fuel cells and batteries, CD2G factories will help lower the cost of storing renewable energy, which will accelerate the transition to renewable energy. Replacing fossil fuel energy with renewable energy will slow the release of carbon dioxide to the atmosphere, also slowing climate change. Converting atmospheric carbon dioxide into graphite will both generate a profit and slow climate change.

Convertibility checking - determining whether two lambda-terms are equal up to reductions - is a crucial component of proof assistants and dependently-typed languages. Practical implementations often use heuristics to quickly conclude that two terms are or are not convertible without reducing them to normal form. However, these heuristics can backfire, triggering huge amounts of unnecessary computation. This paper presents a novel convertibility-checking algorithm that relies crucially on laziness and concurrency} Laziness is used to share computations, while concurrency is used to explore multiple convertibility subproblems in parallel or via fair interleaving. Unlike heuristics-based approaches, our algorithm always finds an easy solution to the convertibility problem, if one exists. The paper presents the algorithm in process calculus style and discusses its mechanized proof of partial correctness, its complexity, and its lightweight experimental evaluation.

Quantum frequency conversion (QFC) which converts the frequencies of photons while preserving the quantum state is an essential technology for realizing the quantum internet and quantum interconnect. For the QFC based on the frequency downconversion from visible to the telecom wavelengths around 1500 nm, it is widely known that noise photons produced by the strong pump light used for QFC contaminate the frequency-converted photon, which degrades the quality of the quantum property of the photon after QFC. In conventional QFC experiments, noise photons are removed using external narrowband frequency filter systems. In contrast, in this study, we implement a compact QFC device integrating the cavity structure only for the converted mode. While the cavity structure can enhance not only the desired QFC efficiency but also the noise photon generation rate, we show that the cavity-enhanced QFC followed by a relatively wide bandpass filter achieves the signal-to-noise ratio comparable to the QFCs with external narrowband filters. We experimentally demonstrate the cavity-enhanced QFC using a single photon at 780 nm to 1540 nm, in which the non-classical photon statistics is clearly observe

This report derives a generalized, converted measurement Kalman filter for the class of filtering problems with a linear state equation and nonlinear measurement equation, for which a bijective mapping exists between the state and measurement coordinate systems. For these problems, a procedure is developed for mapping the observed measurements and their covariance matrices from measurement coordinates to state coordinates, such that the converted measurements are unbiased and the converted measurement covariance matrices are independent of the states and observed measurements. In cases where not all measurement coordinates are observed, predicted measurements of these coordinates are introduced as substitutes, and the impact of these measurements on the filter is mitigated by an information zeroing operation on the corresponding rows and columns of the converted measurement inverse-covariance matrix. Filter performance is demonstrated on two well-known target-tracking problems and is compared with the performance of the standard extended and unscented Kalman filters for these problems. These examples show the proposed filter obtains lower mean squared error, better consistency, and

In this paper, we consider the convertible codes with the maximum distance separable (MDS) property, which can adjust the code rate according to the failure rates of devices. We first extend the notion of convertible codes to allow initial and final codes with different parameters. Then, we investigate the relationship between these parameters and thus establish new lower bounds on the access cost in the merge and split regimes. To gain a deeper understanding of access-optimal MDS convertible codes in the merge regime, we characterize them from the perspective of parity check matrices. Consequently, we present a necessary and sufficient condition for the access-optimal MDS convertible code in the merge regime. Finally, as an application of our characterization, we construct MDS convertible codes in the merge regime with optimal access cost based on the extended generalized Reed-Solomon codes.

State convertibility is fundamental in the study of resource theory of quantum coherence. It is aimed at identifying when it is possible to convert a given coherent state to another using only incoherent operations. In this paper, we give a complete characterization of state convertibility under genuinely incoherent operations. It is found that convexity of the robustness of coherence plays a central role. Based on this, the majorization condition of determining convertibility from pure states to mixed states under strictly incoherent operations is provided. Moreover, maximally coherent states in the set of all states with fixed diagonal elements are determined. It is somewhat surprising that convexity of the robustness of coherence can also decide conversion between off-diagonal parts of coherent states. This might be a big step to answer completely the question of state convertibility for mixed states under incoherent operations.

Microservice architecture is a trending topic in software design architecture and many enterprises adopted microservice design due its benefits and the rapid and wide deployment of cloud computing and as a result, many enterprises transformed their existing monolithic application to microservice to achieve business requirements as scaling up and agile development. In this paper we will guide software developers how to convert their existing monolithic application into microservice application without re-writing the whole microservice application from scratch, and we will also discuss the common issues that may face the software developer during the conversion processes. In addition to converting the business logic to microservice, we mention steps for converting the monolithic database into a database per service. Also, we summarize how Netflix and Airbnb converted their monolithic application to microservice application.

Resonant converters are often being used for high power and high voltage applications to achieve high efficiency, high power density and low EMI. In this paper, we will use a resonant converter for a completely different application. We will take advantage of the Zero Voltage Switching (ZVS) and operating in the vicinity of the series resonance to design a low power and ultra-low noise galvanic isolated half bridge resonant DC-DC converter for powering a medical amplifier. Under lower power we consider up to 6W (500mA @ 12V). The DC-DC converter must meet the safety requirements of the standard IEC 60601.

Some progress is reported on conditions for convertibility among bipartite 2x2 entangled states: An inconvertibility condition related to the rank of an entangled state is given that it is impossible to convert to an entangled state with lower rank under separable operations; a particular set of local operations and classical communication (LOCC) is used to analyze convertibility of three subclasses of states - Werner states, Bell diagonal states and maximally entangled mixed states (MEMS). It is conjectured that MEMS may lie on the bottom of entangled state ordering for given entanglement of formation. A plausible way is suggested of systematically calculating convertibility in a general subclass of bipartite states whose density matrices are defined to be diagonal in a common basis. The set of LOCC adopted in this work is argued to be generalizable to provide sufficient conditions for convertibility among a large range of general 2x2 entangled states.

One of the popular impedance-network converters are Y-source converters which along with their essential characteristics such as reducing the size of converter components, single-stage power transferring, fault tolerance, and wide voltage gain capabilities there are also some drawbacks that one of the most widespread is high leakage inductances which affect performance negatively. This paper introduces a new configuration based on coupled inductors as a power electronic converter in three case studies to verify the high reliability of the proposed converter by using just a simple controller that is substantial for recycling brake energy in the propulsion system of Electric Vehicles and grid-following inverters. This topology with a straightforward structure, computation, and wide voltage gain, provides a proper connection between the components of its network that obtains appropriate paths for leakage energy, and likewise helps soft-switching in some conditions. Additionally, the performance of other previously related constructions is compared with the suggested topology. Simulations based on MATLAB/ SIMULINK have been carried out, and correspondingly experiment results have been

The paper introduces several new concepts for solving nonconvex or nonsmooth optimization problems, including convertible nonconvex function, exact convertible nonconvex function and differentiable convertible nonconvex function. It is proved herein many nonconvex functions or nonsmooth (or discontinuous) functions are actually convertible nonconvex functions and convertible nonconvex function operations such as addition, subtraction, multiplication or division result in convertible nonconvex functions. The sufficient condition for judging a global optimal solution to unconstrained optimization problems with differentiable convertible nonconvex functions is proved, which is equivalent to Karush-Kuhn-Tucker(KKT) condition. Two Lagrange functions of differentiable convertible nonconvex function are defined with their dual problems defined accordingly. The strong duality theorem is proved, showing that the optimal objective value of the global optimal solution is equal to the optimal objective value of the dual problem, which is equivalent to KKT condition. An augmented Lagrangian penalty function algorithm is proposed and its convergence is proved. So the paper provides a new idea fo