Tootfinder

High-Gain Voltage-Multiplier Coupled Quadratic Boost Converter: A New Design for Small Scale PV Integration
Safa Mohammed Sali, Hoach The Nguyen, Ameena Saad Al-Sumaiti
https://arxiv.org/abs/2509.09789

High-Gain Voltage-Multiplier Coupled Quadratic Boost Converter: A New Design for Small Scale PV Integration
This paper introduces a single-switch high-gain voltage-multiplier coupled quadratic boost converter (HGVM-QBC), developed from the conventional quadratic boost converter (QBC). The proposed topology is designed to achieve higher voltage gain, lower semiconductor voltage stress, and continuous current operation, making it particularly suitable for small-scale photovoltaic (PV) systems. By incorporating a voltage multiplier cell into the QBC, the converter significantly improves voltage boosting…

Kronecker second limit formula for real quadratic fields
YoungJu Choie, Rahul Kumar
https://arxiv.org/abs/2510.10554 https://arxiv.org/pdf/2510.10554

Kronecker second limit formula for real quadratic fields
In this paper, the second Kronecker ``limit" formula for a real quadratic field is established for the first time. More precisely, we obtain the second Kronecker limit formula of Zagier's zeta function. Using the reduction theory of Zagier, which connects Zagier's zeta function to the zeta function of real quadratic fields, we express the values of the zeta function of narrow ideal classes in real quadratic fields at natural arguments in terms of an analytic function which we call the \emph{hig…

On Runge-Kutta convolution quadrature based fractional variational integrators
Khaled Hariz, Sina Ober-Bl\"obaum, Fernando Jimenez
https://arxiv.org/abs/2510.11082 https://…

On Runge-Kutta convolution quadrature based fractional variational integrators
Lagrangian systems subject to fractional damping can be incorporated into a variational formalism. The construction can be made by doubling the state variables and introducing fractional derivatives \cite{JiOb2}. The main objective of this paper is to use the Runge-Kutta convolution quadrature (RKCQ) method for approximating fractional derivatives, combined with higher order Galerkin methods in order to derive fractional variational integrators (FVIs). We are specially interested in the CQ base…

Re$^3$MCN: Cubic Newton Variance Reduction Momentum Quadratic Regularization for Finite-sum Non-convex Problems
Dmitry Pasechnyuk-Vilensky, Dmitry Kamzolov, Martin Tak\'a\v{c}
https://arxiv.org/abs/2510.08714

Re$^3$MCN: Cubic Newton + Variance Reduction + Momentum + Quadratic Regularization for Finite-sum Non-convex Problems
We analyze a stochastic cubic regularized Newton method for finite sum optimization $\textstyle\min_{x\in\mathbb{R}^d} F(x) \;=\; \frac{1}{n}\sum_{i=1}^n f_i(x)$, that uses SARAH-type recursive variance reduction with mini-batches of size $b\sim n^{1/2}$ and exponential moving averages (EMA) for gradient and Hessian estimators. We show that the method achieves a $(\varepsilon,\sqrt{L_2\varepsilon})$-second-order stationary point (SOSP) with total stochastic oracle calls $n + \widetilde{\mathcal…

Probing imbalanced Weyl nodes in two-dimensional anisotropic Weyl semimetal via optical conductivity
Suheel Ahmad Malik, M. A. H. Ahshan, SK Firoz Islam
https://arxiv.org/abs/2508.09011

Probing imbalanced Weyl nodes in two-dimensional anisotropic Weyl semimetal via optical conductivity
We present a theoretical investigation of the electronic band structure and optical properties of a two-dimensional anisotropic semimetal that is described by a tilted semi-Dirac type spectrum with a pair of Weyl nodes. We observe that a tilt along the quadratic direction can give rise to an energy imbalance between these nodes, contrary to the effect of tilt along the linear direction. We investigate the optical response of such system subjected to an external AC bias, aiming to probe the ener…

Low dimensional dynamics of a sparse balanced synaptic network of quadratic integrate-and-fire neurons
Maria V. Ageeva, Denis S. Goldobin
https://arxiv.org/abs/2508.06253 https:…

Low dimensional dynamics of a sparse balanced synaptic network of quadratic integrate-and-fire neurons
Kinetics of a balanced network of neurons with a sparse grid of synaptic links is well representable by the stochastic dynamics of a generic neuron subject to an effective shot noise. The rate of delta-pulses of the noise is determined self-consistently from the probability density of the neuron states. Importantly, the most sophisticated (but robust) collective regimes of the network do not allow for the diffusion approximation, which is routinely adopted for a shot noise in mathematical neuro…

FORWARD: A Feasible Radial Reconfiguration Algorithm for Multi-Source Distribution Networks
Joan Vendrell Gallart, Russell Bent, Solmaz Kia
https://arxiv.org/abs/2510.08785 http…

FORWARD: A Feasible Radial Reconfiguration Algorithm for Multi-Source Distribution Networks
This paper considers an optimal radial reconfiguration problem in multi-source distribution networks, where the goal is to find a radial configuration that minimizes quadratic distribution costs while ensuring all sink demands are met. This problem arises in critical infrastructure systems such as power distribution, water networks, and gas distribution, where radial configurations are essential for operational safety and efficiency. Optimal solution for this problem is known to be NP-hard. In …

Safety-Critical Control with Bounded Inputs: A Closed-Form Solution for Backup Control Barrier Functions
David E. J. van Wijk, Ersin Das, Tamas G. Molnar, Aaron D. Ames, Joel W. Burdick
https://arxiv.org/abs/2510.05436

Safety-Critical Control with Bounded Inputs: A Closed-Form Solution for Backup Control Barrier Functions
Verifying the safety of controllers is critical for many applications, but is especially challenging for systems with bounded inputs. Backup control barrier functions (bCBFs) offer a structured approach to synthesizing safe controllers that are guaranteed to satisfy input bounds by leveraging the knowledge of a backup controller. While powerful, bCBFs require solving a high-dimensional quadratic program at run-time, which may be too costly for computationally-constrained systems such as aerospa…

Global Convergence of Policy Gradient for Entropy Regularized Linear-Quadratic Control with multiplicative noise
Gabriel Diaz, Lucky Li, Wenhao Zhang
https://arxiv.org/abs/2510.02896

Global Convergence of Policy Gradient for Entropy Regularized Linear-Quadratic Control with multiplicative noise
Reinforcement Learning (RL) has emerged as a powerful framework for sequential decision-making in dynamic environments, particularly when system parameters are unknown. This paper investigates RL-based control for entropy-regularized Linear Quadratic control (LQC) problems with multiplicative noises over an infinite time horizon. First, we adapt the Regularized Policy Gradient (RPG) algorithm to stochastic optimal control settings, proving that despite the non-convexity of the problem, RPG conv…

Guaranteed Time Control using Linear Matrix Inequalities
V\'ictor Costa da Silva Campos, Mariella Maia Quadros, Luciano Frezzato, Leonardo Mozelli, Anh-Tu Nguyen
https://arxiv.org/abs/2510.02636

Guaranteed Time Control using Linear Matrix Inequalities
This paper presents a synthesis approach aiming to guarantee a minimum upper-bound for the time taken to reach a target set of non-zero measure that encompasses the origin, while taking into account uncertainties and input and state constraints. This approach is based on a harmonic transformation of the Lyapunov function and a novel piecewise quadratic representation of this transformed Lyapunov function over a simplicial partition of the state space. The problem is solved in a policy iteration…