Tootfinder

Control variates from Eulerian and Lagrangian perturbation theory: Application to the bispectrum
Nickolas Kokron, Shi-Fan Chen
https://arxiv.org/abs/2510.07375 https://

Control variates from Eulerian and Lagrangian perturbation theory: Application to the bispectrum
Control variates have seen recent interest as a powerful technique to reduce the variance of summary statistics measured from costly cosmological $N$-body simulations. Of particular interest are the class of control variates which are analytically calculable, such as the recently introduced 'Zeldovich control variates' for the power spectrum of matter and biased tracers. In this work we present the construction of perturbative control variates in Eulerian and Lagrangian perturbation theory, and…

Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates
Zixin Zhang, James Avtges, Todd D. Murphey
https://arxiv.org/abs/2509.08241 https://

Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates
Data-driven control methods need to be sample-efficient and lightweight, especially when data acquisition and computational resources are limited -- such as during learning on hardware. Most modern data-driven methods require large datasets and struggle with real-time updates of models, limiting their performance in dynamic environments. Koopman theory formally represents nonlinear systems as linear models over observables, and Koopman representations can be determined from data in an optimizat…

OCTANE -- Optimal Control for Tensor-based Autoencoder Network Emergence: Explicit Case
Ratna Khatri, Anthony Kolshorn, Colin Olson, Harbir Antil
https://arxiv.org/abs/2509.08169

OCTANE -- Optimal Control for Tensor-based Autoencoder Network Emergence: Explicit Case
This paper presents a novel, mathematically rigorous framework for autoencoder-type deep neural networks that combines optimal control theory and low-rank tensor methods to yield memory-efficient training and automated architecture discovery. The learning task is formulated as an optimization problem constrained by differential equations representing the encoder and decoder components of the network and the corresponding optimality conditions are derived via a Lagrangian approach. Efficient mem…

Universal quantum control over bosonic network
Zhu-yao Jin, Jun Jing
https://arxiv.org/abs/2509.06560 https://arxiv.org/pdf/2509.06560

Universal quantum control over bosonic network
Perfect transfer of unknown states across distinct nodes is fundamental in the construction of bosonic quantum networks. We here develop a general theory to control an $N$-node bosonic network governed by the time-dependent Hamiltonian, as the universal quantum control theory for continuous-variable systems. In particular, we can activate nonadiabatic passages superposed of initial and target modes by the commutation condition for the Hamiltonian's coefficient matrix in the representation of ti…

Distributed Unknown Input Observer Design with Relaxed Conditions: Theory and Application to Vehicle Platooning
Ruixuan Zhao, Guitao Yang, Thomas Parisini, Boli Chen
https://arxiv.org/abs/2509.08783

Distributed Unknown Input Observer Design with Relaxed Conditions: Theory and Application to Vehicle Platooning
Designing observers for linear systems with both known and unknown inputs is an important problem in several research contexts, for example, fault diagnosis and fault-tolerant control, and cyber-secure control systems, and presents significant challenges in distributed state estimation due to the limited sensing capabilities of individual nodes. Existing methods typically impose an individual input-to-output rank condition on each estimator node, which severely restricts applicability in practi…

Using Optimal Transport Aligned Latent Embeddings for Separated Flow Analysis
Jonathan Quang Tran, Chi-An Yeh, Kunihiko Taira
https://arxiv.org/abs/2509.07318 https://

Using Optimal Transport Aligned Latent Embeddings for Separated Flow Analysis
Quantifying differences between flow fields is a key challenge in fluid mechanics, particularly when evaluating the effectiveness of flow control. Traditional vector metrics, such as the Euclidean distance, provide straightforward pointwise comparisons but can fail to distinguish distributional changes in flow fields. To address this limitation, we employ optimal transport (OT) theory, which is a mathematical framework built on probability and measure theory. By aligning Euclidean distances bet…

Magnetic-Field Control of Tomonaga-Luttinger Liquids in Ta2Pd3Te5 Edge States
Xingchen Guo Anqi Wang, Xiutong Deng, Yupeng Li, Guoan Li, Zhiyuan Zhang, Xiaofan Shi, Xiao Deng, Ziwei Dou, Guangtong Liu, Fanming Qu, Zhijun Wang, Tian Qian, Youguo Shi, Li Lu, Jie Shen
https://arxiv.org/abs/2510.07973 …

Magnetic-Field Control of Tomonaga-Luttinger Liquids in Ta2Pd3Te5 Edge States
Ta2Pd3Te5 is a quasi-one-dimensional transition-metal telluride whose heavy atoms endow the material with strong spin-orbit coupling, while the Fermi level inside the bulk gap makes the low-energy electronic structure highly tunable.Theory and early experiments have already identified a wealth of emergent phases in this platform: an excitonic insulator driven by electron-hole binding, a second-order topological insulator protected by crystalline symmetry, a potential topological-protected quant…

Nonlinear dispersive waves in soft elastic laminates under finite magneto-deformations
Harold Berjamin, Stephan Rudykh
https://arxiv.org/abs/2508.06324 https://

Nonlinear dispersive waves in soft elastic laminates under finite magneto-deformations
Layered media can be used as acoustic filters, allowing only waves of certain frequencies to propagate. In soft magneto-active laminates, the shear wave band gaps (i.e., the frequency intervals for which shear waves cannot propagate) can be adjusted after fabrication by exploiting the magneto-elastic coupling. In the present study, the control of shear wave propagation in magneto-active stratified media is revisited by means of homogenisation theory, and extended to nonlinear waves of moderate …

Anarcho-syndicalism is the belief that workers, as the fundamental producers of social value, must seize control of the means of production through direct action and autonomous organization. It rejects both capitalist private ownership and state-controlled systems, arguing instead for a decentralized federation of worker-managed industries. From my perspective, anarcho-syndicalism is not merely an economic strategy but a revolutionary theory of social transformation, one that places the work…

Multivariable Current Controller for Enhancing Dynamic Response and Grid Synchronization Stability of IBRs
Hassan Yazdani, Ali Maleki, Saeed Lotfifard, Ali Saberi
https://arxiv.org/abs/2509.08201

Multivariable Current Controller for Enhancing Dynamic Response and Grid Synchronization Stability of IBRs
This paper develops a multivariable current control strategy for inverter-based resources (IBRs) based on optimal control theory to enhance their dynamic performance and grid synchronization stability. The structure of the implemented multiple-input, multiple-output (MIMO) controller closely resembles that of the commonly used conventional single-input, single-output (SISO) PI controllers for IBRs. As a result, it requires only minor adjustments to conventional vector current control schemes, t…

A set of master variables for the two-star random graph
Pawat Akara-pipattana, Oleg Evnin
https://arxiv.org/abs/2509.07423 https://arxiv.org/pdf/2509.07423…

A set of master variables for the two-star random graph
The two-star random graph is the simplest exponential random graph model with nontrivial interactions between the graph edges. We propose a set of auxiliary variables that control the thermodynamic limit where the number of vertices N tends to infinity. Such 'master variables' are usually highly desirable in treatments of 'large N' statistical field theory problems. For the dense regime when a finite fraction of all possible edges are filled, this construction recovers the mean field solution o…

One rig to control them all
Chris Heunen, Robin Kaarsgaard, Louis Lemonnier
https://arxiv.org/abs/2510.05032 https://arxiv.org/pdf/2510.05032

One rig to control them all
We introduce a theory for computational control, consisting of seven naturally interpretable equations. Adding these to a prop of base circuits constructs controlled circuits, borne out in examples of reversible Boolean circuits and quantum circuits. We prove that this syntactic construction semantically corresponds to taking the free rig category on the base prop.

VoltanaLLM: Feedback-Driven Frequency Control and State-Space Routing for Energy-Efficient LLM Serving
Jiahuan Yu (University of Illinois Urbana-Champaign), Aryan Taneja (University of Illinois Urbana-Champaign), Junfeng Lin (Tsinghua University), Minjia Zhang (University of Illinois Urbana-Champaign)
https://arxiv.org/abs/2509.04827

VoltanaLLM: Feedback-Driven Frequency Control and State-Space Routing for Energy-Efficient LLM Serving
Modern Large Language Model (LLM) serving systems increasingly support interactive applications, like real-time chat assistants, code generation tools, and agentic workflows. However, the soaring energy cost of LLM inference presents a growing challenge for sustainable and cost-effective deployment. This paper introduces VoltanaLLM, a system for SLO-aware, energy-efficient LLM serving, built from a control theory perspective. VoltanaLLM co-designs frequency scaling and request routing in emergi…

Cavity-induced Eliashberg effect: superconductivity vs charge density wave
Md Mursalin Islam, Michele Pini, R. Flores-Calder\'on, Francesco Piazza
https://arxiv.org/abs/2509.07865

Cavity-induced Eliashberg effect: superconductivity vs charge density wave
Recent experiments have shown that non-equilibrium effects can play a key role in cavity-based control of material phases, notably in systems with charge-density-wave order. Motivated by this, we extend the theory of the Eliashberg effect, originally developed for superconducting phases, to charge-density-wave phases. Starting from a minimal electronic model where superconductivity and charge-density-wave order are equivalent at equilibrium, we introduce coupling to cavity photons, which are in…

Exploring epidemic control policies using nonlinear programming and mathematical models
Sandra Montes-Olivas, Adam J. Kucharski, Michael B. Gravenor, Simon D. W. Frost
https://arxiv.org/abs/2508.05290 …

Exploring epidemic control policies using nonlinear programming and mathematical models
Optimal control theory in epidemiology has been used to establish the most effective intervention strategies for managing and mitigating the spread of infectious diseases while considering constraints and costs. Using Pontryagin's Maximum Principle, indirect methods provide necessary optimality conditions by transforming the control problem into a two-point boundary value problem. However, these approaches are often sensitive to initial guesses and can be computationally challenging, especially…

Generalized Wigner-Smith theory for perturbations at exceptional and diabolic point degeneracies
Kaiyuan Wang, Niall Byrnes, Matthew R. Foreman
https://arxiv.org/abs/2508.05039 …

Generalized Wigner-Smith theory for perturbations at exceptional and diabolic point degeneracies
Spectral degeneracies, including diabolic (DP) and exceptional (EP) points, exhibit unique sensitivity to external perturbations, enabling powerful control and engineering of wave phenomena. We present a residue-based perturbation theory that quantifies complex resonance splitting of DP and EP type spectral degeneracies using generalized Wigner-Smith operators. We validate our theory using both analytic Hamiltonian models and numerical electromagnetic simulations, demonstrating excellent agreem…

Optimization via a Control-Centric Framework
Liraz Mudrik, Isaac Kaminer, Sean Kragelund, Abram H. Clark
https://arxiv.org/abs/2510.05455 https://arxiv.org…

Optimization via a Control-Centric Framework
Optimization plays a central role in intelligent systems and cyber-physical technologies, where the speed and reliability of convergence directly impact performance. In control theory, optimization-centric methods are standard: controllers are designed by repeatedly solving optimization problems, as in linear quadratic regulation, $H_\infty$ control, and model predictive control. In contrast, this paper develops a control-centric framework for optimization itself, where algorithms are construct…

Multiport Network Modeling and Optimization for Reconfigurable Pinching-Antenna Systems
Zhaolin Wang, Jiaqi Xu, Chongjun Ouyang, Xidong Mu, Yuanwei Liu
https://arxiv.org/abs/2509.05612

Multiport Network Modeling and Optimization for Reconfigurable Pinching-Antenna Systems
A reconfigurable pinching-antenna system (PASS) is presented, endowing pinching antennas (PAs) with both amplitude- and phase-controllable radiation beyond conventional implementations. To characterize this feature, a general and physically consistent model is established for PASS via multiport network theory. Within this model, the fundamental constraint of ideal reconfigurability of PAs is identified, allowing the full control of signal amplitudes and phases. A practical directional-coupler (…

An efficient grey theory-driven path selection for energy efficiency control in the Internet of Things using fog and cloud computing
Mohammad Reza Akbari, Hamid Barati, Ali Barati
https://arxiv.org/abs/2510.03533

An efficient grey theory-driven path selection for energy efficiency control in the Internet of Things using fog and cloud computing
Due to the big data exchange on the Internet of Things, proper routing and selecting the best routes for fast data transmission improve network performance. There are major challenges, like high delay, when cloud computing is used. Therefore, one solution is to use other schemes, such as fog computing. In fog computing, all data is not sent to the cloud and the fog nodes close to objects are used for data processing. This reduces the network delay. In this paper, we propose an overlapping clust…

On the convergence of the variational quantum eigensolver and quantum optimal control
Marco Wiedmann, Daniel Burgarth, Gunther Dirr, Thomas Schulte-Herbr\"uggen, Emanuel Malvetti, Christian Arenz
https://arxiv.org/abs/2509.05295

On the convergence of the variational quantum eigensolver and quantum optimal control
When does a variational quantum algorithm converge to a globally optimal problem solution? Despite the large literature around variational approaches to quantum computing, the answer is largely unknown. We address this open question by developing a convergence theory for the variational quantum eigensolver (VQE). By leveraging the terminology of quantum control landscapes, we prove a sufficient criterion that characterizes when convergence to a ground state of a Hamiltonian can be guaranteed fo…

Crosslisted article(s) found for math.CT. https://arxiv.org/list/math.CT/new
[1/1]:
- One rig to control them all
Chris Heunen, Robin Kaarsgaard, Louis Lemonnier

Ground state magnetic structure of Mn3Sn
Jeppe Jon Cederholm, Zhian Xu, Yanfeng Guo, Martin Ovesen, Thomas Olsen, Kristine M. L. Krighaar, Chrystalla Knekna, Jian Rui Soh, Youngro Lee, Navid Qureshi, Jose Alberto Rodriguez Velamazan, Eric Ressouche, Andrew T. Boothroyd, Henrik Jacobsen
https://arxiv.org/abs/2510.06808

Ground state magnetic structure of Mn3Sn
We use spherical neutron polarimetry to determine the ground state magnetic structure of Mn3Sn. We find that Mn3Sn adopts an inverse triangular structure with spins parallel to <100> (Type III) rather than spins parallel to <110> (Type IV). Density functional theory calculations reveal no energy difference between these two structures, suggesting that the selection is caused by subtle effects such as sixth-order anisotropy. Partial control of the magnetic domain population through a moderate ma…

Dynamical feedback control with operator learning for the Vlasov-Poisson system
Jingcheng Lu, Li Wang, Jeff Calder
https://arxiv.org/abs/2509.23063 https://

Dynamical feedback control with operator learning for the Vlasov-Poisson system
To meet the demands of instantaneous control of instabilities over long time horizons in plasma fusion, we design a dynamic feedback control strategy for the Vlasov-Poisson system by constructing an operator that maps state perturbations to an external control field. In the first part of the paper, we propose learning such an operator using a neural network. Inspired by optimal control theory for linearized dynamics, we introduce a low-rank neural operator architecture and train it via adjoint …

Decision Theory For Large Scale Outlier Detection Using Aleatoric Uncertainty: With a Note on Bayesian FDR
Ryan Warnick
https://arxiv.org/abs/2508.01988 https://

Decision Theory For Large Scale Outlier Detection Using Aleatoric Uncertainty: With a Note on Bayesian FDR
Aleatoric and Epistemic uncertainty have achieved recent attention in the literature as different sources from which uncertainty can emerge in stochastic modeling. Epistemic being intrinsic or model based notions of uncertainty, and aleatoric being the uncertainty inherent in the data. We propose a novel decision theoretic framework for outlier detection in the context of aleatoric uncertainty; in the context of Bayesian modeling. The model incorporates bayesian false discovery rate control for…

First-order theory of torsion-free Tarski monsters
R\'emi Coulon, Francesco Fournier-Facio, Meng-Che "Turbo" Ho
https://arxiv.org/abs/2508.21244 https://

First-order theory of torsion-free Tarski monsters
We develop methods to control the first-order theory of groups arising as certain direct limits of torsion-free hyperbolic groups. We apply this to construct simple torsion-free Tarski monsters (non-abelian groups whose non-trivial, proper subgroups are infinite cyclic) with the same positive theory as the free group, answering several questions of Casals-Ruiz, Garreta, and de la Nuez González. Moreover, these groups may be chosen so that every non-trivial conjugacy-invariant norm is stably bo…

J4CC, A Frame for Communication Control
Aernout Schmidt, Kunbei Zhang
https://arxiv.org/abs/2508.00485 https://arxiv.org/pdf/2508.00485

J4CC, A Frame for Communication Control
Politics increasingly faces conflicts that appear irreconcilable, where one party's requirements directly contradict those of another. We propose J4CC, a frame for mapping how four forces (Power, Capital, Morality, and Knowledge) influence rule-making. J4CC provides a jargon for analyzing rule-making conversations. Beyond ideas about framing (Lakoff 2004; Rein & Schön, 1996), it draws on ideas from legal theory (Fuller 1967), institutional economics (Coase 1937), anthropology (Douglas 1992), a…

Control of cross-beam energy transfer through laser-plasma parameter adjustment
Yilin Xu, Yao Zhao, Hongwei Yin, Zhuwen Lin, Yan Yin, Liang Hao, Yaozhi Yi, Hongyu Zhou, Jinlong Jiao, Anle Lei
https://arxiv.org/abs/2508.03152

Control of cross-beam energy transfer through laser-plasma parameter adjustment
Cross-beam energy transfer (CBET) between two lasers is investigated through both analytical theory and two-dimensional simulations, with particular attention to its linear and nonlinear evolution under various laser-plasma conditions over timescales from several hundred picoseconds to one nanosecond. Based on the dispersion relation of stimulated Brillouin scattering driven by two laser beams, we obtain a laser frequency difference range within which CBET occurs. In the nonlinear regime, high …

Machine Learning and Control: Foundations, Advances, and Perspectives
Enrique Zuazua
https://arxiv.org/abs/2510.03303 https://arxiv.org/pdf/2510.03303

Machine Learning and Control: Foundations, Advances, and Perspectives
Control theory of dynamical systems offers a powerful framework for tackling challenges in deep neural networks and other machine learning architectures. We show that concepts such as simultaneous and ensemble controllability offer new insights into the classification and representation properties of deep neural networks while the control and optimization of static systems can be employed to better understand the performance of shallow networks. Inspired by the classical concept of turnpike, we…

Cloud-Assisted Remote Control for Aerial Robots: From Theory to Proof-of-Concept Implementation
Achilleas Santi Seisa, Viswa Narayanan Sankaranarayanan, Gerasimos Damigos, Sumeet Gajanan Satpute, George Nikolakopoulos
https://arxiv.org/abs/2509.04095

Cloud-Assisted Remote Control for Aerial Robots: From Theory to Proof-of-Concept Implementation
Cloud robotics has emerged as a promising technology for robotics applications due to its advantages of offloading computationally intensive tasks, facilitating data sharing, and enhancing robot coordination. However, integrating cloud computing with robotics remains a complex challenge due to network latency, security concerns, and the need for efficient resource management. In this work, we present a scalable and intuitive framework for testing cloud and edge robotic systems. The framework co…

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Optimal Modified Feedback Strategies in LQ Games under Control Imperfections
Mahdis Rabbani, Navid Mojahed, Shima Nazari

Passive nonlinear FIR filters for data-driven control
Zixing Wang, Fulvio Forni
https://arxiv.org/abs/2508.05279 https://arxiv.org/pdf/2508.05279

Passive nonlinear FIR filters for data-driven control
We propose a new class of passive nonlinear finite impulse response operators. This class is constructed by the action of finite impulse response filters in a lifted space. This allows for efficient control synthesis through constrained optimization. Closed-loop performance is taken into account through least-squares fitting, based on the theory of virtual reference feedback tuning. Passivity is established through efficient linear constraints, based on sampling in the frequency domain. Because…

Rough Path Approaches to Stochastic Control, Filtering, and Stopping
Jonathan A. Mavroforas, Anthony H. Dooley
https://arxiv.org/abs/2509.03055 https://arx…

Rough Path Approaches to Stochastic Control, Filtering, and Stopping
This paper presents a unified exposition of rough path methods applied to optimal control, robust filtering, and optimal stopping, addressing a notable gap in the existing literature where no single treatment covers all three areas. By bringing together key elements from Lyons' theory of rough paths, Gubinelli's controlled rough paths, and related developments, we recast these classical problems within a deterministic, pathwise framework. Particular emphasis is placed on providing detailed proo…

Criminal Property Rights Suppress Violence in Urban Drug Markets: Theory and Evidence from Merseyside, U.K
Paolo Campana. Andrea Giovannetti, Paolo Pin, Roberto Rozzi
https://arxiv.org/abs/2508.02561

Criminal Property Rights Suppress Violence in Urban Drug Markets: Theory and Evidence from Merseyside, U.K
In this work, we provide empirical evidence on organized criminal groups' (OCGs) behavior across the Liverpool area in the U.K. (Merseyside). We find that violent crimes concerning OCGs concentrate in the areas yielding the highest revenue, while OGCs primarily control areas yielding middle or low revenue. We explain and generalize these empirical observations with a theoretical model examining how OCGs strategically select which area to exploit based on expected revenue and the presence of oth…

Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers
Krati Saxena, Federico Jurado Ruiz, Guido Manzi, Dianbo Liu, Alex Lamb
https://arxiv.org/abs/2509.16058

Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers
Attention mechanisms have become integral in AI, significantly enhancing model performance and scalability by drawing inspiration from human cognition. Concurrently, the Attention Schema Theory (AST) in cognitive science posits that individuals manage their attention by creating a model of the attention itself, effectively allocating cognitive resources. Inspired by AST, we introduce ASAC (Attention Schema-based Attention Control), which integrates the attention schema concept into artificial n…

Covariate balance under Bayesian decision theory
Andr\'e A. F. Fumis, Victor Fossaluza, Rafael B. Stern
https://arxiv.org/abs/2509.01828 https://arxiv.…

Covariate balance under Bayesian decision theory
We study optimal sample allocation between treatment and control groups under Bayesian linear models. We derive an analytic expression for the Bayes risk, which depends jointly on sample size and covariate mean balance across groups. Under a flat conditional prior, the covariate mean balance term simplifies to the Mahalanobis distance. Our results reveal that the optimal allocation does not always correspond to equal sample sizes, and we provide sufficient conditions under which equal allocatio…

Microscopic Theory of Light-Induced Coherent Phonons Mediated by Quantum Geometry
Jiaming Hu, Zhichao Guo, Wenbin Li, Hua Wang, Kai Chang
https://arxiv.org/abs/2508.03257 https:…

Microscopic Theory of Light-Induced Coherent Phonons Mediated by Quantum Geometry
Light-induced coherent phonons provide a powerful platform for ultrafast control of material properties. However, the microscopic theory and quantum geometric nature of this phenomenon remain underexplored. Here, we develop a fully quantum-mechanical framework based on Feynman diagrams to systematically describe the generation of coherent phonons by light. We identify a dominant second-order, double-resonant process in noncentrosymmetric semiconductors that efficiently couples light to both ele…

AI Foundation Model for Time Series with Innovations Representation
Lang Tong, Xinyi Wang
https://arxiv.org/abs/2510.01560 https://arxiv.org/pdf/2510.01560…

AI Foundation Model for Time Series with Innovations Representation
This paper introduces an Artificial Intelligence (AI) foundation model for time series in engineering applications, where causal operations are required for real-time monitoring and control. Since engineering time series are governed by physical, rather than linguistic, laws, large-language-model-based AI foundation models may be ineffective or inefficient. Building on the classical innovations representation theory of Wiener, Kallianpur, and Rosenblatt, we propose Time Series GPT (TS-GPT) -- a…

Varieties and pure symbols
Alexander Vishik
https://arxiv.org/abs/2509.00592 https://arxiv.org/pdf/2509.00592

Varieties and pure symbols
In this article, we prove that the 2-isotropy of any projective variety is controlled by a pure symbol in the Milnor's K-theory (mod 2) of the flexible closure of the base field. We also show that such pure symbols control the 2-equivalence of field extensions as well as the numerical equivalence of algebraic cycles (with mod 2 coefficients).

STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
Gary Simethy, Daniel Ortiz-Arroyo, Petar Durdevic
https://arxiv.org/abs/2508.19011

STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
Most deep learning methods for imputing missing values treat the task as completing patterns within a fixed time window. This assumption often fails in industrial systems, where dynamics are driven by control actions, are highly non-stationary, and can experience long, uninterrupted gaps. We propose STDiff, which reframes imputation as learning how the system evolves from one state to the next. STDiff uses a conditional denoising diffusion model with a causal bias aligned to control theory, gen…

I’m an anarcho-syndicalist through and through, and I’m unapologetic about it. I reject all forms of authoritarianism, including Marxism-Leninism with its centralized, hierarchical party structure. Anarcho-syndicalism demands direct, horizontal worker control through federated assemblies with binding, recallable mandates as the only true path to emancipation.
If you intend to dispute this, I suggest thoroughly engaging with the relevant political theory first, because Marxism-Leninism,…

Crosslisted article(s) found for eess.SP. https://arxiv.org/list/eess.SP/new
[1/1]:
- A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dyna...
Jonathan Gornet, Yilin Mo, Bruno Sinopoli

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains
Dongzhe Zheng, Wenjie Mei
https://arxiv.org/abs/2509.19672 https://

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains
Stochastic optimal control methods often struggle in complex non-convex landscapes, frequently becoming trapped in local optima due to their inability to learn from historical trajectory data. This paper introduces Memory-Augmented Potential Field Theory, a unified mathematical framework that integrates historical experience into stochastic optimal control. Our approach dynamically constructs memory-based potential fields that identify and encode key topological features of the state space, ena…

Global Optimality in Multi-Flyby Asteroid Trajectory Optimization: Theory and Application Techniques
Zhong Zhang, Xiang Guo, Di Wu, Hexi Baoyin, Junfeng Li, Francesco Topputo
https://arxiv.org/abs/2508.02904

Global Optimality in Multi-Flyby Asteroid Trajectory Optimization: Theory and Application Techniques
Designing optimal trajectories for multi-flyby asteroid missions is scientifically critical but technically challenging due to nonlinear dynamics, intermediate constraints, and numerous local optima. This paper establishes a method that approaches global optimality for multi-flyby trajectory optimization under a given sequence. The original optimal control problem with interior-point equality constraints is transformed into a multi-stage decision formulation. This reformulation enables direct a…

Quantum algorithm for linear matrix equations
Rolando D. Somma, Guang Hao Low, Dominic W. Berry, Ryan Babbush
https://arxiv.org/abs/2508.02822 https://arxi…

Quantum algorithm for linear matrix equations
We describe an efficient quantum algorithm for solving the linear matrix equation AX+XB=C, where A, B and C are given complex matrices and X is unknown. This is known as the Sylvester equation, a fundamental equation with applications in control theory and physics. Rather than encoding the solution in a quantum state in a fashion analogous to prior quantum linear algebra solvers, our approach constructs the solution matrix X in a block-encoding, rescaled by some factor. This allows us to obtain…

On the occasion of Dr. Ivan Dmitrievich Remizov's 40th birthday
Ksenia Dragunova, Elmira Kalimulina, Rustem Kalmetev, Nasrin Nikbakht, Elena Nozdrinova, Alexander Pechen, Alexei Savvateev, Evgeni Shavgulidze, Ranjit Singh, Alexander Vedenin, Boris Volkov
https://arxiv.org/abs/2508.18650

On the occasion of Dr. Ivan Dmitrievich Remizov's 40th birthday
This article celebrates the 40th anniversary of Dr. Ivan Dmitrievich Remizov, a mathematician who made a number of important contributions to the theory of one-parameter operator semigroups -- a branch of functional analysis which has applications to differential equations, mathematical physics, random processes, control theory, and quantum mechanics. Born on December 7, 1984, Dr. Remizov obtained his Ph.D. in 2018 from Moscow State University and has made substantial contributions, particularl…

Thermal History of Non-equilibrated Scalars
V. Knapp-Perez, Gopolang Mohlabeng, Michael Ratz, Tim M. P. Tait
https://arxiv.org/abs/2507.21523 https://arxiv…

Thermal History of Non-equilibrated Scalars
Scalar fields in the early Universe are mostly discussed in two limits: either in equilibrium or completely decoupled. In this work we discuss scenarios where there are scalar fields that are not in equilibrium, but for which the coupling to thermal bath leads to interesting non-trivial dynamics. For example, in theories where scalar fields control the effective couplings of the theory, such out-of-equilibrium behavior can lead to cases where the couplings vary during cosmological evolution. We…

A High-Frequency Uncertainty Principle for the Fourier-Bessel Transform
Benjamin Jaye, Rahul Sethi
https://arxiv.org/abs/2509.25500 https://arxiv.org/pdf/2…

A High-Frequency Uncertainty Principle for the Fourier-Bessel Transform
Motivated by problems in control theory concerning decay rates for the damped wave equation $$w_{tt}(x,t) + γ(x) w_t(x,t) + (-Δ+ 1)^{s/2} w(x,t) = 0,$$ we consider an analogue of the classical Paneah-Logvinenko-Sereda theorem for the Fourier Bessel transform. In particular, if $E \subset \mathbb{R}^+$ is $μ_α$-relatively dense (where $dμ_α(x) \approx x^{2α+1}\, dx$) for $α> -1/2$, and $\operatorname{supp} \mathcal{F}_α(f) \subset [R,R+1]$, then we show $$\|f\|_{L^2_α(\mathbb…

Chemical Control of Mechanical Anisotropy and Band Alignment in Perylene-based Two-dimensional MoS$_2$-Organic Hybrids
Mohammed El Amine Miloudi, Oliver K\"uhn
https://arxiv.org/abs/2508.21526

Chemical Control of Mechanical Anisotropy and Band Alignment in Perylene-based Two-dimensional MoS$_2$-Organic Hybrids
This study presents a comprehensive investigation of hybrid interfaces formed by monolayer MoS$_2$ coupled with the organic molecules perylene (P), perylene diimide (PDI), and perylene orange (PO). Using density functional theory, we demonstrate the extent to which the mechanical and electronic properties of a hybrid system can be altered by the chemical modification of a given chromophore. The three systems exhibit distinct differences due to their chemical composition and van der Waals contac…

A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
https://arxiv.org/abs/2510.01364

A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
The paper introduces a linear bandit environment where the reward is the output of a known Linear Gaussian Dynamical System (LGDS). In this environment, we address the fundamental challenge of balancing exploration -- gathering information about the environment -- and exploitation -- selecting to the action with the highest predicted reward. We propose two algorithms, Kalman filter Upper Confidence Bound (Kalman-UCB) and Information filter Directed Exploration Action-selection (IDEA). Kalman-UC…

Synaptic bundle theory for spike-driven sensor-motor system: More than eight independent synaptic bundles collapse reward-STDP learning
Takeshi Kobayashi, Shogo Yonekura, Yasuo Kuniyoshi
https://arxiv.org/abs/2508.14492

Synaptic bundle theory for spike-driven sensor-motor system: More than eight independent synaptic bundles collapse reward-STDP learning
Neuronal spikes directly drive muscles and endow animals with agile movements, but applying the spike-based control signals to actuators in artificial sensor-motor systems inevitably causes a collapse of learning. We developed a system that can vary \emph{the number of independent synaptic bundles} in sensor-to-motor connections. This paper demonstrates the following four findings: (i) Learning collapses once the number of motor neurons or the number of independent synaptic bundles exceeds a cr…

Efficient Optimal Path Planning in Dynamic Environments Using Koopman MPC
Mohammad Abtahi, Navid Mojahed, Shima Nazari
https://arxiv.org/abs/2510.02584 https://

Efficient Optimal Path Planning in Dynamic Environments Using Koopman MPC
This paper presents a data-driven model predictive control framework for mobile robots navigating in dynamic environments, leveraging Koopman operator theory. Unlike the conventional Koopman-based approaches that focus on the linearization of system dynamics only, our work focuses on finding a global linear representation for the optimal path planning problem that includes both the nonlinear robot dynamics and collision-avoidance constraints. We deploy extended dynamic mode decomposition to ide…

Chemical and Conformational Control of the Spectroscopic Properties of Multi-Layer and Multi-Defect Carbon Dots
Arshad Mehmood, Caitlin V. Hetherington, Zain Zaidi, Benjamin G. Levine
https://arxiv.org/abs/2508.16520

Chemical and Conformational Control of the Spectroscopic Properties of Multi-Layer and Multi-Defect Carbon Dots
Carbon dots (CDs) are renowned for their bright and tunable photoluminescence (PL), stability, and biocompatibility, yet it remains challenging to link their heterogeneous structures to their spectroscopic properties. This study utilizes density functional theory (DFT) and time-dependent DFT (TD-DFT) to systematically investigate how the spectroscopic properties of CDs of complex CDs with multiple layers and multiples defects are determined by their structures and compositions. Calculations rev…

Probability Density Estimation via Optimal Control
Markus Hegland, C. Yal\c{c}{\i}n Kaya
https://arxiv.org/abs/2510.00835 https://arxiv.org/pdf/2510.00835

Probability Density Estimation via Optimal Control
We employ optimal control theory to study the problem of estimating the probability density function from a data set originating from an unknown probability distribution. The original variational problem is reformulated as a multi-stage optimal control problem and the associated maximum principle, or conditions of optimality, is reduced to a two-point boundary-value problem with interior conditions. A numerical scheme is proposed to solve the discretization of this problem. Estimates of density…

Semantic Numeration Systems as Dynamical Systems
Alexander Yu. Chunikhin
https://arxiv.org/abs/2507.21295 https://arxiv.org/pdf/2507.21295

Semantic Numeration Systems as Dynamical Systems
The foundational concepts of semantic numeration systems theory are briefly outlined. The action of cardinal semantic operators unfolds over a set of cardinal abstract entities belonging to the cardinal semantic multeity. The cardinal abstract object (CAO) formed by them in a certain connectivity topology is proposed to be considered as a linear discrete dynamical system with nonlinear control. Under the assumption of ideal observability, the CAO state equations are provided for both stationary…

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Feedback Control for Small Budget Pacing
Sreeja Apparaju, Yichuan Niu, Xixi Qi
h…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Large-scale Multiple Testing: Fundamental Limits of False Discovery Rate Control and Compound Oracle
Yutong Nie, Yihong Wu

A Crime/S.I.R. optimal control problem
Mariana \'Alvarez, Alexander Alegr\'ia, Andr\'es Rivera, Sebasti\'an Pedersen
https://arxiv.org/abs/2509.21406 https://

A Crime/S.I.R. optimal control problem
This paper presents and discusses a mathematical model inspired by control theory to derive optimal public policies for minimizing costs associated with the reduction and control of criminal activity in a population. Specifically, we analyze the optimal control problem \begin{equation*} \min G(u_1, u_2, u_3) = \int_{0}^{t_{\text{F}}} \left( I(t) - R(t) + \frac{B_1}{2} u_1^2(t) + \frac{B_2}{2} u_2^2(t) + \frac{B_3}{2} u_3^2(t) \right) \, dt. \end{equation*} where $I=I(t)$ and $R=R(t)$ satisfies …

Hamilton--Jacobi--Bellman equation for optimal control of stochastic Wasserstein--Hamiltonian system on graphs
Jianbo Cui, Tonghe Dang
https://arxiv.org/abs/2509.25965 https://

Hamilton--Jacobi--Bellman equation for optimal control of stochastic Wasserstein--Hamiltonian system on graphs
Stochastic optimal control problems for Hamiltonian dynamics on graphs have wide-ranging applications in mechanics and quantum field theory, particularly in systems with graph-based structures. In this paper, we establish the existence and uniqueness of viscosity solutions for a new class of Hamilton--Jacobi--Bellman (HJB) equations arising from the optimal control of stochastic Wasserstein--Hamiltonian systems (SWHSs) on graphs. One distinctive feature of these HJB equations is the simultaneou…

Generalized Beyond-Diagonal RIS Architectures: Theory and Design via Structure-oriented Symmetric Unitary Projection
Xiaohua Zhou, Tianyu Fang, Yijie Mao, Bruno Clerckx
https://arxiv.org/abs/2509.17804

Generalized Beyond-Diagonal RIS Architectures: Theory and Design via Structure-oriented Symmetric Unitary Projection
Beyond-diagonal reconfigurable intelligent surface (BD-RIS), which enables advanced wave control through interconnection of RIS elements, are gaining growing recognition as a promising technology for 6G and beyond. However, the enhanced flexibility of BD-RIS in controlling the phase and amplitude of reflected signals comes at the cost of high circuit complexity. In this paper, we propose two novel BD-RIS architectures, namely, the stem-connected RIS and cluster-connected RIS, to explore trade-o…

Electromagnetically driven, environmentally adaptive, and functionally switchable hydrodynamic devices
Chen-Long Wu, Bin Wang, Hao Wang, Neng-Zhi Yao, Liujun Xu, Xuesheng Wang, Jiping Huang
https://arxiv.org/abs/2509.26491

Electromagnetically driven, environmentally adaptive, and functionally switchable hydrodynamic devices
Metamaterials provide exceptional control over physical phenomena, enabling many disruptive technologies. However, researches in hydrodynamic meta-devices have mainly used intrusive methods to manipulate material structures, limited by material properties and specific environmental conditions. Each design serves a single function, reducing versatility. This study introduces a meta-hydrodynamics theory using applied force fields to avoid physical contact with the fluid and eliminate the need for…

Dispersion Formation Control: from Geometry to Distribution
Jin Chen, Jesus Bautista Villar, Bayu Jayawardhana, Hector Garcia de Marina
https://arxiv.org/abs/2509.19784 https://…

Dispersion Formation Control: from Geometry to Distribution
We introduce and develop the concept of dispersion formation control, bridging a gap between shape-assembly studies in physics and biology and formation control theory. In current formation control studies, the control objectives typically focus on achieving desired local geometric properties, such as inter-agent distances, bearings, or relative positions. In contrast, our dispersion formation control approach enables agents to directly regulate the dispersion of their spatial distribution, a g…

The effect of dephasing and spin-lattice relaxation during the switching processes in quantum antiferromagnets
Asliddin Khudoyberdiev, G\"otz S. Uhrig
https://arxiv.org/abs/2508.00430

The effect of dephasing and spin-lattice relaxation during the switching processes in quantum antiferromagnets
The control of antiferromagnetic order can pave the way to large storage capacity as well as fast manipulation of stored data. Here achieving a steady-state of sublattice magnetization after switching is crucial to prevent loss of stored data. The present theoretical approach aims to obtain instantaneous stable states of the order after reorienting the Néel vector in open quantum antiferromagnets using time-dependent Schwinger boson mean-field theory. The Lindblad formalism is employed to coup…

Koopman Operator Based Linear Model Predictive Control for 2D Quadruped Trotting, Bounding, and Gait Transition
Chun-Ming Yang, Pranav A. Bhounsule
https://arxiv.org/abs/2507.14605

Koopman Operator Based Linear Model Predictive Control for 2D Quadruped Trotting, Bounding, and Gait Transition
Online optimal control of quadrupedal robots would enable them to plan their movement in novel scenarios. Linear Model Predictive Control (LMPC) has emerged as a practical approach for real-time control. In LMPC, an optimization problem with a quadratic cost and linear constraints is formulated over a finite horizon and solved on the fly. However, LMPC relies on linearizing the equations of motion (EOM), which may lead to poor solution quality. In this paper, we use Koopman operator theory and …

Theory of Multi-photon Processes for Applications in Quantum Control
Longxiang Huang, Jacquelin Luneau, Johannes Schirk, Florian Wallner, Christian M. F. Schneider, Stefan Filipp, Klaus Liegener, Peter Rabl
https://arxiv.org/abs/2509.16074

Theory of Multi-photon Processes for Applications in Quantum Control
We present a general theoretical framework for evaluating multi-photon processes in periodically driven quantum systems, which have been identified as a versatile tool for engineering and controlling nontrivial interactions in various quantum technology platforms. To achieve the accuracy required for such applications, the resulting effective coupling rates, as well as any drive-induced frequency shifts, must be determined with very high precision. Here, we employ degenerate Floquet perturbatio…

Optimal Impulsive Control of Cislunar Relative Motion using Reachable Set Theory
Matthew Hunter, Walter J. Manuel, Simone D'Amico
https://arxiv.org/abs/2507.21425 https://…

Optimal Impulsive Control of Cislunar Relative Motion using Reachable Set Theory
This work presents the first application of the state-of-the-art Koenig-D'Amico reachable set theory solver to cislunar, chaotic relative motion in the Circular-Restricted Three-Body Problem (CR3BP). The relative motion dynamics of two spacecraft, a chief and a deputy, in the CR3BP are formulated as a Linear Time-Variant (LTV) system, allowing the solver to find an optimal impulsive control maneuver plan. This methodology demonstrates robust and accurate control performance for both small and l…

Emergent Cognitive Convergence via Implementation: A Structured Loop Reflecting Four Theories of Mind (A Position Paper)
Myung Ho Kim
https://arxiv.org/abs/2507.16184

Emergent Cognitive Convergence via Implementation: A Structured Loop Reflecting Four Theories of Mind (A Position Paper)
We report the discovery of a structural convergence across four influential theories of mind: Kahneman's dual-system theory, Friston's predictive processing, Minsky's society of mind, and Clark's extended mind-emerging unintentionally within a practical AI agent architecture called Agentic Flow. Designed to address limitations in large language models (LLMs), Agentic Flow comprises five interdependent modules such as Retrieval, Cognition, Control, Memory, and Action arranged in a recurrent cogn…

Tight Bounds for Schr\"odinger Potential Estimation in Unpaired Image-to-Image Translation Problems
Nikita Puchkin, Denis Suchkov, Alexey Naumov, Denis Belomestny
https://arxiv.org/abs/2508.07392 …

Tight Bounds for Schrödinger Potential Estimation in Unpaired Image-to-Image Translation Problems
Modern methods of generative modelling and unpaired image-to-image translation based on Schrödinger bridges and stochastic optimal control theory aim to transform an initial density to a target one in an optimal way. In the present paper, we assume that we only have access to i.i.d. samples from initial and final distributions. This makes our setup suitable for both generative modelling and unpaired image-to-image translation. Relying on the stochastic optimal control approach, we choose an Or…

Designing efficient interventions for pre-disease states using control theory
Makito Oku
https://arxiv.org/abs/2507.18269 https://arxiv.org/pdf/2507.18269

Designing efficient interventions for pre-disease states using control theory
To extend healthy life expectancy in an aging society, it is crucial to prevent various diseases at pre-disease states. Although dynamical network biomarker theory has been developed for pre-disease detection, mathematical frameworks for pre-disease treatment have not been well established. Here I propose a control theory-based approach for pre-disease treatment, named Markov chain sparse control (MCSC), where time evolution of a probability distribution on a Markov chain is described as a disc…

A Game-Theoretic Framework for Network Formation in Large Populations
Gokce Dayanikli, Mathieu Lauriere
https://arxiv.org/abs/2508.03847 https://arxiv.org/…

A Game-Theoretic Framework for Network Formation in Large Populations
In this paper, we study a model of network formation in large populations. Each agent can choose the strength of interaction (i.e. connection) with other agents to find a Nash equilibrium. Different from the recently-developed theory of graphon games, here each agent's control depends not only on her own index but also on the index of other agents. After defining the general model of the game, we focus on a special case with piecewise constant graphs and we provide optimality conditions through…

Excited State Absorption Drives Low-Energy Optical Limiting in Oligothiophenes
Mustapha Driouech, Michele Guerrini, Caterina Cocchi
https://arxiv.org/abs/2507.21578 https://

Excited State Absorption Drives Low-Energy Optical Limiting in Oligothiophenes
Optical limiting (OL), a crucial mechanism for protecting human eyes and sensitive sensors from intense radiation, relies on understanding the optical nonlinearities acting on the systems. Assessing and disentangling the effects at play is crucial to predict and control the nonlinear optical response in real materials. In this ab initio study based on real-time time-dependent density-functional theory, we investigate non-perturbatively the absorption spectra of a set of thiophene oligomers, the…

Adaptive Model-Predictive Control of a Soft Continuum Robot Using a Physics-Informed Neural Network Based on Cosserat Rod Theory
Johann Licher, Max Bartholdt, Henrik Krauss, Tim-Lukas Habich, Thomas Seel, Moritz Schappler
https://arxiv.org/abs/2508.12681

Adaptive Model-Predictive Control of a Soft Continuum Robot Using a Physics-Informed Neural Network Based on Cosserat Rod Theory
Dynamic control of soft continuum robots (SCRs) holds great potential for expanding their applications, but remains a challenging problem due to the high computational demands of accurate dynamic models. While data-driven approaches like Koopman-operator-based methods have been proposed, they typically lack adaptability and cannot capture the full robot shape, limiting their applicability. This work introduces a real-time-capable nonlinear model-predictive control (MPC) framework for SCRs based…

Refine coherent control of atomic qubits via wave-function approach conditioned on no-decay
Yuan Sun
https://arxiv.org/abs/2509.20042 https://arxiv.org/pdf…

Refine coherent control of atomic qubits via wave-function approach conditioned on no-decay
As a fundamental phenomenon in quantum systems, spontaneous emission constitutes an inevitable source of error, which ultimately degrades the fidelity of quantum logic gates. A successful quantum logic gate needs to operate on the condition that no decay event, such as spontaneous emission, occurs. Such successes can be ensured by post-selection based on syndrome extraction according to the theory of quantum error correction or quantum error mitigation. In this case, the wave function of qubits…

Chemical control of polymorphism and ferroelectricity in PbTiO3 and SrTiO3 monolayers and bilayers
Shaowen Xu, Jeffrey R. Reimers, Fanhao Jia, Wei Ren
https://arxiv.org/abs/2508.18777

Chemical control of polymorphism and ferroelectricity in PbTiO3 and SrTiO3 monolayers and bilayers
Layers of perovskites, found in 3D materials, 2D heterostructures, and nanotubes, often distort from high symmetry to facilitate dipole polarisation that is exploitable in many applications. Using density-functional theory calculations, ferroelectricity in bilayers of the 2D materials PbTiO3 and SrTiO3 is shown to be controlled by bond breakage and formation processes that act as binary switches. These stacking-dependent processes turn on and off as a function of relaxation from high-symmetry s…

Robust Load Disturbance Rejection in PWM DC-DC Buck Converters
Simone Pirrera, Francesco Gabriele, Davide Lena, Fabio Pareschi, Diego Regruto, Gianluca Setti
https://arxiv.org/abs/2509.02102

Robust Load Disturbance Rejection in PWM DC-DC Buck Converters
This paper presents a novel approach to robust load disturbance rejection in DC-DC Buck converters. We propose a novel control scheme based on the design of two nested feedback loops. First, we design the controller in the outer loop using H infinity optimal control theory, and we show, by means of mu-analysis, that such a controller provides robust stability in the presence of uncertainty affecting the physical parameters of the circuit. Then, we introduce an inner feedback loop to improve the…

Distance Between Stochastic Linear Systems
Venkatraman Renganathan, Sei Zhen Khong
https://arxiv.org/abs/2509.04014 https://arxiv.org/pdf/2509.04014…

Distance Between Stochastic Linear Systems
This manuscript proposes a distance measure between stochastic linear dynamical systems. While the existing stochastic control theory is well equipped to handle dynamical systems with stochastic uncertainties, a paradigm shift using distance measure based decision making is required for the effective further exploration of the field. As a first step, a distance measure between two linear time invariant stochastic dynamical systems is proposed here, extending the existing distance metrics betwee…

Optimized Control of Duplex Networks
Haoyu Zheng, Xizhe Zhang
https://arxiv.org/abs/2509.21767 https://arxiv.org/pdf/2509.21767

Optimized Control of Duplex Networks
Many real-world complex systems can be modeled as multiplex networks, where each layer represents a distinct set of interactions among the same entities. Controlling such systems-steering them toward desired states using external inputs-is crucial across many domains. However, existing network control theory largely focuses on single-layer networks, and applying separate controls to each layer of a multiplex system often leads to redundant sets of driver nodes, increasing cost and complexity. …

Multi-robot Path Planning and Scheduling via Model Predictive Optimal Transport (MPC-OT)
Usman A. Khan, Mouhacine Benosman, Wenliang Liu, Federico Pecora, Joseph W. Durham
https://arxiv.org/abs/2508.21205

Multi-robot Path Planning and Scheduling via Model Predictive Optimal Transport (MPC-OT)
In this paper, we propose a novel methodology for path planning and scheduling for multi-robot navigation that is based on optimal transport theory and model predictive control. We consider a setup where $N$ robots are tasked to navigate to $M$ targets in a common space with obstacles. Mapping robots to targets first and then planning paths can result in overlapping paths that lead to deadlocks. We derive a strategy based on optimal transport that not only provides minimum cost paths from robot…

Quantum control of Nitrogen-Vacancy spin in Diamonds: Towards matter-wave interferometry with massive objects
N. Levi, O. Feldman, Y. Rosenzweig, D. Groswasser, A. Elgarat, M. Gal-Katizri, R. Folman
https://arxiv.org/abs/2508.15504

Quantum control of Nitrogen-Vacancy spin in Diamonds: Towards matter-wave interferometry with massive objects
Quantum mechanics (QM) and General relativity (GR), also known as the theory of gravity, are the two pillars of modern physics. A matter-wave interferometer with a massive particle can test numerous fundamental ideas, including the spatial superposition principle - a foundational concept in QM - in previously unexplored regimes. It also opens the possibility of probing the interface between QM and GR, such as testing the quantization of gravity. Consequently, there exists an intensive effort to…

Unlocking reversible and nonvolatile anomalous valley Hall control through multiferroic van der Waals heterostructures
Ankita Phutela, Saswata Bhattacharya
https://arxiv.org/abs/2508.13614

Unlocking reversible and nonvolatile anomalous valley Hall control through multiferroic van der Waals heterostructures
Achieving external control over the anomalous valley Hall (AVH) effect is essential for advancing valleytronic applications. However, many of the existing approaches suffer from limitations such as irreversibility or volatility. In this work, we propose a general strategy for enabling nonvolatile electrical tuning of the AVH effect by utilizing multiferroic van der Waals heterostructures. Using first-principles density functional theory calculations, we demonstrate that a heterostructure compos…

Limit theory for mean-field control problems with common noise adapted controls
Bruno Bouchard, Xiaolu Tan
https://arxiv.org/abs/2509.14734 https://arxiv.o…

Limit theory for mean-field control problems with common noise adapted controls
We consider a mean-field control problem in which admissible controls are required to be adapted to the common noise filtration. The main objective is to show how the mean-field control problem can be approximates by time consistent centralized finite population problems in which the central planner has full information on all agents' states and gives an identical signal to all agents. We also aim at establishing the optimal convergence rate. In a first general path-dependent setting, we only p…

Control and Navigation of a 2-D Electric Rocket
Andr\'e Fonte, Pedro Santos, Paulo Oliveira
https://arxiv.org/abs/2509.19970 https://arxiv.org/pdf/2509…

Control and Navigation of a 2-D Electric Rocket
This work addresses the control and navigation of a simulated two-dimensional electric rocket. The model provides a simplified framework that neglects actuator dynamics and aerodynamic effects while capturing the complexities of underactuation and state coupling. Trajectory tracking is achieved through a modularized and layered control architecture, with employement of a Linear Quadratic Regulator (LQR) and Lyapunov theory. Full-state estimation is achieved through Kalman filtering techniques, …

Optimal Control in Infinite Dimensional Spaces and Economic Modeling: State of the Art and Perspectives
Giorgio Fabbri, Silvia Faggian, Salvatore Federico, Fausto Gozzi
https://arxiv.org/abs/2509.19909

Optimal Control in Infinite Dimensional Spaces and Economic Modeling: State of the Art and Perspectives
This survey collects, within a unified framework, various results (primarily by the authors themselves) on the use of Deterministic Infinite-Dimensional Optimal Control Theory to address applied economic models. The main aim is to illustrate, through several examples, the typical features of such models (including state constraints, non-Lipschitz data, and non-regularizing differential operators) and the corresponding methods needed to handle them. This necessitates developing aspects of the ex…

Large-Scale Self-Powered Vibration Control: Theory and Experiment
Connor Ligeikis, Heath Hofmann, Jeff Scruggs
https://arxiv.org/abs/2509.11346 https://arx…

Large-Scale Self-Powered Vibration Control: Theory and Experiment
A self-powered system is a control technology that powers itself by harvesting energy from exogenous disturbances. This article details the design and experimental validation of a prototype self-powered vibration control system, for larger-scale applications (i.e., power flows above 1W and forces on the order of 1kN.) The prototype consists of a linear ballscrew coupled with a permanent-magnet synchronous machine. A custom three-phase inverter is used to control power flow, and a custom half-br…

A Fast Initialization Method for Neural Network Controllers: A Case Study of Image-based Visual Servoing Control for the multicopter Interception
Chenxu Ke, Congling Tian, Kaichen Xu, Ye Li, Lingcong Bao
https://arxiv.org/abs/2509.19110

A meaningful optimal control problem in quantum and classical physics
Arnaud Lazarus (DALEMBERT), Emmanuel Tr\'elat (LJLL)
https://arxiv.org/abs/2507.13125

A meaningful optimal control problem in quantum and classical physics
In this paper we study and solve an optimal control problem motivated by applications in quantum and classical physics. Although apparently simple, this optimal control problem is not easy to solve and we resort to various elaborated methods of optimal control theory. We finally show its relationships to two problems in physics: the computation of the ground state for 1D Schr{ö}dinger operators with a finite potential well, and the optimal dynamical Kapitza stabilization problem.

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Qingyang Liu (University of Science and Technology of China), Tianlong Fan (University of Science and Technology of China), Liming Pan (University of Science and Technology of China), Linyuan Lv (University of Science and Technology of China)
https://

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Identifying an optimal set of driver nodes to achieve synchronization via pinning control is a fundamental challenge in complex network science, limited by computational intractability and the lack of general theory. Here, leveraging a degree-based mean-field (annealed) approximation from statistical physics, we analytically reveal how the structural degree distribution systematically governs synchronization performance, and derive an analytic characterization of the globally optimal pinning se…

The Bode Plots for Sliding-Mode Control Design
Ulises P\'erez-Ventura
https://arxiv.org/abs/2507.16281 https://arxiv.org/pdf/2507…

The Bode Plots for Sliding-Mode Control Design
This paper develops a unified frequency-domain framework for the analysis of sliding-mode control systems, encompassing both discontinuous and Lipschitz-continuous implementations. Using describing function (DF) theory, closed-form expressions are derived for the amplitude and frequency of chattering oscillations, as well as equivalent gain (EG) models that enable closed-loop sensitivity analysis. The proposed methodology captures the influence of actuator dynamics, control parameters, and dist…

Deep Bilinear Koopman Model for Real-Time Vehicle Control in Frenet Frame
Mohammad Abtahi, Farhang Motallebi Araghi, Navid Mojahed, Shima Nazari
https://arxiv.org/abs/2507.12578

Deep Bilinear Koopman Model for Real-Time Vehicle Control in Frenet Frame
Accurate modeling and control of autonomous vehicles remain a fundamental challenge due to the nonlinear and coupled nature of vehicle dynamics. While Koopman operator theory offers a framework for deploying powerful linear control techniques, learning a finite-dimensional invariant subspace for high-fidelity modeling continues to be an open problem. This paper presents a deep Koopman approach for modeling and control of vehicle dynamics within the curvilinear Frenet frame. The proposed framewo…

Implicit Third-Order Peer Triplets with Variable Stepsizes for Gradient-Based Solutions in Large-Scale ODE-Constrained Optimal Control
Jens Lang, Bernhard A. Schmitt
https://arxiv.org/abs/2509.11684

Implicit Third-Order Peer Triplets with Variable Stepsizes for Gradient-Based Solutions in Large-Scale ODE-Constrained Optimal Control
This paper is concerned with the theory, construction and application of variable-stepsize implicit Peer two-step methods that are super-convergent for variable stepsizes, i.e., preserve their classical order achieved for uniform stepsizes when applied in a gradient-based solution algorithm to solve ODE-constrained optimal control problems in a first-discretize-then-optimize setting. Gradients of the objective function can be computed most efficiently using approximate adjoint variables. High a…

Koopman-Operator-Based Model Predictive Control for Drag-free Satellite
Yankai Wang, Ti Chen
https://arxiv.org/abs/2509.20100 https://arxiv.org/pdf/2509.20…

Koopman-Operator-Based Model Predictive Control for Drag-free Satellite
This paper presents a data-driven modelling method for nonlinear dynamics of drag-free satellite based on Koopman operator theory, and a model predictive controller is designed based on the identified model. The nonlinear dynamics of drag-free satellite are identified and controlled based on Sparse Identification of Nonlinear Dynamics (SINDy). Using the manually constructed nonlinear function dictionary as observables, the system approximation is obtained by SINDy algorithm, and a linear Model …

Uniform Sampling from the Reachable Set Using Optimal Transport
Karthik Elamvazhuthi, Sachin Shivakumar
https://arxiv.org/abs/2509.15571 https://arxiv.org/…

Uniform Sampling from the Reachable Set Using Optimal Transport
Finding the reachable set of a system has a wide range of applications, but is a fundamental challenge in control theory, especially when controls are bounded. Although one can simply integrate the system samples forward in time by applying random admissible control to approximate the reachable set, the samples typically cluster near an attractor (if one is present) -- yielding a poor representation of the reachable set. A better representation can be found by applying controls that specificall…

Automated Algorithm Design via Nevanlinna-Pick Interpolation
Ibrahim K. Ozaslan, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.21416 https://

Automated Algorithm Design via Nevanlinna-Pick Interpolation
The synthesis of optimization algorithms typically follows a design-first-analyze-later approach, which often obscures fundamental performance limitations and hinders the systematic design of algorithms operating at the achievable theoretical boundaries. Recently, a framework based on frequency-domain techniques from robust control theory has emerged as a powerful tool for automating algorithm synthesis. By integrating the design and analysis stages, this framework enables the identification of…

Crosslisted article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm
Oscar Leong, Yann Traonmilin

Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
Taiki Nakano, Ahmed Aboudonia, Jaap Eising, Andrea Martinelli, Florian D\"orfler, John Lygeros
https://arxiv.org/abs/2509.14047

Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
We propose data-driven decentralized control algorithms for stabilizing interconnected systems. We first derive a data-driven condition to synthesize a local controller that ensures the dissipativity of the local subsystems. Then, we propose data-driven decentralized stability conditions for the global system based on the dissipativity of each local system. Since both conditions take the form of linear matrix inequalities and are based on dissipativity theory, this yields a unified pipeline, re…

Design of MIMO Lur'e oscillators via dominant system theory with application in multi-agent rhythm synchronization
Yu Kawano, Fulvio Forni
https://arxiv.org/abs/2508.12141 h…

Design of MIMO Lur'e oscillators via dominant system theory with application in multi-agent rhythm synchronization
This paper presents a new design framework for dynamic output-feedback controllers for Lur'e oscillation in a multiple-input multiple-output setting. We first revisit and extend dominant system theory to state-dependent rates, with the goal of deriving conditions based on linear matrix inequalities. Then, we introduce a separation principle for Lur'e oscillator design, which allows for the independent design of a state-feedback oscillator and an observer. Our proposed control synthesis is demon…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
El Mahdi Chayti, Nikita Doikov, Martin Jaggi

Lyndon Word Transduction to Improve the Efficiency of Computing Chen-Fliess Series
W. Steven Gray, Fatima Raza, Lance Berlin, Luis A. Duffaut Espinosa
https://arxiv.org/abs/2509.19908

Lyndon Word Transduction to Improve the Efficiency of Computing Chen-Fliess Series
The class of input-output systems representable as Chen-Fliess series arises often in control theory. One well known drawback of this representation, however, is that the iterated integrals which appear in these series are algebraically related by the shuffle product. This becomes relevant when one wants to numerically evaluate these series in applications, as this redundancy leads to unnecessary computational expense. The general goal of this paper is to present a computationally efficient way…

Automated algorithm design for convex optimization problems with linear equality constraints
Ibrahim K. Ozaslan, Wuwei Wu, Jie Chen, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.20746

Automated algorithm design for convex optimization problems with linear equality constraints
Synthesis of optimization algorithms typically follows a {\em design-then-analyze\/} approach, which can obscure fundamental performance limits and hinder the systematic development of algorithms that operate near these limits. Recently, a framework grounded in robust control theory has emerged as a powerful tool for automating algorithm synthesis. By integrating design and analysis stages, fundamental performance bounds are revealed and synthesis of algorithms that achieve them is enabled. In …

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
Dhruv S. Kushwaha, Zoleikha A. Biron
https://arxiv.org/abs/2508.09128 https://…

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
Reinforcement learning (RL) has proven to be particularly effective in solving complex decision-making problems for a wide range of applications. From a control theory perspective, RL can be considered as an adaptive optimal control scheme. Lyapunov and barrier functions are the most commonly used certificates to guarantee system stability for a proposed/derived controller and constraint satisfaction guarantees, respectively, in control theoretic approaches. However, compared to theoretical gua…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A Universal Birkhoff Theory for Fast Trajectory Optimization
I. M. Ross
https…