Tootfinder

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…

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…

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…

Conditions for positivity of energy in superrenormalizable polynomial gravity
P\'ublio Rwany B. R. do Vale
https://arxiv.org/abs/2508.07508 https://arx…

Conditions for positivity of energy in superrenormalizable polynomial gravity
At the quantum level, the polynomial models of gravity with six and eight derivatives are superrenormalizable, but suffer from higher derivative ghost and/or tachyonic ghost states. On the other hand, these models may have advantages in the control of negative effects of ghosts, compared to the more common fourth-derivative theory. We explore the positiveness of energy of the individual plane wave solutions in the general models with six and eight derivatives. Different from the fourth-order gr…

Boundary layers in quasi-static magnetoconvection with a vertical field and their implications for heat transport
Talal AlRefae, Michael A. Calkins
https://arxiv.org/abs/2508.08623

Boundary layers in quasi-static magnetoconvection with a vertical field and their implications for heat transport
Heat transport in quasi-static magnetoconvection with a vertical magnetic field in a plane layer geometry is investigated with direct numerical simulations and asymptotic theory in the limit of large Chandrasekhar number ($Q$). It is shown that thermal and magnetic boundary layers with thickness $O(Q^{-1/6})$, of the same order as the horizontal scale of the convection, are persistent over the range of investigated parameters. Thermal boundary layer control of the heat transport indicates that …

Reducing Cartel Violence: The Mexican Dilemma Between Social and Security Spending
Rafael Prieto-Curiel, Dieter Grass, Stefan Wrzaczek, Gian Maria Campedelli, Gernot Tragler, Gustav Feichtinger
https://arxiv.org/abs/2508.06509

Reducing Cartel Violence: The Mexican Dilemma Between Social and Security Spending
Organised crime in Mexico threatens societal stability and public safety, driving pervasive violence and economic disruption. Despite security investments and social programs designed in part to reduce involvement in crime, cartel power and violence continue to persist. This study evaluates existing policies and introduces a novel framework using optimal control theory to analyse cartel dynamics. Specifically, by modelling resource allocation between security measures and social programs, we id…

A Complete Derivation of Complex Circle Manifold (CCM) Riemannian manifold Optimization Equations
Amirreza Tabrizi, Mohammad Hadi Mirmohammadi
https://arxiv.org/abs/2508.07396 h…

A Complete Derivation of Complex Circle Manifold (CCM) Riemannian manifold Optimization Equations
After reviewing manifold optimization techniques in applications like MIMO communication systems, phased array beamforming, radar, and control theory, we observed that the Complex Circle Manifold (CCM) is widely employed, yet its foundational relations and equations lack a rigorous, self-contained derivation in the literature. This paper provides a systematic and rigorous proof of CCM's key properties, including its tangent space and Riemannian gradient operations, with explicit connections to …

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…

A New Perspective On AI Safety Through Control Theory Methodologies
Lars Ullrich, Walter Zimmer, Ross Greer, Knut Graichen, Alois C. Knoll, Mohan Trivedi
https://arxiv.org/abs/2506.23703

A New Perspective On AI Safety Through Control Theory Methodologies
While artificial intelligence (AI) is advancing rapidly and mastering increasingly complex problems with astonishing performance, the safety assurance of such systems is a major concern. Particularly in the context of safety-critical, real-world cyber-physical systems, AI promises to achieve a new level of autonomy but is hampered by a lack of safety assurance. While data-driven control takes up recent developments in AI to improve control systems, control theory in general could be leveraged t…

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 …

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…

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…

First- and Zeroth-Order Learning in Asynchronous Games
Zifan Wang, Xinlei Yi, Michael M. Zavlanos, Karl H. Johansson
https://arxiv.org/abs/2508.09111 https://

First- and Zeroth-Order Learning in Asynchronous Games
This paper investigates the discrete-time asynchronous games in which noncooperative agents seek to minimize their individual cost functions. Building on the assumption of partial asynchronism, i.e., each agent updates at least once within a fixed-length time interval, we explore the conditions to ensure convergence of such asynchronous games. The analysis begins with a simple quadratic game from which we derive tight convergence conditions through the lens of linear control theory. Then, we pr…

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…

Bayesian optimization of a cost function in suboptimal control for reducing skin friction drag in wall turbulence
Yusuke Yugeta, Yosuke Hasegawa
https://arxiv.org/abs/2507.04654

Bayesian optimization of a cost function in suboptimal control for reducing skin friction drag in wall turbulence
A systematic and automated framework for developing closed-loop flow control strategies is proposed, integrating suboptimal control theory [Lee et al., J. Fluid Mech. 358, 245 (1998)] with Bayesian optimization. The approach is demonstrated in the context of reducing skin friction drag in a low-Reynolds-number turbulent channel flow. A cost function in the suboptimal control framework is formulated as a linear combination of various wall quantities, with the corresponding weight coefficients op…

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…

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…

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 (…

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack)
Elija Perrier
https://arxiv.org/abs/2506.17846 https://…

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack)
This position paper argues that formal optimal control theory should be central to AI alignment research, offering a distinct perspective from prevailing AI safety and security approaches. While recent work in AI safety and mechanistic interpretability has advanced formal methods for alignment, they often fall short of the generalisation required of control frameworks for other technologies. There is also a lack of research into how to render different alignment/control protocols interoperable.…

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,…

Characterizing control between interacting subsystems with deep Jacobian estimation
Adam J. Eisen, Mitchell Ostrow, Sarthak Chandra, Leo Kozachkov, Earl K. Miller, Ila R. Fiete
https://arxiv.org/abs/2507.01946

Characterizing control between interacting subsystems with deep Jacobian estimation
Biological function arises through the dynamical interactions of multiple subsystems, including those between brain areas, within gene regulatory networks, and more. A common approach to understanding these systems is to model the dynamics of each subsystem and characterize communication between them. An alternative approach is through the lens of control theory: how the subsystems control one another. This approach involves inferring the directionality, strength, and contextual modulation of c…

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…

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…

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…

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…

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 …

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…

When do World Models Successfully Learn Dynamical Systems?
Edmund Ross, Claudia Drygala, Leonhard Schwarz, Samir Kaiser, Francesca di Mare, Tobias Breiten, Hanno Gottschalk
https://arxiv.org/abs/2507.04898

When do World Models Successfully Learn Dynamical Systems?
In this work, we explore the use of compact latent representations with learned time dynamics ('World Models') to simulate physical systems. Drawing on concepts from control theory, we propose a theoretical framework that explains why projecting time slices into a low-dimensional space and then concatenating to form a history ('Tokenization') is so effective at learning physics datasets, and characterise when exactly the underlying dynamics admit a reconstruction mapping from the history of pre…

Replaced article(s) found for math.SP. https://arxiv.org/list/math.SP/new
[1/1]:
- Schr{\"o}dinger eigenfunctions sharing the same modulus and applications to the control of quantu...
Ugo Boscain (CaGE), K\'evin Le Balc'H (CaGE), Mario Sigalotti (CaGE)

Long; central Massachusetts colonial history
Today on a whim I visited a site in Massachusetts marked as "Huguenot Fort Ruins" on OpenStreetMaps. I drove out with my 4-year-old through increasingly rural central Massachusetts forests & fields to end up on a narrow street near the top of a hill beside a small field. The neighboring houses had huge lawns, some with tractors.
Appropriately for this day and this moment in history, the history of the site turns out to be a microcosm of America. Across the field beyond a cross-shaped stone memorial stood an info board with a few diagrams and some text. The text of the main sign (including typos/misspellings) read:
"""
Town Is Formed
Early in the 1680's, interest began to generate to develop a town in the area west of Natick in the south central part of the Commonwealth that would be suitable for a settlement. A Mr. Hugh Campbell, a Scotch merchant of Boston petitioned the court for land for a colony. At about the same time, Joseph Dudley and William Stoughton also were desirous of obtaining land for a settlement. A claim was made for all lands west of the Blackstone River to the southern land of Massachusetts to a point northerly of the Springfield Road then running southwesterly until it joined the southern line of Massachusetts.
Associated with Dudley and Stoughton was Robert Thompson of London, England, Dr. Daniel Cox and John Blackwell, both of London and Thomas Freak of Hannington, Wiltshire, as proprietors. A stipulation in the acquisition of this land being that within four years thirty families and an orthodox minister settle in the area. An extension of this stipulation was granted at the end of the four years when no group large enough seemed to be willing to take up the opportunity.
In 1686, Robert Thompson met Gabriel Bernor and learned that he was seeking an area where his countrymen, who had fled their native France because of the Edict of Nantes, were desirous of a place to live. Their main concern was to settle in a place that would allow them freedom of worship. New Oxford, as it was the so-named, at that time included the larger part of Charlton, one-fourth of Auburn, one-fifth of Dudley and several square miles of the northeast portion of Southbridge as well as the easterly ares now known as Webster.
Joseph Dudley's assessment that the area was capable of a good settlement probably was based on the idea of the meadows already established along with the plains, ponds, brooks and rivers. Meadows were a necessity as they provided hay for animal feed and other uses by the settlers. The French River tributary books and streams provided a good source for fishing and hunting. There were open areas on the plains as customarily in November of each year, the Indians burnt over areas to keep them free of underwood and brush. It appeared then that this area was ready for settling.
The first seventy-five years of the settling of the Town of Oxford originally known as Manchaug, embraced three different cultures. The Indians were known to be here about 1656 when the Missionary, John Eliott and his partner Daniel Gookin visited in the praying towns. Thirty years later, in 1686, the Huguenots walked here from Boston under the guidance of their leader Isaac Bertrand DuTuffeau. The Huguenot's that arrived were not peasants, but were acknowledged to be the best Agriculturist, Wine Growers, Merchant's, and Manufacter's in France. There were 30 families consisting of 52 people. At the time of their first departure (10 years), due to Indian insurrection, there were 80 people in the group, and near their Meetinghouse/Church was a Cemetery that held 20 bodies. In 1699, 8 to 10 familie's made a second attempt to re-settle, failing after only four years, with the village being completely abandoned in 1704.
The English colonist made their way here in 1713 and established what has become a permanent settlement.
"""
All that was left of the fort was a crumbling stone wall that would have been the base of a higher wooden wall according to a picture of a model (I didn't think to get a shot of that myself). Only trees and brush remain where the multi-story main wooden building was.
This story has so many echoes in the present:
- The rich colonialists from Boston & London agree to settle the land, buying/taking land "rights" from the colonial British court that claimed jurisdiction without actually having control of the land. Whether the sponsors ever actually visited the land themselves I don't know. They surely profited somehow, whether from selling on the land rights later or collecting taxes/rent or whatever, by they needed poor laborers to actually do the work of developing the land (& driving out the original inhabitants, who had no say in the machinations of the Boston court).
- The land deal was on condition that there capital-holders who stood to profit would find settlers to actually do the work of colonizing. The British crown wanted more territory to be controlled in practice not just in theory, but they weren't going to be the ones to do the hard work.
- The capital-holders actually failed to find enough poor suckers to do their dirty work for 4 years, until the Huguenots, fleeing religious persecution in France, were desperate enough to accept their terms.
- Of course, the land was only so ripe for settlement because of careful tending over centuries by the natives who were eventually driven off, and whose land management practices are abandoned today. Given the mention of praying towns (& dates), this was after King Phillip's war, which resulted in at least some forced resettlement of native tribes around the area, but the descendants of those "Indians" mentioned in this sign are still around. For example, this is the site of one local band of Nipmuck, whose namesake lake is about 5 miles south of the fort site: #LandBack.

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…

Yudovich theory under geometric regularity for density-dependent incompressible fluids
Francesco Fanelli
https://arxiv.org/abs/2506.23365 https://

Yudovich theory under geometric regularity for density-dependent incompressible fluids
This paper focuses on the study of the density-dependent incompressible Euler equations in space dimension $d=2$, for low regularity (\textsl{i.e.} non-Lipschitz) initial data satisfying assumptions in spirit of the celebrated Yudovich theory for the classical homogeneous Euler equations. We show that, under an \textsl{a priori} control of a non-linear geometric quantity, namely the directional derivative $\partial_Xu$ of the fluid velocity $u$ along the vector field $X:=\nabla^\perpρ$, wher…

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…

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…

On the Dynamics of Control
Rachit Mehra, M Parimi, S. R. Wagh, Navdeep M Singh
https://arxiv.org/abs/2507.04181 https://arxiv.org/pdf…

On the Dynamics of Control
We present a dynamical system approach for the control of a nonlinear dynamical system by defining the control problem in a Fiber bundle framework. The constructive procedure derived results in the generation of a NHIM/NAIM which facilitates the use of tools and ideas from dynamical system theory to analyze and understand the properties associated with the controlled system. The time scale separation, decoupling of system dynamics, and their role in the system behavior are analyzed. An overview…

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…

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…

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).

Control of Marine Robots in the Era of Data-Driven Intelligence
Lin Hong, Lu Liu, Zhouhua Peng, Fumin Zhang
https://arxiv.org/abs/2506.21063 https://

Control of Marine Robots in the Era of Data-Driven Intelligence
The control of marine robots has long relied on model-based methods grounded in classical and modern control theory. However, the nonlinearity and uncertainties inherent in robot dynamics, coupled with the complexity of marine environments, have revealed the limitations of conventional control methods. The rapid evolution of machine learning has opened new avenues for incorporating data-driven intelligence into control strategies, prompting a paradigm shift in the control of marine robots. This…

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…

Grid-Connected, Data-Driven Inverter Control, Theory to Hardware
Sebastian Graf, Keith Moffat, Anurag Mohapatra, Alessandro Chiuso, Florian D\"orfler
https://arxiv.org/abs/2507.02325

Grid-Connected, Data-Driven Inverter Control, Theory to Hardware
Grid-connected inverter control is challenging to implement due to the difficulty of obtaining and maintaining an accurate grid model. Direct Data-Driven Predictive Control provides a model-free alternative to traditional model-based control methods. This paper describes how the recently-proposed Transient Predictive Control (TPC) can be used for real-world, plug-and-play inverter control. The following hypotheses were tested: 1) The TPC algorithm can be run online using standard hardware, and …

Graph theory inspired anomaly detection at the LHC
Jack Y. Araz, Dimitrios Athanasakos, Mateusz Ploskon, Felix Ringer
https://arxiv.org/abs/2506.19920 http…

Graph theory inspired anomaly detection at the LHC
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collider events. In this work, we develop a graph autoencoder as an unsupervised, model-agnostic tool for anomaly detection, using the LHC Olympics dataset as a benchmark. By representing jet constituents as a graph, we introduce a method to systematically control the information available to the model through sparse graph c…

When learning analytics dashboard is explainable: An exploratory study on the effect of GenAI-supported learning analytics dashboard
Angxuan Chen
https://arxiv.org/abs/2506.16312 …

When learning analytics dashboard is explainable: An exploratory study on the effect of GenAI-supported learning analytics dashboard
This study investigated the impact of a theory-driven, explainable Learning Analytics Dashboard (LAD) on university students' human-AI collaborative academic abstract writing task. Grounded in Self-Regulated Learning (SRL) theory and incorporating Explainable AI (XAI) principles, our LAD featured a three-layered design (Visual, Explainable, Interactive). In an experimental study, participants were randomly assigned to either an experimental group (using the full explainable LAD) or a control gr…

Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies
Samuel N. Cohen, Jackson Hebner, Deqing Jiang, Justin Sirignano
https://arxiv.org/abs/2507.06428

Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies
We mathematically analyze and numerically study an actor-critic machine learning algorithm for solving high-dimensional Hamilton-Jacobi-Bellman (HJB) partial differential equations from stochastic control theory. The architecture of the critic (the estimator for the value function) is structured so that the boundary condition is always perfectly satisfied (rather than being included in the training loss) and utilizes a biased gradient which reduces computational cost. The actor (the estimator f…

A Review on Zeroing Neural Networks
Chengze Jiang, Jie Gui, Long Jin, Shuai Li
https://arxiv.org/abs/2507.00387 https://arxiv.org/pdf…

A Review on Zeroing Neural Networks
Zeroing neural networks (ZNNs) have demonstrated outstanding performance on time-varying optimization and control problems. Nonetheless, few studies are committed to illustrating the relationship among different ZNNs and the derivation of them. Therefore, reviewing the advances for a systematical understanding of this field is desirable. This paper provides a survey of ZNNs' progress regarding implementing methods, analysis theory, and practical applications.

On gradient descent-ascent flows in metric spaces
Noboru Isobe, Sho Shimoyama
https://arxiv.org/abs/2506.20258 https://arxiv.org/pdf/…

On gradient descent-ascent flows in metric spaces
Gradient descent-ascent (GDA) flows play a central role in finding saddle points of bivariate functionals, with applications in optimization, game theory, and robust control. While they are well-understood in Hilbert and Banach spaces via maximal monotone operator theory, their extension to general metric spaces, particularly Wasserstein spaces, has remained largely unexplored. In this paper, we develop a mathematical theory of GDA flows on the product of two complete metric spaces, formulating…

Full history recursive multilevel Picard approximations suffer from the curse of dimensionality for the Hamilton-Jacobi-Bellman equation of a stochastic control problem
Martin Hutzenthaler, Tuan Anh Nguyen
https://arxiv.org/abs/2506.23969

Full history recursive multilevel Picard approximations suffer from the curse of dimensionality for the Hamilton-Jacobi-Bellman equation of a stochastic control problem
Full history recursive multilevel Picard (MLP) approximations have been proved to overcome the curse of dimensionality in the numerical approximation of semilinear heat equations with nonlinearities which are globally Lipschitz continuous with respect to the maximum-norm. Nonlinearities in Hamilton-Jacobi-Bellman equations in stochastic control theory, however, are often (locally) Lipschitz continuous with respect to the standard Euclidean norm. In this paper we prove the surprising fact that M…

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…

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…

Replaced article(s) found for cs.IT. https://arxiv.org/list/cs.IT/new
[1/1]:
- Time-Series JEPA for Predictive Remote Control under Capacity-Limited Networks
Abanoub M. Girgis, Alvaro Valcarce, Mehdi Bennis

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…

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…

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…

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…

Data-driven phase control for limit-cycle oscillators under partial observation
Koichiro Yawata, Norihisa Namura, Yuzuru Kato, Hiroya Nakao
https://arxiv.org/abs/2508.16957 http…

Data-driven phase control for limit-cycle oscillators under partial observation
Controlling rhythmic systems, typically modeled as limit-cycle oscillators, is an important subject in real-world problems. Phase reduction theory, which simplifies the multidimensional oscillator state under weak input to a single phase variable, is useful for analyzing the oscillator dynamics. In the control of limit-cycle oscillators with unknown dynamics, the oscillator phase should be estimated from time series under partial observation in real time. In this study, we present an autoencode…

Safe Deep Reinforcement Learning for Resource Allocation with Peak Age of Information Violation Guarantees
Berire Gunes Reyhan, Sinem Coleri
https://arxiv.org/abs/2507.08653

Safe Deep Reinforcement Learning for Resource Allocation with Peak Age of Information Violation Guarantees
In Wireless Networked Control Systems (WNCSs), control and communication systems must be co-designed due to their strong interdependence. This paper presents a novel optimization theory-based safe deep reinforcement learning (DRL) framework for ultra-reliable WNCSs, ensuring constraint satisfaction while optimizing performance, for the first time in the literature. The approach minimizes power consumption under key constraints, including Peak Age of Information (PAoI) violation probability, tra…

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

Homotopy continuation method for solving Dyson equation fully self-consistently: theory and application to NdNiO2
Pavel Pokhilko, Dominika Zgid
https://arxiv.org/abs/2507.00290

Homotopy continuation method for solving Dyson equation fully self-consistently: theory and application to NdNiO2
Solution of the Dyson equation for the small-gap systems can be plagued by large non-converging iterations. In addition to the convergence issues, due to a high non-linearity, the Dyson equation may have multiple solutions. We apply the homotopy continuation approach to control the behavior of iterations. We used the homotopy continuation to locate multiple fully self-consistent GW solutions for NdNiO2 solid and to establish the corresponding Hartree-Fock limits. Some of the solutions found are…

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…

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 …

An approximation theory for Markov chain compression
Mark Fornace, Michael Lindsey
https://arxiv.org/abs/2506.22918 https://arxiv.org…

An approximation theory for Markov chain compression
We develop a framework for the compression of reversible Markov chains with rigorous error control. Given a subset of selected states, we construct reduced dynamics that can be lifted to an approximation of the full dynamics, and we prove simple spectral and nuclear norm bounds on the recovery error in terms of a suitably interpreted Nyström approximation error. We introduce two compression schemes: a projective compression based on committor functions and a structure-preserving compression de…

Reconfiguring Digital Accountability: AI-Powered Innovations and Transnational Governance in a Postnational Accounting Context
Claire Li, David Freeborn
https://arxiv.org/abs/2507.00288

Reconfiguring Digital Accountability: AI-Powered Innovations and Transnational Governance in a Postnational Accounting Context
This study explores how AI-powered digital innovations are reshaping organisational accountability in a transnational governance context. As AI systems increasingly mediate decision-making in domains such as auditing and financial reporting, traditional mechanisms of accountability, based on control, transparency, and auditability, are being destabilised. We integrate the Technology Acceptance Model (TAM), Actor-Network Theory (ANT), and institutional theory to examine how organisations adopt A…

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…

Tunable Dot Platform for Controlling Electron Flow in Graphene
Fereshte Ildarabadi, Stephen R. Power
https://arxiv.org/abs/2507.01585 https://

Tunable Dot Platform for Controlling Electron Flow in Graphene
We introduce an innovative graphene-based architecture to control electronic current flows. The tunable dot platform (TDP) consists of an array of gated dots, with independently adjustable potentials, embedded in graphene. Inspired by Mie theory, and leveraging multiscattering effects, we demonstrate that tailored current behavior can be achieved due to the variety of possible dot configurations. Optimization is performed using differential evolution, which identifies configurations that maximi…

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…

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…

Discretization of Continuous Frames by Quasi-Monte Carlo Methods
Jan Zimmermann, Andreas Klotz, Nicki Holighaus
https://arxiv.org/abs/2507.00618 https://…

Discretization of Continuous Frames by Quasi-Monte Carlo Methods
We introduce a discretization scheme for continuous localized frames using quasi-Monte Carlo integration and discrepancy theory. By generalizing classical concepts, we define a discrepancy measure on the entire phase space $\mathbb{R}^2$ and establish a corresponding Koksma-Hlawka inequality. This approach enables control over the density of the discretized frame and ensures the universality of the sampling set, relying only on the discrepancy of the sampling set and on the Sobolev-type seminor…

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…

Molecular Control of Floquet Topological Phase in Non-adiabatic Thouless Pumping
Ruiyi Zhou, Yosuke Kanai
https://arxiv.org/abs/2506.12147 https://

Molecular Control of Floquet Topological Phase in Non-adiabatic Thouless Pumping
Nonadiabatic Thouless pumping of electrons is studied in the framework of topological Floquet engineering, particularly focused on how changes to chemical moieties can control the emergence of the Floquet topological phase. We employ real-time time-dependent density functional theory to investigate the extent to which the topological invariant, the winding number, is impacted by molecular-level changes to trans-polyacetylene. In particular, several substitutions to trans-polyacetylene are studi…

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…

Geo-Somatic Resonance Theory A Vibrational Framework for Sleep as Planetary Entrainment
Brathikan Vijayamohan Mankayarkarasi
https://arxiv.org/abs/2506.14760

Geo-Somatic Resonance Theory A Vibrational Framework for Sleep as Planetary Entrainment
Sleep is commonly studied through neurochemical, evolutionary, and behavioral frameworks, typically emphasizing circadian rhythms and energy conservation. However, these approaches do not fully explain a deeper biophysical question: why does sleep universally involve physical stillness, a lying posture, and disconnection from conscious control? This paper introduces a new hypothesis that sleep is not merely a biological function, but a state of vibrational synchronization between the human body…

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…

Diffusive charge transport in the gapped 1D Hubbard model at all finite temperatures
J. M. P. Carmelo, P. D. Sacramento
https://arxiv.org/abs/2507.02753 ht…

Diffusive charge transport in the gapped 1D Hubbard model at all finite temperatures
Studies relying on hydrodynamic theory and Kardar-Parisi-Zhang (KPZ) scaling have found that in the one-dimensional Hubbard model spin and charge transport are for all temperatures T > 0 anomalous superdiffusive at zero magnetic field, h = 0, and zero chemical potential, μ = 0, respectively. However, this contradicts recent exact results that at very low temperature charge transport rather is normal diffusive. In this Letter we identify the mechanisms that control the different types of temper…

Control and optimization for Neural Partial Differential Equations in Supervised Learning
Alain Bensoussan, Minh-Binh Tran, Bangjie Wang
https://arxiv.org/abs/2506.20764

Control and optimization for Neural Partial Differential Equations in Supervised Learning
Although there is a substantial body of literature on control and optimization problems for parabolic and hyperbolic systems, the specific problem of controlling and optimizing the coefficients of the associated operators within such systems has not yet been thoroughly explored. In this work, we aim to initiate a line of research in control theory focused on optimizing and controlling the coefficients of these operators-a problem that naturally arises in the context of neural networks and super…

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…

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…

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…

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…

Anisotropic nonlinear transport in two-dimensional ferroelectrics
Qin Zhang, Xu Chen, Mingbo Dou, M. Ye. Zhuravlev, A. V. Nikolaev, Xianjie Wang, L. L. Tao
https://arxiv.org/abs/2506.22739

Anisotropic nonlinear transport in two-dimensional ferroelectrics
The longitudinal nonlinear response plays a crucial role in the nonreciprocal charge transport and may provide a simple electrical means to probe the spin-orbit coupling, magnetic order and polarization states, etc. Here, we report on a study on the polarization and magnetic field control of longitudinal nonlinear transport in two-dimensional (2D) ferroelectrics with in-plane polarization. Based on the Boltzmann transport theory, we first study that using a general Hamiltonian model and show th…

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…

Propagation of Chaos for Singular Interactions via Regular Drivers
Qian Qi
https://arxiv.org/abs/2507.14981 https://arxiv.org/pdf/250…

Propagation of Chaos for Singular Interactions via Regular Drivers
We introduce a framework to prove propagation of chaos for interacting particle systems with singular, density-dependent interactions, a classical challenge in mean-field theory. Our approach is to define the dynamics implicitly via a regular driver function. This regular driver is engineered to generate a singular effective interaction, yet its underlying regularity provides the necessary analytical control. Our main result establishes propagation of chaos under a key dissipation condition. Th…

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…

Instant Folded Strings, Dark Energy and a Cyclic Bouncing Universe
Nissan Itzhaki, Uri Peleg, Paul J. Steinhardt
https://arxiv.org/abs/2508.09745 https://a…

Instant Folded Strings, Dark Energy and a Cyclic Bouncing Universe
We present a wholly self-consistent, complete cyclic bouncing cosmology based on components drawn from string theory and constructed in a way that is under perturbative control throughout (e.g., with temperature much less than the string scale and string coupling $g_s \ll 1$ at all times). The cyclic evolution is governed by standard dilaton-gravity in $(3+1)$-dimensions with a perturbatively generated potential and a coupling between the dilaton and a second field that becomes massless at $ϕ=…

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…

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…

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.

Weyl semimetal engineering by symmetry control in NiTe$_2$
Marcos G. O. Junior, Augusto L. Ara\'ujo, Emmanuel V. C. Lopes, Tome M. Schmidt
https://arxiv.org/abs/2506.13908

Weyl semimetal engineering by symmetry control in NiTe$_2$
In this work, we investigate the emergence of Weyl points in an inversion symmetry-breaking 1T-NiTe$_2$ system. Through first-principles calculations based on the density functional theory combined with tight-binding methods, distinct number of Weyl crossings arise under an appropriate symmetry breaking. We identify three sets of Weyl points by breaking the inversion symmetry in NiTe$_2$, resulting in a total of 28 Weyl crossings. The first set comes from the Dirac semimetal, whereas the other …

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…

A Hybrid Perspective on Suboptimal Mixed-Integer Quadratic Programming
Luke Fina, Christopher Petersen
https://arxiv.org/abs/2507.02772 https://

A Hybrid Perspective on Suboptimal Mixed-Integer Quadratic Programming
This work solves suboptimal mixed-integer quadratic programs recursively for feedback control of dynamical systems. The proposed framework leverages parametric mixed-integer quadratic programming (MIQP) and hybrid systems theory to model a recursive MIQP feedback controller and a feedback controlled dynamical system. The proposed hybrid framework theoretically encodes the suboptimal part via solver parameters as bounded perturbations from the optimal solution set. The stability of the proposed …

Splitting-based randomised dynamical low-rank approximations for stiff matrix differential equations
Zi Wu, Yong-Liang Zhao
https://arxiv.org/abs/2506.15259

Splitting-based randomised dynamical low-rank approximations for stiff matrix differential equations
In the fields of control theory and machine learning, the dynamic low-rank approximation for large-scale matrices has received substantial attention. Considering the large-scale semilinear stiff matrix differential equations, we propose a dynamic numerical integrator for obtaining low-rank approximations of solutions. We first decompose the differential equation into a stiff linear component and a nonstiff nonlinear term, then employ an exponential integrator along with a dynamic low-rank appro…

Electronic Correlations Control Interlayer Coupling and Magnetic Transition in MnBi$_2$Te$_4$/MnBr$_3$ Heterostructure
Yuanhao Zhu, Xixi Yuan, Ying Zhao, Jin Zhang, Zijing Ding, Huixia Fu
https://arxiv.org/abs/2506.13448

Electronic Correlations Control Interlayer Coupling and Magnetic Transition in MnBi$_2$Te$_4$/MnBr$_3$ Heterostructure
Bulk MnBi$_2$Te$_4$ (MBT) is an intrinsic antiferromagnetic topological insulator. However, its low Néel temperature of $\sim 25\,\mathrm{K}$ severely restricts its practical applications. Here, we propose a van der Waals heterostructure composed of monolayer MBT (ML-MBT) and monolayer MnBr$_3$, an intrinsic Chern insulator possessing a high Curie temperature ($T_\mathrm{C} \sim 200\,\mathrm{K}$). By employing density functional theory calculations and Monte Carlo simulations, we demonstrate t…

Research on Optimal Control Problem Based on Reinforcement Learning under Knightian Uncertainty
Ziyu Li, Chen Fei, Weiyin Fei
https://arxiv.org/abs/2506.13207

Research on Optimal Control Problem Based on Reinforcement Learning under Knightian Uncertainty
Considering that the decision-making environment faced by reinforcement learning (RL) agents is full of Knightian uncertainty, this paper describes the exploratory state dynamics equation in Knightian uncertainty to study the entropy-regularized relaxed stochastic control problem in a Knightian uncertainty environment. By employing stochastic analysis theory and the dynamic programming principle under nonlinear expectation, we derive the Hamilton-Jacobi-Bellman (HJB) equation and solve for the …

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…

Projected integral control of impedance passive nonlinear systems
Nicolas Vanspranghe (CRAN), Pietro Lorenzetti (CRAN), Lassi Paunonen (TUT), George Weiss (TAU)
https://arxiv.org/abs/2506.14267

Projected integral control of impedance passive nonlinear systems
We propose an abstract framework for solving the constrained set-point tracking problem for impedance passive infinite-dimensional nonlinear systems. The class of systems considered is governed by monotone differential inclusions and allows us to exploit the theory of contraction semigroups. To account for possible operational constraints, e.g., bounds on the input, we replace a classical integral controller with a projected integral controller. This guarantees that the integrator state remains…

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