Tootfinder

Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems
Laksh Patel, Akhilesh Raj
https://arxiv.org/abs/2506.17283

Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems
The increasing deployment of multi-agent systems (MAS) in critical infrastructures such as autonomous transportation, disaster relief, and smart cities demands robust formation control mechanisms resilient to adversarial attacks. Traditional consensus-based controllers, while effective under nominal conditions, are highly vulnerable to data manipulation, sensor spoofing, and communication failures. To address this challenge, we propose Second-Order State Hallucination (SOSH), a novel framework …

Infinite horizon discounted LQ optimal control problems for mean-field switching diffusions
Kai Ding, Xun Li, Siyu Lv, Zuo Quan Xu
https://arxiv.org/abs/2506.16033

Infinite horizon discounted LQ optimal control problems for mean-field switching diffusions
This paper investigates an infinite horizon discounted linear-quadratic (LQ) optimal control problem for stochastic differential equations (SDEs) incorporating regime switching and mean-field interactions. The regime switching is modeled by a finite-state Markov chain acting as common noise, while the mean-field interactions are characterized by the conditional expectation of the state process given the history of the Markov chain. To address system stability in the infinite horizon setting, a …

Scaling GR(1) Synthesis via a Compositional Framework for LTL Discrete Event Control
Hern\'an Gagliardi, Victor Braberman, Sebastian Uchitel
https://arxiv.org/abs/2506.16557

Scaling GR(1) Synthesis via a Compositional Framework for LTL Discrete Event Control
We present a compositional approach to controller synthesis of discrete event system controllers with linear temporal logic (LTL) goals. We exploit the modular structure of the plant to be controlled, given as a set of labelled transition systems (LTS), to mitigate state explosion that monolithic approaches to synthesis are prone to. Maximally permissive safe controllers are iteratively built for subsets of the plant LTSs by solving weaker control problems. Observational synthesis equivalence i…

Hardware-efficient quantum phase estimation via local control
Benjamin F. Schiffer, Dominik S. Wild, Nishad Maskara, Mikhail D. Lukin, J. Ignacio Cirac
https://arxiv.org/abs/2506.18765

Hardware-efficient quantum phase estimation via local control
Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary evolution conditioned on the state of one or more auxiliary qubits, posing a significant challenge for current quantum devices. In this work, we present an approach to quantum phase estimation that uses only locally controlled operations, resulting in a signif…

Koopman Operator Based Time-Delay Embeddings and State History Augmented LQR for Periodic Hybrid Systems: Bouncing Pendulum and Bipedal Walking
Chun-Ming Yang, Pranav A. Bhounsule
https://arxiv.org/abs/2507.14455

Koopman Operator Based Time-Delay Embeddings and State History Augmented LQR for Periodic Hybrid Systems: Bouncing Pendulum and Bipedal Walking
Time-delay embedding is a technique that uses snapshots of state history over time to build a linear state space model of a nonlinear smooth system. We demonstrate that periodic non-smooth or hybrid system can also be modeled as a linear state space system using this approach as long as its behavior is consistent in modes and timings. We extended time-delay embeddings to generate a linear model of two periodic hybrid systems: the bouncing pendulum and the simplest walker with control inputs. Th…

A $C^0$ weak Galerkin method with preconditioning for constrained optimal control problems with general tracking
SeongHee Jeong, Seulip Lee, Kening Wang
https://arxiv.org/abs/2506.17619

A $C^0$ weak Galerkin method with preconditioning for constrained optimal control problems with general tracking
This paper presents a $C^0$ weak Galerkin ($C^0$-WG) method combined with an additive Schwarz preconditioner for solving optimal control problems (OCPs) governed by partial differential equations with general tracking cost functionals and pointwise state constraints. These problems pose significant analytical and numerical challenges due to the presence of fourth-order variational inequalities and the reduced regularity of solutions. Our first contribution is the design of a $C^0$-WG method bas…

Quasi-Contact Forces with Resonant Range Control in Rydberg Atoms
Mohammadsadegh Khazali
https://arxiv.org/abs/2507.17361 https://arxiv.org/pdf/2507.17361 https://arxiv.org/html/2507.17361
arXiv:2507.17361v1 Announce Type: new
Abstract: We introduce a novel method to engineer sharply peaked, distance-selective interactions between neutral atoms by exploiting interaction-induced resonances within a resonantly driven Rydberg ladder system. By tuning laser parameters, a subsystem eigenstate twist rapidly and brought into degeneracy with the atomic ground state at precisely defined interatomic separations, resulting in an effective potential sharply localized around this resonance distance. Unlike previous off-resonant macrodimer-based schemes, our approach significantly enhances interaction sharpness and strength, reaching MHz scales, and provides straightforward experimental tunability without requiring sub-wavelength positional control. Analytic expressions, validated through comprehensive master-equation simulations, detail the interaction profile's amplitude, width, and resonant distance. This precise control facilitates parallel entangling gates crucial for measurement-based quantum computing and enables simulation of complex lattice Hamiltonians with customizable connectivity. Additionally, our scheme opens possibilities for novel studies in molecular physics through micrometer-scale bond-length diatomic molecules.
toXiv_bot_toot

ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search
Olivia Dry, Timothy L. Molloy, Wanxin Jin, Iman Shames
https://arxiv.org/abs/2507.17096

ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search
We propose Zeroth-Order Random Matrix Search for Learning from Demonstrations (ZORMS-LfD). ZORMS-LfD enables the costs, constraints, and dynamics of constrained optimal control problems, in both continuous and discrete time, to be learned from expert demonstrations without requiring smoothness of the learning-loss landscape. In contrast, existing state-of-the-art first-order methods require the existence and computation of gradients of the costs, constraints, dynamics, and learning loss with re…

Output Feedback Design for Parameter Varying Systems subject to Persistent Disturbances and Control Rate Constraints
Jackson G. Ernesto, Eugenio B. Castelan, Walter Lucia
https://arxiv.org/abs/2507.17475

Output Feedback Design for Parameter Varying Systems subject to Persistent Disturbances and Control Rate Constraints
This paper presents a technique for designing output feedback controllers for constrained linear parameter-varying systems that are subject to persistent disturbances. Specifically, we develop an incremental parameter-varying output feedback control law to address control rate constraints, as well as state and control amplitude constraints. The proposal is based on the concept of robust positively invariant sets and applies the extended Farkas' lemma to derive a set of algebraic conditions that…

Economic inequality has reached a staggering milestone in Silicon Valley:
just nine households hold 15% of the region’s wealth, according to new research from San Jose State University.
🔥A mere 0.1% of residents hold 71% of the tech hub’s wealth.
The findings come from the 2025 “Silicon Valley Pain Index”,
a report published by SJSU’s Human Rights Institute each year since 2020. The report aims to quantify “structured inequalities” in Silicon Valley, and measures “pai…

Pontryagin Maximum Principle for McKean-Vlasov Reaction-Diffusion Equations
Johan Benedikt Spille, Wilhelm Stannat
https://arxiv.org/abs/2507.16288 https:/…

Pontryagin Maximum Principle for McKean-Vlasov Reaction-Diffusion Equations
We consider the stochastic control of a semi-linear stochastic partial differential equations (SPDE) of McKean-Vlasov type. Based on a recent novel approach to the Lions derivative for Banach space valued functions, we prove the Gateaux differentiability of the control to state map and, using adjoint calculus, we derive explicit representations of the gradient of the cost functional and a Pontryagin maximum principle. On the way, we also prove a novel existence and uniqueness result for linear …

Electric field control of superconducting fluctuations and quasiparticle interference at oxide interfaces
Graham Kimbell (Department of Quantum Matter Physics, University of Geneva, Geneva, Switzerland), Ulderico Filippozzi (Kavli Institute of Nanoscience, Delft University of Technology, Delft, Netherlands), Stefano Gariglio (Department of Quantum Matter Physics, University of Geneva, Geneva, Switzerland), Marc Gabay (Laboratoire de Physique des Solides, Universite Paris Saclay, CNRS U…

Electric field control of superconducting fluctuations and quasiparticle interference at oxide interfaces
We investigate tunable superconducting transitions in (111)$\mathrm{LaAlO}_3/\mathrm{KTaO}_3$ field-effect devices. Large increases in conductivity, associated with superconducting fluctuations, are observed far above the transition temperature. However, the standard Aslamazov-Larkin paraconductivity model significantly underestimates the effect observed here. We use a model that includes conductivity corrections from normal state quasiparticle interference together with all contributions from …

An adaptive procedure for detecting replicated signals with $k$-family-wise error rate control
Ninh Tran
https://arxiv.org/abs/2508.15363 https://arxiv.org…

An adaptive procedure for detecting replicated signals with $k$-family-wise error rate control
Partial conjunction (PC) hypothesis testing is widely used to assess the replicability of scientific findings across multiple comparable studies. In high-throughput meta-analyses, testing a large number of PC hypotheses with k-family-wise error rate (k-FWER) control often suffers from low statistical power due to the multiplicity burden. The state-of-the-art AdaFilter-Bon procedure by Wang et al. (2022, Ann. Stat., 50(4), 1890-1909) alleviates this problem by filtering out hypotheses unlikely t…

Low-Power Control of Resistance Switching Transitions in First-Order Memristors
Valeriy A. Slipko, Alon Ascoli, Fernando Corinto, Yuriy V. Pershin
https://arxiv.org/abs/2508.15620

Low-Power Control of Resistance Switching Transitions in First-Order Memristors
In many cases, the behavior of physical memristive devices can be relatively well captured by using a single internal state variable. This study investigates the low-power control of first-order memristive devices to derive the most energy-efficient protocols for programming their resistances. A unique yet general approach to optimizing the switching transitions in devices of this kind is introduced. For pedagogical purposes, without loss of generality, the proposed control paradigm is applied …

CPED-NCBFs: A Conformal Prediction for Expert Demonstration-based Neural Control Barrier Functions
Sumeadh MS, Kevin Dsouza, Ravi Prakash
https://arxiv.org/abs/2507.15022

CPED-NCBFs: A Conformal Prediction for Expert Demonstration-based Neural Control Barrier Functions
Among the promising approaches to enforce safety in control systems, learning Control Barrier Functions (CBFs) from expert demonstrations has emerged as an effective strategy. However, a critical challenge remains: verifying that the learned CBFs truly enforce safety across the entire state space. This is especially difficult when CBF is represented using neural networks (NCBFs). Several existing verification techniques attempt to address this problem including SMT-based solvers, mixed-integer …

Effects of Cognitive Distraction and Driving Environment Complexity on Adaptive Cruise Control Use and Its Impact on Driving Performance: A Simulator Study
Ana\"is Halin, Marc Van Droogenbroeck, Christel Devue
https://arxiv.org/abs/2507.13886

Effects of Cognitive Distraction and Driving Environment Complexity on Adaptive Cruise Control Use and Its Impact on Driving Performance: A Simulator Study
In this simulator study, we adopt a human-centered approach to explore whether and how drivers' cognitive state and driving environment complexity influence reliance on driving automation features. Besides, we examine whether such reliance affects driving performance. Participants operated a vehicle equipped with adaptive cruise control (ACC) in a simulator across six predefined driving scenarios varying in traffic conditions while either performing a cognitively demanding task (i.e., respondin…

Optically tunable linear and nonlinear enhancement of index of refraction
Elif Ozturk, Hira Asif, Mehmet Gunay, Mehmet Emre Tasgin, Ramazan Sahin
https://arxiv.org/abs/2506.17703 …

Optically tunable linear and nonlinear enhancement of index of refraction
Control of optical properties of materials by tuning their refractive index can revolutionize the current state-of-the-art technology to manipulate light propagation in the high loss media. Here we demonstrate active optical tuning of the plasmonic analog of enhancement of index of refraction (EIR) in both linear and nonlinear regimes using a quantum mechanical approach. By employing a pump-probe scheme, we investigate the tuning of refractive index of the probe field by varying amplitude and p…

General Linear-Quadratic Mean Field Stochastic Differential Game with Common Noise: a Direct Method
Yu Si, Jingtao Shi
https://arxiv.org/abs/2506.16779 htt…

General Linear-Quadratic Mean Field Stochastic Differential Game with Common Noise: a Direct Method
This paper investigates a class of general linear-quadratic mean field games with common noise, where the diffusion terms of the system contain the state variables, control variables, and the average state terms. We solve the problem using both the direct method and the fixed-point method in the paper. First, by using the variational method to solve a finite $N$-players game problem, we obtain the necessary and sufficient conditions for the centralized open-loop Nash equilibrium strategy. Subse…

Data assimilation using a global Girsanov nudged particle filter
Maneesh Kumar Singh, Joshua Hope-Collins, Colin J. Cotter, Dan Crisan
https://arxiv.org/abs/2507.17685 https://

Data assimilation using a global Girsanov nudged particle filter
We present a particle filtering algorithm for stochastic models on infinite dimensional state space, making use of Girsanov perturbations to nudge the ensemble of particles into regions of higher likelihood. We argue that the optimal control problem needs to couple control variables for all of the particles to maintain an ensemble with good effective sample size (ESS). We provide an optimisation formulation that separates the problem into three stages, separating the nonlinearity in the ESS ter…

Free-Particle State Realized via Optimal Filtering in Optomechanics: Implications for Gravity-Induced Entanglement
Ryotaro Fukuzumi, Kosei Hatakeyama, Daisuke Miki, Kazuhiro Yamamoto
https://arxiv.org/abs/2508.14337

Free-Particle State Realized via Optimal Filtering in Optomechanics: Implications for Gravity-Induced Entanglement
We analyze the conditional quantum state of a mechanical mirror in an optomechanical system under continuous measurement, feedback control, and quantum filtering. Our study identifies a regime in which the mirror's momentum is squeezed beyond the standard quantum limit achievable through appropriate tuning of the homodyne detection angle. We show that in this regime, optimal filtering effectively realizes a free-particle-like state. Notably, when applied to a setup involving two optomechanical …

SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip
Ziteng Hu, Yingjie Xia, Xiyuan Chen, Li Kuang
https://arxiv.org/abs/2508.12910

SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip
Finite State Machines (FSMs) play a critical role in implementing control logic for Systems-on-Chip (SoC). Traditionally, FSMs are implemented by hardware engineers through Verilog coding, which is often tedious and time-consuming. Recently, with the remarkable progress of Large Language Models (LLMs) in code generation, LLMs have been increasingly explored for automating Verilog code generation. However, LLM-generated Verilog code often suffers from security vulnerabilities, which is particula…

Fast charge noise sensing using a spectator valley state in a singlet-triplet qubit
David W. Kanaar, Yasuo Oda, Mark F. Gyure, J. P. Kestner
https://arxiv.org/abs/2507.14108

Fast charge noise sensing using a spectator valley state in a singlet-triplet qubit
Semiconductor spin qubits are a promising platform for quantum computing but remain vulnerable to charge noise. Accurate, in situ measurement of charge noise could enable closed-loop control and improve qubit performance. Here, we propose a method for real-time detection of charge noise using a silicon singlet-triplet qubit with one electron initialized in an excited valley state. This valley excitation acts as a spectator degree of freedom, coupled to a high-quality resonator via the exchange …

Conformal Safety Shielding for Imperfect-Perception Agents
William Scarbro, Calum Imrie, Sinem Getir Yaman, Kavan Fatehi, Corina S. Pasareanu, Radu Calinescu, Ravi Mangal
https://arxiv.org/abs/2506.17275

Conformal Safety Shielding for Imperfect-Perception Agents
We consider the problem of safe control in discrete autonomous agents that use learned components for imperfect perception (or more generally, state estimation) from high-dimensional observations. We propose a shield construction that provides run-time safety guarantees under perception errors by restricting the actions available to an agent, modeled as a Markov decision process, as a function of the state estimates. Our construction uses conformal prediction for the perception component, which…

The influence of nitrogen doping and annealing on the silicon vacancy in 4H-SiC
Samuel G. Carter, Infiter Tathfif, Charity Burgess, Brenda VanMil, Suryakanti Debata, Pratibha Dev
https://arxiv.org/abs/2506.17478

The influence of nitrogen doping and annealing on the silicon vacancy in 4H-SiC
The silicon vacancy ($V_{Si}$) in 4H-SiC at its cubic site (V2-center) has shown significant promise for quantum technologies, due to coherent spin states, the mature material system, and stable optical emission. In these SiC-based applications, doping plays a crucial role. It can be used to control the charge state of $V_{Si}$ and formation of different types of defects. Despite its importance, there has been little research on the effects of doping. In this work, we perform a study of the eff…

Trump keeps control of National Guard in LA for now • Washington State Standard
https://washingtonstatestandard.com/2025/06/13/repub/trump-keeps-control-of-california-national-guard-in-la-for-now-after-appeals-court-order/

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
Fengxian Ji, Jingpu Yang, Zirui Song, Yuanxi Wang, Zhexuan Cui, Yuke Li, Qian Jiang, Miao Fang, Xiuying Chen
https://arxiv.org/abs/2508.09241

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing daily tasks through natural language instructions. However, current evaluation frameworks for GUI agents suffer from fundamental flaws: existing benchmarks overly focus on coarse-grained task completion while neglecting fine-grained control capabilities crucial for real-world applications. To address this, we introduc…

Synchronization driven acoustics: The nonlinear scattering of a self-oscillating meta-atom
Alexander K. Stoychev, Xinxin Guo, Ulrich Kuhl, Nicolas Noiray
https://arxiv.org/abs/2508.14819

Synchronization driven acoustics: The nonlinear scattering of a self-oscillating meta-atom
In this study we demonstrate a self-oscillating acoustic meta-atom functioning as an amplifying transistor, where a steady external flow serves as a control signal to switch between reflective (off-state) and transmissive (on-state) regimes. In the on-state, an acoustic limit cycle synchronizes with incident sound waves. This process governs the energy transfer across the device, with a transmission bandwidth dictated by the synchronization region in parameter space (Arnold tongue). Our experim…

Observed Control -- Linearly Scalable Nonlinear Model Predictive Control with Adaptive Horizons
Eugene T. Hamzezadeh, Andrew J. Petruska
https://arxiv.org/abs/2508.13339 https:/…

Observed Control -- Linearly Scalable Nonlinear Model Predictive Control with Adaptive Horizons
This work highlights the duality between state estimation methods and model predictive control. A predictive controller, observed control, is presented that uses this duality to efficiently compute control actions with linear time-horizon length scalability. The proposed algorithms provide exceptional computational efficiency, adaptive time horizon lengths, and early optimization termination criteria. The use of Kalman smoothers as the backend optimization framework provides for a straightforwa…

The israeli-american genocide of the Palestinian people continues. It’s not just israel. It was never just israel.
“‘This is an administration that is committed to Palestinian erasure, both physical and political,’ Elgindy said. ‘The signs were there even in the first Trump term, which nominally supported a Palestinian ‘state’ that was shorn of all sovereignty and under permanent Israeli control. At least now they’ve abandoned the pretense.’
Yousef Munayyer, head of Palestine/Isr…

US ambassador to Israel says US no longer pursuing goal of independent Palestinian state
Mike Huckabee suggested any future Palestinian state should be carved out of ‘a Muslim country’

Enhancing Parameter Control Policies with State Information
Gianluca Covini, Denis Antipov, Carola Doerr
https://arxiv.org/abs/2507.08368 https://

Enhancing Parameter Control Policies with State Information
Parameter control and dynamic algorithm configuration study how to dynamically choose suitable configurations of a parametrized algorithm during the optimization process. Despite being an intensively researched topic in evolutionary computation, optimal control policies are known only for very few cases, limiting the development of automated approaches to achieve them. With this work we propose four new benchmarks for which we derive optimal or close-to-optimal control policies. More precisel…

President Trump's spending bill could limit local control over zoning and environmental regulations for AI data centers, worrying state lawmakers (Molly Taft/Wired)
https://www.wired.com/story/a-political-battle-is-brewing-over-data-centers/…

A Political Battle Is Brewing Over Data Centers
An AI-related provision in the “Big Beautiful Bill” could restrict state-level legislation of energy-hungry data centers—and is raising bipartisan objections across the US.

Replaced article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Trapped-ion laser cooling in structured light fields
Zhenzhong Xing, Karan K. Mehta
https://arxiv.org/abs/2411.08844 https://mastoxiv.page/@arXiv_physicsatomph_bot/113480313003086521
- Lorentz and CPT violation and the (anti-)hydrogen molecular ion
Graham M. Shore
https://arxiv.org/abs/2412.09730 https://mastoxiv.page/@arXiv_physicsatomph_bot/113661506443273739
- Bremsstrahlung induced atomic processes
Singh, Kumar, Chatterjee, Swami, Kaur, Jha, Oswal, Singh, Nandi
https://arxiv.org/abs/2501.02967 https://mastoxiv.page/@arXiv_physicsatomph_bot/113786077273931578
- Clarifying Self Seed in 391-nm N$_2^{ }$ Air Lasing by Vectorially Structured Light Fields
Jingsong Gao, Yang Wang, Jiahao Dong, Yi Liu, Chengyin Wu, Hongbing Jiang, Yunquan Liu, Meng Han
https://arxiv.org/abs/2502.01414 https://mastoxiv.page/@arXiv_physicsatomph_bot/113944386182439139
- Linear dichroism signals due to the alignment in the ground state of hydrogen-like atoms and thei...
M. V. Petrenko, A. S. Pazgalev, A. K. Vershovskii
https://arxiv.org/abs/2504.20716 https://mastoxiv.page/@arXiv_physicsatomph_bot/114425750205554960
- Sub-Doppler cooling of bosonic strontium in a two-color MOT
Negyedi, Deutschle, Jessen, Fort\'agh, S\'ark\'any
https://arxiv.org/abs/2507.02693 https://mastoxiv.page/@arXiv_physicsatomph_bot/114794127138414131
- Molecular Quantum Control Algorithm Design by Reinforcement Learning
Anastasia Pipi, Xuecheng Tao, Arianna Wu, Prineha Narang, David R. Leibrandt
https://arxiv.org/abs/2410.11839 https://mastoxiv.page/@arXiv_quantph_bot/113316450427865660
- Single-atom resolved collective spectroscopy of a one-dimensional atomic array
Britton Hofer, Damien Bloch, Giulio Biagioni, Nathan Bonvalet, Antoine Browaeys, Igor Ferrier-Barbut
https://arxiv.org/abs/2412.02541 https://mastoxiv.page/@arXiv_quantph_bot/113593627161222722
- Mutual friction and vortex Hall angle in a strongly interacting Fermi superfluid
Nicola Grani, et al.
https://arxiv.org/abs/2503.21628 https://mastoxiv.page/@arXiv_condmatquantgas_bot/114238880586578320
- Lorentz and CPT violation and the (anti-)hydrogen molecular ion II -- hyperfine-Zeeman spectrum
Graham M Shore
https://arxiv.org/abs/2504.19015 https://mastoxiv.page/@arXiv_hepph_bot/114420102398265292
- Cooling of an optically levitated nanoparticle via measurement-free coherent feedback
Bruno Melo, Daniel Veldhuizen, Gregoire F. M. Tomassi, Nadine Meyer, Romain Quidant
https://arxiv.org/abs/2506.21341 https://mastoxiv.page/@arXiv_quantph_bot/114754750333187473
toXiv_bot_toot

Superconducting critical temperature and dimensionality tuning of RbV$_3$Sb$_5$ via biaxial strain
Tsz Fung Poon, King Yau Yip, Ying Kit Tsui, Lingfei Wang, Kai Ham Yu, Wei Zhang, Zheyu Wang, Taketo Nakatani, Chishiro Michioka, Hiroaki Ueda, Siu Tung Lam, Kwing To Lai, Swee K. Goh
https://arxiv.org/abs/2506.16165

Superconducting critical temperature and dimensionality tuning of RbV$_3$Sb$_5$ via biaxial strain
Kagome metal AV$_3$Sb$_5$ (A=K, Rb, Cs) has emerged as an intriguing platform for exploring the interplay between superconductivity and other quantum states. Among the three compounds, RbV$_3$Sb$_5$ has a notably lower superconducting critical temperature ($T_c$) at ambient pressure, posing challenges in exploring the superconducting state. For instance, the upper critical field ($H_{c2}$) is small and thus difficult to measure accurately against other control parameters. Hence, enhancing super…

Sparse Autoencoders for Sequential Recommendation Models: Interpretation and Flexible Control
Anton Klenitskiy, Konstantin Polev, Daria Denisova, Alexey Vasilev, Dmitry Simakov, Gleb Gusev
https://arxiv.org/abs/2507.12202

Sparse Autoencoders for Sequential Recommendation Models: Interpretation and Flexible Control
Many current state-of-the-art models for sequential recommendations are based on transformer architectures. Interpretation and explanation of such black box models is an important research question, as a better understanding of their internals can help understand, influence, and control their behavior, which is very important in a variety of real-world applications. Recently sparse autoencoders (SAE) have been shown to be a promising unsupervised approach for extracting interpretable features f…

Autonomous Control Leveraging LLMs: An Agentic Framework for Next-Generation Industrial Automation
Javal Vyas, Mehmet Mercangoz
https://arxiv.org/abs/2507.07115

Autonomous Control Leveraging LLMs: An Agentic Framework for Next-Generation Industrial Automation
The increasing complexity of modern chemical processes, coupled with workforce shortages and intricate fault scenarios, demands novel automation paradigms that blend symbolic reasoning with adaptive control. In this work, we introduce a unified agentic framework that leverages large language models (LLMs) for both discrete fault-recovery planning and continuous process control within a single architecture. We adopt Finite State Machines (FSMs) as interpretable operating envelopes: an LLM-driven…

Safe and Performant Controller Synthesis using Gradient-based Model Predictive Control and Control Barrier Functions
Aditya Singh, Aastha Mishra, Manan Tayal, Shishir Kolathaya, Pushpak Jagtap
https://arxiv.org/abs/2507.13872

Safe and Performant Controller Synthesis using Gradient-based Model Predictive Control and Control Barrier Functions
Ensuring both performance and safety is critical for autonomous systems operating in real-world environments. While safety filters such as Control Barrier Functions (CBFs) enforce constraints by modifying nominal controllers in real time, they can become overly conservative when the nominal policy lacks safety awareness. Conversely, solving State-Constrained Optimal Control Problems (SC-OCPs) via dynamic programming offers formal guarantees but is intractable in high-dimensional systems. In thi…

Time Scale Separation and Hierarchical Control with the Koopman Operator
Craig Bakker
https://arxiv.org/abs/2506.15586 https://arxiv.…

Time Scale Separation and Hierarchical Control with the Koopman Operator
The Koopman Operator (KO) is a mathematical construct that maps nonlinear (state space) dynamics to corresponding linear dynamics in an infinite-dimensional functional space. For practical applications, finite-dimensional approximations can be constructed with machine learning. The linearity of the KO facilitates the use of linear tools and theories on nonlinear dynamical systems without relying on local approximations. Additionally, the KO has the ability to incorporate forms of domain knowled…

Series A, Episode 04 - Time Squad
BLAKE: Oh, what do you say to that Zen?
ZEN: Please state course and speed.
BLAKE: Very diplomatic. Set a course for Centero, speed standard by two.
ZEN: Confirmed.
[End of episode. Roll credits.]
https://blake.torpidity.net/m/104/504 …

Multiple-Noise-Resilient Nonadiabatic Geometric Quantum Control of Solid-State Spins in Diamond
Si-Qi Chen, Qi-Tao Duan, Chengxian Zhang, He Lu
https://arxiv.org/abs/2508.12221 …

Multiple-Noise-Resilient Nonadiabatic Geometric Quantum Control of Solid-State Spins in Diamond
Reliable and robust control lies at the core of implementing quantum information processing with diamond nitrogen-vacancy (NV) centers. However, control pulses inevitably introduce multiple errors, leading to decoherence and hindering scalable applications. Here, we experimentally report an experiment-friendly multiple-noise-resilient nonadiabatic geometric quantum gate~(MNR-NGQG) that can significantly improve conventional dynamical gate in both robustness and coherence. Notably, even when the…

A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
Bolin Li, Gewei Zuo, Zhixiang Wang, Xiaotian Ke, Lijun Zhu, Han Ding
https://arxiv.org/abs/2508.13531

A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
This paper presents a control framework designed to enhance the stability and robustness of legged robots in the presence of uncertainties, including model uncertainties, external disturbances, and faults. The framework enables the full-state feedback estimator to estimate and compensate for uncertainties in whole-body dynamics of the legged robots. First, we propose a novel moving horizon extended state observer (MH-ESO) to estimate uncertainties and mitigate noise in legged systems, which can…

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
Sihang Wei, Melkior Ornik, Hiroyasu Tsukamoto
https://arxiv.org/abs/2507.13613

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
We present a novel robust control framework for continuous-time, perturbed nonlinear dynamical systems with uncertainty that depends nonlinearly on both the state and control inputs. Unlike conventional approaches that impose structural assumptions on the uncertainty, our framework enhances contraction-based robust control with data-driven uncertainty prediction, remaining agnostic to the models of the uncertainty and predictor. We statistically quantify how reliably the contraction conditions …

Advancing the Control of Low-Altitude Wireless Networks: Architecture, Design Principles, and Future Directions
Haijia Jin, Weijie Yuan, Jun Wu, Jiacheng Wang, Dusit Niyato, Xianbin Wang, George K. Karagiannidis, Zhiyun Lin, Yi Gong, Dong In Kim, Athina Petropulu, Maria Sabrina Greco, Abbas Jamalipour, Sumei Sun
https://arxiv.org/abs/2508.…

Advancing the Control of Low-Altitude Wireless Networks: Architecture, Design Principles, and Future Directions
This article introduces a control-oriented low-altitude wireless network (LAWN) that integrates near-ground communications and remote estimation of the internal system state. This integration supports reliable networked control in dynamic aerial-ground environments. First, we introduce the network's modular architecture and key performance metrics. Then, we discuss core design trade-offs across the control, communication, and estimation layers. A case study illustrates closed-loop coordination …

There’s another name for that…
Analysis | The U.S. Marches Toward State Capitalism With American Characteristics - The Wall Street Journal https://apple.news/AX_EJXTACTMSc4TPv3huykQ

Analysis | The U.S. Marches Toward State Capitalism With American Characteristics — The Wall Street Journal
President Trump is imitating Chinese Communist Party by extending political control ever deeper into economy

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/2]:
- Worst-Case Services and State-Based Scheduling
Yike Xu, Mark S. Andersland

Mean-Field Stochastic Linear-Quadratic Optimal Controls: Roles of Expectation and Conditional Expectation Operators
Hanxiao Wang, Jiongmin Yong
https://arxiv.org/abs/2507.16582

Mean-Field Stochastic Linear-Quadratic Optimal Controls: Roles of Expectation and Conditional Expectation Operators
This paper investigates a mean-field linear-quadratic optimal control problem where the state dynamics and cost functional incorporate both expectation and conditional expectation terms. We explicitly derive the pre-committed, na\"ıve, and equilibrium solutions and establish the well-posedness of the associated Riccati equations. This reveals how the expectation and conditional expectation operators influence time-consistency.

Attosecond high-harmonic interferometry probes orbital- and band-dependent dipole phase in magnesium oxide
Nataliia Kuzkova, Pieter J. van Essen, Brian de Keijzer, Rui E. F. Silva, Alvaro Jimenez Galan, Peter M. Kraus
https://arxiv.org/abs/2508.15076

Attosecond high-harmonic interferometry probes orbital- and band-dependent dipole phase in magnesium oxide
Control over the spatial coherence, wavefront, and focusability of emitted light relies on understanding the intrinsic phase of the emission process, and vice versa, measuring phase can reveal insights about microscopic generation mechanisms. A thorough understanding of the origin of the dipole phase in solid-state high-harmonic generation is currently missing. Here, by employing attosecond interferometry with phase-locked XUV pulses, we directly assess the intensity- and frequency-dependent di…

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
Satyajith Bommana Boyana, Thomas Lewis, Sijing Liu, Yi Zhang
https://arxiv.org/abs/2506.12330

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
This paper investigates a symmetric dual-wind discontinuous Galerkin (DWDG) method for solving an elliptic optimal control problem with control constraints. The governing constraint is an elliptic partial differential equation (PDE), which is discretized using the symmetric DWDG approach. We derive error estimates in the energy norm for both the state and the adjoint state, as well as in the $L^2$ norm of the control variable. Numerical experiments are provided to demonstrate the robustness and…

MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
Yuchen Zhu, Wei Guo, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, Molei Tao
https://arxiv.org/abs/2508.10684 h…

MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
We study the problem of learning a neural sampler to generate samples from discrete state spaces where the target probability mass function $π\propto\mathrm{e}^{-U}$ is known up to a normalizing constant, which is an important task in fields such as statistical physics, machine learning, combinatorial optimization, etc. To better address this challenging task when the state space has a large cardinality and the distribution is multi-modal, we propose $\textbf{M}$asked $\textbf{D}$iffusion $\te…

Online Feedback Optimization for Monotone Systems without Timescale Separation
Mattia Bianchi, Florian D\"orfler
https://arxiv.org/abs/2506.16564 http…

Online Feedback Optimization for Monotone Systems without Timescale Separation
Online Feedback Optimization (OFO) steers a dynamical plant to a cost-efficient steady-state, only relying on input-output sensitivity information, rather than on a full plant model. Unlike traditional feedforward approaches, OFO leverages real-time measurements from the plant, thereby inheriting the robustness and adaptability of feedback control. Unfortunately, existing theoretical guarantees for OFO assumes that the controller operates on a slower timescale than the plant, which can affect r…

Efficient Environment Design for Multi-Robot Navigation via Continuous Control
Jahid Chowdhury Choton, John Woods, William Hsu
https://arxiv.org/abs/2508.14105 https://

Efficient Environment Design for Multi-Robot Navigation via Continuous Control
Multi-robot navigation and path planning in continuous state and action spaces with uncertain environments remains an open challenge. Deep Reinforcement Learning (RL) is one of the most popular paradigms for solving this task, but its real-world application has been limited due to sample inefficiency and long training periods. Moreover, the existing works using RL for multi-robot navigation lack formal guarantees while designing the environment. In this paper, we introduce an efficient and high…

All-mechanical coherence protection and fast control of a spin qubit
Eliza Cornell, Zhujing Xu, Zhaoyou Wang, Hana K. Warner, Eliana Mann, Michael Haas, Smarak Maity, Graham Joe, Liang Jiang, Peter Rabl, Benjamin Pingault, Marko Lon\v{c}ar
https://arxiv.org/abs/2508.13356

All-mechanical coherence protection and fast control of a spin qubit
In a phononic quantum network, quantum information is stored and processed within stationary nodes defined by solid-state spins, and the information is routed between nodes by phonons. The phonon holds distinct advantages over its electromagnetic counterpart the photon, including smaller device footprints, reduced crosstalk, long coherence times at low temperatures, and strong interactions with both solid-state spins and electromagnetic waves. Enhanced interactions between a phononic cavity and…

A federal judge ruled on Thursday that Donald Trump illegally deployed the California national guard to suppress protests against immigration raids in Los Angeles
and ordered the force to be returned to the control of the state governor, Gavin Newsom.
The order by the US district judge Charles Breyer will not take effect until noon on Friday,
but it marked a stinging defeat for the Trump administration that is sure to touch off a pitched legal battle destined for the US supr…

A Distributed Actor-Critic Algorithm for Fixed-Time Consensus in Nonlinear Multi-Agent Systems
Aria Delshad, Maryam Babazadeh
https://arxiv.org/abs/2507.16520

A Distributed Actor-Critic Algorithm for Fixed-Time Consensus in Nonlinear Multi-Agent Systems
This paper proposes a reinforcement learning (RL)-based backstepping control strategy to achieve fixed time consensus in nonlinear multi-agent systems with strict feedback dynamics. Agents exchange only output information with their neighbors over a directed communication graph, without requiring full state measurements or symmetric communication. Achieving fixed time consensus, where convergence occurs within a pre-specified time bound that is independent of initial conditions is faced with si…

Understanding Inconsistent State Update Vulnerabilities in Smart Contracts
Lantian Li, Yuyu Chen, Jingwen Wu, Yue Pan, Zhongxing Yu
https://arxiv.org/abs/2508.06192 https://

Understanding Inconsistent State Update Vulnerabilities in Smart Contracts
Smart contracts enable contract terms to be automatically executed and verified on the blockchain, and recent years have witnessed numerous applications of them in areas such as financial institutions and supply chains. The execution logic of a smart contract is closely related to the contract state, and thus the correct and safe execution of the contract depends heavily on the precise control and update of the contract state. However, the contract state update process can have issues. In parti…

State-based approach to the numerical solution of Dirichlet boundary optimal control problems for the Laplace equation
Ulrich Langer, Richard L\"oscher, Olaf Steinbach, Huidong Yang
https://arxiv.org/abs/2507.11646

State-based approach to the numerical solution of Dirichlet boundary optimal control problems for the Laplace equation
We investigate the Dirichlet boundary control of the Laplace equation, considering the control in $H^{1/2}(\partial Ω)$, which is the natural space for Dirichlet data when the state belongs to $H^1(Ω)$. The cost of the control is measured in the $H^{1/2}(\partial Ω)$ norm that also plays the role of the regularization term. We discuss regularization and finite element error estimates enabling us to derive an optimal relation between the finite element mesh size $h$ and the regularization par…

Application of Optimal Control to Time-Resolution Protocol for Quantum Sensing
Chungwei Lin, Qi Ding, Yanting Ma
https://arxiv.org/abs/2508.13405 https://a…

Application of Optimal Control to Time-Resolution Protocol for Quantum Sensing
Time-resolution protocol of quantum sensing aims to measure the fast temporal variation of an external field and demands a high field sensitivity in a short interrogation time $τ$. Since any operation that evolves the quantum state takes time and is counted as part of the interrogation, evaluating the performance of time-resolution protocol requires a complete end-to-end description of the measurement process. In particular, the initial state has to be one of the sensor qubit's eigenstates in …

Linear Quadratic Regulation for First Order Hyperbolic PDEs
Arthur J. Krener
https://arxiv.org/abs/2508.15028 https://arxiv.org/pdf/2508.15028

Linear Quadratic Regulation for First Order Hyperbolic PDEs
We consider transport processes that are modeled by first order hyperbolic partial differential equations. Our goal is to find a full state feedback that makes a given reference profile locally asymptotically stable. To accomplish this we employ Linear Quadratic Regulation (LQR) with finite dimensional patch or point control actuation. We derive the Riccati partial differential equation whose solution is the kernel of the optimal cost. The optimal state feedback is also found. The derivation is…

Quantum sensing of electron beams using solid-state spins
Jakob M. Grzesik, Dominic Catanzaro, Charles Roques-Carmes, Eric I. Rosenthal, Guido L. van de Stolpe, Aviv Karnieli, Giovanni Scuri, Souvik Biswas, Kenneth J. Leedle, Dylan S. Black, Robert L. Byer, Ido Kaminer, R. Joel England, Shanhui Fan, Olav Solgaard, Jelena Vu\v{c}kovi\'c
https://

Quantum sensing of electron beams using solid-state spins
Scattering experiments with energetic particles, such as free electrons, have been historically used to reveal the quantum structure of matter. However, realizing coherent interactions between free-electron beams and solid-state quantum systems has remained out of reach, owing to their intrinsically weak coupling. Realizing such coherent control would open up opportunities for hybrid quantum platforms combining free electrons and solid-state qubits for coincident quantum information processing …

Invariance Guarantees using Continuously Parametrized Control Barrier Functions
Inkyu Jang, H. Jin Kim
https://arxiv.org/abs/2507.12743 https://

Invariance Guarantees using Continuously Parametrized Control Barrier Functions
Constructing a control invariant set with an appropriate shape that fits within a given state constraint is a fundamental problem in safety-critical control but is known to be difficult, especially for large or complex spaces. This paper introduces a safe control framework of utilizing PCBF: continuously parametrized control barrier functions (CBFs). In PCBF, each choice of parameter corresponds to a control invariant set of relatively simple shape. Invariance-preserving control is done by dyna…

Pose State Perception of Interventional Robot for Cardio-cerebrovascular Procedures
Shunhan Ji, Yanxi Chen, Zhongyu Yang, Quan Zhang, Xiaohang Nie, Jingqian Sun, Yichao Tang
https://arxiv.org/abs/2506.14201

Pose State Perception of Interventional Robot for Cardio-cerebrovascular Procedures
In response to the increasing demand for cardiocerebrovascular interventional surgeries, precise control of interventional robots has become increasingly important. Within these complex vascular scenarios, the accurate and reliable perception of the pose state for interventional robots is particularly crucial. This paper presents a novel vision-based approach without the need of additional sensors or markers. The core of this paper's method consists of a three-part framework: firstly, a dual-he…

Deterministic time rewinding of waves in time-varying media
Seulong Kim, Kihong Kim
https://arxiv.org/abs/2508.14241 https://arxiv.org/pdf/2508.14241

Deterministic time rewinding of waves in time-varying media
Temporal modulation of material parameters offers unprecedented control over wave dynamics, enabling phenomena beyond the capabilities of static systems. Here we introduce and analyze a robust mechanism for time rewinding, whereby a temporally evolved wave is fully restored to its original state through a carefully engineered sequence of temporal modulations. In electromagnetic systems, time rewinding emerges from impedance-matched or anti-matched hierarchical bilayer structures with matched mo…

Supreme Court clears way for Trump to gut education department – live updates
The supreme court has cleared the way for Donald Trump’s administration to resume dismantling the Department of Education -- part of his effort to shrink the federal government’s role in education in favor of more state control.
In the latest high court win for Trump, the justices lifted a federal judge’s order that had reinstated nearly 1,400 workers affected by mass layoffs at the department and block…

Neural Co-state Regulator: A Data-Driven Paradigm for Real-time Optimal Control with Input Constraints
Lihan Lian, Yuxin Tong, Uduak Inyang-Udoh
https://arxiv.org/abs/2507.12259

Neural Co-state Regulator: A Data-Driven Paradigm for Real-time Optimal Control with Input Constraints
We propose a novel unsupervised learning framework for solving nonlinear optimal control problems (OCPs) with input constraints in real-time. In this framework, a neural network (NN) learns to predict the optimal co-state trajectory that minimizes the control Hamiltonian for a given system, at any system's state, based on the Pontryagin's Minimum Principle (PMP). Specifically, the NN is trained to find the norm-optimal co-state solution that simultaneously satisfies the nonlinear system dynamic…

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.

Reversing adiabatic state preparation
L. Romanato, N. Eshaqi-Sani, L. Lepori, T. Kirova, E. Arimondo, S. Wimberger
https://arxiv.org/abs/2507.08439 https:/…

Reversing adiabatic state preparation
We present a detailed study of an adiabatic state preparation in an effective three-level quantum system. States can be prepared with high speed and fidelity by adding a counterdiabatic quantum control protocol. As a second step, we invert the preparation protocol to get back to the initial state. This describes an overall cyclic evolution in state space. Using counterdiabatic terms, the resulting composed fast evolution can be repeated many times. We then analyze the control of Berry's phase a…

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
Abhinav Chalise, Nimesh Gopal Pradhan, Nishan Khanal, Prashant Raj Bista, Dinesh Baniya Kshatri
https://arxiv.org/abs/2508.12469 …

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
The core mechanical system is built around three stepper motors for physical manipulation, a microcontroller for hardware control, a camera and YOLO detection model for real-time cube state detection. A significant software component is the development of a user-friendly graphical user interface (GUI) designed in Unity. The initial state after detection from real-time YOLOv8 model (Precision 0.98443, Recall 0.98419, Box Loss 0.42051, Class Loss 0.2611) is virtualized on GUI. To get the solution…

A bang-bang solution with infinitely many switching points for a parabolic boundary control problem with terminal observation
Constantin Christof
https://arxiv.org/abs/2506.12768 …

A bang-bang solution with infinitely many switching points for a parabolic boundary control problem with terminal observation
We study a parabolic boundary control problem with one spatial dimension, control constraints of box type, and an objective function that measures the $L^2$-distance to a desired terminal state. It is shown that, for a certain choice of the desired state, the considered problem possesses an optimal control that is chattering, i.e., of bang-bang type with infinitely many switching points and a positive objective function value. Whether such a solution is possible has been an open question in the…

System-Level Performance and Communication Tradeoff in Networked Control with Predictions
Yifei Wu, Jing Yu, Tongxin Li
https://arxiv.org/abs/2508.13475 https://

System-Level Performance and Communication Tradeoff in Networked Control with Predictions
Distributed control of large-scale systems is challenging due to the need for scalable and localized communication and computation. In this work, we introduce a Predictive System-Level Synthesis PredSLS framework that designs controllers by jointly integrating communication constraints and local disturbance predictions into an affine feedback structure. Rather than focusing on the worst-case uncertainty, PredSLS leverages both current state feedback and future system disturbance predictions to …

Fabrication of oriented NV center arrays in diamond via femtosecond laser writing and reorientation
Kai Klink, Andrew Raj Kirkpatrick, Yukihiro Tadokoro, Jonas Nils Becker, Shannon Singer Nicley
https://arxiv.org/abs/2507.14047

Fabrication of oriented NV center arrays in diamond via femtosecond laser writing and reorientation
Nitrogen-vacancy (NV) centers in diamond are widely recognized as highly promising solid-state quantum sensors due to their long room temperature coherence times and atomic-scale size, which enable exceptional sensitivity and nanoscale spatial resolution under ambient conditions. Ultrafast laser writing has demonstrated the deterministic spatial control of individual NV$^-$ centers, however, the resulting random orientation of the defect axis limits the magnetic field sensitivity and signal con…

AutoMPC: A Code Generator for MPC-based Automated Driving
Georg Schildbach, Jasper Pflughaupt
https://arxiv.org/abs/2508.13656 https://arxiv.org/pdf/2508.1…

AutoMPC: A Code Generator for MPC-based Automated Driving
Model Predictive Control (MPC) is a powerful technique to control nonlinear, multi-input multi-output systems subject to input and state constraints. It is now a standard tool for trajectory tracking control of automated vehicles. As such it has been used in many research and development projects. However, MPC faces several challenges to be integrated into industrial production vehicles. The most important ones are its high computational demands and the complexity of implementation. The softwar…

Ocean Diviner: A Diffusion-Augmented Reinforcement Learning for AUV Robust Control in the Underwater Tasks
Weiyi Liu, Jingzehua Xu, Guanwen Xie, Yi Li
https://arxiv.org/abs/2507.11283

Ocean Diviner: A Diffusion-Augmented Reinforcement Learning for AUV Robust Control in the Underwater Tasks
This paper presents a diffusion-augmented reinforcement learning (RL) approach for robust autonomous underwater vehicle (AUV) control, addressing key challenges in underwater trajectory planning and dynamic environment adaptation. The proposed method integrates three core innovations: (1) A diffusion-based trajectory generation framework that produces physically feasible multi-step trajectories, enhanced by a high-dimensional state encoding mechanism combining current observations with historic…

A Dual Quaternion Control Law for Formation Control of Multiple 3-D Rigid Bodies
Chunfeng Cui, Liqun Qi, Hao Chen, Xiangke Wang
https://arxiv.org/abs/2508.10519 https://

A Dual Quaternion Control Law for Formation Control of Multiple 3-D Rigid Bodies
This paper studies the integrated position and attitude control problem for multi-agent systems of 3D rigid bodies. While the state-of-the-art method in [Olfati-Saber and Murray, 2004] established the theoretical foundation for rigid-body formation control, it requires all agents to asymptotically converge to identical positions and attitudes, limiting its applicability in scenarios where distinct desired relative configurations must be maintained. In this paper, we develop a novel dual-quatern…

Expanding a 4-qubit Dicke State a to 5-qubit Dicke State with Limited Qubit Access
Bibhuti Thapa, Oberon Moran, Duc-Kha Vu, Fatih Ozaydin
https://arxiv.org/abs/2508.07977 https:…

Expanding a 4-qubit Dicke State a to 5-qubit Dicke State with Limited Qubit Access
In scenarios where full access to all qubits of a multipartite quantum system is available and global operations can be implemented, the preparation of arbitrary entangled states - including multipartite Dicke states - is theoretically straightforward. However, practical constraints often limit direct control over all qubits. In this work, we first present an efficient method for preparing a four-qubit Dicke state, and then demonstrate how a four-qubit Dicke state can be expanded to a five-qubi…

Data-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics
Mahdi Nazeri, Thom Badings, Anne-Kathrin Schmuck, Sadegh Soudjani, Alessandro Abate
https://arxiv.org/abs/2508.15543

Data-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics
We study the automated abstraction-based synthesis of correct-by-construction control policies for stochastic dynamical systems with unknown dynamics. Our approach is to learn an abstraction from sampled data, which is represented in the form of a finite Markov decision process (MDP). In this paper, we present a data-driven technique for constructing finite-state interval MDP (IMDP) abstractions of stochastic systems with unknown nonlinear dynamics. As a distinguishing and novel feature, our te…

Coherent control of interacting solid-state spins below the diffraction limit
Haitong Xu, Mehmet T. Uysal, Lukasz Dusanowski, Adam Turflinger, Ashwin Boddeti, Joseph Alexander, Jeff D. Thompson
https://arxiv.org/abs/2508.09122

Coherent control of interacting solid-state spins below the diffraction limit
Optically addressed atomic defects in the solid-state are widely used as single-photon sources and memories for quantum network applications. The solid-state environment allows for a high density of electron and nuclear spins with the potential to form registers for coherent information processing. However, it is challenging to reliably address individual spins at nanometer separations where interactions are large. Rare-earth ions offer a unique solution, as their narrow homogeneous optical lin…

Synthesis and SOS-based Stability Verification of a Neural-Network-Based Controller for a Two-wheeled Inverted Pendulum
Alvaro Detailleur, Dalim Wahby, Guillaume Ducard, Christopher Onder
https://arxiv.org/abs/2508.15616

Synthesis and SOS-based Stability Verification of a Neural-Network-Based Controller for a Two-wheeled Inverted Pendulum
This work newly establishes the feasibility and practical value of a sum of squares (SOS)-based stability verification procedure for applied control problems utilizing neural-network-based controllers (NNCs). It successfully verifies closed-loop stability properties of a NNC synthesized using a generalizable procedure to imitate a robust, tube-based model predictive controller (MPC) for a two-wheeled inverted pendulum demonstrator system. This is achieved by first developing a state estimator a…

A stochastic Galerkin method for optimal Dirichlet boundary control problems with uncertain data
Max Winkler, Hamdullah Y\"ucel
https://arxiv.org/abs/2506.11479

A stochastic Galerkin method for optimal Dirichlet boundary control problems with uncertain data
The paper deals with a stochastic Galerkin approximation of elliptic Dirichlet boundary control problems with random input data. The expectation of a tracking cost functional with the deterministic constrained control is minimized. Error estimates are derived for the control variable in $L^2(\partial \mathcal D)$-norm and state variable in $L^2(Ω\times\mathcal D)$-norm. To solve large linear systems, appropriate preconditioners are proposed for both unconstrained and constrained scenarios. To …

Distributed Resilient State Estimation and Control with Strategically Implemented Security Measures
Takumi Shinohara, Karl H. Johansson, Henrik Sandberg
https://arxiv.org/abs/2507.12052

Distributed Resilient State Estimation and Control with Strategically Implemented Security Measures
This paper addresses the problem of distributed resilient state estimation and control for linear time-invariant systems in the presence of malicious false data injection sensor attacks and bounded noise. We consider a system operator (defender) capable of deploying cybersecurity measures to counteract the sensor compromises. Although such measures enhance resilience against adversarial attacks, they may incur substantial costs; hence, it is crucial to select countermeasures to balance resilien…

Stochastic Optimal Control with Control-Dependent Diffusion and State Constraints: A Degenerate Elliptic Approach
Anderson O. Calixto, Bernardo Freitas Paulo da Costa, Glauco Valle
https://arxiv.org/abs/2508.04809

Stochastic Optimal Control with Control-Dependent Diffusion and State Constraints: A Degenerate Elliptic Approach
We study a stochastic optimal control problem with the state constrained to a smooth, compact domain. The control influences both the drift and a possibly degenerate, control-dependent dispersion matrix, leading to a fully nonlinear, degenerate elliptic Hamilton--Jacobi--Bellman (HJB) equation with a nontrivial Neumann boundary condition. Although these features have been studied separately, this work provides the first unified treatment combining them all. We establish that the optimal value f…

Norm Inequality for Perturbed Quantum Evolutions and Its Application to Grover's Algorithm
Kohei Kobayashi
https://arxiv.org/abs/2506.14230 https://

Norm Inequality for Perturbed Quantum Evolutions and Its Application to Grover's Algorithm
We investigate the impact of coherent control errors on quantum state evolution by deriving a general norm inequality based on Gronwall's lemma. This inequality provides an explicit upper bound on the deviation between an ideal quantum state and one subject to arbitrary coherent perturbations, including both time-dependent and time-independent cases. The framework is broadly applicable, requiring no assumptions about the detailed structure of the perturbation and full dynamics of the quantum sy…

Model Predictive Path-Following Control for a Quadrotor
David Leprich, Mario Rosenfelder, Mario Hermle, Jingshan Chen, Peter Eberhard
https://arxiv.org/abs/2506.15447

Model Predictive Path-Following Control for a Quadrotor
Automating drone-assisted processes is a complex task. Many solutions rely on trajectory generation and tracking, whereas in contrast, path-following control is a particularly promising approach, offering an intuitive and natural approach to automate tasks for drones and other vehicles. While different solutions to the path-following problem have been proposed, most of them lack the capability to explicitly handle state and input constraints, are formulated in a conservative two-stage approach,…

Control-affine Schr\"odinger Bridge and Generalized Bohm Potential
Alexis M. H. Teter, Abhishek Halder, Michael D. Schneider, Alexx S. Perloff, Jane Pratt, Conor M. Artman, Maria Demireva
https://arxiv.org/abs/2508.08511

Control-affine Schrödinger Bridge and Generalized Bohm Potential
The control-affine Schrödinger bridge concerns with a stochastic optimal control problem. Its solution is a controlled evolution of joint state probability density subject to a control-affine Itô diffusion with a given deadline connecting a given pair of initial and terminal densities. In this work, we recast the necessary conditions of optimality for the control-affine Schrödinger bridge problem as a two point boundary value problem for a quantum mechanical Schrödinger PDE with complex pot…

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
Aiham M. Rostom, Saeed Haddadi, Vladimir A. Tomilin
https://arxiv.org/abs/2508.13934 https://

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
We unveil the noncyclic Pancharatnam phase as a fundamental geometric criterion governing the optimal operation of quantum compression channels in postselected metrology. Harnessing this phase enables precise control over the interplay between orthogonal parameter sensitivity and parallel evolution in the meter state, thereby maximizing the quantum Fisher information per trial. Strikingly, fine-tuning the postselection parameter just below this optimal phase incurs substantial information loss,…

Sensitivity of Optimal Control Solutions and Quantities of Interest with Respect to Component Functions
Jonathan R. Cangelosi, Matthias Heinkenschloss
https://arxiv.org/abs/2506.10804

Sensitivity of Optimal Control Solutions and Quantities of Interest with Respect to Component Functions
This work establishes sensitivities of the solution of an optimal control problem (OCP) and a corresponding quantity of interest (QoI) to perturbations in a state/control-dependent component function that appears in the governing ODEs and the objective function. This extends existing OCP sensitivity results, which consider the sensitivity of the OCP solution with respect to state/control-independent parameters. It is shown that with Carathéodory-type assumptions, the Implicit Function Theorem …

Synthesizing Min-Max Control Barrier Functions For Switched Affine Systems
Sara Kamali, Guillaume O. Berger, Sriram Sankaranarayanan
https://arxiv.org/abs/2506.10296

Synthesizing Min-Max Control Barrier Functions For Switched Affine Systems
We study the problem of synthesizing non-smooth control barrier functions (CBFs) for continuous-time switched affine systems. Switched affine systems are defined by a set of affine dynamical modes, wherein the control consists of a state-based switching signal that determines the current operating mode. The control barrier functions seek to maintain the system state inside a control invariant set that excludes a given set of unsafe states. We consider CBFs that take the form of pointwise minima…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
N. J. Martin, A. J. Brash, A. Tomlinson, E. M. Sala, E. O. Mills, C. L. Phillips, R. Dost, L. Hallacy, P. Millington-Hotze, D. Hallett, K. A. O'Flaherty, J. Heffernan, M. S. Skolnick, A. M Fox, L. R. Wilson
https://arxiv.org/abs/2506.07951…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
Telecom-wavelength quantum dots (QDs) are emerging as a promising solution for generating deterministic single-photons compatible with existing fiber-optic infrastructure. Emission in the low-loss C-band minimizes transmission losses, making them ideal for long-distance quantum communication. In this work, we present the first demonstration of both Stark tuning and charge state control of individual InAs/InP QDs operating within the telecom C-band. These QDs are grown by droplet epitaxy and emb…

On the factorization of matrices into products of positive definite ones
Mahmoud Abdelgalil, Tryphon T. Georgiou
https://arxiv.org/abs/2507.12560 https://

On the factorization of matrices into products of positive definite ones
The present work revisits and provides a new approach on a result by Charles Ballantine, on the factorization of a square matrix with positive determinant into a product of positive definite factors. {\em Ballantine-type} factorizations, that bound the number of positive definite factors, proved central in solving a basic, yet elusive control problem--the strong controllability of a linear system via control in the form of state feedback. Ballantine's result transcends control engineering, and …

Coherent phase control of two-color continuous variable entangled light
Andrea Grimaldi, Valeriy Novikov, T\'ulio Brito Brasil, Eugene Simon Polzik
https://arxiv.org/abs/2508.03303

Coherent phase control of two-color continuous variable entangled light
A continuous variable Einstein-Podolsky-Rosen (EPR) state is a resource for secure quantum communication and distributed quantum sensing. Here we present a technique for coherent control of the two-color EPR state generated by a frequency nondegenerate optical parametric oscillator. The scheme allows for robust control of the homodyne detection of each of the two EPR quantum fields separated by 200 nanometers. We apply our control scheme to stabilize and characterize a strong entangled state of…

Near optimal controls for partially observed stochastic linear quadratic problems
Jingrui Sun, Jiaqiang Wen, Jie Xiong, Wen Xu
https://arxiv.org/abs/2506.11778

Near optimal controls for partially observed stochastic linear quadratic problems
In this article, we consider a stochastic linear quadratic control problem with partial observation. A near optimal control in the weak formulation is characterized. The main features of this paper are the presence of the control in the diffusion term of the state equation, the circular dependence between the control process and the filtration generated by the observation, and the observation process contains an unbounded drift term. We address these difficulties by first restricting the contro…

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 …

Parallel Branch Model Predictive Control on GPUs
Luyao Zhang, Chenghuai Lin, Sergio Grammatico
https://arxiv.org/abs/2506.13624 https://

Parallel Branch Model Predictive Control on GPUs
We present a parallel GPU-accelerated solver for branch Model Predictive Control problems. Based on iterative LQR methods, our solver exploits the tree-sparse structure and implements temporal parallelism using the parallel scan algorithm. Consequently, the proposed solver enables parallelism across both the prediction horizon and the scenarios. In addition, we utilize an augmented Lagrangian method to handle general inequality constraints. We compare our solver with state-of-the-art numerical …

Noise-Canceling Quantum Feedback: non-Hermitian Dynamics with Applications to State Preparation and Magic State Distillation
Tathagata Karmakar, Philippe Lewalle, Yipei Zhang, K. Birgitta Whaley
https://arxiv.org/abs/2507.05611

Noise-Canceling Quantum Feedback: non-Hermitian Dynamics with Applications to State Preparation and Magic State Distillation
Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. We here consi…

On Exact Solutions to the Linear Bellman Equation
David Ohlin, Richard Pates, Murat Arcak
https://arxiv.org/abs/2506.15527 https://ar…

On Exact Solutions to the Linear Bellman Equation
This paper presents sufficient conditions for optimal control of systems with dynamics given by a linear operator, in order to obtain an explicit solution to the Bellman equation that can be calculated in a distributed fashion. Further, the class of Linearly Solvable MDP is reformulated as a continuous-state optimal control problem. It is shown that this class naturally satisfies the conditions for explicit solution of the Bellman equation, motivating the extension of previous results to semili…

When are safety filters safe? On minimum phase conditions of control barrier functions
Jason J. Choi, Claire J. Tomlin, Shankar Sastry, Koushil Sreenath
https://arxiv.org/abs/2508.07684

When are safety filters safe? On minimum phase conditions of control barrier functions
In emerging control applications involving multiple and complex tasks, safety filters are gaining prominence as a modular approach to enforcing safety constraints. Among various methods, control barrier functions (CBFs) are widely used for designing safety filters due to their simplicity, imposing a single linear constraint on the control input at each state. In this work, we focus on the internal dynamics of systems governed by CBF-constrained control laws. Our key observation is that, althoug…

State constrained stochastic optimal control of a PV system with battery storage via Fokker-Planck and Hamilton-Jacobi-Bellman equations
Alfredo Berm\'udez, Iago Pad\'in
https://arxiv.org/abs/2506.11765

State constrained stochastic optimal control of a PV system with battery storage via Fokker-Planck and Hamilton-Jacobi-Bellman equations
With the growing global emphasis on sustainability and the implementation of contemporary environmental policies, the penetration of renewable energy sources has significantly increased --primarily due to their inexhaustible nature. In this context, integrating photovoltaic (PV) modules with energy storage systems offers a means to mitigate the inherent variability of solar energy. This paper proposes an optimal methodology for power management and market bidding strategies tailored to PV power…

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…

Nonlinear Control of a Quadrotor UAV Using Backstepping-Based Sliding Mode Technique
Thien Nhan Vo
https://arxiv.org/abs/2506.14195 https://

Nonlinear Control of a Quadrotor UAV Using Backstepping-Based Sliding Mode Technique
This paper presents the development of a sliding mode controller using the backstepping approach. The controller is employed to synthesize tracking errors and Lyapunov functions. A novel state-space representation is formulated by incorporating the dynamics of the quadrotor and accounting for non-holonomic constraints. The proposed sliding mode controller effectively addresses system nonlinearities and improves tracking of predefined trajectories. Simulation results are presented graphically to…

Approximate Controllability Problems for the Heat Equation in a Half-Plane Controlled by the Dirichlet Boundary Condition with a Bounded Control
Larissa Fardigola, Kateryna Khalina
https://arxiv.org/abs/2506.10466

Approximate Controllability Problems for the Heat Equation in a Half-Plane Controlled by the Dirichlet Boundary Condition with a Bounded Control
In the paper, the problems of approximate controllability are studied for the control system $w_t=Δw$, $w(0,x_2,t)=u(x_2,t)$, $x_1\in\mathbb R_+=(0,+\infty)$, $x_2\in\mathbb R$, $t\in(0,T)$, where $u$ is a control belonging to a special subset of $L^\infty(\mathbb R\times (0,T))\cap L^2(\mathbb R\times (0,T))$. It is proved that each initial state belonging to $L^2(\mathbb R_+\times\mathbb R)$ is approximately controllable to an arbitrary end state belonging to $L^2(\mathbb R_+\times\mathbb R)…

Robust Contextual State Estimation with Limited Measurement Data
J. G. De la Varga, J. M. Morales, S. Pineda
https://arxiv.org/abs/2507.08767 https://

Robust Contextual State Estimation with Limited Measurement Data
The increasing integration of distributed energy resources (DERs) is transforming power systems into complex, decentralized networks, particularly at the distribution level, where active distribution networks (ADNs) introduce new challenges for monitoring and control. Accurate state estimation in these systems is complicated by limited and heterogeneous measurement infrastructures, where real-time data from supervisory control and data acquisition (SCADA) and micro-phasor measurement units ($μ…