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Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

At least 469 records · Page 26Linked to original sources

arXiv2026

On a cross-coupling of Rulkov neural maps

We introduce a novel coupling of Rulkov neural maps, proposing a heuristic biological interpretation for the transition to non-small values of the perturbations acting on the slow variables. We analytically prove that the coupling of two identical neurons preserves the emergence of Devaney chaos through the existence of a generalized snap-back repeller, provided that a snap back repeller exists for the original system. We present numerical simulations for the coupling of two different neurons showing the arising of a potential global strange attractor, whose fractal structure is strongly suggested by the computation of a non-integer Kaplan-Yorke dimension. Furthermore, we perform standard numerical studies concerning time series, Lyapunov exponents spectra, bifurcation diagrams and basins of attraction. Finally, we briefly propose a generalization of the coupling to an arbitrary number of neurons.

nlin.CD↗

arXiv2026

Quantum many-body scars with tunable entanglement and Hamiltonian inverse design from ZX-calculus

Diagrammatic languages such as ZX-calculus provide compact and intuitive descriptions of quantum processes and have become established tools for circuit simplification, verification, and compilation. However, their potential as a framework for constructing many-body states and the Hamiltonians that host them remains largely unexplored. Here, we introduce families of fractal many-body states obtained from ZX-diagrams based on the Sierpiński triangle and Sierpiński carpet. By construction, the underlying graph connectivity imposes atypical subvolume-law minimum-cut upper bounds on entanglement: at most logarithmic scaling for the triangle family and sublinear power-law for the carpet family. By adjusting the free parameters of the ZX-diagram construction, we can tune the actual entanglement scaling: we demonstrate both area-law and logarithmic scaling for the triangle, and both log law and power-law for the carpet. Additionally, their local observables retain fractal-like spatial structure, identifying these states as natural candidates for atypical eigenstates in otherwise thermalizing systems. For the triangle family, we combine parent-Hamiltonian methods, insights from ZX-calculus, and local ZX identities that certify exact annihilation of the target state, producing frustration-free Hamiltonians whose terms admit simple representations in the same diagrammatic language as the states themselves. We then construct a local deformation that produces chaotic level statistics while embedding the fractal ZX state in the bulk of the energy spectrum as an exact quantum many-body scar. Our results demonstrate, through this explicit construction, that ZX-calculus can serve as a framework for Hamiltonian inverse design, in which quantum many-body scars, their local annihilators, and the chaotic Hamiltonians embedding them can be constructed and related through a set of graphical identities.

quant-ph↗

arXiv2026

Fully Convergent Projection-based Methods with Momentum under Nonconvex Geometric Constraints

Nonlinear optimization problems with complicated, nonconvex, yet geometrically structured constraints can be tackled by projected-gradient methods: under weak regularity assumptions, these approaches were recently proved to possess convergence properties to the strongest stationarity conditions. In this work, we show how momentum terms, commonly used in nonlinear optimization to speed up the convergence process, can be integrated within this algorithmic framework without harming convergence guarantees. Preliminarily, we highlight an intrinsic issue induced by the direct replacement of the negative gradient with a general descent direction within the projected approach. Then, we present suitable backtracking mechanisms for the pre-projection step, allowing us to integrate momentum terms in the direction. By this technique, we can specifically ensure, without any smoothness assumptions, convergence to Mordukhovich stationarity as long as the base directions asymptotically revert to the negative gradient for small stepsizes; moreover, if the base search direction reverts exactly to the negative gradient for the smallest steps, the algorithm is proved to converge to Bouligand and Proximally stationary points, with and without (local) smoothness assumptions respectively. Finally, the proposed procedure is numerically tested on some classes of problems, namely, sparsity and bounded-rank constrained problems; the results indicate that the proposed method is computationally effective, taking advantage of the additional information provided by the momentum term.

math.OC↗

arXiv2026

Exact Nambu-Goto 4-Surfaces and Octonionic Cayley Selection in 8D

We study four-dimensional Euclidean Nambu-Goto embeddings in eight dimensions in the presence of the Spin(7)-invariant four-form constructed from octonionic structure constants. A broad class of holomorphic maps is shown by direct substitution to satisfy the nonlinear Nambu-Goto Euler-Lagrange equations. For a compatible Spin(7) structure these same embeddings satisfy the Cayley calibration condition. The calculation therefore gives a discrete octonionic selection rule for the relative orientation of an exact Nambu-Goto 4-surface and the Spin(7) structure of the target.

hep-th↗

arXiv2026

Off-shell Higgs boson measurements: Yukawa couplings, self-coupling, compositeness, and width

Measurements of Higgs boson production in the off-shell region are presented, using the four-lepton decay channel. Data from proton-proton collisions at the CERN LHC, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb$^{-1}$ at a center-of-mass energy of 13 TeV, are utilized. The first direct test of composite Higgs boson models is performed, with a lower limit on the compositeness scale $Λ_\mathrm{H}$ set at 870 GeV at the 95% confidence level. Tests of gluon-fusion production within the standard model effective field theory framework are performed. The first constraint on the Higgs boson self-coupling in the off-shell region is obtained. By combining on- and off-shell measurements, the analysis sets the tightest constraints to date on light-quark Yukawa couplings, while relaxing assumptions such as the bound on the Higgs boson coupling to vector bosons, thereby providing more model-independent results. Constraints on the Higgs boson width are provided while accounting for a range of beyond-the-standard-model effects, including both light and heavy particles in the gluon-fusion production loop, as well as modified couplings to vector bosons. A combined analysis of the H$\to$ZZ and PH$\to$WW channels is performed to improve sensitivity to the Higgs boson width, yielding $Γ_\mathrm{H}$ = 5.1$^{+2.0}_{-1.8}$ MeV. The scenario of no off-shell Higgs boson production is excluded at a confidence level exceeding 5 standard deviations.

hep-ex↗

arXiv2026

Experimentation and Commitment under Reward Shifts

Decision-makers in learning environments face a dilemma when their short-term optimal actions may not favor their long-term benefits the most. To understand the fundamental tradeoff behind the dilemma, we study adaptive experimentation with post-commitment reward shifts. During an experiment phase, the decision-maker may adaptively test multiple options; during a subsequent commitment phase, the decision-maker must commit to a single option, whose reward may differ from its pre-commitment reward. We propose the Reserved Arm Eliminations for Commitment (RAEC) algorithm, which reserves a predetermined portion of the experiment phase to identify the best post-shift option while using the remaining rounds to minimize short-run regret. We establish regret upper bounds for RAEC across all parameter regimes and matching minimax lower bounds, providing a tight characterization of the cost of balancing short-term performance and long-term commitment. A key implication is that deciding in advance how much of the experiment phase to reserve for the commitment decision is sufficient to achieve the best possible worst-case regret rate; adapting this amount as more data are observed does not improve the rate. We further study extensions with structural knowledge of reward shifts and with concave commitment rewards and portfolio choice. Numerical experiments confirm that our proposed algorithms achieve the regret predicted by our theory and outperform other baselines.

cs.LG↗

arXiv2026

BC-NMPC: Battery-Constrained NMPC with Propulsion Prediction and Replanning for High-Speed Flight

Trajectory tracking performance of Uncrewed Aerial Vehicles (UAVs) degrades during an agile high-speed flight due to the depletion of the battery and subsequent loss of maximum available thrust. In applications such as drone racing, this leads to a failure to complete the race due to possible collisions with obstacles. In this paper, we present a novel method for integrating battery and propulsion system models into a Nonlinear Model Predictive Controller (NMPC) framework to enable real-time prediction of the voltage, current, power, and maximum available thrust of the platform. Our proposed approach achieves lower trajectory tracking error as a result of its real-time thrust awareness, and with the help of trajectory replanning, it allows the UAV to fly in time-optimal regime throughout the mission. The accuracy of this proposed model was verified in real-world flight experiments, while the effectiveness of the replanning algorithm was evaluated in simulation. By the end of the battery capacity, compared to an unaware controller, our novel controller achieved a 25% reduction in mean position error without replanning, and an 88 % reduction with replanning.

cs.RO↗

arXiv2026

Simulation-consistent Estimation of the Marginal Likelihood for Block Models

We propose a methodology for computing marginal likelihoods for block models. The proposed estimator computes the marginal likelihood from Markov chain Monte Carlo (MCMC) samples and is simulation-consistent, even when the size of the dataset is fixed. Moreover, it is asymptotically normal, of finite variance, invariant to label switching and can be computed efficiently, even for models with an arbitrarily large number of components. We evaluate the method through simulation studies in settings where the true marginal likelihood is available analytically. Finally, we apply the approach to a social network dataset based on the 2023 United Nations Climate Change Conference (COP28) and discuss the resulting insights.

stat.ME↗

arXiv2026

The mathematical theory of photomultiplier tube calibration

In this technical note we describe the main features of the mathematical theory of photomultiplier tube (PMT) calibration. Attention was paid to explain the various arguments and concepts in a simple and pedagogical manner that everybody understands. The basic operational principles of a PMT are discussed from a theoretical standpoint. The essential steps of its function (photoconversion, focusing, multiplication, etc.) are laid down together with the mathematical schemes necessary to model the charge output of a PMT when illuminated by a faint poissonian light source. In case of important omissions we direct the reader to some of the standard references. The most common numerical methods, used to calculate the charge amplification function $S_R(x)$, are also presented. As an example, we plot $S_R(x)$ utilizing a gamma function model for the single photoelectron (SPE) response and showcase its main characteristics. The basic techniques for gain calibration are also introduced, and we probed their precision using toy Monte Carlo data. Additionally, data from a Hamamatsu R1408 PMT were analyzed. Finally, we show how the presence of soft charge component can affect the results of gain determination. We conclude this report with some general comments regarding \emph{in situ} calibration of large-scale detectors. We hope that this document can serve as a reference for students and young researchers that want to learn more about the theory of PMT calibration.

hep-ex↗

arXiv2026

Quantum incapacity from observable shadows

Quantum communication is ruled out when an eavesdropper can reconstruct the receiver's state. Yet states are operationally specified by measurement statistics, raising a sharper question: can access to every expectation value destroy communication? We show that it can. We call unbiased, variance-nonincreasing reconstruction under arbitrary reference extensions \emph{complete observable shadowing} and prove that it forces unassisted private and quantum capacities to vanish. An explicit qutrit channel realizes this mechanism while being neither antidegradable nor PPT, resolving the long-standing questions of whether quantum capacity can vanish outside those two classes and whether antidegradability is the only route to zero private capacity. Notably, it superactivates every finite-dimensional channel with zero quantum but positive private capacity. Statistical access can therefore preclude standalone communication without erasing latent coherent utility.

quant-ph↗

arXiv2026

Gravitational wave constraints on corrections to Bekenstein-Hawking Area Formula in classical F(R) gravity and quantum GR : implications for theory parameters

This contribution considers constraints from analyses of gravitational wave data from binary black hole coalescence, on possible corrections to the Bekenstein-Hawking Area Formula for black hole entropy. Most recent analyses of gravitational wave data from the LVK Consortium appear to confirm the Hawking Area Theorem for black holes at a $5 σ$ accuracy, for the `loudest' signal (SNR of the order of $80$) of binary black hole merger inherent in the recent observation GW250114. Amalgamating this result with Bekenstein's ideas of black hole entropy and the generalized second law of thermodynamics, we constrain leading inverse area corrections for large horizon area spherical black hole solutions of classical $F(R)$ gravity, using the Wald entropy function formalism. The implementation of the observational constraints entails the notion of `absolute consistency' which we introduce and contrast with `relative consistency'. This absolute consistency criterion is shown to relate some of the parameters of $F(R)$ gravity. Next we consider leading quantum general relativistic corrections to the Area formula, arising both from the non-perturbative matter-free Loop Quantum Gravity and matter-dependent, perturbative Entanglement entropy approaches. Combining the leading logarithmic corrections in horizon area (for large areas) from both approaches, and imposing absolute consistency with the observational validation of the Area Theorem, is shown to lead to significant restrictions on the spin and number of species of Beyond Standard Model spectrum of elementary particles, some of which are often assumed to be Dark Matter candidates.

gr-qc↗

arXiv2026

Measurement of the fragmentation properties of jets containing $Υ$(nS) mesons in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the fragmentation properties of jets containing $Υ$(nS) mesons using proton-proton collision data at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$, is presented. The $Υ$(nS) mesons associated with jets are reconstructed via their decays producing pairs of oppositely charged muons. The longitudinal and transverse projections of the momenta of the $Υ$(nS) mesons along the momenta of the corresponding jets are studied. The results are compared with Monte Carlo predictions, including recent developments in the modelling of quarkonia production in parton showers. The description of the data by these Monte Carlo predictions is found to be unsatisfactory, leaving room for improvements in the modelling of such processes.

hep-ex↗

arXiv2026

Quenched fluctuation-induced force arising from polarization disorder

We investigate the zero-temperature behavior of the fluctuation force induced by the quenched disorder of electric dipoles frozen randomly into a material. Examples of such materials include relaxor ferroelectrics. In terms of the setup and geometry, we focus on a layered system comprising two coplanar semi-infinite slabs separated by a distance $\ell$ as well as a system comprising a neutral atom in the vacuum located at a distance $\ell$ above the surface of a semi-infinite slab. For both systems, we consider the cases where the quenched random dipolar disorder occurs inside the bulk as well as on the surface of the slabs. In all of these cases, we find that the bulk (surface) dipolar disorder-induced force grows with the mean square quenched electric dipole moment per unit volume (area). The bulk (surface) dipolar disorder-induced pressure between two semi-infinite single-layered slabs decays with $\ell^{-3}$ ($\ell^{-4}$), whereas the bulk (surface) dipolar disorder-induced force on an atom in the vacuum near a slab containing the disorder decays with $\ell^{-4}$ ($\ell^{-5}$). We also find that the quenched dipolar disorder-induced force between two coplanar slabs can be repulsive in a three-layered dielectric system that obeys a zero-frequency analogue of the Dzyaloshinskii-Lifshitz-Pitaevskii condition, and serve to enhance the ``nanolevitation effect" if the latter is present in the disorder-free system.

cond-mat.dis-nn↗

arXiv2026

Robust quantum state certification and uncertainty principles for total influence

We show that nonadaptive single-qubit Pauli measurements suffice to test whether an unknown $n$-qubit state $ρ$ is $\varepsilon$-close to or $O(\varepsilon)$-far from an ideal target state $|ψ\rangle$, for all but a $2^{-Ω(n)}$ fraction of target states. The test uses $O(\varepsilon^{-2}\log(1/δ))$ copies of $ρ$ to achieve confidence $1-δ$, which is information-theoretically optimal even among protocols with arbitrary joint measurements. The main technical innovation is an uncertainty principle for weighted generalizations of the total influence of Boolean functions. As a simple example, the unweighted variant states that $\mathbf{Inf}[f]+\mathbf{Inf}[\widehat{f}] = Ω(n)$, which is a natural hypercube analogue of the Heisenberg uncertainty principle (here $\widehat{\,\cdot\,}$ denotes the $2^{-n/2}$-normalized Fourier transform). The weighted case generalizes $\mathbf{Inf}[\,\cdot\,]$ and $\mathbf{Inf}[\,\widehat{\,\cdot\,}\,]$ to Dirichlet energies associated with Glauber dynamics for certain dual measures on the cube.

quant-ph↗

arXiv2026

Sharp Bounds on Ground State Energy of the SYK Model

We study the Sachdev-Ye-Kitaev (SYK) Hamiltonian $H_{\operatorname{SYK}}$ on $n$ Majorana modes with $k$-body interactions, and prove that $\mathbb{E}\|H_{\operatorname{SYK}}\|_{\operatorname{op}} = (1 - o(1))\cdot\sqrt{2n}/k$ for super-constant $k\leq o(\sqrt{n})$, where the expectation is over the disorder variables in the Hamiltonian. This confirms predictions due to Garcia-Garcia, Jia and Verbaarschot and answers a question posed by Feng, Tian, and Wei. Our results extend to the sparse SYK Hamiltonian. As a corollary, we obtain that a dissipative quantum algorithm due to Basso, Chen, and Dalzell provably computes the ground state energy of the SYK Hamiltonian up to an $O(1)$-multiplicative factor for all $k < \sqrt{n}/4$. Our key technical idea is identifying an explicit, deterministic linear operator $\mathsf{x}$ such that a fixed quadratic form of $\mathsf{x}^{2\ell}$ exactly equals the expected trace moments of the SYK Hamiltonian for every $n$ and $k$. This linear operator can be naturally viewed as a twisted model of bosons on the space of hyperedges of a hypergraph. The problem thus reduces to identifying the spectral edge of $\mathsf{x}$, which we show is dominated by the spectrum of a natural ${n \choose k}$-dimensional matrix from the Johnson scheme and is straightforward to compute using known results. To show that our bound is sharp, we construct a witness state with a large quadratic form on $\mathsf{x}$ and transform it into a certificate of a lower bound on the largest quadratic form on $H_{\operatorname{SYK}}$. Beyond the SYK Hamiltonian, our techniques also apply to the $k-$local quantum spin glass (QSG), yielding $\mathbb{E}\|H_{k-\operatorname{QSG}}\|_{\operatorname{op}}\leq O(\sqrt{n/k})$ for all $1\leq k\leq\sqrt{n}/2$, thus improving the standard $O(\sqrt{n})$ bound by a factor of $\sqrt{k}$.

quant-ph↗

arXiv2026

Comparison of a Parametric Physics-Informed Neural Network and a Tensorial Reduced-Order Model for the Shallow-Water Dam-Break Problem

We develop two parametric data-driven reduced models: a physics-informed neural network (PINN) and a non-intrusive tensorial reduced-order model (TROM), and apply both approaches to the parametrized one-dimensional shallow-water dam-break problem. Neither reduced model requires time integration: both learn a direct parameter-to-solution map from space, time, and dam-break parameters to the physical state, with the PINN providing predictions at arbitrary times and the TROM reconstructing solutions at the stored snapshot times. In addition, we demonstrate that it is essential to introduce shock-aware collocation to improve the robustness of the PINN model.

math.NA↗

arXiv2026

SKILL-KD: Contrastive Skill Distillation for LLM Agents

Skill-based prompting has become a practical mechanism for improving LLM agents, yet existing methods often treat skills as summaries of the agent's own experience or of successful demonstrations. This creates a mismatch for weaker student agents. A failed trajectory may not reveal the missing knowledge or strategy, while a teacher trajectory may be too implicit to internalize. We propose SKILL-KD, a contrastive skill distillation framework that treats skills as an explicit distillation medium between agents of different capabilities. Given a student failure and the teacher trajectory on the same task, SKILL-KD distills their actionable discrepancy into a textual skill patch, evaluates it by re-running the student, and iteratively refines it when the student still fails. To prevent skill drift from repeated local updates, SKILL-KD maintains trace-linked edit histories and performs Drift-Aware Skill Consolidation to decide whether each patch is added, merged, or skipped. Across five agent benchmarks and two student settings, SKILL-KD consistently improves frozen student agents over fixed-model adaptation baselines.

cs.AI↗

arXiv2026

A measurement of the Higgs boson mass in the diphoton decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the Higgs boson mass in the diphoton decay channel is performed using proton-proton collision data at a center-of-mass energy of 13 TeV. The data set recorded with the CMS detector between 2016 and 2018 is used, corresponding to an integrated luminosity of 138 fb$^{-1}$. A refined detector calibration and new analysis techniques are employed to improve the precision of the results compared to earlier measurements. The Higgs boson mass is measured to be $m_\mathrm{H}$ = 125.13 $\pm$ 0.15 GeV = 125.13 $\pm$ 0.10 (stat) $\pm$ 0.12 (syst) GeV. In addition, a combination with the mass measurement at center-of-mass energies of 7 and 8 TeV in the diphoton final state is performed resulting in $m_\mathrm{H}$ = 125.06 $\pm$ 0.14 GeV = 125.06 $\pm$ 0.09 (stat) $\pm$ 0.11 (syst) GeV.

hep-ex↗