Search

Learning-based approaches for constructing Control Barrier Functions (CBFs) are increasingly being explored for safety-critical control systems. However, these methods typically require complete retraining when applied to unseen environments, limiting their adaptability. To address this, we propose a self-supervised deep operator learning framework that learns the mapping from environmental parameters to the corresponding CBF, rather than learning the CBF directly. Our approach leverages the residual of a parametric Partial Differential Equation (PDE), where the solution defines a parametric CBF approximating the maximal control invariant set. This framework accommodates complex safety constraints, higher relative degrees, and actuation limits. We demonstrate the effectiveness of the method through numerical experiments on navigation tasks involving dynamic obstacles., Comment: 63rd IEEE Conference on Decision and Control (CDC)

When using AI to detect signs of depressive disorder, AI models habitually draw preemptive conclusions. We theorize that using chain-of-thought (CoT) prompting to evaluate Patient Health Questionnaire-8 (PHQ-8) scores will improve the accuracy of the scores determined by AI models. In our findings, when the models reasoned with CoT, the estimated PHQ-8 scores were consistently closer on average to the accepted true scores reported by each participant compared to when not using CoT. Our goal is to expand upon AI models' understanding of the intricacies of human conversation, allowing them to more effectively assess a patient's feelings and tone, therefore being able to more accurately discern mental disorder symptoms; ultimately, we hope to augment AI models' abilities, so that they can be widely accessible and used in the medical field.

We present a deep X-Shooter rest-frame UV to optical spectral analysis of the heavily reddened quasar, ULASJ2315+043 at z=2.566, known to reside in a major-merger host galaxy. The rest-frame optical is best-fit by a dust-reddened quasar E(B-V)_QSO = 1.55 with black-hole mass log10(Hbeta, MBH [M_sol]) = 10.26 +\- 0.05, bolometric luminosity L_Bol = 10^48.16 erg s^-1 and Eddington-scaled accretion rate log10(\lambda_Edd) = -0.19. We find remarkable similarities between ULASJ2315+043 and the high-redshift Little Red Dots (LRDs). The rest-frame UV cannot be explained by a dusty quasar component alone and requires an additional blue component consistent with either a star-forming host galaxy or scattered AGN light. We detect broad high-ionisation emission lines in the rest-UV, supporting the scattered light interpretation for the UV excess. The scattering fraction represents just 0.05% of the total luminosity of ULASJ2315+043. Analysis of the mid infra-red SED suggests an absence of hot dust on torus-scales similar to what is observed for LRDs. The obscuring medium is therefore likely on galaxy scales. We detect narrow, blueshifted associated absorption line systems in CIV, NV, SiIV and SiIII. There is evidence for significant high-velocity (>1000 km s^-1) outflows in both the broad and narrow line regions as traced by CIV and [OIII] emission. The kinetic power of the [OIII] wind is e_ion = 10^44.61 erg s^-1 ~ 0.001 L_Bol. ULASJ2315+043 is likely in an important transition phase where star formation, black-hole accretion and multi-phase gas flows are simultaneously occurring., Comment: Accepted to MNRAS: 13th Aug 2024. 18 pages, 12 figures

We present a study of the molecular gas in five closely-spaced ($R_{\perp}<20$ kpc) dual quasars ($L_{\rm bol}\gtrsim10^{44}~\mathrm{erg~s}^{-1}$) at redshifts $0.4

We present a method for the computation of the Generalized Alignment Index (GALI), a fast and effective chaos indicator, using a multi-particle approach that avoids variational equations. We show that this approach is robust and accurate by deriving a leading-order error estimation for both the variational (VM) and the multi-particle (MPM) methods, which we validate by performing extensive numerical simulations on two prototypical models: the two degrees of freedom H\'enon-Heiles system and the multidimensional $\beta$-Fermi-Pasta-Ulam-Tsingou chain of oscillators. The dependence of the accuracy of the GALI on control parameters such as the renormalization time, the integration time step and the deviation vector size is studied in detail. We test the MPM implemented with double precision accuracy ($\varepsilon \approx 10^{-16}$) and find that it performs reliably for deviation vector sizes $d_0\approx \varepsilon^{1/2}$, renormalization times $\tau \lesssim 1$, and relative energy errors $E_r \lesssim \varepsilon^{1/2}$. These results hold for systems with many degrees of freedom and demonstrate that the MPM is a robust and efficient method for studying the chaotic dynamics of Hamiltonian systems. Our work makes it possible to explore chaotic dynamics with the GALI in a vast number of systems by eliminating the need for variational equations., Comment: 17 pages, 13 figures, Accepted for publication in Communications in Nonlinear Science and Numerical Simulation

This paper is the first attempt at providing a holistic view of the Chrome Web Store (CWS). We leverage historical data provided by ChromeStats to study global trends in the CWS and security implications. We first highlight the extremely short life cycles of extensions: roughly 60% of extensions stay in the CWS for one year. Second, we define and show that Security-Noteworthy Extensions (SNE) are a significant issue: they pervade the CWS for years and affect almost 350 million users. Third, we identify clusters of extensions with a similar code base. We discuss how code similarity techniques could be used to flag suspicious extensions. By developing an approach to extract URLs from extensions' comments, we show that extensions reuse code snippets from public repositories or forums, leading to the propagation of dated code and vulnerabilities. Finally, we underline a critical lack of maintenance in the CWS: 60% of the extensions in the CWS have never been updated; half of the extensions known to be vulnerable are still in the CWS and still vulnerable 2 years after disclosure; a third of extensions use vulnerable library versions. We believe that these issues should be widely known in order to pave the way for a more secure CWS., Comment: Published in ACM AsiaCCS 2024

Understanding the links between different phases of outflows from active galactic nuclei is a key goal in extragalactic astrophysics. Here we compare [OIII] $\lambda\lambda$4960,5008 outflow signatures in quasars with and without Broad Absorption Lines (BALs), aiming to test how the broad absorption troughs seen in the rest-frame ultraviolet are linked to the narrow line region outflows seen in the rest-frame optical. We present new near-infrared spectra from Magellan/FIRE which cover [OIII] in 12 quasars with 2.1 < z < 2.3, selected to have strong outflow signatures in CIV $\lambda$1550. Combining with data from the literature, we build a sample of 73 BAL, 115 miniBAL and 125 non-BAL QSOs with 1.5 < z < 2.6. The strength and velocity width of [OIII] correlate strongly with the CIV emission properties, but no significant difference is seen in the [OIII] emission-line properties between the BALs, non-BALs and miniBALs once the dependence on CIV emission is taken into account. A weak correlation is observed between the velocities of CIV BALs and [OIII] emission, which is accounted for by the fact that both outflow signatures correlate with the underlying CIV emission properties. Our results add to the growing evidence that BALs and non-BALs are drawn from the same parent population and are consistent with a scenario wherein BAL troughs are intermittent tracers of persistent quasar outflows, with a part of such outflow becoming optically thick along our line-of-sight for sporadic periods of time within which BALs are observed., Comment: 14 pages, 6 figures. Accepted for publication in MNRAS

Residential fixed broadband internet access in the United States (US) has long been distributed inequitably, drawing significant attention from researchers and policymakers. This paper evaluates the efficacy of the Connect America Fund (CAF), a key policy intervention aimed at addressing disparities in US internet access. CAF subsidizes the creation of new regulated broadband monopolies in underserved areas, aiming to provide comparable internet access, in terms of price and speed, to that available in urban regions. Oversight of CAF largely relies on data self-reported by internet service providers (ISPs), which is often questionable. We use the broadband-plan querying tool (BQT) to curate a novel dataset that complements ISP-reported information with ISP-advertised broadband plan details (download speed and monthly cost) on publicly accessible websites. Specifically, we query advertised broadband plans for 687k residential addresses across 15 states, certified as served by ISPs to regulators. Our analysis reveals significant discrepancies between ISP-reported data and actual broadband availability. We find that the serviceability rate-defined as the fraction of addresses ISPs actively serve out of the total queried, weighted by the number of CAF addresses in a census block group-is only 55%, dropping to as low as 18% in some states. Additionally, the compliance rate-defined as the weighted fraction of addresses where ISPs actively serve and advertise download speeds above the FCC's 10 Mbps threshold-is only 33%. We also observe that in a subset of census blocks, CAF-funded addresses receive higher broadband speeds than their monopoly-served neighbors. These results indicate that while a few users have benefited from this multi-billion dollar program, it has largely failed to achieve its intended goal, leaving many targeted rural communities with inadequate or no broadband connectivity.

We present new frontiers in the modelling of the spectral energy distributions (SED) of active galaxies by introducing the radio-to-X-ray fitting capabilities of the publicly available Bayesian code AGNfitter. The new code release, called AGNfitter-rx, models the broad-band photometry covering the radio, infrared (IR), optical, ultraviolet (UV) and X-ray bands consistently, using a combination of theoretical and semi-empirical models of the AGN and host galaxy emission. This framework enables the detailed characterization of four physical components of the active nuclei: the accretion disk, the hot dusty torus, the relativistic jets/core radio emission, and the hot corona; alongside modeling three components within the host galaxy: stellar populations, cold dust, and the radio emission from the star-forming regions. Applying AGNfitter-rx to a diverse sample of 36 AGN SEDs at z<0.7 from the AGN SED ATLAS, we investigate and compare the performance of state-of-the-art torus and accretion disk emission models on fit quality and inferred physical parameters. We find that clumpy torus models that include polar winds and semi-empirical accretion disk templates including emission line features significantly increase the fit quality in 67% of the sources, by effectively reducing by $2\sigma$ fit residuals in the $1.5-5 \mu \rm m$ and $0.7 \mu \rm m$ regimes.We demonstrate that, by applying AGNfitter-rx on photometric data, we are able to estimate inclination and opening angles of the torus, consistent with spectroscopic classifications within the AGN unified model, as well as black hole mass estimates in agreement with virial estimates based on H$\alpha$. The wavelength coverage and the flexibility for the inclusion of state-of-the-art theoretical models make AGNfitter-rx a unique tool for the further development of SED modelling for AGNs in present and future radio-to-X-ray galaxy surveys., Comment: 20 pages, 10 figures, Accepted for publication by A&A

In this work, we demonstrate that the synergetic interplay of topology, nonreciprocity and nonlinearity is capable of unprecedented effects. We focus on a nonreciprocal variant of the Su-Shrieffer-Heeger chain with local Kerr nonlinearity. We find a continuous family of non-reciprocal edge solitons (NESs) emerging from the topological edge mode, with near-zero energy, in great contrast from their reciprocal counterparts. Analytical results show that this energy decays exponentially towards zero when increasing the lattice size. Consequently, despite the absence of chiral symmetry within the system, we obtain zero-energy NESs, which are insensitive to growing Kerr nonlinearity. Even more surprising, these zero-energy NESs also persist in the strong nonlinear limit. Our work may enable new avenues for the control of nonlinear topological waves without requiring the addition of complex chiral-preserving nonlinearities., Comment: 5 figures

The discovery of Higgs mechanism within the context of spontaneous symmetry breaking has offered a new perspective on the early time cosmic inflation and also on the relationship between elementary particles and dark energy, believed to drive the universe's accelerating expansion. We suggest an inflation scenario driven by the Higgs boson within the framework of unimodular gravity, where the Higgs field acts as the inflaton and has a significant non-minimal coupling to the gravity. We present a detailed analysis of the problem in the Jordan and then Einstein frame for a unimodular Higgs inflation, followed by a comparison of our findings with the Cosmic Microwave Background observations made by the Planck Collaboration and other joint data sets. Therefore, new constraints are imposed on the non-minimal coupling parameter, $\xi$, by determining the magnitudes required for effective cosmic inflation. We demonstrate that a substantial non-minimal coupling of order $\xi\sim 10^{2}-10^{4}$ is required for this model to match with the observed primordial spectrum., Comment: 22 pages, 4 figures, 3 table, accepted for publication in PTEP

Profiling is a process that finds similarities between different RNA secondary structures by extracting signals from the Boltzmann sampling. The reproducibility of profiling can be identified by the standard deviation of number of features among Boltzmann samples. We found a strong relationship between the frequency of each helix class and its standard deviation of the frequency upon repeated Boltzmann sampling. We developed a perturbation technique to predict the stability of these featured helix classes without the need for repeated Boltzmann sampling, with accuracy between 84% and 94%, depending on the type of RNA. Our technique only requires 0.2% of the computation time compared to one profiling process., Comment: 14 pages

Control Barrier Functions (CBFs) provide an elegant framework for constraining nonlinear control system dynamics to remain within an invariant subset of a designated safe set. However, identifying a CBF that balances performance-by maximizing the control invariant set-and accommodates complex safety constraints, especially in systems with high relative degree and actuation limits, poses a significant challenge. In this work, we introduce a novel self-supervised learning framework to comprehensively address these challenges. Our method begins with a Boolean composition of multiple state constraints that define the safe set. We first construct a smooth function whose zero superlevel set forms an inner approximation of this safe set. This function is then combined with a smooth neural network to parameterize the CBF candidate. To train the CBF and maximize the volume of the resulting control invariant set, we design a physics-informed loss function based on a Hamilton-Jacobi Partial Differential Equation (PDE). We validate the efficacy of our approach on a 2D double integrator (DI) system and a 7D fixed-wing aircraft system (F16)., Comment: 8th Conference on Robot Learning (CoRL 2024), Munich, Germany