Search

Blazars are beamed active galactic nuclei known for their strong multi-wavelength variability on timescales from years down to minutes. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions. We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019-2022, together with radio data from the WEBT and other teams, and gamma-ray data from the Fermi satellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical and gamma-ray brightness maxima. The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, and gamma-ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. The gamma-ray emitting region is found to be co-spatial with the optical one, and the analysis of the gamma-optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons. We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability., Comment: In press for A&A

The coupling between acoustic vibrations in a lithium niobate bulk acoustic wave resonator and microwave photons of a re-entrant microwave cavity was investigated at a temperature close to 4 K. Coupling was achieved by placing the acoustic resonator in the location of the re-entrant cavity electric field maxima, in a symmetric ``split-post'' configuration, with a large overlap between the microwave field and the acoustic mode, allowing acoustic modulations of the microwave frequency. We show that the acoustic modes in this setup retain large inherent quality factors of greater than $10^6$. A maximum optomechanical coupling rate was determined to be $g_0$ = 0.014 mHz, four orders of magnitude larger than previous results obtained using a quartz BAW at 4 K in a similar experimental setup, but using a single post-re-entrant cavity resonator.

We consider metric versions of weak soficity, LEF and residual finiteness. The main results of the paper extend Glebsky and Rivera's characterization of weak soficity to the case of normally finitely generated groups with word metrics. Metric LEF and residual finiteness are also characterized in this class. We deduce that the free group $\mathsf{F}_2$ is not metrically weakly sofic with respect to its standard invariant word norm., Comment: 21 pages

This paper presents a new look at the neural network (NN) robustness problem, from the point of view of graph theory analysis, specifically graph curvature. Graph curvature (e.g., Ricci curvature) has been used to analyze system dynamics and identify bottlenecks in many domains, including road traffic analysis and internet routing. We define the notion of neural Ricci curvature and use it to identify bottleneck NN edges that are heavily used to ``transport data" to the NN outputs. We provide an evaluation on MNIST that illustrates that such edges indeed occur more frequently for inputs where NNs are less robust. These results will serve as the basis for an alternative method of robust training, by minimizing the number of bottleneck edges.

We present an all-optical concept for measuring the electric field of light spanning from infrared to extreme ultraviolet with multi-petahertz detection bandwidth. Our approach employs a heterodyne detection of light produced by a highly nonlinear light-matter interaction gate. We establish a numerical model of a complex spectral response for unambiguous electric field extraction and benchmark it against the experiment. We show that the concept can be applied for measuring wavelengths down to about 60 nm with a high sensitivity and dynamic range of about 40 decibels. This opens up unprecedented perspectives for spatio-temporal electric field-resolved experiments and control of broadband dynamics of matter.

In this paper we derive a higher-order KdV equation (HKdV) as a model to describe the unidirectional propagation of waves on an internal interface separating two fluid layers of varying densities. Our model incorporates underlying currents by permitting a sheared current in both fluid layers, and also accommodates the effect of the Earth's rotation by including Coriolis forces (restricted to the Equatorial region). The resulting governing equations describing the water wave problem in two fluid layers under a `flat surface' assumption are expressed in a general form as a system of two coupled equations through Dirichlet-Neumann (DN) operators. The DN operators also facilitate a convenient Hamiltonian formulation of the problem. We then derive the HKdV equation from this Hamiltonian formulation, in the long-wave, and small-amplitude, asymptotic regimes. Finally, it is demonstrated that there is an explicit transformation connecting the HKdV we derive with the following integrable equations of similar type: KdV5, Kaup-Kuperschmidt equation, Sawada-Kotera equation, Camassa-Holm and Degasperis-Procesi equations., Comment: 29 pages, 2 figures. Dedicated to the memory of Prof. David J. Kaup (1939-2022)

Parameter estimation from galaxy survey data from the full-shape method depends on scale cuts and priors on EFT parameters. The effects of priors, including the so-called "prior volume" phenomenon have been originally studied in Ivanov et al. (2019) and subsequent works. In this note, we repeat and extend these tests and also apply them to the priors used by D'Amico et al. (2019). We point out that in addition to the "prior volume" effect there is a much more dangerous effect that is largely overlooked: a systematic bias on cosmological parameters due to overoptimistic scale cuts. Unlike the "prior volume" effect, this is a genuine systematic bias due to two-loop corrections that does not vanish with better priors or with larger data volumes. Our study is based on the high fidelity BOSS-like PT Challenge simulation data which offer many advantages over analyses based on synthetic data generated with fitting pipelines. We show that the analysis choices of D'Amico et al.~(2019), especially their scale cuts, significantly bias parameter recovery, overestimating $\sigma_8$ by over $5\%$ (equivalent to $1\sigma$). The bias on measured EFT parameters is even more significant. In contrast, the analysis choices associated with the CLASS-PT code lead to a negligible ($\lesssim 1\%$) bias in the recovery of cosmological parameters based on their best-fit values., Comment: 14 pages, 3 figures, 2 tables

The currents in the ocean have a serious impact on ocean dynamics, since they affect the transport of mass and thus the distribution of salinity, nutrients and pollutants. In many physically important situations the current depends quadratic-ally on the depth. We consider a single layer of fluid and study the propagation of the surface waves in the presence of depth-dependent current with quadratic profile. We select the scale of parameters and quantities, which are typical for the Boussinesq propagation regime (long wave and small amplitude limit) and we also derive the well known KdV model for the surface waves interacting with current., Comment: 16 pages, 1 figure

The study of cosmic rays in the energy range from 1 to 1000 PeV is crucial for understanding their origins and propagation paths. As part of this research, a new SPHERE-3 installation is being developed, featuring enhanced light sensitivity and optical resolution, based on the experience gained with the balloon-borne SPHERE-2 installation. This report describes a computational complex designed for simulating the formation of Cherenkov light on the detector grid of the SPHERE-3 telescope., Comment: Published as a conference paper at X International Conference on Mathematial Modeling. 4 pages, 1 figure

We present a novel method for automatically detecting and characterising semi-resolved star clusters: clusters where the observational point-spread function (PSF) is smaller than the cluster's radius, but larger than the separations between individual stars. We apply our method to a 1.77 deg$^2$ field located in the Large Magellanic Cloud (LMC) using the VISTA survey of the Magellanic Clouds (VMC), which surveyed the LMC in the $YJK_\text{s}$ bands. Our approach first models the position-dependent PSF to detect and remove point sources from deep $K_\text{s}$ images; this leaves behind extended objects such as star clusters and background galaxies. We then analyse the isophotes of these extended objects to characterise their properties, perform integrated photometry, and finally remove any spurious objects this procedure identifies. We demonstrate our approach in practice on a deep VMC $K_\text{s}$ tile that contains the most active star-forming regions in the LMC: 30 Doradus, N158, N159, and N160. We select this tile because it is the most challenging for automated techniques due both to crowding and nebular emission. We detect 682 candidate star clusters, with an estimated contamination rate of 13% from background galaxies and chance blends of physically unrelated stars. We compare our candidates to publicly available James Webb Space Telescope data and find that at least 80% of our detections appear to be star clusters., Comment: 26 pages, 17 figures, submitted to MNRAS

A new Cherenkov telescope of the SPHERE type is under development. Its main goal is to promote the solution of the problem of the primary cosmic ray mass composition at ultra high energies (1--100 PeV) using a newly developed technique of the primary mass assignment to EAS event on event-by-event basis. The telescope will carry out measurements of both the Cherenkov light reflected from the snow surface as well as the direct one. Sensitivity of the direct Cherenkov images' shapes to the primary mass is demonstrated., Comment: Published as a conference paper at 21st Lomonosov Conference on Elementary Particle Physics. 7 pages, 5 figures

We introduce DynaCLR, a self-supervised framework for modeling cell dynamics via contrastive learning of representations of time-lapse datasets. Live cell imaging of cells and organelles is widely used to analyze cellular responses to perturbations. Human annotation of dynamic cell states captured by time-lapse perturbation datasets is laborious and prone to bias. DynaCLR integrates single-cell tracking with time-aware contrastive learning to map images of cells at neighboring time points to neighboring embeddings. Mapping the morphological dynamics of cells to a temporally regularized embedding space makes the annotation, classification, clustering, or interpretation of the cell states more quantitative and efficient. We illustrate the features and applications of DynaCLR with the following experiments: analyzing the kinetics of viral infection in human cells, detecting transient changes in cell morphology due to cell division, and mapping the dynamics of organelles due to viral infection. Models trained with DynaCLR consistently achieve $>95\%$ accuracy for infection state classification, enable the detection of transient cell states and reliably embed unseen experiments. DynaCLR provides a flexible framework for comparative analysis of cell state dynamics due to perturbations, such as infection, gene knockouts, and drugs. We provide PyTorch-based implementations of the model training and inference pipeline (https://github.com/mehta-lab/viscy) and a user interface (https://github.com/czbiohub-sf/napari-iohub) for the visualization and annotation of trajectories of cells in the real space and the embedding space., Comment: 20 pages, 6 figures, 3 appendix figures, 4 videos (ancillary files)

The multiplicities of positive and negative pions, kaons and unidentified hadrons produced in deep-inelastic scattering are measured in bins of the Bjorken scaling variable $x$, the relative virtual-photon energy $y$ and the fraction of the virtual-photon energy transferred to the final-state hadron $z$. Data were obtained by the COMPASS Collaboration using a 160 GeV muon beam of both electric charges and a liquid hydrogen target. These measurements cover the kinematic domain with photon virtuality $Q^2 > 1$ (GeV/$c)^2$, $0.004 < x < 0.4$, $0.1 < y < 0.7$ and $0.2 < z < 0.85$, in accordance with the kinematic domain used in earlier published COMPASS multiplicity measurements with an isoscalar target. The calculation of radiative corrections was improved by using the Monte Carlo generator DJANGOH, which results in up to 12\% larger corrections in the low-$x$ region., Comment: 19 pages, 29 figures

Nanoscale self-localized topological spin textures, such as domain walls and skyrmions, are of interest for the fundamental physics of magnets and spintronics applications. Ferrimagnets (FiMs), in the region close to the angular momentum compensation point, are promising materials because of their ultrafast spin dynamics at nonzero magnetization. In this work, we study specific features of the FiM domain wall (DW) dynamics, which are absent in both ferromagnets (FM) and antiferromagnets (AFM). In low-damping FMs and AFMs ($\alpha \ll 1$), the non-stationary forced motion of DWs is characterized by slow ($t_{diss}\propto 1/\alpha$) changes of the DW's velocity and internal structure for all accepted values of the DW energy $E$ and its linear momentum $P$ -- a consequence of the stability of DWs for any value of $P$. In contrast, the dispersion law of FiM DWs has specific points, $P=P_{cr}$ and $E_{cr}=E(P_{cr})$, such that stable DWs are only present for $P

Hidden-charm strong decays of the spin-2 partner $X_2(4014)$ of the charmonium-like state $X(3872)$ have been studied in the framework of the covariant confined quark model. The exotic state $X_2$ has been interpreted as a four-quark state with molecular-type interpolating current. We have considered the decay widths of $X_2$ on the level of two-petal quark loops. The partial widths of the strong decays $X_2\!\to\!\omega \, J/\Psi$ and $X_2\!\to\!\rho^0 \, J/\Psi$ have been calculated and the related branching ratio has been analyzed.

Semiconductor quantum dots in microcavities are an excellent platform for the efficient generation of indistinguishable single photons. However, their use in a wide range of quantum technologies requires their controlled fabrication and integration in compact closed-cycle cryocoolers, with a key challenge being the efficient and stable extraction of the single photons into a single-mode fiber. Here we report on a novel method for fiber-pigtailing of deterministically fabricated single-photon sources. Our technique allows for nanometer-scale alignment accuracy between the source and a fiber, alignment that persists all the way from room temperature to 2.4 K. We demonstrate high performance of the device under near-resonant optical excitation with g$^{(2)}$(0) = 1.3 %, a photon indistinguishability of 97.5 % and a fibered brightness of 20.8 %. We show that the indistinguishability and single-photon rate are stable for over ten hours of continuous operation in a single cooldown. We further confirm that the device performance is not degraded by nine successive cooldown-warmup cycles., Comment: 7 pages, 5 figures

We study a difference Riccati equation $\Phi(x) + \rho(x)/\Phi(x-\omega) = v(x)$ with $1-$periodic continuos coefficients. Using continued fraction theory we investigate a problem of existence of continuos solutions for this equation. It is shown that convergence of a continued fraction representing a solution of the Riccati equation can be expressed in terms of hyperbolicity of a cocycle naturally associated to this continued fraction. We apply the critical set method to establish the uniform hyperbolicity of the cocycle and to obtain sufficient conditions for the convergence of a continued fraction giving a representation for a solution of the Riccati equation.

Differentiable simulation has become a powerful tool for system identification. While prior work has focused on identifying robot properties using robot-specific data or object properties using object-specific data, our approach calibrates object properties by using information from the robot, without relying on data from the object itself. Specifically, we utilize robot joint encoder information, which is commonly available in standard robotic systems. Our key observation is that by analyzing the robot's reactions to manipulated objects, we can infer properties of those objects, such as inertia and softness. Leveraging this insight, we develop differentiable simulations of robot-object interactions to inversely identify the properties of the manipulated objects. Our approach relies solely on proprioception -- the robot's internal sensing capabilities -- and does not require external measurement tools or vision-based tracking systems. This general method is applicable to any articulated robot and requires only joint position information. We demonstrate the effectiveness of our method on a low-cost robotic platform, achieving accurate mass and elastic modulus estimations of manipulated objects with just a few seconds of computation on a laptop., Comment: arXiv admin comment: This version has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission

Frameworks and DSLs auto-generating code have traditionally relied on human experts developing them to have in place rigorous methods to assure the legality of the applied code transformations. Machine Learning (ML) is gaining wider adoption as a means to auto-generate code optimised for the hardware target. However, ML solutions, and in particular black-box DNNs, provide no such guarantees on legality. In this paper we propose a library, Tadashi, which leverages the polyhedral model to empower researchers seeking to curate datasets crucial for applying ML in code-generation. Tadashi provides the ability to reliably and practically check the legality of candidate transformations on polyhedral schedules applied on a baseline reference code. We provide a proof that our library guarantees the legality of generated transformations, and demonstrate its lightweight practical cost. Tadashi is available at https://github.com/vatai/tadashi/., Comment: Submitted to CGO

While multimodal foundation models can now natively work with data beyond text, they remain underutilized in analyzing the considerable amounts of multi-dimensional time-series data in fields like healthcare, finance, and social sciences, representing a missed opportunity for richer, data-driven insights. This paper proposes a simple but effective method that leverages the existing vision encoders of these models to "see" time-series data via plots, avoiding the need for additional, potentially costly, model training. Our empirical evaluations show that this approach outperforms providing the raw time-series data as text, with the additional benefit that visual time-series representations demonstrate up to a 90% reduction in model API costs. We validate our hypothesis through synthetic data tasks of increasing complexity, progressing from simple functional form identification on clean data, to extracting trends from noisy scatter plots. To demonstrate generalizability from synthetic tasks with clear reasoning steps to more complex, real-world scenarios, we apply our approach to consumer health tasks - specifically fall detection, activity recognition, and readiness assessment - which involve heterogeneous, noisy data and multi-step reasoning. The overall success in plot performance over text performance (up to an 120% performance increase on zero-shot synthetic tasks, and up to 150% performance increase on real-world tasks), across both GPT and Gemini model families, highlights our approach's potential for making the best use of the native capabilities of foundation models., Comment: 49 pages

A new SPHERE-3 telescope is being developed for cosmic rays spectrum and mass composition studies in the 5--1000 PeV energy range. Registration of extensive air showers using reflected Cherenkov light method applied in the SPHERE detector series requires a good trigger system for accurate separation of events from the background produced by starlight and airglow photons reflected from the snow. Here we present the results of convolutional networks application for the classification of images obtained from Monte Carlo simulation of the detector. Detector response simulations include photons tracing through the optical system, silicon photomultiplier operation and electronics response and digitization process. The results are compared to the SPHERE-2 trigger system performance., Comment: 7 pages, 5 figures Published as a conference paper at DLCP2024, June 19-21, 2024, Moscow, Russia. https://dlcp2024.sinp.msu.ru Submitted to Moscow University Physics Bulletin

The second PyHEP.dev workshop, part of the "Python in HEP Developers" series organized by the HEP Software Foundation (HSF), took place in Aachen, Germany, from August 26 to 30, 2024. This gathering brought together nearly 30 Python package developers, maintainers, and power users to engage in informal discussions about current trends in Python, with a primary focus on analysis tools and techniques in High Energy Physics (HEP). The workshop agenda encompassed a range of topics, such as defining the scope of HEP data analysis, exploring the Analysis Grand Challenge project, evaluating statistical models and serialization methods, assessing workflow management systems, examining histogramming practices, and investigating distributed processing tools like RDataFrame, Coffea, and Dask. Additionally, the workshop dedicated time to brainstorming the organization of future PyHEP.dev events, upholding the tradition of alternating between Europe and the United States as host locations. This document, prepared by the session conveners in the weeks following the workshop, serves as a summary of the key discussions, salient points, and conclusions that emerged., Comment: 16 pages, 0 figures; workshop summary

The current-voltage (I-V) properties along the c axis on Nd2-xCexCuO4 /SrTiO3 epitaxial films with x = 0.145, 0.15 were investigated. For all the samples it has been established that the I-V characteristics exhibit several resistive branches, which correspond to the resistive states of individual Josephson junctions. The results confirm the idea of a tunneling mechanism between the CuO2 layers (superconductor - insulator - superconductor junction) for the investigated Nd2-xCexCuO4 compound. The I-V dependence of this compound with x = 0.15 points out on the nonmonotonic nature of the d-wave or anisotropic s-wave symmetry order parameter associated with the coexistence of superconductivity and antiferromagnetic fluctuations., Comment: 20 pages, 6 figures, 2 tables

We obtain three Helly-type results. First, we establish a Quantitative Colorful Helly-type theorem with the optimal Helly number \(2d\) concerning the diameter of the intersection of a family of convex bodies. Second, we prove a Quantitative Helly-type theorem with the optimal Helly number \(2d+1\) for the pointwise minimum of logarithmically concave functions. Finally, we present a colorful version of the latter result with Helly number (number of color classes) \(3d+1\); however, we have no reason to believe that this bound is sharp.

Automatic Speech Recognition (ASR) systems have achieved remarkable performance on widely used benchmarks such as LibriSpeech and Fleurs. However, these benchmarks do not adequately reflect the complexities of real-world conversational environments, where speech is often unstructured and contains disfluencies such as pauses, interruptions, and diverse accents. In this study, we introduce a multilingual conversational dataset, derived from TalkBank, consisting of unstructured phone conversation between adults. Our results show a significant performance drop across various state-of-the-art ASR models when tested in conversational settings. Furthermore, we observe a correlation between Word Error Rate and the presence of speech disfluencies, highlighting the critical need for more realistic, conversational ASR benchmarks.

Large language models (LLMs) have enabled a range of applications in zero-shot and few-shot learning settings, including the generation of synthetic datasets for training and testing. However, to reliably use these synthetic datasets, it is essential to understand how representative they are of real-world data. We investigate this by assessing the effectiveness of generating synthetic data through LLM and using it as a benchmark for various NLP tasks. Our experiments across six datasets, and three different tasks, show that while synthetic data can effectively capture performance of various methods for simpler tasks, such as intent classification, it falls short for more complex tasks like named entity recognition. Additionally, we propose a new metric called the bias factor, which evaluates the biases introduced when the same LLM is used to both generate benchmarking data and to perform the tasks. We find that smaller LLMs exhibit biases towards their own generated data, whereas larger models do not. Overall, our findings suggest that the effectiveness of synthetic data as a benchmark varies depending on the task, and that practitioners should rely on data generated from multiple larger models whenever possible.