Search

Recently published work on rephrasing natural text data for pre-training LLMs has shown promising results when combining the original dataset with the synthetically rephrased data. We build upon previous work by replicating existing results on C4 and extending them with our optimized rephrasing pipeline to the English, German, Italian, and Spanish Oscar subsets of CulturaX. Our pipeline leads to increased performance on standard evaluation benchmarks in both the mono- and multilingual setup. In addition, we provide a detailed study of our pipeline, investigating the choice of the base dataset and LLM for the rephrasing, as well as the relationship between the model size and the performance after pre-training. By exploring data with different perceived quality levels, we show that gains decrease with higher quality. Furthermore, we find the difference in performance between model families to be bigger than between different model sizes. This highlights the necessity for detailed tests before choosing an LLM to rephrase large amounts of data. Moreover, we investigate the effect of pre-training with synthetic data on supervised fine-tuning. Here, we find increasing but inconclusive results that highly depend on the used benchmark. These results (again) highlight the need for better benchmarking setups. In summary, we show that rephrasing multilingual and low-quality data is a very promising direction to extend LLM pre-training data., Comment: 21 pages, 4 figures, 12 tables

We investigate the dynamical and physical structures of bright-rimmed clouds (BRCs) in a nearby HII region. We focused on carbon- and oxygen-bearing species that trace photon-dominated regions (PDRs) and warm molecular cloud surfaces in order to understand the effect of UV radiation from the exciting stars on the cloud structure. We mapped four regions around the most prominent BRCs at scales of 4--10 arcmin in the HII region IC 1396 in [CII] 158 micron with (up)GREAT on board SOFIA. IC 1396 is predominantly excited by an O6.5V star. Toward IC 1396A, we also observed [OI] 63 micron and 145 micron. We combined these observations with JCMT archive data, which provide the low-J transitions of CO, $^{13}$CO, and C$^{18}$O. All spectra are velocity-resolved. The line profiles show a variety of velocity structures, which we investigated in detail for all observed emission lines. We find no clear sign of photoevaporating flows in the [CII] spectra, although the uncertainty in the location of the BRCs along the line of sight makes this interpretation inconclusive. Our analysis of the [$^{13}$CII] emission in IC 1396A suggests that the [CII] is likely mostly optically thin. The heating efficiency, measured by the ([CII]+[OI] 63 micron)/far-infrared intensity ratio, is higher in the northern part of IC 1396A than in the southern part, which may indicate a difference in the dust properties of the two areas. The complex velocity structures identified in the BRCs of IC 1396, which is apparently a relatively simple HII region, highlight the importance of velocity-resolved data for disentangling different components along the line of sight and thus facilitating a detailed study of the dynamics of the cloud. We also demonstrate that the optically thin [$^{13}$CII] and [OI] 145 micron emission lines are essential for a conclusive interpretation of the [CII] 158 micron and [OI] 63 micron line profiles., Comment: Accepted for publication in A&A, 26 pages including Appendices

The incompatibility of explicit diffeomorphism violation with Riemannian geometry within the gravitational Standard-Model Extension (SME) is revisited. We review two methods of how to deal with this problem. The first is based on an approach proposed originally by St\"{u}ckelberg and the latter is to restrict spacetime geometry via the dynamical field equations and the second Bianchi identity. Moreover, a third technique is introduced, which is novel and relies on isometries of a gravitational system. Our conclusion is that an SME background field configuration compatible with Riemannian geometry is more likely to be determined the more diffeomorphisms are isometries of the particular system. This finding has the potential to provide an alternative treatment of explicit spacetime symmetry violation in gravity., Comment: 6 pages, 1 figure

Scaling up interferometry to 8m collectors should smooth-out the optical piston perturbations and allow a slow fringe tracker to obtain high precision correction on faint targets. In practice, the GRAVITY fringe tracker still observes high frequency OPD components that limit the exposure time, its precision and limiting magnitude. Perturbations seem to come from mechanical vibrations in the train of mirrors. As part of the GRAVITY+ efforts, accelerometers were added to all the mirrors of the coud\'e train to compensate in real-time the optical path using the main delay lines. We show their effectiveness on vibrations peaks between 40 and 200Hz and outline prospects for the upgrade of the deformable mirrors and the beam-compressor differential delay lines., Comment: 11 pages, 12 figures, Proc. SPIE Astronomical Telescopes + Instrumentation 2024 (Yokohama Japan), Optical and Infrared Interferometry and Imaging VI

The expanding molecular ring (EMR) manifests itself as a parallelogram in the position-velocity diagram of spectral line emission from the Central Molecular Zone (CMZ) surrounding the Galacic centre (GC). Using multiwavelength data, we investigate the gas kinematics, star formation activity, and the presence of shocked gas in a 200 pc long high velocity gas stream (V~ +150 km/s) with a double helix morphology named the helix stream, that is located 15-55 pc above the CMZ and is kinematically associated with the EMR/parallelogram. We carried out molecular line observations using the IRAM 30m, Yebes 40m, and APEX 12m telescopes. The detection of four rotational transitions of the SiO molecule indicate the presence of shocks. We derived the SiO column densities and abundances in different regions of the helix stream. The presence of protostellar clumps and a candidate HII region signify the ongoing star formation activity within the helix stream. The cloud is massive (2.5x10^6 M_sun) and highly turbulent. We find evidence of cloud-cloud collisions towards the eastern edge (l~1.3{\deg}), suggesting a dynamic interaction with the CMZ. An expanding shell is detected within the cloud with radius of 6.7 pc and an expansion velocity of 35 km/s. The shell might be powered by several supernovae or a single hypernova. The SiO abundance within the helix stream implies extensive shock processes occurring on large scales. The helical or cork-screw velocity structure of the helix stream indicates twisting and turning motions within the cloud. We propose that the helix stream is the continuation of the near side bar lane, that is overshooting after brushing the CMZ. Our findings carry profound implications for understanding star formation in extreme conditions and elucidate the intricate properties of gas and dust associated with nuclear inflows in barred spiral galaxies., Comment: 20 pages, 20 figures, 4 tables, accepted for publication in A&A

We study a general class of effective backgrounds that break diffeomorphism invariance and their potential roles in cosmology. Specifically, we examine both explicit and spontaneous background fields which display distinct transformation properties and are characterized with different dynamics. For explicit breaking, we focus on the $t$-sector of the minimal gravitational Standard-Model Extension (SME) and for spontaneous breaking on a vector field called the bumblebee model. In both cases, we derive the modified Friedmann equations and find a configuration of the background fields that preserve isotropy and homogeneity. We show that the explicit $t$-sector admits phases of accelerated expansion of the universe with standard matter., Comment: 45 pages and 2 figures

Sharp restriction theory and the finite field extension problem have both received a great deal of attention in the last two decades, but so far they have not intersected. In this paper, we initiate the study of sharp restriction theory on finite fields. We prove that constant functions maximize the Fourier extension inequality from the parabola $\mathbb{P}^1\subset \mathbb{F}^{2\ast}_q$ and the paraboloid $\mathbb{P}^2\subset \mathbb{F}_q^{3\ast}$ at the euclidean Stein-Tomas endpoint; here, $\mathbb{F}_q^{d\ast}$ denotes the (dual) $d$-dimensional vector space over the finite field $\mathbb F_q$ with $q=p^n$ elements, where $p$ is a prime number greater than $3$ or $2$, respectively. We fully characterize the maximizers for the $L^2\to L^4$ extension inequality from $\mathbb{P}^2$ whenever $q\equiv 1(\text{mod}\, 4)$. Our methods lead to analogous results on the hyperbolic paraboloid, whose corresponding euclidean problem remains open. We further establish that constants maximize the $L^2\to L^4$ extension inequality from the cone $\Gamma^3:=\{(\boldsymbol{\xi},\tau, \sigma)\in \mathbb{F}^{4\ast}_q: \tau\sigma=\boldsymbol{\xi}^2\}\setminus \{{\bf 0}\}$ whenever $q\equiv 3(\text{mod}\, 4)$. By contrast, we prove that constant functions fail to be critical points for the corresponding inequality on $\Gamma^3\cup \{{\bf 0}\}$ over $\mathbb{F}_p^4$. While some inspiration is drawn from the euclidean setting, entirely new phenomena emerge which are related to the underlying arithmetic and discrete structures., Comment: 34 pages; v2: typos corrected, references added

Context. The diffuse TeV gamma-ray emission detected in the inner $\sim$ 100 pc of the Galactic Center suggests the existence of a central cosmic-ray accelerator reaching $\sim$ PeV energies. It is interesting to associate this so-called PeVatron with the point source HESS J1745$-$290, whose position is consistent with that of the central supermassive black hole, Sgr A*. However, the point source shows a spectral break at a few TeV, which is not shown by the diffuse emission, challenging this association. Aims. We seek to build an emission model for the point source consistent with both emissions being produced by the same population of relativistic protons, continuously injected with a power-law spectrum up to $\sim$ PeV energies, near Sgr A*. Methods. In our model, we assume that the point source is produced by hadronic collisions between the cosmic rays and the gas in the accretion flow of Sgr A*. The cosmic-ray density is calculated taking into consideration cosmic-ray transport due to diffusion and advection, while the properties of the gas are obtained from previous numerical simulations of the accretion flow. Results. Our model succeeds in explaining both the point source and the diffuse emission with the same cosmic rays injected in the vicinity of Sgr A*, as long as the coherence length of the magnetic turbulence in the accretion flow is $l_c\sim(1-3)\times 10^{14}\,\mathrm{cm}$. The spectral break of the point source appears naturally due to an energy-dependent transition in the way the cosmic rays diffuse within the inner $\sim 0.1$ pc of the accretion flow (where most of the emission is produced) Conclusions. Our model supports the idea that Sgr A* can be a PeVatron, whose accelerated cosmic rays give rise to both the point source and the diffuse emission. Future TeV telescopes, like CTAO, will be able to test this model.

We introduce Stable Code, the first in our new-generation of code language models series, which serves as a general-purpose base code language model targeting code completion, reasoning, math, and other software engineering-based tasks. Additionally, we introduce an instruction variant named Stable Code Instruct that allows conversing with the model in a natural chat interface for performing question-answering and instruction-based tasks. In this technical report, we detail the data and training procedure leading to both models. Their weights are available via Hugging Face for anyone to download and use at https://huggingface.co/stabilityai/stable-code-3b and https://huggingface.co/stabilityai/stable-code-instruct-3b. This report contains thorough evaluations of the models, including multilingual programming benchmarks, and the MT benchmark focusing on multi-turn dialogues. At the time of its release, Stable Code is the state-of-the-art open model under 3B parameters and even performs comparably to larger models of sizes 7 billion and 15 billion parameters on the popular Multi-PL benchmark. Stable Code Instruct also exhibits state-of-the-art performance on the MT-Bench coding tasks and on Multi-PL completion compared to other instruction tuned models. Given its appealing small size, we also provide throughput measurements on a number of edge devices. In addition, we open source several quantized checkpoints and provide their performance metrics compared to the original model.

We introduce StableLM 2 1.6B, the first in a new generation of our language model series. In this technical report, we present in detail the data and training procedure leading to the base and instruction-tuned versions of StableLM 2 1.6B. The weights for both models are available via Hugging Face for anyone to download and use. The report contains thorough evaluations of these models, including zero- and few-shot benchmarks, multilingual benchmarks, and the MT benchmark focusing on multi-turn dialogues. At the time of publishing this report, StableLM 2 1.6B was the state-of-the-art open model under 2B parameters by a significant margin. Given its appealing small size, we also provide throughput measurements on a number of edge devices. In addition, we open source several quantized checkpoints and provide their performance metrics compared to the original model., Comment: 23 pages, 6 figures

Mixture-of-Experts (MoE) models are a promising way to scale up model capacity without significantly increasing computational cost. A key component of MoEs is the router, which decides which subset of parameters (experts) process which feature embeddings (tokens). In this paper, we present a comprehensive study of routers in MoEs for computer vision tasks. We introduce a unified MoE formulation that subsumes different MoEs with two parametric routing tensors. This formulation covers both sparse MoE, which uses a binary or hard assignment between experts and tokens, and soft MoE, which uses a soft assignment between experts and weighted combinations of tokens. Routers for sparse MoEs can be further grouped into two variants: Token Choice, which matches experts to each token, and Expert Choice, which matches tokens to each expert. We conduct head-to-head experiments with 6 different routers, including existing routers from prior work and new ones we introduce. We show that (i) many routers originally developed for language modeling can be adapted to perform strongly in vision tasks, (ii) in sparse MoE, Expert Choice routers generally outperform Token Choice routers, and (iii) soft MoEs generally outperform sparse MoEs with a fixed compute budget. These results provide new insights regarding the crucial role of routers in vision MoE models.

Tight relationships exist in the local universe between the central stellar properties of galaxies and the mass of their supermassive black hole. These suggest galaxies and black holes co-evolve, with the main regulation mechanism being energetic feedback from accretion onto the black hole during its quasar phase. A crucial question is how the relationship between black holes and galaxies evolves with time; a key epoch to probe this relationship is at the peaks of star formation and black hole growth 8-12 billion years ago (redshifts 1-3). Here we report a dynamical measurement of the mass of the black hole in a luminous quasar at a redshift of 2, with a look back time of 11 billion years, by spatially resolving the broad line region. We detect a 40 micro-arcsecond (0.31 pc) spatial offset between the red and blue photocenters of the H$\alpha$ line that traces the velocity gradient of a rotating broad line region. The flux and differential phase spectra are well reproduced by a thick, moderately inclined disk of gas clouds within the sphere of influence of a central black hole with a mass of 3.2x10$^{8}$ solar masses. Molecular gas data reveal a dynamical mass for the host galaxy of 6x10$^{11}$ solar masses, which indicates an under-massive black hole accreting at a super-Eddington rate. This suggests a host galaxy that grew faster than the supermassive black hole, indicating a delay between galaxy and black hole formation for some systems., Comment: 5 pages Main text, 8 figures, 2 tables, to be published in Nature, under embargo until 29 January 2024 16:00 (London)

Background: Pain assessment in individuals with neurological conditions, especially those with limited self-report ability and altered facial expressions, presents challenges. Existing measures, relying on direct observation by caregivers, lack sensitivity and specificity. In cerebral palsy, pain is a common comorbidity and a reliable evaluation protocol is crucial. Thus, having an automatic system that recognizes facial expressions could be of enormous help when diagnosing pain in this type of patient. Objectives: 1) to build a dataset of facial pain expressions in individuals with cerebral palsy, and 2) to develop an automated facial recognition system based on deep learning for pain assessment addressed to this population. Methods: Ten neural networks were trained on three pain image databases, including the UNBC-McMaster Shoulder Pain Expression Archive Database, the Multimodal Intensity Pain Dataset, and the Delaware Pain Database. Additionally, a curated dataset (CPPAIN) was created, consisting of 109 preprocessed facial pain expression images from individuals with cerebral palsy, categorized by two physiotherapists using the Facial Action Coding System observational scale. Results: InceptionV3 exhibited promising performance on the CP-PAIN dataset, achieving an accuracy of 62.67% and an F1 score of 61.12%. Explainable artificial intelligence techniques revealed consistent essential features for pain identification across models. Conclusion: This study demonstrates the potential of deep learning models for robust pain detection in populations with neurological conditions and communication disabilities. The creation of a larger dataset specific to cerebral palsy would further enhance model accuracy, offering a valuable tool for discerning subtle and idiosyncratic pain expressions. The insights gained could extend to other complex neurological conditions.

Dye Sensitized Solar Cells (DSSCs) have recently regained attention for indoor light harvesting and powering wireless devices. Advantages such as cost-effectiveness, flexibility, wide angular response, and lightweight design have driven the fostering of the implementation of advanced photonic architectures, dedicated photosensitizers and compatibility with wearable carriers. However, to fully exploit their potential, crucial aspects require further attention, in particular the improvement of spectral compatibility and low-light harvesting mechanisms, as well as the development of efficient photoanodes through high-yield scalable methods. In this article, we propose the use of nanocomposite photoanodes integrating mesoporous TiO2 (m-TiO2) nanoparticles, ITO nanotubes (NTs) and TiO2 anatase shells (ITO@TiO2 NTs) prepared by step-by-step method relying on mild temperature conditions and avoiding toxic precursors. These photoanodes outperform previous attempts to implement low-dimensional ITO and ITO@TiO2 nanowires and nanotubes for outdoor light conversion, demonstrating an outstanding PCE under low artificial light intensity of 24 % for at 0.014 mWcm-2, a 166 % increase compared to the conventional architectures. Advanced microstructural, optical, and electrochemical characterizations have revealed that the strong scattering effect of the light in the visible range coupled with enhanced charge collection at low-intensity illumination are the essential mechanisms responsible for such enhanced energy conversion. Remarkably, our devices retain up to 90% of the normal incidence efficiency even under glancing illumination, while conventional reference devices show a drop down to 50%.

Multivariate spatial modeling is key to understanding the behavior of materials downstream in a mining operation. The ore recovery depends on the mineralogical composition, which needs to be properly captured by the model to allow for good predictions. Multivariate modeling must also capture the behavior of tailings and waste materials to understand the environmental risks involved in their disposal. However, multivariate spatial modeling is challenging when the variables show complex relationships, such as non-linear correlation, heteroscedastic behavior, or spatial trends. This contribution proposes a novel methodology for general multivariate contexts, with the idea of disaggregating the global non-linear behavior among variables into the spatial domain in a piece-wise linear fashion. We demonstrate that the complex multivariate behavior can be reproduced by looking at local correlations between variables at sample locations, inferred from a local neighborhood, and interpolating these local linear dependencies by using a non-stationary version of the Linear Model of Coregionalization. This mixture of locally varying linear correlations is combined to reproduce the global complex behavior seen in the multivariate distribution. The main challenge is to solve appropriately the interpolation of the known correlation matrices over the domain, as these local correlations defined at sample locations can be endowed with a manifold structure, on which the Euclidean distance is not a suitable metric for interpolation of such correlations. This is addressed by using tools from Riemannian geometry: correlation matrices are interpolated using a weighted Fr\'echet mean of the correlations inferred at sample locations. An application of the procedure is shown in a real case study with good results in terms of accuracy and reproduction of the reference multivariate distributions and semi-variograms.

Electron cyclotron waves (whistlers), are commonly observed in plasmas near Earth and the solar wind. In the presence of nonlinear mirror modes, bursts of whistlers, usually called lion roars, have been observed within low magnetic field regions associated to these modes. In the intracluster medium (ICM) of galaxy clusters, the excitation of the mirror instability is expected, but it is not yet clear whether electron and ion cyclotron waves can also be present under conditions where gas pressure dominates over magnetic pressure (high $\beta$). In this work, we perform fully kinetic particle-in-cell (PIC) simulations of a plasma subject to a continuous amplification of the mean magnetic field $\textbf{B}(t)$ to study the nonlinear stages of the mirror instability and the ensuing excitation of whistler and ion cyclotron (IC) waves under ICM conditions. Once mirror modes reach nonlinear amplitudes, both whistler and IC waves start to emerge simultaneously, with sub-dominant amplitudes, propagating in low-$\textbf{B}$ regions, and quasi-parallel to $\textbf{B}(t)$. We show that the underlying source of excitation is the pressure anisotropy of electrons and ions trapped in mirror modes with loss-cone type distributions. We also observe that IC waves play an essential role in regulating the ion pressure anisotropy at nonlinear stages. We argue that whistler and IC waves are a concomitant feature at late stages of the mirror instability even at high-$\beta$, and therefore expected to be present in astrophysical environments like the ICM. We discuss the implications of our results for collisionless heating and dissipation of turbulence in the ICM., Comment: 22 pages, 17 figures. Submitted to ApJ. Comments are welcome

We explore the impact of parameter sparsity on the scaling behavior of Transformers trained on massive datasets (i.e., "foundation models"), in both vision and language domains. In this setting, we identify the first scaling law describing the relationship between weight sparsity, number of non-zero parameters, and amount of training data, which we validate empirically across model and data scales; on ViT/JFT-4B and T5/C4. These results allow us to characterize the "optimal sparsity", the sparsity level which yields the best performance for a given effective model size and training budget. For a fixed number of non-zero parameters, we identify that the optimal sparsity increases with the amount of data used for training. We also extend our study to different sparsity structures (such as the hardware-friendly n:m pattern) and strategies (such as starting from a pretrained dense model). Our findings shed light on the power and limitations of weight sparsity across various parameter and computational settings, offering both theoretical understanding and practical implications for leveraging sparsity towards computational efficiency improvements.

The magnetorotational instability (MRI) plays a crucial role in regulating the accretion efficiency in astrophysical accretion disks. In low-luminosity disks around black holes, such as Sgr A* and M87, Coulomb collisions are infrequent, making the MRI physics effectively collisionless. The collisionless MRI gives rise to kinetic plasma effects that can potentially affect its dynamic and thermodynamic properties. We present 2D and 3D particle-in-cell (PIC) plasma simulations of the collisionless MRI in stratified disks using shearing boxes with net vertical field. We use pair plasmas, with initial $\beta=100$ and concentrate on sub-relativistic plasma temperatures ($k_BT \lesssim mc^2$). Our 2D and 3D runs show disk expansion, particle and magnetic field outflows, and a dynamo-like process. They also produce magnetic pressure dominated disks with (Maxwell stress dominated) viscosity parameter $\alpha \sim 0.5-1$. By the end of the simulations, the dynamo-like magnetic field tends to dominate the magnetic energy and the viscosity in the disks. Our 2D and 3D runs produce fairly similar results, and are also consistent with previous 3D MHD simulations. Our simulations also show nonthermal particle acceleration, approximately characterized by power-law tails with temperature dependent spectral indices $-p$. For temperatures $k_BT \sim 0.05-0.3\, mc^2$, we find $p\approx 2.2-1.9$. The maximum accelerated particle energy depends on the scale separation between MHD and Larmor-scale plasma phenomena in a way consistent with previous PIC results of magnetic reconnection-driven acceleration. Our study constitutes a first step towards modeling from first principles potentially observable stratified MRI effects in low-luminosity accretion disks around black holes.

In this article we prove that the Hausdorff dimension of geodesic directions that are recurrent and diverge on average coincides with the entropy at infinity of the geodesic flow for any complete, pinched negatively curved Riemannian manifold. We derive an interesting consequence from this result, we prove that the entropy of a {\sigma}-finite, ergodic and conservative infinite invariant measure is bounded from above by the entropy at infinity of the geodesic flow., Comment: 23 pages, 1 figure

Sparse mixture of expert architectures (MoEs) scale model capacity without significant increases in training or inference costs. Despite their success, MoEs suffer from a number of issues: training instability, token dropping, inability to scale the number of experts, or ineffective finetuning. In this work, we propose Soft MoE, a fully-differentiable sparse Transformer that addresses these challenges, while maintaining the benefits of MoEs. Soft MoE performs an implicit soft assignment by passing different weighted combinations of all input tokens to each expert. As in other MoEs, experts in Soft MoE only process a subset of the (combined) tokens, enabling larger model capacity (and performance) at lower inference cost. In the context of visual recognition, Soft MoE greatly outperforms dense Transformers (ViTs) and popular MoEs (Tokens Choice and Experts Choice). Furthermore, Soft MoE scales well: Soft MoE Huge/14 with 128 experts in 16 MoE layers has over 40x more parameters than ViT Huge/14, with only 2% increased inference time, and substantially better quality., Comment: Published as a conference paper at ICLR 2024

We present a method to test and monitor structural relationships between time variables. The distribution of the first eigenvalue for lagged correlation matrices (Tracy-Widom distribution) is used to test structural time relationships between variables against the alternative hypothesis (Independence). This distribution studies the asymptotic dynamics of the largest eigenvalue as a function of the lag in lagged correlation matrices. By analyzing the time series of the standard deviation of the greatest eigenvalue for $2\times 2$ correlation matrices with different lags we can analyze deviations from the Tracy-Widom distribution to test structural relationships between these two time variables. These relationships can be related to causality. We use the standard deviation of the explanatory power of the first eigenvalue at different lags as a proxy for testing and monitoring structural causal relationships. The method is applied to analyse causal dependencies between daily monetary flows in a retail brokerage business allowing to control for liquidity risks., Comment: 10 pages, 11 Figures. arXiv admin note: text overlap with arXiv:0910.1205 by other authors

Information disorders on social media can have a significant impact on citizens' participation in democratic processes. To better understand the spread of false and inaccurate information online, this research analyzed data from Twitter, Facebook, and Instagram. The data was collected and verified by professional fact-checkers in Chile between October 2019 and October 2021, a period marked by political and health crises. The study found that false information spreads faster and reaches more users than true information on Twitter and Facebook. Instagram, on the other hand, seemed to be less affected by this phenomenon. False information was also more likely to be shared by users with lower reading comprehension skills. True information, on the other hand, tended to be less verbose and generate less interest among audiences. This research provides valuable insights into the characteristics of misinformation and how it spreads online. By recognizing the patterns of how false information diffuses and how users interact with it, we can identify the circumstances in which false and inaccurate messages are prone to become widespread. This knowledge can help us develop strategies to counter the spread of misinformation and protect the integrity of democratic processes.

We report the discovery of a velocity coherent, funnel shaped ^13CO emission feature in the Galactic centre (GC) using data from the SEDIGISM survey. The molecular cloud appears as a low velocity structure (V_LSR=[-3.5, +3.5] km/s) with an angular extent of 0.95{\deg} x 1{\deg}, extending toward positive Galactic latitudes. The structure is offset from Sgr A* toward negative Galactic longitudes and spatially and morphologically correlates well with the northern lobe of the 430 pc radio bubble, believed to be the radio counterpart of the multiwavelength GC chimney. Spectral line observations in the frequency range of 85-116 GHz have been carried out using the IRAM 30 metre telescope toward 12 positions along the funnel-shaped emission. We examine the ^12C/^13C isotopic ratios using various molecules and their isotopologues. The mean ^12C/^13C isotope ratio (30.6+-2.9) is consistent with the structure located within inner 3 kpc of the Galaxy and possibly in the GC. The velocity of the molecular funnel is consistent with previous radio recombination line measurements of the northern lobe of radio bubble. Our multiwavelength analysis suggests that the funnel shaped structure extending over 100 pc above the Galactic plane is the molecular counterpart of the northern GC chimney., Comment: Accepted for publication in A&A Letters