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This work aims to spectroscopically characterize and provide for the first time direct experimental frequencies of the ground vibrational state and two excited states of the simplest alkynyl thiocyanate (HCCSCN) for astrophysical use. Both microwave (8-16~GHz) and millimeter wave regions (50-120~GHz) of the spectrum have been measured and analyzed in terms of Watson's semirigid rotor Hamiltonian. A total of 314 transitions were assigned to the ground state of HCCSCN and a first set of spectroscopic constants have been accurately determined. Spectral features of the molecule were then searched for in Sgr B2(N), NGC 6334I, G+0.693-0.027 and TMC-1 molecular clouds. Upper limits to the column density are provided., Comment: 9 Pages, 6 Figures, 3 Tables

We report the discovery in TMC-1 of two cyano derivatives of the PAH acenaphthylene (C$_{12}$H$_8$). We have found two series of lines with the QUIJOTE line survey that we assign to 1-C$_{12}$H$_7$CN and 5-C$_{12}$H$_7$CN. For the 1-isomer, we have detected and assigned 173 rotational transitions with $J$ up to 46 and $K_a$ up to 9, corresponding to 107 independent frequencies. For the 5-isomer, the identification is based on 56 individual lines, corresponding to 117 rotational transitions with $J$ up to 40 and $K_a$ up to 8. Identification of the carriers was achieved through a careful analysis of the derived rotational constants, which permit us to focus on molecules larger than naphthalene but smaller than anthracene and phenanthrene. Moreover, the derived rotational constants indicate that the species are planar; this allows us to discard derivatives of fluorene and acenaphthene, which are non-planar species. Quantum chemical calculations and subsequent chemical synthesis of these molecules, as well as the observation of their rotational transitions in the laboratory, unequivocally support our identifications. We also confirm, via a robust line-by-line detection, the previous claimed detection of 1- and 2- cyanonaphthalene, which were obtained through statistical stacking techniques. The column densities of 1- and 5-cyanoacenaphthylene are (9.5\,$\pm$\,0.9)$\,\times$\,10$^{11}$ cm$^{-2}$, while those of 1- and 2-cyanonapthalene are (5.5\,$\pm$\,0.5)$\,\times$\,10$^{11}$ cm$^{-2}$. Hence, it seems that acenaphthylene could be a factor of 1.7 more abundant than naphthalene. These results support a scenario in which PAHs grow in cold dark clouds based on fused five- and six-membered carbon rings., Comment: Accepted as a Letter to the Editor in Astronomy and Astrophysics on 18th September 2024

We study the formation of the dynamic adsorption layer when a bubble is released in a tank containing water with a tiny amount of surfactant. The influence of the sorption kinetic constants is examined by comparing the experiments with Sodium Dodecyl Sulfate (SDS) and Triton X-100. The experiments allowed us to determine the parameter conditions that lead to a stable bubble rising and to validate the simulation. A simple scaling analysis and the simulation show that the formation of the dynamic adsorption layer can be split into three phases characterized by disparate time scales. The mechanisms controlling those phases are surfactant convection, adsorption-desorption, and diffusion. The amount of surfactant adsorbed onto the interface increases monotonously throughout the three phases. The experiments and the simulation show that the rising velocity reaches a maximum at times of the order of $k_d^{-1}$ ($k_d$ is the desorption constant) when the dynamic adsorption layer is practically formed. This occurs even when only traces of surfactant are present in the liquid. The non-monotonous behavior of the maximum surfactant surface concentration is explained in terms of the reverse flow in the rear of the bubble right after the bubble release. This work contributes to the understanding of the complex interplay between hydrodynamics and surfactant transport and kinetics over bubble rising.

Diffusion-weighted imaging (DWI) is a type of Magnetic Resonance Imaging (MRI) technique sensitised to the diffusivity of water molecules, offering the capability to inspect tissue microstructures and is the only in-vivo method to reconstruct white matter fiber tracts non-invasively. The DWI signal can be analysed with the diffusion tensor imaging (DTI) model to estimate the directionality of water diffusion within voxels. Several scalar metrics, including axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA), can be further derived from DTI to quantitatively summarise the microstructural integrity of brain tissue. These scalar metrics have played an important role in understanding the organisation and health of brain tissue at a microscopic level in clinical studies. However, reliable DTI metrics rely on DWI acquisitions with high gradient directions, which often go beyond the commonly used clinical protocols. To enhance the utility of clinically acquired DWI and save scanning time for robust DTI analysis, this work proposes DirGeo-DTI, a deep learning-based method to estimate reliable DTI metrics even from a set of DWIs acquired with the minimum theoretical number (6) of gradient directions. DirGeo-DTI leverages directional encoding and geometric constraints to facilitate the training process. Two public DWI datasets were used for evaluation, demonstrating the effectiveness of the proposed method. Extensive experimental results show that the proposed method achieves the best performance compared to existing DTI enhancement methods and potentially reveals further clinical insights with routine clinical DWI scans., Comment: Accepted to ICONIP2024, Diffusion Weighted Imaging, Diffusion Tensor Imaging, Angular Resolution Enhancement, Fractional Anisotropy

This paper represents a continuation of our previous work, where the Bolzmann weights (BWs) for several Interaction-Round-the Face (IRF) lattice models were computed using their relation to rational conformal field theories. Here, we focus on deriving solutions for the Boltzmann weights of the Interaction-Round the Face lattice model, specifically the unrestricted face model, based on the $\mathfrak{su}(3)_k$ affine Lie algebra. The admissibility conditions are defined by the adjoint representation. We find the BWs by determining the quantum $R$ matrix of the $U_q(\mathfrak{sl} (3))$ quantum algebra in the adjoint representation and then applying the so-called Vertex-IRF correspondence. The Vertex-IRF correspondence defines the BWs of IRF models in terms of $R$ matrix elements., Comment: one figure

Shadow formalism is a technique in two-dimensional CFT allowing straightforward computation of conformal blocks in the limit of infinitely large central charge. We generalize the construction of shadow operator for superconformal field theories. We demonstrate that shadow formalism yields known expressions for the large-c limit of the four-point superconformal block on a plane and of the one-point superconformal block on a torus. We also explicitly find the two-point global torus superconformal block in the necklace channel and check it against the Casimir differential equation.

While the nitrile group is by far the most prevalent one among interstellar molecules, the existence of interstellar dinitriles (molecules containing two -CN groups) has recently been proven. Here we report the discovery of two new dinitriles in the cold dense cloud TMC-1. These newly identified species are malononitrile, CH2(CN)2, and maleonitrile, the Z isomer of NC-CH=CH-CN, which can be seen as the result of substituting two H atoms with two -CN groups in methane and ethylene, respectively. These two molecules were detected using data from the ongoing QUIJOTE line survey of TMC-1 that is being carried out with the Yebes 40m telescope. We derive column densities of 1.8e11 cm-2 and 5.1e10 cm-2 for malononitrile and maleonitrile, respectively. This means that they are eight and three times less abundant than HCC-CH2-CN and (E)-HCC-CH=CH-CN, respectively, which are analog molecules detected in TMC-1 in which one -CN group is converted into a -CCH group. This is in line with previous findings in which -CCH derivatives are more abundant than the -CN counterparts in TMC-1. We examined the potential chemical pathways to these two dinitriles, and we find that while maleonitrile can be efficiently formed through the reaction of CN with CH2CHCN, the formation of malononitrile is not clear because the neutral-neutral reactions that could potentially form it are not feasible under the physical conditions of TMC-1., Comment: Accepted for publication in A&A Letters

We present the detection of the free radicals NC$_3$S and HC$_3$S towards TMC-1 with the QUIJOTE line survey. The derived column densities are (1.4$\pm$0.2)$\times$10$^{11}$ for NC$_3$S and (1.5$\pm$0.2)$\times$10$^{11}$ for HC$_3$S. We searched for NCCS, but only three transitions are within the domain of our QUIJOTE line survey and the observed lines are marginally detected at the 3$\sigma$ level, providing an upper limit to its column density of $\leq$6$\times$10$^{10}$ cm$^{-2}$. We also unsuccessfully searched for longer species of the NC$_n$S (n$\ge$4) and HC$_n$S (n$\ge$5) families in our TMC-1 data. A chemical model based on a reduced set of reactions involving HC$_3$S and NC$_3$S predicts abundances that are 10-100 times below the observed values. These calculations indicate that the most efficient reactions of formation of HC$_3$S and NC$_3$S in the model are S + C$_3$H$_2$ and N + HC$_3$S, respectively, while both radicals are very efficiently destroyed through reactions with neutral atoms., Comment: Article proposed for acceptance in Astronomy and Astrophysics on 5th July 2024

We present the first detection in space of 1,4-pentadiyne. It has been found towards TMC-1 with the QUIJOTE line survey in the 31-50 GHz range. We observed a total of 17 transitions with J = 2 up to 13 and Ka = 0, 1 and 2. The observed transitions allowed us to derive a rotational temperature of 9.5 +- 0.5 K and a column density of (5.0 +- 0.5) x 10^12 cm-2. This molecule was the last non-cyclic isomer of the C5H4 family that could be detected via radio astronomy. A computational chemistry study was performed to determine the energies of the five most stable isomers. The isomer (c-C3H3CCH) has a considerably higher energy than the others, and it has not yet been detected. To better understand the chemical reactions involving these species, we compared the ethynyl and cyano derivatives. The observed abundances of these species are in good agreement with the branching ratios of the formation reactions studied with our chemical model of TMC-1.

We infer the growth of large scale structure over the redshift range $0.4\lesssim z \lesssim 1$ from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latest Planck and ACT data. We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime. We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample. We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales. From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with $\Lambda$CDM with an overall amplitude that is $\simeq5-7\%$ lower than predicted by primary CMB measurements with modest $(\sim2\sigma)$ statistical significance. From the combined analysis of all four bins and their cross-correlations with Planck we obtain $S_8 = 0.765\pm0.023$, which is less discrepant with primary CMB measurements than previous DESI LRG cross Planck CMB lensing results. From the cross-correlation with ACT we obtain $S_8 = 0.790^{+0.024}_{-0.027}$, while when jointly analyzing Planck and ACT we find $S_8 = 0.775^{+0.019}_{-0.022}$ from our data alone and $\sigma_8 = 0.772^{+0.020}_{-0.023}$ with the addition of BAO data. These constraints are consistent with the latest Planck primary CMB analyses at the $\simeq 1.6-2.2\sigma$ level, and are in excellent agreement with galaxy lensing surveys., Comment: 60 pages, 26 figures, comments welcome

We present a high-significance cross-correlation of CMB lensing maps from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) with spectroscopically calibrated luminous red galaxies (LRGs) from the Dark Energy Spectroscopic Instrument (DESI). We detect this cross-correlation at a significance of 38$\sigma$; combining our measurement with the Planck Public Release 4 (PR4) lensing map, we detect the cross-correlation at 50$\sigma$. Fitting this jointly with the galaxy auto-correlation power spectrum to break the galaxy bias degeneracy with $\sigma_8$, we perform a tomographic analysis in four LRG redshift bins spanning $0.4 \le z \le 1.0$ to constrain the amplitude of matter density fluctuations through the parameter combination $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4}$. Prior to unblinding, we confirm with extragalactic simulations that foreground biases are negligible and carry out a comprehensive suite of null and consistency tests. Using a hybrid effective field theory (HEFT) model that allows scales as small as $k_{\rm max}=0.6$ $h/{\rm Mpc}$, we obtain a 3.3% constraint on $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4} = 0.792^{+0.024}_{-0.028}$ from ACT data, as well as constraints on $S_8^\times(z)$ that probe structure formation over cosmic time. Our result is consistent with the early-universe extrapolation from primary CMB anisotropies measured by Planck PR4 within 1.2$\sigma$. Jointly fitting ACT and Planck lensing cross-correlations we obtain a 2.7% constraint of $S_8^\times = 0.776^{+0.019}_{-0.021}$, which is consistent with the Planck early-universe extrapolation within 2.1$\sigma$, with the lowest redshift bin showing the largest difference in mean. The latter may motivate further CMB lensing tomography analyses at $z<0.6$ to assess the impact of potential systematics or the consistency of the $\Lambda$CDM model over cosmic time., Comment: Prepared for submission to JCAP (47 pages, 13 figures)

We report the first identification in space of HC$_3$N$^+$, the simplest member of the family of cyanopolyyne cations. Three rotational transitions with half-integer quantum numbers from $J$=7/2 to 11/2 have been observed with the Yebes 40m radio telescope and assigned to HC$_3$N$^+$, which has an inverted $^2\Pi$ ground electronic state. The three rotational transitions exhibit several hyperfine components due to the magnetic and nuclear quadrupole coupling effects of the H and N nuclei. We confidently assign the characteristic rotational spectrum pattern to HC$_3$N$^+$ based on the good agreement between the astronomical and theoretical spectroscopic parameters. We derived a column density of (6.0$\pm$0.6)$\times$10$^{10}$ cm$^{-2}$ and a rotational temperature of 4.5$\pm$1\,K. The abundance ratio between HC$_3$N and HC$_3$N$^+$ is 3200$\pm$320. As found for the larger members of the family of cyanopolyyne cations (HC$_5$N$^+$ and HC$_7$N$^+$), HC$_3$N$^+$ is mainly formed through the reactions of H$_2$ and the cation C$_3$N$^+$ and by the reactions of H$^+$ with HC$_3$N. In the same manner than other cyanopolyyne cations, HC$_3$N$^+$ is mostly destroyed through a reaction with H$_2$ and a dissociative recombination with electrons., Comment: Accepted as a Letter to the Editor in Astronomy & Astrophysics on June 28th 2024

Context. Solar filament eruptions usually appear to occur in association with the sudden explosive release of magnetic energy accumulated in long-lived arched magnetic structures. It is the released energy that occasionally drives fast-filament eruptions that can be source regions of coronal mass ejections. Aim. The goal of this paper is to investigate the dynamic processes of a fast-filament eruption by using unprecedented high-resolution full-disk H$\alpha$ imaging spectroscopy observations. Methods. The whole process of the eruption was captured in a wide spectral window of the H$\alpha$ line ($\pm9.0$ A). Applying the "cloud model" and obtaining two dimensional optical thickness spectra we derive the Doppler velocity, the true eruption profiles (height, velocity, and acceleration), and the trajectory of the filament eruption in 3D space. Results. The Doppler velocity maps show that the filament was predominantly blue-shifted. During the main and final process of the eruption, strongly blue-shifted materials are manifested traveling with velocities exceeding $250~km/s$. The spectral analysis further revealed that the erupting filament is made of multiple components, some of which were Doppler-shifted approximately to $-300 ~km/s$. It is found that the filament eruption attains a maximum true velocity and acceleration of about $600~km/s$ and $2.5~km/s^2$, respectively, and its propagation direction deviates from the radial direction. On the other hand, downflows manifested as red-shifted plasma close to the footpoints of the erupting filament move with velocities $45-125~ km/s$. We interpret these red-shifted signatures as draining material, and therefore mass loss of the filament that has implications for the dynamic and the acceleration process of the eruption. Furthermore, we have estimated the total mass of the H$\alpha$ filament resulting in $\sim$$5.4\times10^{15}g$., Comment: Accepted for publication in Astronomy & Astrophysics

Brain development involves a sequence of structural changes from early stages of the embryo until several months after birth. Currently, ultrasound is the established technique for screening due to its ability to acquire dynamic images in real-time without radiation and to its cost-efficiency. However, identifying abnormalities remains challenging due to the difficulty in interpreting foetal brain images. In this work we present a set of 104 2D foetal brain ultrasound images acquired during the 20th week of gestation that have been co-registered to a common space from a rough skull segmentation. The images are provided both on the original space and template space centred on the ellipses of all the subjects. Furthermore, the images have been annotated to highlight landmark points from structures of interest to analyse brain development. Both the final atlas template with probabilistic maps and the original images can be used to develop new segmentation techniques, test registration approaches for foetal brain ultrasound, extend our work to longitudinal datasets and to detect anomalies in new images.

We present the first X-ray spectropolarimetric results for Cygnus X-1 in its soft state from a campaign of five IXPE observations conducted during 2023 May-June. Companion multiwavelength data during the campaign are likewise shown. The 2-8 keV X-rays exhibit a net polarization degree PD=1.99%+/-0.13% (68% confidence). The polarization signal is found to increase with energy across IXPE's 2-8 keV bandpass. The polarized X-rays exhibit an energy-independent polarization angle of PA=-25.7+/-1.8 deg. East of North (68% confidence). This is consistent with being aligned to Cyg X-1's AU-scale compact radio jet and its pc-scale radio lobes. In comparison to earlier hard-state observations, the soft state exhibits a factor of 2 lower polarization degree, but a similar trend with energy and a similar (also energy-independent) position angle. When scaling by the natural unit of the disk temperature, we find the appearance of a consistent trendline in the polarization degree between soft and hard states. Our favored polarimetric model indicates Cyg X-1's spin is likely high (a* above ~0.96). The substantial X-ray polarization in Cyg X-1's soft state is most readily explained as resulting from a large portion of X-rays emitted from the disk returning and reflecting off the disk surface, generating a high polarization degree and a polarization direction parallel to the black hole spin axis and radio jet. In IXPE's bandpass, the polarization signal is dominated by the returning reflection emission. This constitutes polarimetric evidence for strong gravitational lensing of X-rays close to the black hole., Comment: 20 pages, accepted for publication in ApJL

We present the discovery with the QUIJOTE line survey of the cations HC5N+ and HC7N+ in the direction of TMC-1. Seven lines with half-integer quantum numbers from J=25/2-23/2 to 37/2-35/2 have been assigned to HC5N+ and eight lines from J=55/2-53/2 to 71/2-69/2 to HC7N+. Both species have inverted 2Pi ground electronic states with very good estimates for their B0 and AS0 constants based on optical observations. The lines with the lowest J of HC5N+ exhibit multiple components due to the hyperfine structure introduced by the H and N nuclei. However, these different components collapse for the higher J. No hyperfine structure is found for any of the lines of HC7N+. The derived effective rotational and distortion constants for HC5N+ are Beff = 1336.662+/- 0.001 MHz and Deff = 27.4+/-2.6 Hz, while for HC7N+ they are Beff = 567.85036+/-0.00037 MHz and Deff = 4.01+/-0.19 Hz. From the observed intensities, we derived Trot = 5.5+/-0.5K and N = (9.9+/-1.0)x 1010 cm-2 for HC5N+, while we obtained Trot = 8.5+/-0.5K and N = (2.3+/-0.2)x1010 cm-2 for HC7N+. The HC5N/HC5N+, C5N/HC5N+, C5N-/HC5N+, HC7N/HC7N+, HC5N+/HC7N+, and C7N-/HC7N+ abundance ratios are 670+/-80, 4.8+/-0.8, 1.2+/-0.2, 1000+/-150, 4.2+/-0.5, and 2.2+/-0.2, respectively. We have run chemical modelling calculations to investigate the formation and destruction of these new cations. We find that these species are mainly formed through the reactions of H2 and the cations C5N+ and C7N+, and by the reactions of H+ with HC5N and HC7N, while they are mostly destroyed through a reaction with H2 and a dissociative recombination with electrons. Based on the underestimation of the abundances of HC5N+ and HC7N+ by the chemical model by a factor around 20, we suggest that the rate coefficients currently assumed for the reactions of these cations with H2 could be too high by the same factor, something that will be worth investigating., Comment: Accepted as a Letter in Astronomy & Astrophysics on May 31st 2024

Continuous normalizing flows (CNFs) learn the probability path between a reference distribution and a target distribution by modeling the vector field generating said path using neural networks. Recently, Lipman et al. (2022) introduced a simple and inexpensive method for training CNFs in generative modeling, termed flow matching (FM). In this paper, we repurpose this method for probabilistic inference by incorporating Markovian sampling methods in evaluating the FM objective, and using the learned CNF to improve Monte Carlo sampling. Specifically, we propose an adaptive Markov chain Monte Carlo (MCMC) algorithm, which combines a local Markov transition kernel with a non-local, flow-informed transition kernel, defined using a CNF. This CNF is adapted on-the-fly using samples from the Markov chain, which are used to specify the probability path for the FM objective. Our method also includes an adaptive tempering mechanism that allows the discovery of multiple modes in the target distribution. Under mild assumptions, we establish convergence of our method to a local optimum of the FM objective. We then benchmark our approach on several synthetic and real-world examples, achieving similar performance to other state-of-the-art methods, but often at a significantly lower computational cost.

Background We aim to use Natural Language Processing (NLP) to automate the extraction and classification of thyroid cancer risk factors from pathology reports. Methods We analyzed 1,410 surgical pathology reports from adult papillary thyroid cancer patients at Mayo Clinic, Rochester, MN, from 2010 to 2019. Structured and non-structured reports were used to create a consensus-based ground truth dictionary and categorized them into modified recurrence risk levels. Non-structured reports were narrative, while structured reports followed standardized formats. We then developed ThyroPath, a rule-based NLP pipeline, to extract and classify thyroid cancer features into risk categories. Training involved 225 reports (150 structured, 75 unstructured), with testing on 170 reports (120 structured, 50 unstructured) for evaluation. The pipeline's performance was assessed using both strict and lenient criteria for accuracy, precision, recall, and F1-score. Results In extraction tasks, ThyroPath achieved overall strict F-1 scores of 93% for structured reports and 90 for unstructured reports, covering 18 thyroid cancer pathology features. In classification tasks, ThyroPath-extracted information demonstrated an overall accuracy of 93% in categorizing reports based on their corresponding guideline-based risk of recurrence: 76.9% for high-risk, 86.8% for intermediate risk, and 100% for both low and very low-risk cases. However, ThyroPath achieved 100% accuracy across all thyroid cancer risk categories with human-extracted pathology information. Conclusions ThyroPath shows promise in automating the extraction and risk recurrence classification of thyroid pathology reports at large scale. It offers a solution to laborious manual reviews and advancing virtual registries. However, it requires further validation before implementation., Comment: 21 pages, 6 figures, 7 tables

This paper explores the potential of large language models (LLMs) to make the Aeronautical Regulations of Colombia (RAC) more accessible. Given the complexity and extensive technicality of the RAC, this study introduces a novel approach to simplifying these regulations for broader understanding. By developing the first-ever RAC database, which contains 24,478 expertly labeled question-and-answer pairs, and fine-tuning LLMs specifically for RAC applications, the paper outlines the methodology for dataset assembly, expert-led annotation, and model training. Utilizing the Gemma1.1 2b model along with advanced techniques like Unsloth for efficient VRAM usage and flash attention mechanisms, the research aims to expedite training processes. This initiative establishes a foundation to enhance the comprehensibility and accessibility of RAC, potentially benefiting novices and reducing dependence on expert consultations for navigating the aviation industry's regulatory landscape. You can visit the dataset (https://huggingface.co/somosnlp/gemma-1.1-2b-it_ColombiaRAC_FullyCurated_format_chatML_V1) and the model (https://huggingface.co/datasets/somosnlp/ColombiaRAC_FullyCurated) here.

The employment of unmanned aerial vehicles (UAVs) aligned with multistatic sensing in integrated sensing and communication (ISAC) systems can provide remarkable performance gains in sensing, by taking advantage of the cell-free massive multiple-input multiple-output (mMIMO) architecture. Under these considerations, in this paper, the achievable sensing signal-to-noise-plus-interference ratio (SINR) of a cell-free mMIMO ISAC UAV-based network is evaluated for two different deployments of UAVs, namely, mobile and tethered. In both scenarios, a transmit precoder that jointly optimizes the sensing and communication requirements subjected to power constraints is designed. Specifically, for the scenario with mobile UAVs, beyond the transmit precoding, we also optimize the position of the transmit UAVs through particle swarm optimization (PSO). The results show that, although tethered UAVs have a more efficient power allocation, the proposed position control algorithm for the mobile UAVs can achieve a superior gain in terms of sensing SINR., Comment: Submitted to IEEE ICC'24 - SAC-13 ISAC Track

We present the detection of cyanothioketene, NCCHCS, in the laboratory and toward TMC-1. This transient species was produced through a discharge of a gas mixture of CH2CHCN and CS2 using argon as carrier gas, and its rotational spectrum between 9 and 40 GHz was characterized using a Balle-Flygare narrowband-type Fourier-transform microwave spectrometer. A total of 21 rotational transitions were detected in the laboratory, all of them exhibiting hyperfine structure induced by the spin of the N nucleus. The spectrum for NCCHCS was predicted in the domain of our line surveys using the derived rotational and distortion constants. The detection in the cold starless core TMC-1 was based on the QUIJOTE line survey performed with the Yebes 40m radio telescope. Twenty-three lines were detected with K_a=0, 1, and 2 and J_u=9 up to 14. The derived column density is (1.2+/-0.1)e11 cm-2 for a rotational temperature of 8.5+/-1 K. The abundance ratio of thioketene and its cyano derivative, H2CCS/NCCHCS, is 6.5+/-1.3. Although ketene is more abundant than thioketene by about 15 times, its cyano derivative NCCHCO surprisingly is not detected with a 3sigma upper level to the column density of 3.0e10 cm-2, which results in an abundance ratio H2CCO/NCCHCO > 430. Hence, the chemistry of CN derivatives seems to be more favored for S-bearing than for O-bearing molecules. We carried out chemical modeling calculations and found that the gas-phase neutral-neutral reactions CCN + H2CS and CN + H2CCS could be a source of NCCHCS in TMC-1., Comment: Accepted as a Letter in Astronomy & Astrophysics on May 2nd 2024. arXiv admin note: text overlap with arXiv:2311.13860, arXiv:2404.07585

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio $r$ from measurements of CMB polarization $B$-modes. Its nominal design targets a precision $\sigma(r=0) \leq 0.003$ without delensing. Achieving this goal and further reducing uncertainties requires the mitigation of other sources of large-scale $B$-modes such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate $r$ by including delensing within a cross-spectral likelihood, and demonstrate it on SO-like simulations. Lensing $B$-modes are synthesised using internal CMB lensing reconstructions as well as Planck-like CIB maps and LSST-like galaxy density maps. This $B$-mode template is then introduced into SO's power-spectrum-based foreground-cleaning algorithm by extending the likelihood function to include all auto- and cross-spectra between the lensing template and the SAT $B$-modes. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions (SEDs). In the absence of primordial $B$-modes, $\sigma(r)$ decreases by 37% as a result of delensing. Tensor modes at the level of $r=0.01$ are successfully detected by our pipeline. Even with more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of $r$ by employing the moment-expansion method. In this case, delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO's nominal sensitivity level. (Abridged), Comment: Updated version accepted by Physical Review D

We present a study of CH$_3$CH$_2$CCH, CH$_3$CH$_2$CN, CH$_2$CHCCH, and CH$_2$CHCN in TMC-1 using the QUIJOTE$^1$ line survey. We confirm the presence of CH$_3$CH$_2$CCH in TMC-1, which was previously reported as tentative by our group. From a detailed study of the ethynyl and cyanide derivatives of CH$_2$CH$_2$ and CH$_3$CH$_3$ in TMC-1, we found that the CH$_2$CHCCH/CH$_2$CHCN and CH$_3$CH$_2$CCH/CH$_3$CH$_2$CN abundance ratios are 1.5$\pm$0.1 and 4.8$\pm$0.5, respectively. The derived CH$_2$CHCCH/CH$_3$CH$_2$CCH abundance ratio is 15.3$\pm$0.8, and that of CH$_2$CHCN over CH$_3$CH$_2$CN is 48$\pm$5. All the single substituted isotopologs of vinyl cyanide have been detected, and we found that the first and second carbon substitutions in CH$_2$CHCN provide a $^{12}$C/$^{13}$C ratio in line with that found for other three-carbon bearing species such as HCCNC and HNCCC. However, the third $^{13}$C isotopolog, CH$_2$CH$^{13}$CN, presents an increase in its abundance similar to that found for HCCCN. Finally, we observed eight $b$-type transitions of CH$_2$CHCN, and we find that their intensity cannot be fitted adopting the dipole moment $\mu_b$ derived previously. These transitions involve the same rotational levels as those of the $a$-type transitions. From their intensity, we obtain $\mu_b$=0.80$\pm$0.03\,D, which is found to be in between earlier values derived in the laboratory using intensity measurements or the Stark effect. Our chemical model indicates that the abundances of CH$_3$CH$_2$CCH, CH$_3$CH$_2$CN, CH$_2$CHCCH, and CH$_2$CHCN observed in TMC-1 can be explained in terms of gas-phase reactions., Comment: Accepted as a Letter in Astronomy & Astrophysics on March 8th 2024

Training deep neural networks reliably requires access to large-scale datasets. However, obtaining such datasets can be challenging, especially in the context of neuroimaging analysis tasks, where the cost associated with image acquisition and annotation can be prohibitive. To mitigate both the time and financial costs associated with model development, a clear understanding of the amount of data required to train a satisfactory model is crucial. This paper focuses on an early stage phase of deep learning research, prior to model development, and proposes a strategic framework for estimating the amount of annotated data required to train patch-based segmentation networks. This framework includes the establishment of performance expectations using a novel Minor Boundary Adjustment for Threshold (MinBAT) method, and standardizing patch selection through the ROI-based Expanded Patch Selection (REPS) method. Our experiments demonstrate that tasks involving regions of interest (ROIs) with different sizes or shapes may yield variably acceptable Dice Similarity Coefficient (DSC) scores. By setting an acceptable DSC as the target, the required amount of training data can be estimated and even predicted as data accumulates. This approach could assist researchers and engineers in estimating the cost associated with data collection and annotation when defining a new segmentation task based on deep neural networks, ultimately contributing to their efficient translation to real-world applications.

We construct weak solutions of the anisotropic inverse mean curvature flow (A-IMCF) under very mild assumptions both on the anisotropy (which is simply a norm in $\mathbb R^N$ with no ellip\-ticity nor smoothness requirements, in order to include the crystalline case) and on the initial data. By means of an approximation procedure introduced by Moser, our solutions are limits of anisotropic $p$-harmonic functions or $p$-capacitary functions (after a change of variable), and we get uniqueness both for the approximating solutions (i.e., uniqueness of $p$-capacitary functions) and the limiting ones. Our notion of weak solution still recovers variational and geometric definitions similar to those introduced by Huisken-Ilmanen, but requires to work within the broader setting of $BV$-functions. Despite of this, we still reach classical results like the continuity and exponential growth of perimeter, as well as outward minimizing properties of the sublevel sets. Moreover, by assuming the extra regularity given by an interior rolling ball condition (where a sliding Wulff shape plays the role of a ball), the solutions are shown to be continuous and satisfy Harnack inequalities. Finally, examples of explicit solutions are built.

The pseudopotential and free energy models are two popular extensions of the lattice Boltzmann method for multiphase flows. Until now, they have been developed apart from each other in the literature. However, important questions about whether each method performs better needs to be solved. In this work, we perform a theoretical and numerical comparison between both methods. This comparison is only possible because we developed a novel approach for controlling the interface thickness in the pseudopotential method independently on the equation of state. In this way, it is possible to compare both methods maintaining the same equilibrium densities, interface thickness, surface tension and equation of state parameters. The well-balanced approach was selected to represent the free energy. We found that the free energy one is more practical to use, as it is not necessary to carry out previous simulations to determine simulation parameters (interface thickness, surface tension, etc). In addition, the tests proofed that the free energy model is more accurate than the pseudopotential model. Furthermore, the pseudopotential method suffers from a lack of thermodynamic consistency even when applying the corrections proposed in the literature. On the other hand, for both static and dynamic tests we verified that the pseudopotential method is more stable than the free energy one, allowing simulations with lower reduced temperatures. We hope that these results will guide authors in the use of each method., Comment: 20 pages, 9 figures

An important question in dynamical systems is the classification problem, i.e., the ability to distinguish between two isomorphic systems. In this work, we study the topological factors between a family of multidimensional substitutive subshifts generated by morphisms with uniform support. We prove that it is decidable to check whether two minimal aperiodic substitutive subshifts are isomorphic. The strategy followed in this work consists of giving a complete description of the factor maps between these subshifts. Then, we deduce some interesting consequences on coalescence, automorphism groups, and the number of aperiodic symbolic factors of substitutive subshifts. We also prove other combinatorial results on these substitutions, such as the decidability of defining a subshift, the computability of the constant of recognizability, and the conjugacy between substitutions with different supports., Comment: Changes given by the referee's comments

BlackJAX is a library implementing sampling and variational inference algorithms commonly used in Bayesian computation. It is designed for ease of use, speed, and modularity by taking a functional approach to the algorithms' implementation. BlackJAX is written in Python, using JAX to compile and run NumpPy-like samplers and variational methods on CPUs, GPUs, and TPUs. The library integrates well with probabilistic programming languages by working directly with the (un-normalized) target log density function. BlackJAX is intended as a collection of low-level, composable implementations of basic statistical 'atoms' that can be combined to perform well-defined Bayesian inference, but also provides high-level routines for ease of use. It is designed for users who need cutting-edge methods, researchers who want to create complex sampling methods, and people who want to learn how these work., Comment: Companion paper for the library https://github.com/blackjax-devs/blackjax Update: minor changes and updated the list of authors to include technical contributors

Context. Stars that are found on the blue horizontal-branch (BHB) have evolved from low-mass stars that have completed their core hydrogen burning main sequence stage and have undergone the helium flash at the end of their red-giant phase. The fact that their luminosity is virtually constant at all effective temperatures also makes them good standard candles. Aims. We provide a catalogue of BHB stars with stellar parameters that have been calculated from spectral energy distributions (SED), as constructed from multiple large-scale photometric surveys. In addition, we update our previous, Gaia Early Data Release 3 catalogue of BHB stars with parallax errors less than 20% by using the SED results to define the selection criteria. Methods. We selected a large dataset of Gaia Data Release 3 (DR3) objects based only on their position in the colour magnitude diagram, tangential velocity and parallax errors. Spectral energy distributions were then used to evaluate contamination levels in the dataset and derive optimised data quality acceptance constraints. This allowed us to extend the Gaia DR3 colour and absolute magnitude criteria further towards the extreme horizontal-branch. The level of contamination found using SED analysis was confirmed by acquiring spectra using the Ondrejov Echelle spectrograph attached to the Perek 2m telescope at the Astronomical Institute of the Czech Academy of Sciences. Results. We present a catalogue of 9,172 Galactic Halo BHB candidate stars with atmospheric and stellar parameters calculated from synthetic SEDs. We also present an extended Gaia DR3 based catalogue of 22,335 BHB candidate stars with a wider range of effective temperatures and Gaia DR3 parallax errors of less than 20%. This represents an increase of 33% compared to the our 2021 catalogue, with a contamination level of 10%., Comment: 15 pages, 12 figures, 1 data file

Predictive models make mistakes. Hence, there is a need to quantify the uncertainty associated with their predictions. Conformal inference has emerged as a powerful tool to create statistically valid prediction regions around point predictions, but its naive application to regression problems yields non-adaptive regions. New conformal scores, often relying upon quantile regressors or conditional density estimators, aim to address this limitation. Although they are useful for creating prediction bands, these scores are detached from the original goal of quantifying the uncertainty around an arbitrary predictive model. This paper presents a new, model-agnostic family of methods to calibrate prediction intervals for regression problems with local coverage guarantees. Our approach is based on pursuing the coarsest partition of the feature space that approximates conditional coverage. We create this partition by training regression trees and Random Forests on conformity scores. Our proposal is versatile, as it applies to various conformity scores and prediction settings and demonstrates superior scalability and performance compared to established baselines in simulated and real-world datasets. We provide a Python package clover that implements our methods using the standard scikit-learn interface.

We report the first detection in space of a complete sample of nine doubly substituted isotopologues of HCCCN towards the cyanopolyyne peak of TMC-1 using observations of the QUIJOTE line survey taken with the Yebes 40 m telescope. We detected D13CCCN, DC13CCN, DCC13CN, DCCC15N, H13C13CCN, H13CC13CN, HC13C13CN, HCC13C15N, and HC13CC15N through their J=4-3 and J=5-4 lines in the 7 mm window. In addition, we present an extensive analysis of the emission of HCCCN and its singly substituted isotopologues through a large velocity gradient model of the lines detected at 7 mm and 3 mm using the Yebes 40 m and the IRAM 30 m telescopes, respectively. The derived column densities for all the isotopologues are consistent in the two spectral bands for an H2 volume density of 1e4 cm-3 and a kinetic temperature of 10 K. Whereas we observed a 13C fractionation for HCC13CN and other double isotopologues with a 13C atom adjacent to the nitrogen atom, we derived similar C/13C abundance ratios for the three 13C substituted species of DCCCN. This suggests additional chemical discrimination for deuterated isotopologues of HCCCN. Finally, we present the spatial distribution of the J=4-3 and J=5-4 lines from the singly substituted species observed with the Yebes 40 m telescope. The emission peak of the spatial distribution of DCCCN appears to be displaced by 40'' with respect to that of HCCCN and the 13C and 15N isotopologues. In addition to a different formation route for the deuterated species, we could also expect that this differentiation owing to the deuterium fractionation is more efficient at low temperatures, and therefore, that deuterated species trace a colder region of the cloud., Comment: Accepted for publication in A&A

We present the detection of the three 13C isotopologs of HCCNC and HNCCC toward TMC-1 using the QUIJOTE line survey. In addition, the D species has also been detected for these two isomers of HCCCN, whereas the 15N isotopolog was only detected for HCCNC. Using high-J lines of HCCNC and HNCCC, we were able to derive very precise rotational temperatures, column densities, and subsequently the isotopic abundance ratios. We found that 12C/13C is around 90 for the three possible substitutions in both isomers. These results are slightly different from what has been found for the most abundant isomer HCCCN, for which abundances of 105, 95, and 66 were found for each one of the three possible positions of 13C. The H/D abundance ratio was found to be 31+/-4 for HCCNC and of 53+/-6 for HNCCC. The latter is similar to the H/D abundace ratio derived for HCCCN (59). The 14N/15N isotopic abundance ratio in HCCNC is 243+/-24., Comment: Accepted as a Letter in Astronomy & Astrophysics on 22 January 2024

We present the first detection of HCNS (thiofulminic acid) in space with the QUIJOTE line survey in the direction of TMC-1. We performed a complete study of the isomers of CHNS and CHNO, including NCO and NCS. The derived column densities for HCNS, HNCS, and HSCN are (9.0+/-0.5)e9, (3.2+/-0.1)e11, and (8.3+/-0.4)e11 cm-2, respectively. The HNCS/HSCN abundance ratio is 0.38. The abundance ratios HNCO/HNCS, HCNO/HCNS, HOCN/HSCN, and NCO/NCS are 34+/-4, 8.3+/-0.7, 0.18+/-0.03, and 0.78+/-0.07, respectively. These ratios cannot be correctly reproduced by our gas-phase chemical models, which suggests that formation paths for these species are missing, and/or that the adopted dissociative recombination rates for their protonated precursors have to be revised. The isotopologues H15NCO, DNCO, N13CO, DCNO, H34SCN, and DSCN have also been detected with the ultrasensitive QUIJOTE line survey., Comment: Accepted as a Letter in Astronomy & Astrophysics on 09 January 2024

We study $\mathfrak{sl}_2$ and $\mathfrak{sl}_3$ global conformal blocks on a sphere and a torus, using the shadow formalism. These blocks arise in the context of Virasoro and $\mathcal{W}_3$ conformal field theories in the large central charge limit. In the $\mathfrak{sl}_2$ case, we demonstrate that the shadow formalism yields the known expressions in terms of conformal partial waves. Then, we extend this approach to the $\mathfrak{sl}_3$ case and show that it allows to build simple integral representations for $\mathfrak{sl}_3$ global blocks. We demonstrate this construction on two examples: the four-point block on the sphere and the one-point torus block.

The early Universe, spanning 400,000 to 400 million years after the Big Bang ($z\approx1100-11$), has been left largely unexplored as the light from luminous objects is too faint to be observed directly. While new experiments are pushing the redshift limit of direct observations, measurements in the low-frequency radio band promise to probe early star and black hole formation via observations of the hydrogen 21-cm line. In this work we explore synergies between 21-cm data from the HERA and SARAS 3 experiments and observations of the unresolved radio and X-ray backgrounds using multi-wavelength Bayesian analysis. We use the combined data set to constrain properties of Population II and Population III stars as well as early X-ray and radio sources. The joint fit reveals a 68 percentile disfavouring of Population III star formation efficiencies $\gtrsim5.7\%$. We also show how the 21-cm and the X-ray background data synergistically constrain opposite ends of the X-ray efficiency prior distribution to produce a peak in the 1D posterior of the X-ray luminosity per star formation rate. We find (at 68\% confidence) that early galaxies were likely 0.3 to 318 times as X-ray efficient as present-day starburst galaxies. We also show that the functional posteriors from our joint fit rule out global 21-cm signals deeper than $\lesssim-203\ \mathrm{mK}$ and power spectrum amplitudes at $k=0.34\ h\mathrm{Mpc^{-1}}$ greater than $\Delta_{21}^2 \gtrsim 946\ \mathrm{mK}^2$ with $3\sigma$ confidence.

Van der Waals heterostructures are promising for adding new functionalities to two-dimensional materials. In this study, we focus on single photon emitters hosted in one layer and adjacent to other insulating two-dimensional material. Specifically, we show how the emission energy is modified by such a heterostructure. We developed a general approach to elucidate the mechanisms affecting the emission energy and studied the particular case of carbon substitutions in the hexagonal boron nitride bilayer., Comment: ACS Appl. Nano Mater