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In this work, we present the detection of twelve doublets with quantum numbers of N=12-11 to N=17-16 of the v11 vibrationally excited state of C6H towards TMC-1. This marks the first time that an excited vibrational state of a molecule has been detected in a cold starless core. The data are part of the QUIJOTE line survey gathered with the Yebes 40m radio telescope. The line intensities have been aptly reproduced with a rotational temperature of 6.2 +/- 0.4K and a column density of (1.2+/-0.2)e11 cm-2. We also analysed the ground state transitions of C6H, detecting fourteen lines with quantum numbers of J = 23/2-21/2 to J = 35/2 for each of the two 2Pi_3/2 and 2Pi_1/2 ladders. It is not possible to model the intensities of all the transitions of the ground state simultaneously using a single column density. We considered the two ladders as two different species and found that the rotational temperature is the same for both ladders, Trot(2Pi_3/2)=Trot(2Pi_1/2)=6.2+/-0.2, achieving a result that is comparable to that of the v11 state. The derived column densities are N(2Pi_3/2)(6.2+/-0.3)e12cm-2 and N(2Pi_1/2)=(8.0+/-0.4)e10cm-2. The fraction of C6H molecules in its 2Pi_3/2, 2Pi_1/2, and v11 states is 96.8 %, 1.3 %, and 1.9 %, respectively. Finally, we report that this vibrational mode has also been detected towards the cold cores Lupus-1A and L1495B, as well as the low-mass star forming cores L1527 and L483, with fractions of C6H molecules in this mode of 3.8%, 4.1%, 14.8%, and 6%, respectively., Comment: Accepted as a Letter in Astronomy & Astrophysics on 17/11/2023

A good knowledge of pollutant time series behavior is fundamental to elaborate strategies and construct tools to protect human health. In Caribbean area, air quality is frequently deteriorated by the transport of African dust. In the literature, it is well known that exposure to particulate matter with an aerodynamic diameter of 10 {\mu}m or less (PM10) have many adverse health effects as respiratory and cardiovascular diseases. To our knowledge, no study has yet performed an analysis of PM10 time series using complex network framework. In this study, the so-called Visibility Graph (VG) method is used to describe PM10 dynamics in Guadeloupe archipelago with a database of 11 years. Firstly, the fractal nature of PM10 time series is highlighted using degree distribution for all data, low dust season (October to April) and high dust season (May to September). Thereafter, a profound description of PM10 time series dynamics is made using multifractal analysis through two approaches, i.e. Renyi and singularity spectra. Achieved results are consistent with PM10 behavior in the Caribbean basin. Both methods showed a higher multifractality degree during the low dust season. In addition, multifractal parameters exhibited that the low dust season has the higher recurrence and the lower uniformity degrees. Lastly, centrality measures (degree, closeness and betweenness) highlighted PM10 dynamics through the year with a decay of centrality values during the high dust season. To conclude, all these results clearly showed that VG is a robust tool to describe times series properties.

The usage of multilayer complex networks for the analysis of correlations among environmental variables (such as O3 and NO2 concentrations from the photochemical smog) is investigated in this work. The mentioned technique is called Multiplex Visibility Graphs (MVG). By performing the joint analysis of those layers, the parameters named Average Edge Overlap and Interlayer Mutual Information are extracted, which accounts for the microscopical time coherence and the correlation between the time series behavior, respectively. These parameters point to the possibility of using them independently to describe the correlation between atmospheric pollutants (which could be extended to environmental time series). More precisely the first one of them is considered to be a potential new approach to determine the time required for the correlation of NO2 and O3 to be observed, since it is obtained from the correlation of the pollutants at the smallest time scale. As for the second one, it has been checked that the proposed technique can be used to describe the variation of the correlation between the two gases along the seasons. In short, MVGs parameters are introduced and results show that they could be potentially used in a future for correlation studies, supplementing already existing techniques., Comment: 29 pages, 7 figures

Recently, a set of graph-based tools have been introduced for the identification of singular events of O3, NO2 and temperature time series, as well as description of their dynamics. These are based on the use of the Visibility Graphs (VG). In this work, an improvement of the original approach is proposed, being called Upside-Down Visibility Graph (UDVG). It adds the possibility of investigating the singular lowest episodes, instead of the highest. Results confirm the applicability of the new method for describing the multifractal nature of the underlying O3, NO2, and temperature. Asymmetries in the NO2 degree distribution are observed, possibly due to the interaction with different chemicals. Furthermore, a comparison of VG and UDVG has been performed and the outcomes show that they describe opposite subsets of the time series (low and high values) as expected. The combination of the results from the two networks is proposed and evaluated, with the aim of obtaining all the information at once. It turns out to be a more complete tool for singularity detection in photochemical time series, which could be a valuable asset for future research., Comment: 35 pages, 7 figures

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Holder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature., Comment: 32 pages, 7 figures

This paper reports the results of research on PM10 wet scavenging by rainfall using a new multilayer complex networks called Multiplex Visibility Graphs (MVG). To the best of our knowledge, this work is the first to assess PM10 wet deposition using multivariate time series according to African dust seasonality. We considered 11 years of daily PM10 and rainfall data from the Guadeloupe archipelago. To analyse the impact of rainfall on PM10 behaviour, two MVG parameters were computed: the average edge overlap ({\omega}) and the interlayer mutual information (IPM). On the 1-d scale, the {\omega} results showed that the wet scavenging process was higher during the second half of the year when the high dust season and the rainy season are juxtaposed. This highlights a greater correlation between the microscopic structure of the signal, and the impact of rainfall on PM10 concentrations is more significant when the atmosphere is loaded with dust. The joint probability computed between the PM10 and rainfall nodes confirmed this trend. The IPM results indicated a correlation between PM10 and rainfall structures throughout the year. Furthermore, IPM values were higher during the transition periods between winter and summer (and vice versa). Our study showed that MVG is a powerful technique for investigating the relationship between at least two nonlinear time series using a multivariate time series.

In the literature, several epidemiological studies have already associated respiratory and cardiovascular diseases to acute exposure of mineral dust. However, frail people are also sensitive to chronic exposure to particulate matter with an aerodynamic diameter 10{\mu}m or less (PM10). Consequently, it is crucial to better understand PM10 fluctuations at all scales. This study investigates PM10 background atmosphere in the Caribbean area according to African dust seasonality with complex network framework. For that purpose, the regular Visibility Graph (VG) and the new Upside-Down Visibility Graph (UDVG) are used for a multifractal analysis. Firstly, concentration vs degree (v-k) plots highlighted that high degree values (hubs behavior) are related to the highest PM10 concentrations in VG while hubs is associated to the lowest concentrations in UDVG, i.e. probably the background atmosphere. Then, the degree distribution analysis showed that VG and UDVG difference is reduced for high dust season contrary to the low one. As regards the multifractal analysis, the multifractal degree is higher for the low season in VG while it is higher for the high season in UDVG. The degree distribution behavior and the opposite trend in multifractal degree for UDVG are due to the increase of PM10 background atmosphere during the high season, i.e. from May to September. To sum up, UDGV is an efficient tool to perform noise fluctuations analysis in environmental time series where low concentrations play an important role as well.

Previous works have analysed the relationship existing between reference evapotranspiration (ET0) and other climatic variables under a one-at-a-time perturbation condition. However, due to the physical relationships between these climatic variables is advisable to study their joint influence on ET0. The box-counting joint multifractal algorithm describes the relations between variables using relevant information extracted from the data singularities. This work investigated the use of this algorithm to describe the simultaneous behaviour of ET0, calculated by means of Penman-Monteith (PM) equation, and relative humidity (RH) and air temperature (T), influencing on it in the middle zone of the Guadalquivir river valley, Andalusia, southern Spain. The studied cases were grouped according to the fractal dimension values, which were related to their probability of occurrence. The most likely cases were linked to smooth behaviour and weak dependence between variables, both circumstances were detected in the local multifractal analysis. For these cases, the rest of Penman Monteith (PM) equation variables, neither the T nor the RH, seemed to influence on ET0 determination, especially when low T values were involved. By contrast, the least frequent cases were those with variables showing high fluctuations and strong relationship between them. In these situations, when T is low, the ET0 is affected by the rest of PM equation variables. This fact confirmed T as main driver of ET0 because the higher T values the lesser influence of other climate variables on ET0. Joint multifractal analysis shows some limitations when it is applied to large number of variables, the results reported are promising and suggest the convenience of exploring the relationships between ET0 and other climatic variables not considered here with this framework such as wind speed and net radiation., Comment: 40 pages, 10 figures

A new alternative method to approximate the Visibility Graph (VG) of a time series has been introduced here. It exploits the fact that most of the nodes in the resulting network are not connected to those that are far away from them. This means that the adjacency matrix is almost empty, and its nonzero values are close to the main diagonal. This new method is called Sliding Visibility Graph (SVG). Numerical tests have been performed for several time series, showing a time efficiency that scales linearly with the size of the series [O(N)], in contrast to the original VG that does so quadratically [O(N2)]. This fact is noticeably convenient when dealing with very large time series. The results obtained from the SVG of the studied time series have been compared to the exact values of the original VG. As expected, the SVG outcomes converge very rapidly to the desired ones, especially for random and stochastic series. Also, this method can be extended to the analysis of time series that evolve in real time, since it does not require the entire dataset to perform the analysis but a shorter segment of it. The length segment can remain constant, making possible a simple analysis as the series evolves in time., Comment: 33 pages, 8 figures

In this work, an analysis of multifractal parameters of daily precipitation series over the Iberian Peninsula was performed in two 30-year periods to explore whether these properties follow any pattern. Fluctuations of precipitation series show three different scaling regions. Only two distinct regimes for small and large timescales can be confirmed, while intermediate scales are part of a transition region. It is also observed a certain degree of multifractality, which is higher for small timescales. At these scales, there is a high persistence which follows the spatial gradient of the annual precipitation. Moreover, multifractal parameters of the precipitation are modified according to complex spatial and temporal patterns. Only persistence uniformly decreases in the last period. Other relevant findings are the changes in the asymmetry of multifractal spectra in the eastern belt at larger timescales, which might be related to the change in the behavior of the Mediterranean cyclones., Comment: 12 pages, 8 figures

Tropospheric ozone (O3) time series have been converted into complex networks through the recent so-called Visibility Graph (VG), using the data from air quality stations located in the western part of Andalusia (Spain). The aim is to apply this novel method to differentiate the behavior between rural and urban regions when it comes to the ozone dynamics. To do so, some centrality parameters of the resulting complex networks have been investigated: the degree, betweenness and shortest path. Some of them are expected to corroborate previous works in order to support the use of this technique; while others to supply new information. Results coincide when describing the difference that tropospheric ozone exhibits seasonally and geographically. It is seen that ozone behavior is fractal, in accordance to previous works. Also, it has been demonstrated that this methodology is able to characterize the divergence encountered between measurements in urban environments and countryside. In addition to that, the promising outcomes of this technique support the use of complex networks for the study of air pollutants dynamics. Particularly, new nuances are offered such as the identification and description of singularities in the signal., Comment: 27 pages, 7 figures, 1 graphical abstract

A recent method based on the concurrence of complex networks and multifractal analyses is applied for the first time to explore ground-level ozone behavior. Ozone time series are converted into complex networks for their posterior analysis. The searched purpose is to check the suitability of this transformation and to see whether some features of these complex networks could constitute a preliminary analysis before the more thorough multifractal formalism. Results show effectively that the exposed transformation stores the original information about the ozone dynamics and gives meaningful knowledge about the time series. Based on these results, the multifractal analysis of the complex networks is performed. Looking at the physical meaning of the multifractal properties (such as fractal dimensions and singularity spectrum), a relationship between those and the degree distribution of the complex networks is found. In addition to all the promising results, this novel connection between time series and complex networks can deal with both stationary and non-stationary time series, overcoming one of the main limitations of multifractal analysis. Therefore, this technique can be regarded as an alternative to give supplementary information within the study of complex signals., Comment: 34 pages, 8 figures, 1 graphical abstract

In the last decades, an ever-growing number of studies are focusing on the extreme weather conditions related to the climate change. Some of them are based on multifractal approaches, such as the Multifractal Detrended Fluctuation Analysis (MF-DFA), which has been used in this work. Daily diurnal temperature range (DTR), maximum, minimum and mean temperature from five coastal and five mainland stations in Spain have been analyzed. For comparison, two periods of 30 years have been considered: 1960-1989 and 1990-2019. By using the MF-DFA method, generalized Hurst exponents and multifractal spectra have been obtained. Outcomes corroborate that all these temperature variables have multifractal nature and show changes in multifractal properties between both periods. Also, Hurst exponents values indicate that all time series exhibit long-range correlations and a stationary behavior. Coastal locations exhibit in general wider spectra for minimum and mean temperature than for maximum and DTR, in both periods. On the contrary, the mainland ones do not show this pattern. Also, width from multifractal spectra of these two variables (minimum and mean temperature) is shortened in the last period in almost every case. To authors' mind, changes in multifractal features might be related to the climate change experienced in the studied region. Furthermore, reduction of spectra width for minimum and mean temperature implies a decrease of the complexity of these temperature variables between both studied periods. Finally, the wider spectra found in coastal stations might be useful as a discriminator element to improve climate models., Comment: 35 pages, 8 figures, 1 graphical abstract

For a ${\mathbb Z}^{d}$-topological dynamical system $(X, T, {\mathbb Z}^{d})$, an isomomorphism is a self-homeomorphism $\phi : X\to X$ such that for some matrix $M\in {\rm GL}(d,{\mathbb Z})$ and any ${n}\in {\mathbb Z}^{d}$, $\phi\circ T^{{n}}=T^{M{n}}\circ \phi$, where $T^{n}$ denote the self-homeomorphism of $X$ given by the action of ${n}\in {\mathbb Z}^d$. The collection of all the isomorphisms forms a group that is the normalizer of the set of transformations $T^{n}$. In the one-dimensional case, isomorphisms correspond to the notion of flip conjugacy of dynamical systems and by this fact are also called reversing symmetries. These isomorphisms are not well understood even for classical systems. We present a description of them for odometers and more precisely for constant-base ${\mathbb Z}^{2}$-odometers, which is surprisingly not simple. We deduce a complete description of the isomorphisms of some minimal ${\mathbb Z}^{d}$-substitutive subshifts. This enables us to provide the first example known of a minimal zero-entropy subshift with the largest possible normalizer group., Comment: 30 pages, 4 figures

A key challenge in the search for primordial B-modes is the presence of polarized Galactic foregrounds, especially thermal dust emission. Power-spectrum-based analysis methods generally assume the foregrounds to be Gaussian random fields when constructing a likelihood and computing the covariance matrix. In this paper, we investigate how non-Gaussianity in the dust field instead affects CMB and foreground parameter inference in the context of inflationary B-mode searches, capturing this effect via modifications to the dust power-spectrum covariance matrix. For upcoming experiments such as the Simons Observatory, we find no dependence of the tensor-to-scalar ratio uncertainty $\sigma(r)$ on the degree of dust non-Gaussianity or the nature of the dust covariance matrix. We provide an explanation of this result, noting that when frequency decorrelation is negligible, dust in mid-frequency channels is cleaned using high-frequency data in a way that is independent of the spatial statistics of dust. We show that our results hold also for non-zero levels of frequency decorrelation that are compatible with existing data. We find, however, that neglecting the impact of dust non-Gaussianity in the covariance matrix can lead to inaccuracies in goodness-of-fit metrics. Care must thus be taken when using such metrics to test B-mode spectra and models, although we show that any such problems can be mitigated by using only cleaned spectrum combinations when computing goodness-of-fit statistics., Comment: 16 pages, 8 figures, accepted version

We present tomographic measurements of structure growth using cross-correlations of Atacama Cosmology Telescope (ACT) DR6 and Planck CMB lensing maps with the unWISE Blue and Green galaxy samples, which span the redshift ranges $0.2 \lesssim z \lesssim 1.1$ and $0.3 \lesssim z \lesssim 1.8$, respectively. We improve on prior unWISE cross-correlations not just by making use of the new, high-precision ACT DR6 lensing maps, but also by including additional spectroscopic data for redshift calibration and by analysing our measurements with a more flexible theoretical model. An extensive suite of systematic and null tests within a blind analysis framework ensures that our results are robust. We determine the amplitude of matter fluctuations at low redshifts ($z\simeq 0.2-1.6$), finding $S_8 \equiv \sigma_8 (\Omega_m / 0.3)^{0.5} = 0.813 \pm 0.021$ using the ACT cross-correlation alone and $S_8 = 0.810 \pm 0.015$ with a combination of Planck and ACT cross-correlations; these measurements are fully consistent with the predictions from primary CMB measurements assuming standard structure growth. The addition of Baryon Acoustic Oscillation data breaks the degeneracy between $\sigma_8$ and $\Omega_m$, allowing us to measure $\sigma_8 = 0.813 \pm 0.020$ from the cross-correlation of unWISE with ACT and $\sigma_8 = 0.813\pm 0.015$ from the combination of cross-correlations with ACT and Planck. These results also agree with the expectations from primary CMB extrapolations in $\Lambda$CDM cosmology; the consistency of $\sigma_8$ derived from our two redshift samples at $z \sim 0.6$ and $1.1$ provides a further check of our cosmological model. Our results suggest that structure formation on linear scales is well described by $\Lambda$CDM even down to low redshifts $z\lesssim 1$., Comment: 73 pages (incl. 31 pages of appendices), 52 figures, 16 tables, published in ApJ. Watch G. S. Farren and A. Krolewski discuss the analysis and results under https://cosmologytalks.com/2023/09/11/act-unwise

This paper proposes an unmanned aerial vehicle (UAV)-based distributed sensing framework that uses orthogonal frequency-division multiplexing (OFDM) waveforms to detect the position of a ground target, and UAVs operate in half-duplex mode. A spatial grid approach is proposed, where an specific area in the ground is divided into cells of equal size, then the radar cross-section (RCS) of each cell is jointly estimated by a network of dual-function UAVs. For this purpose, three estimation algorithms are proposed employing the maximum likelihood criterion, and digital beamforming is used for the local signal acquisition at the receive UAVs. It is also considered that the coordination, fusion of sensing data, and central estimation is performed at a certain UAV acting as a fusion center (FC). Monte Carlo simulations are performed to obtain the absolute estimation error of the proposed framework. The results show an improved accuracy and resolution by the proposed framework, if compared to a single monostatic UAV benchmark, due to the distributed approach among the UAVs. It is also evidenced that a reduced overhead is obtained when compared to a general compressive sensing (CS) approach.

Security provisioning for low-complex and constrained devices in the Internet of Things (IoT) is exacerbating the concerns for the design of future wireless networks. To unveil the full potential of the sixth generation (6G), it is becoming even more evident that security measurements should be considered at all layers of the network. This work aims to contribute in this direction by investigating the employment of unmanned aerial vehicles (UAVs) for providing secure transmissions in ground IoT networks. Toward this purpose, it is considered that a set of UAVs acting as aerial base stations provide secure connectivity between the network and multiple ground nodes. Then, the association of IoT nodes, the 3D positioning of the UAVs and the power allocation of the UAVs are obtained by leveraging game theoretic and convex optimization-based tools with the goal of improving the secrecy of the system. It is shown that the proposed framework obtains better and more efficient secrecy performance over an IoT network than state-of-the-art greedy algorithms for positioning and association.

The aim of this paper is to analyse the Bitcoin in order to shed some light on its nature and behaviour. We select 9 cryptocurrencies that account for almost 75\% of total market capitalisation and compare their evolution with that of a wide variety of traditional assets: commodities with spot and futures contracts, treasury bonds, stock indices, growth and value stocks. Fractal geometry will be applied to carry out a careful statistical analysis of the performance of the Bitcoin returns. As a main conclusion, we have detected a high degree of persistence in its prices, which decreases the efficiency but increases its predictability. Moreover, we observe that the underlying technology influences price dynamics, with fully decentralised cryptocurrencies being the only ones to exhibit self-similarity features at any time scale.

Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct therapeutic strategy. Deep learning models have shown promise for automatically segmenting MS lesions, but the scarcity of accurately annotated data hinders progress in this area. Obtaining sufficient data from a single clinical site is challenging and does not address the heterogeneous need for model robustness. Conversely, the collection of data from multiple sites introduces data privacy concerns and potential label noise due to varying annotation standards. To address this dilemma, we explore the use of the federated learning framework while considering label noise. Our approach enables collaboration among multiple clinical sites without compromising data privacy under a federated learning paradigm that incorporates a noise-robust training strategy based on label correction. Specifically, we introduce a Decoupled Hard Label Correction (DHLC) strategy that considers the imbalanced distribution and fuzzy boundaries of MS lesions, enabling the correction of false annotations based on prediction confidence. We also introduce a Centrally Enhanced Label Correction (CELC) strategy, which leverages the aggregated central model as a correction teacher for all sites, enhancing the reliability of the correction process. Extensive experiments conducted on two multi-site datasets demonstrate the effectiveness and robustness of our proposed methods, indicating their potential for clinical applications in multi-site collaborations., Comment: 11 pages, 4 figures, journal submission

Interaction-Round the Face (IRF) models are two-dimensional lattice models of statistical mechanics defined by an affine Lie algebra and admissibility conditions depending on a choice of representation of that affine Lie algebra. Integrable IRF models, i.e., the models the Boltzmann weights of which satisfy the quantum Yang-Baxter equation, are of particular interest. In this paper, we investigate trigonometric Boltzmann weights of integrable IRF models. By using an ansatz proposed by one of the authors in some previous works, the Boltzmann weights of the restricted IRF models based on the affine Lie algebras $\mathfrak{su}(2)_k$ and $\mathfrak{su}(3)_k$ are computed for fundamental and adjoint representations for some fixed levels $k$. New solutions for the Boltzmann weights are obtained. We also study the vertex-IRF correspondence in the context of an unrestricted IRF model based on $\mathfrak {su}(3)_k$ (for general $k$) and discuss how it can be used to find Boltzmann weights in terms of the quantum $\hat{R}$ matrix when the adjoint representation defines the admissibility conditions.

While Null Hypothesis Significance Testing (NHST) remains a widely used statistical tool, it suffers from several shortcomings, such as conflating statistical and practical significance, sensitivity to sample size, and the inability to distinguish between accepting the null hypothesis and failing to reject it. Recent efforts have focused on developing alternatives to NHST to address these issues. Despite these efforts, conventional NHST remains dominant in scientific research due to its simplicity and perceived ease of interpretation. Our work presents a novel alternative to NHST that is just as accessible and intuitive: REACT. It not only tackles the shortcomings of NHST but also offers additional advantages over existing alternatives. For instance, REACT is easily applicable to multiparametric hypotheses and does not require stringent significance-level corrections when conducting multiple tests. We illustrate the practical utility of REACT through real-world data examples, using criteria aligned with common research practices to distinguish between the absence of evidence and evidence of absence.

Two recent preprints in the physics archive (arXiv) have called attention as they claim experimental evidence that a Cu-substituted apatite material (dubbed LK-99) exhibits superconductivity at room temperature and pressure. If this proves to be true, LK-99 will be a ``holy grail" of superconductors. In this work, we used Density Functional Theory (DFT+U) calculations to elucidate some key features of the electronic structure of LK-99. We find two different phases of this material: (i) a hexagonal lattice featuring metallic half-filled and spin-split bands, a nesting of the Fermi surface, a remarkably large electron-phonon coupling, but this lattice is vibrationally unstable. (ii) a triclinic lattice, with the Cu and surrounding O distorted. This lattice is vibrationally stable and its bands correspond to an insulator. In a crystal, the Cu atoms should oscillate between equivalent triclinic positions, with an average close to the hexagonal positions. We discuss the electronic structure expected from these fluctuations and if it is compatible with superconductivity.

We report the first laboratory and interstellar detection of the alpha-cyano vinyl radical (H2CCCN). This species was produced in the laboratory by an electric discharge of a gas mixture of vinyl cyanide, CH2CHCN, and Ne, and its rotational spectrum was characterized using a Balle-Flygare narrowband-type Fourier-transform microwave spectrometer operating in the frequency region of 8-40 GHz. The observed spectrum shows a complex structure due to tunneling splittings between two torsional sublevels of the ground vibronic state, 0+ and 0-, derived from a large-amplitude inversion motion. In addition, the presence of two equivalent hydrogen nuclei makes necessary to discern between ortho- and para-H2CCCN. A least squares analysis reproduces the observed transition frequencies with a standard deviation of ca. 3 kHz. Using the laboratory predictions, this radical is detected in the cold dark cloud TMC-1 using the Yebes 40m telescope and the QUIJOTE line survey. The 404-303 and 505-404 rotational transitions, composed of several hyperfine components, were observed in the 31.0-50.4 GHz range. Adopting a rotational temperature of 6K we derive a column density of (1.4+/-0.2)e11 cm-2 and (1.1+/-0.2)e11 cm-2 for ortho-H2CCCN and para-H2CCCN, respectively. The reactions C + CH3CN, and perhaps also N + CH2CCH, emerge as the most likely routes to H2CCCN in TMC-1., Comment: Accepted for publication in A&A Letters on 18/07/2023

Based on a novel laboratory method, 14 mm-wave lines of the molecular ion H$_2$CCCH$^+$ have been measured in high resolution, and the spectroscopic constants of this asymmetric rotor determined with high accuracy. Using the Yebes 40 m and IRAM 30 m radio telescopes, we detect four lines of H$_2$CCCH$^+$ towards the cold dense core TMC-1. With a dipole moment of about 0.55 Debye obtained from high-level ab initio calculations, we derive a column density of 5.4$\pm$1$\times$10$^{11}$ cm$^{-2}$ and 1.6$\pm$0.5$\times$10$^{11}$ cm$^{-2}$ for the ortho and para species, respectively, and an abundance ratio N(H$_2$CCC)/N(H$_2$CCCH$^+$)= 2.8$\pm$0.7. The chemistry of H$_2$CCCH$^+$ is modelled using the most recent chemical network for the reactions involving the formation of H$_2$CCCH$^+$. We find a reasonable agreement between model predictions and observations, and new insights into the chemistry of C$_3$ bearing species in TMC-1 are obtained.

Observations of the millimeter sky contain valuable information on a number of signals, including the blackbody cosmic microwave background (CMB), Galactic emissions, and the Compton-$y$ distortion due to the thermal Sunyaev-Zel'dovich (tSZ) effect. Extracting new insight into cosmological and astrophysical questions often requires combining multi-wavelength observations to spectrally isolate one component. In this work, we present a new arcminute-resolution Compton-$y$ map, which traces out the line-of-sight-integrated electron pressure, as well as maps of the CMB in intensity and E-mode polarization, across a third of the sky (around 13,000 sq.~deg.). We produce these through a joint analysis of data from the Atacama Cosmology Telescope (ACT) Data Release 4 and 6 at frequencies of roughly 93, 148, and 225 GHz, together with data from the \textit{Planck} satellite at frequencies between 30 GHz and 545 GHz. We present detailed verification of an internal linear combination pipeline implemented in a needlet frame that allows us to efficiently suppress Galactic contamination and account for spatial variations in the ACT instrument noise. These maps provide a significant advance, in noise levels and resolution, over the existing \textit{Planck} component-separated maps and will enable a host of science goals including studies of cluster and galaxy astrophysics, inferences of the cosmic velocity field, primordial non-Gaussianity searches, and gravitational lensing reconstruction of the CMB., Comment: The Compton-y map and associated products will be made publicly available upon publication of the paper. The CMB T and E mode maps will be made available when the DR6 maps are made public