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Massive star formation involves significant ionization in the innermost regions near the central object, such as gravitationally trapped H II regions, jets, ionized disks, or winds. Resolved observations of the associated continuum and recombination line emission are crucial for guiding theory. The next-generation Very Large Array (ngVLA) will enable unprecedented observations of thermal emission with 1 mas resolution, providing a new perspective on massive star formation at scales down to a few astronomical units at kiloparsec distances. This work presents synthetic interferometric ngVLA observations of the free-free continuum (93-GHz band), $\mathrm{H41\alpha}$, and $\mathrm{H38\alpha}$ recombination lines from ionized jets and disks around massive protostars. Using the sf3dmodels Python package, we generate gas distributions based on analytical models, which are then processed through the RADMC-3D radiative transfer code. Our results indicate that the ngVLA can easily resolve, both spatially and spectrally, the ionized jet from a 15 $\mathrm{M_\odot}$ protostar at 700 pc, distinguishing between collimated jets and wide-angle winds, and resolving their launching radii, widths, and any substructure down to a few astronomical units. Detailed studies of radio jets launched by massive protostars will be feasible up to distances of $\sim 2$ kpc. Furthermore, ngVLA will be able to study in detail the ionized disks around massive ($> 10~\mathrm{M_\odot}$) protostars up to distances from 4 to 12 kpc, resolving their kinematics and enabling the measurement of their central masses across the Galaxy. These observations can be conducted with on-source integrations of only a few hours., Comment: Accepted for publication in ApJ

Carbyne, a one-dimensional (1D) carbon allotrope with alternating triple and single bonds, has the highest known mechanical strength but is unstable to bending, limiting synthesis to short linear chains. Encapsulation within carbon nanotubes (CNTs) stabilizes carbyne, forming confined carbyne (CC), thus enabling further research concerning attractive 1D physics and materials properties of carbyne. While CC has been synthesized in multi-walled CNTs (MWCNTs) using the arc-discharge method and in double-walled CNTs (DWCNTs) via high-temperature high-vacuum (HTHV) method, synthesis in single-walled CNTs (SWCNTs) has been challenging due to their fragility under such conditions. In this work, we report a low-temperature method to synthesize CC inside SWCNTs (CC@SWCNT). By annealing SWCNTs containing ammonium deoxycholate (ADC) at 400{\deg}C, ADC is converted into CC without damaging the SWCNTs. Raman spectroscopy revealed a strong CC phonon (CC-mode) peak at 1860-1870 cm^-1, much stronger than the SWCNT G-band peak, confirming a high fraction of CC in the resulting material. The Raman mapping result showed the uniformity of the CC-mode signal across the entire film sample, proving the high efficiency of this method in synthesizing CC in every SWCNT of appropriate size. Notably, the CC-mode peaks of CC@SWCNT (above 1860 cm^-1) are higher than those reported in previous CC@CNT samples (mostly less than 1856 cm^-1). This is attributed to larger SWCNT diameters (over 0.95 nm) used in this study, compared to the typical 0.6-0.8 nm range. Larger diameters result in reduced confinement, allowing carbyne to closely resemble free-standing carbyne while remaining stabilized. This low-temperature synthesis of long-chain, nearly free-standing carbyne within large-diameter SWCNTs offers new opportunities for exploring 1D physics and the unique properties of carbyne for potential applications.

In many applications, SMT solvers are used to solve similar or identical tasks over time. When the performance of the solver varies significantly despite only small changes, this leads to frustration for users. This has been called the stability problem, and it represents an important usability challenge for SMT solvers. In this paper, we introduce an approach for mitigating the stability problem based on normalizing solver inputs. We show that a perfect normalizing algorithm exists but is computationally expensive. We then describe an approximate algorithm and evaluate it on a set of benchmarks from related work, as well as a large set of benchmarks sampled from SMT-LIB. Our evaluation shows that our approximate normalizer reduces runtime variability with minimal overhead and is able to normalize a large class of mutated benchmarks to a unique normal form.

Brown Dwarfs (BDs) are crucial objects in our understanding of both star and planet formation. However, there is still an unconcluded debate about which is the dominant formation mechanism of these objects. For this, it is mandatory to study BDs in their earliest evolutionary stages (what we call pre- and proto-BDs), comparable to the `pre-stellar' and `Class 0/I' stages well characterized for the formation of low-mass stars. In this review, the recent efforts aimed at searching, identifying and characterising pre- and proto-BD candidates in nearby star-forming regions are presented, and revised requirements for an object to be a promising proto-BD or pre-BD candidate are provided, based on a new, unexplored so far, relation between the internal luminosity and the accreted mass. By applying these requirements, a list of 67 promising proto-BD candidates is presented, along with a compilation of possible pre-BDs from the literature. Updated correlations of protostellar properties such as mass infall rate or outflow momentum rate with bolometric luminosity are provided down to the low-mass BD regime, where no significant deviations are apparent. Furthermore, the number of proto-BD candidates in different clouds of the Solar Neighborhood seem to follow the known relations of number of protostars with cloud properties. In addition, proto(star-to-BD) ratios for the different clouds are also explored, unveiling a particular underproduction of low-mass proto-BD candidates in Ophiuchus compared to Lupus and Taurus. Possible explanations for this behavior are discussed, including heating of the Ophiuchus cloud by the nearby OB stars. The overall results of this work tend to favor a star-like process for BD formation down to the planetary boundary, of about 10 Mjup, below which other mechanisms might be at work., Comment: Invited review to New Astronomy Reviews. 63 pages. In press

Hub-filament systems are considered as natural sites for high-mass star formation. Kinematic analysis of the surroundings of hub-filaments is essential to better understand high-mass star formation within such systems. In this work, we present a detailed study of the massive Galactic protocluster IRAS 15394$-$5358, using continuum and molecular line data from the ALMA Three-millimeter Observations of Massive Star-forming Regions (ATOMS) survey. The 3~mm dust continuum map reveals the fragmentation of the massive ($\rm M=843~M_{\odot}$) clump into six cores. The core C-1A is the largest (radius = 0.04~pc), the most massive ($\rm M=157~M_{\odot}$), and lies within the dense central region, along with two smaller cores ($\rm M=7~and~3~M_{\odot}$). The fragmentation process is consistent with the thermal Jeans fragmentation mechanism and virial analysis shows that all the cores have small virial parameter values ($\rm \alpha_{vir}<<2$), suggesting that the cores are gravitationally bound. The mass vs. radius relation indicates that three cores can potentially form at least a single massive star. The integrated intensity map of $\rm H^{13}CO^{+}$ shows that the massive clump is associated with a hub-filament system, where the central hub is linked with four filaments. A sharp velocity gradient is observed towards the hub, suggesting a global collapse where the filaments are actively feeding the hub. We discuss the role of global collapse and the possible driving mechanisms for the massive star formation activity in the protocluster., Comment: 23 pages, 19 figures, accepted for publication in MNRAS

We explore the Schmidt-Kennicutt (SK) relations and the star formation efficiency per free-fall time ($\eff$), mirroring observational studies, in numerical simulations of filamentary molecular clouds undergoing gravitational contraction. We find that {\it a)} collapsing clouds accurately replicate the observed SK relations for galactic clouds and {\it b)} the so-called efficiency per free-fall time ($\eff$) is small and constant in space and in time, with values similar to those found in local clouds. This constancy is a consequence of the similar radial scaling of the free-fall time and the internal mass in density structures with spherically-averaged density profiles near $r^{-2}$. We additionally show that {\it c)} the star formation rate (SFR) increases rapidly in time; {\it d)} the low values of $\eff$ are due to the different time periods over which $\tauff$ and $\tausf$ are evaluated, together with the fast increasing SFR, and {\it e)} the fact that star clusters are significantly denser than the gas clumps from which they form is a natural consequence of the fast increasing SFR, the continuous replenishment of the star-forming gas by the accretion flow, and the near $r^{-2}$ density profile generated by the collapse Finally, we argue that the interpretation of $\eff$ as an efficiency is problematic because its maximum value is not bounded by unity, and because the total gas mass in the clouds is not fixed, but rather depends on the environment where clouds are embedded. In summary, our results show that the SK relation, the typical observed values of $\eff$, and the mass density of clusters arise as a natural consequence of gravitational contraction., Comment: Submitted to MNRAS

We explain the large variety of star formation laws in terms of one single, simple law that can be inferred from the definition of the star formation rate and basic algebra. The resulting equation, $\SFR = \eff\ \Mcollapsing/\tauff$, although it has been presented elsewhere, is interpreted in terms of clouds undergoing collapse { rather than being turbulence-supported, an idea that different groups have pursued this century}. Under such assumption, one can explain the constancy of $\eff$, the different intra-cloud correlations observed in Milky Way's molecular clouds, as well as the resolved and unresolved extragalactic relationships between SFR and a measurement of the mass in CO, HCN, and CO+HI. We also explain why the slope of the correlation changes when the orbital time $\tauorb$ is considered instead of the free-fall time, and why estimations of the free-fall time from extragalactic observations skew the correlation, providing a false sublinear correlation. We furthermore show that the apparent nearly linear correlation between the star formation rate and the dynamical equilibrium pressure in the midplane of the galaxies, $\PDE$, is just a consequence of $\PDE$ values being dominated by the variation of the column density of molecular gas. All in all, we argue that the star formation law is driven by the collapse of cold, dense gas, which happens to be primarily molecular in the present Universe, and that the role of stellar feedback is just to shut down the star formation process, not to shape the star formation law., Comment: 17 pages, one figure. Accepted by MNRAS

We provide a detailed comparison between the ``gravoturbulent'' (GT) and ``global hierarchical collapse'' (GHC) models for molecular clouds and star formation, their respective interpretations of the observational data, the features they share, and suggested tests and observations to discern between them. Also, we clarify common misconceptions in recent literature about the global and hierarchical nature of the GHC scenario, and briefly discuss the evolution of some aspects of both models toward convergence. GT assumes that molecular clouds and their substructures are in approximate virial equilibrium and are in a near-stationary state, interprets the linewidth-derived nonthermal motions exclusively as turbulence, which provides additional pressure against self-gravity. Conversely, GHC assumes that most star-forming molecular clouds and their substructures are part of a continuous gravitationally-driven flow, each accreting from their parent structure. Thus, the clouds and their star formation rate evolve in time. GHC interprets nonthermal motions as a mixture of infall and turbulent components, with the relative importance of the former increasing as the objects become denser and/or more massive. Tests that may provide clues to distinguishing between GT and GHC must take into account that the innermost parts of globally gravitationally bound structures may not locally appear bound, and thus the binding may have to be searched for at the largest scale of the structure., Comment: Submitted to MNRAS. Comments welcome. Animation for Fig. 3 available at https://www.irya.unam.mx/gente/g.gomez/publica/24-GT_vs_GHC-f3.mpg

The relation between magnetic field strength B and gas density n in the interstellar medium is of fundamental importance to many areas of astrophysics, from protostellar disks to galaxy evolution. We present and compare Bayesian analyses of the B - n relation for a comprehensive observational data set, as well as a large body of numerical MHD simulations. We extend the original Zeeman relation of Crutcher et al. (2010) with a large body of magnetic data that includes 700 observations with the Davis-Chandrasekhar-Fermi method. By using a new multiparameter Bayesian analysis we present a new, more general, time-averaged observational relation: B \propto n^{0.27 \pm 0.017} for n \leq n_0 and B \propto n^{0.54 \pm 0.18} for n \geq n_0, with n_0 = 924^(+145-144) cm^-3. We perform a separate analysis on 19 numerical magnetohydrodynamics simulations that cover a wide range of scales, resolutions, initial conditions, and completed with a variety of codes: arepo, flash, pencil, and ramses. The power law exponents derived from the simulations depend on several physical factors including: dynamo effects, time scales, turbulence, and the initial seed field strength. In particular, early-time simulations where the density, velocity and magnetic fields are unevolved do not match the observational scalings. The simulations that trace the observed density range best, the evolved dwarf galaxy and Milky Way like galaxy simulations, settle into a near consistent exponent of = 0.5 in the dense gas, with variability in the diffuse gas exponent., Comment: 23 figures, 28 pages, submitted to MNRAS, Comments welcome

Large Language Models (LLMs) tend to be unreliable in the factuality of their answers. To address this problem, NLP researchers have proposed a range of techniques to estimate LLM's confidence over facts. However, due to the lack of a systematic comparison, it is not clear how the different methods compare to one another. To fill this gap, we present a survey and empirical comparison of estimators of factual confidence. We define an experimental framework allowing for fair comparison, covering both fact-verification and question answering. Our experiments across a series of LLMs indicate that trained hidden-state probes provide the most reliable confidence estimates, albeit at the expense of requiring access to weights and training data. We also conduct a deeper assessment of factual confidence by measuring the consistency of model behavior under meaning-preserving variations in the input. We find that the confidence of LLMs is often unstable across semantically equivalent inputs, suggesting that there is much room for improvement of the stability of models' parametric knowledge. Our code is available at (https://github.com/amazon-science/factual-confidence-of-llms)., Comment: accepted on the main track of ACL 2024

We introduce two uncertainty relations based on the state-dependent norm of commutators, utilizing generalizations of the B\"ottcher-Wenzel inequality. The first relation is mathematically proven, while the second, tighter relation is strongly supported by numerical evidence. Both relations surpass the conventional Robertson and Schr\"odinger bounds, particularly as the quantum state becomes increasingly mixed. This reveals a previously undetected complementarity of quantum uncertainty, stemming from the non-commutativity of observables. We also compare our results with the Luo-Park uncertainty relation, demonstrating that our bounds can outperform especially for mutually unbiased observables., Comment: 9 pages, 2 figures

By employing a weighted Frobenius norm with a positive matrix $\omega$, we introduce natural generalizations of the famous B\"ottcher-Wenzel (BW) inequality. Based on the combination of the weighted Frobenius norm $\|A\|_\omega := \sqrt{{\rm tr}(A^\ast A \omega)}$ and the standard Frobenius norm $\|A\| := \sqrt{{\rm tr}(A^\ast A)}$, there are exactly five possible generalizations, labeled (i) through (v), for the bounds on the norms of the commutator $[A,B]:= AB - BA$. In this paper, we establish the tight bounds for cases (iii) and (v), and propose conjectures regarding the tight bounds for cases (i) and (ii). Additionally, the tight bound for case (iv) is derived as a corollary of case (i). All these bounds (i)-(v) serve as generalizations of the BW inequality. The conjectured bounds for cases (i) and (ii) (and thus also (iv)) are numerically supported for matrices up to size $n=15$. Proofs are provided for $n=2$ and certain special cases. Interestingly, we find applications of these bounds in quantum physics, particularly in the contexts of the uncertainty relation and open quantum dynamics., Comment: 18 pages, 2 figures

When deriving contextualized word representations from language models, a decision needs to be made on how to obtain one for out-of-vocabulary (OOV) words that are segmented into subwords. What is the best way to represent these words with a single vector, and are these representations of worse quality than those of in-vocabulary words? We carry out an intrinsic evaluation of embeddings from different models on semantic similarity tasks involving OOV words. Our analysis reveals, among other interesting findings, that the quality of representations of words that are split is often, but not always, worse than that of the embeddings of known words. Their similarity values, however, must be interpreted with caution., Comment: Accepted to TACL

Undefined behavior in C often causes devastating security vulnerabilities. One practical mitigation is compartmentalization, which allows developers to structure large programs into mutually distrustful compartments with clearly specified privileges and interactions. In this paper we introduce SECOMP, a compiler for compartmentalized C code that comes with machine-checked proofs guaranteeing that the scope of undefined behavior is restricted to the compartments that encounter it and become dynamically compromised. These guarantees are formalized as the preservation of safety properties against adversarial contexts, a secure compilation criterion similar to full abstraction, and this is the first time such a strong criterion is proven for a mainstream programming language. To achieve this we extend the languages of the CompCert verified C compiler with isolated compartments that can only interact via procedure calls and returns, as specified by cross-compartment interfaces. We adapt the passes and optimizations of CompCert as well as their correctness proofs to this compartment-aware setting. We then use compiler correctness as an ingredient in a larger secure compilation proof that involves several proof engineering novelties, needed to scale formally secure compilation up to a C compiler., Comment: CCS'24 version, slightly updated and extended with appendices and a few more references

A number of works infer radial temperature profiles of envelopes surrounding young stellar objects using several rotational transitions in a pixel-by-pixel or azimuthally-averaged basis. However, in many cases the assumption that the rotational temperature is constant along the line of sight is made, while this is not the case when a partially resolved envelope, assumed to be spherically symmetric, is used to obtain values of temperature for different projected radii. This kind of analysis (homogeneous analysis) is intrinsically inconsistent. By using a spherical envelope model to interpret NH3 (1, 1) and (2, 2) observations, we tested how robust it is to infer radial temperature profiles of an envelope. The temperature and density of the model envelope are power laws of radius, but the density can be flat for an inner central part. The homogeneous analysis was applied to obtain radial temperature profiles, and resulted that for small projected radii, where the optical depth of the lines is high, the homogeneous temperature can be much higher than the actual envelope temperature. In general, for larger projected radii, both the temperature and the temperature power-law index can be underestimated by as much as 40%, and 0.15, respectively. We applied this study to the infrared dark cloud G14.225-0.506 for which the radial temperature profile was previously derived from the dust emission at submillimeter wavelengths and the spectral energy distribution. As expected, the homogeneous analysis underestimated both the temperature and the temperature power-law index., Comment: Accepted for publication in MNRAS

Partial differential equations (PDEs) are commonly employed to model complex industrial systems characterized by multivariable dependence. Existing physics-informed neural networks (PINNs) excel in solving PDEs in a homogeneous medium. However, their feasibility is diminished when PDE parameters are unknown due to a lack of physical attributions and time-varying interface is unavailable arising from heterogeneous media. To this end, we propose a data-physics-hybrid method, physically informed synchronic-adaptive learning (PISAL), to solve PDEs for industrial systems modeling in heterogeneous media. First, Net1, Net2, and NetI, are constructed to approximate the solutions satisfying PDEs and the interface. Net1 and Net2 are utilized to synchronously learn each solution satisfying PDEs with diverse parameters, while NetI is employed to adaptively learn the unavailable time-varying interface. Then, a criterion combined with NetI is introduced to adaptively distinguish the attributions of measurements and collocation points. Furthermore, NetI is integrated into a data-physics-hybrid loss function. Accordingly, a synchronic-adaptive learning (SAL) strategy is proposed to decompose and optimize each subdomain. Besides, we theoretically prove the approximation capability of PISAL. Extensive experimental results verify that the proposed PISAL can be used for industrial systems modeling in heterogeneous media, which faces the challenges of lack of physical attributions and unavailable time-varying interface.

Only a handful of massive starless core candidates have been discovered so far, but none of them have been fully confirmed. Within the MM1 clump in the filamentary infrared dark cloud G34.43+0.24 that was covered by the ALMA-ATOMS survey at Band 3 ($\sim2\arcsec$, 6000\,au) and the ALMA-QUARKS survey at Band 6 ($\sim 0.3\arcsec$, 900\,au), two prestellar core candidates MM1-C and E1 with masses of 71 and 20 \solarmass~and radii of 2100--4400\,au were discovered. The two cores show no obvious sign of star-formation activities. In particular, MM1-C is a very promising massive prestellar core candidate with a total gas mass of 71\,\solarmass. Within MM1-C, we detected two extremely dense substructures, C1 and C2, as characterized by their high densities of $\rm n_{H_2}\sim 10^{8-9} cm^{-3}$. Moreover, evidence of further fragmentation in C2 was also revealed. We have detected the primordial fragmentation in the earliest stage of massive star formation, and we speculate that MM1-C would be the birthplace of a massive multiple system. However, we cannot fully rule out the possibility that the massive prestellar core MM1-C will just form a cluster of low-mass stars if it undergoes further fragmentation., Comment: 12 pages, 6 figures