Can Sgr A* flares reveal the molecular gas density PDF?

Illumination of dense gas in the Central Molecular Zone (CMZ) by powerful X-ray flares from Sgr A* leads to prominent structures in the reflected emission that can be observed long after the end of the flare. By studying this emission we learn about past activity of the supermassive black hole in our Galactic Center and, at the same time, we obtain unique information on the structure of molecular clouds that is essentially impossible to get by other means. Here we discuss how X-ray data can improve our knowledge of both sides of the problem. Existing data already provide: i) an estimate of the flare age, ii) a model-independent lower limit on the luminosity of Sgr A* during the flare and iii) an estimate of the total emitted energy during Sgr A* flare. On the molecular clouds side, the data clearly show a voids-and-walls structure of the clouds and can provide an almost unbiased probe of the mass/density distribution of the molecular gas with the hydrogen column densities lower than few $10^{23}\;{\rm cm^{-2}}$. For instance, the probability distribution function of the gas density $PDF(\rho)$ can be measured this way. Future high energy resolution X-ray missions will provide the information on the gas velocities, allowing, for example a reconstruction of the velocity field structure functions and cross-matching the X-ray and molecular data based on positions and velocities.Comment: 13 pages, 7 figures; Accepted for publication in MNRA

Not that long time ago in the nearest galaxy: 3D slice of molecular gas revealed by a 110 years old flare of Sgr A*

A powerful outburst of X-ray radiation from the supermassive black hole Sgr A* at the center of the Milky Way is believed to be responsible for the illumination of molecular clouds in the central ~100 pc of the Galaxy (Sunyaev et al., 1993, Koyama et al., 1996). The reflected/reprocessed radiation comes to us with a delay corresponding to the light propagation time that depends on the 3D position of molecular clouds with respect to Sgr A*. We suggest a novel way of determining the age of the outburst and positions of the clouds by studying characteristic imprints left by the outburst in the spatial and time variations of the reflected emission. We estimated the age of the outburst that illuminates the Sgr A molecular complex to be ~110 yr. This estimate implies that we see the gas located ~10 pc further away from us than Sgr A*. If the Sgr B2 complex is also illuminated by the same outburst, then it is located ~130 pc closer than our Galactic Center. The outburst was short (less than a few years) and the total amount of emitted energy in X-rays is $\displaystyle \sim 10^{48}\rho_3^{-1}$ erg, where $\rho_3$ is the mean hydrogen density of the cloud complex in units of $10^3 {\rm cm^{-3}}$. Energetically, such fluence can be provided by a partial tidal disruption event or even by a capture of a planet. Further progress in more accurate positioning and timing of the outburst should be possible with future X-ray polarimetric observations and long-term systematic observations with Chandra and XMM-Newton. A few hundred-years long X-ray observations would provide a detailed 3D map of the gas density distribution in the central $\sim 100$ pc region.Comment: 10 pages, 7 figures, accepted for publication in MNRA

Polarization and long-term variability of Sgr A* X-ray echo

We use a model of the molecular gas distribution within ~100 pc from the center of the Milky Way (Kruijssen, Dale & Longmore) to simulate time evolution and polarization properties of the reflected X-ray emission, associated with the past outbursts from Sgr A*. While this model is too simple to describe the complexity of the true gas distribution, it illustrates the importance and power of long-term observations of the reflected emission. We show that the variable part of X-ray emission observed by Chandra and XMM from prominent molecular clouds is well described by a pure reflection model, providing strong support of the reflection scenario. While the identification of Sgr A* as a primary source for this reflected emission is already a very appealing hypothesis, a decisive test of this model can be provided by future X-ray polarimetric observations, that will allow placing constraints on the location of the primary source. In addition, X-ray polarimeters (like, e.g., XIPE) have sufficient sensitivity to constrain the line-of-sight positions of molecular complexes, removing major uncertainty in the model.Comment: 17 pages, 10 figures, accepted for publication in MNRA

Social motives vs social influence: an experiment on interdependent time preferences

We report experimental evidence on the effects of social preferences on intertemporal decisions. To this aim, we design an intertemporal Dictator Game to test whether Dictators modify their discounting behavior when their own decision is imposed on their matched Recipients. We run four different treatments to identify the effect of payoffs externalities from those related to information and beliefs. Our descriptive statistics show that heterogeneous social time preferences and information about others’ time preferences are significant determinants of choices: Dictators display a marked propensity to account for the intertemporal preferences of Recipients, both in the presence of externalities (social motives) and/or when they know about the decisions of their matched partners (social influence). We also perform a structural estimation exercise to control for heterogeneity in risk attitudes. As for individual behavior, our estimates confirm previous studies in that high risk aversion is associated with low discounting. As for social behavior, we find that social motives outweigh social influence, especially when we restrict our sample to pairs of Dictators and Recipients who satisfy minimal consistency conditions

Probing 3D Density and Velocity Fields of ISM in Centers of Galaxies with Future X-Ray Observations

Observations of bright and variable "reflected" X-ray emission from molecular clouds located within inner hundred parsec of our Galaxy have demonstrated that the central supermassive black hole, Sgr A*, experienced short and powerful flares in the past few hundred years. These flares offer a truly unique opportunity to determine 3D location of the illuminated clouds (with ~10 pc accuracy) and to reveal their internal structure (down to 0.1 pc scales). Short duration of the flare(s), combined with X-rays high penetration power and insensitivity of the reflection signal to thermo- and chemo-dynamical state of the gas, ensures that the provided diagnostics of the density and velocity fields is unbiased and almost free of the projection and opacity effects. Sharp and sensitive snapshots of molecular gas accessible with aid of future X-ray observatories featuring large collecting area and high angular (arcsec-level) and spectral (eV-level) resolution cryogenic bolometers will present invaluable information on properties of the supersonic turbulence inside the illuminated clouds, map their shear velocity field and allow cross-matching between X-ray data and velocity-resolved emission of various molecular species provided by ALMA and other ground-based facilities. This will highlight large and small-scale dynamics of the dense gas and help uncovering specifics of the ISM lifecycle and high-mass star formation under very extreme conditions of galactic centers. While the former is of particular importance for the SMBH feeding and triggering AGN feedback, the latter might be an excellent test case for star formation taking place in high-redshift galaxies.Comment: White paper submitted to the Astro2020 Decadal Surve

Myopic loss aversion under ambiguity and gender effects

Experimental evidence suggests that the frequency with which individuals get feedback information on their investments has an effect on their risk-taking behavior. In particular, when they are given information sufficiently often, they take less risks compared with a situation in which they are informed less frequently. We find that this result still holds when subjects do not know the probabilities of the lotteries they are betting upon. We also detect significant gender effects, in that the frequency with which information is disclosed mostly affects male betting behavior, and that males become more risk-seeking after experiencing a loss

Isomorphic Transfer of Syntactic Structures in Cross-Lingual NLP

The transfer or share of knowledge between languages is a popular solution to resource scarcity in NLP. However, the effectiveness of cross-lingual transfer can be challenged by variation in syntactic structures. Frameworks such as Universal Dependencies (UD) are designed to be cross-lingually consistent, but even in carefully designed resources trees representing equivalent sentences may not always overlap. In this paper, we measure cross-lingual syntactic variation, or anisomorphism, in the UD treebank collection, considering both morphological and structural properties. We show that reducing the level of anisomorphism yields consistent gains in cross-lingual transfer tasks. We introduce a source language selection procedure that facilitates effective cross-lingual parser transfer, and propose a typologically driven method for syntactic tree processing which reduces anisomorphism. Our results show the effectiveness of this method for both machine translation and cross-lingual sentence similarity, demonstrating the importance of syntactic structure compatibility for boosting cross-lingual transfer in NLP

Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization

Semantic \specialization is a process of fine-tuning pre-trained distributional word vectors using external lexical knowledge (e.g., WordNet) to accentuate a particular semantic relation in the specialized vector space. While post-processing specialization methods are applicable to arbitrary distributional vectors, they are limited to updating only the vectors of words occurring in external lexicons (i.e., seen words), leaving the vectors of all other words unchanged. We propose a novel approach to specializing the full distributional vocabulary. Our adversarial post-specialization method propagates the external lexical knowledge to the full distributional space. We exploit words seen in the resources as training examples for learning a global specialization function. This function is learned by combining a standard L2-distance loss with a adversarial loss: the adversarial component produces more realistic output vectors. We show the effectiveness and robustness of the proposed method across three languages and on three tasks: word similarity, dialog state tracking, and lexical simplification. We report consistent improvements over distributional word vectors and vectors specialized by other state-of-the-art specialization frameworks. Finally, we also propose a cross-lingual transfer method for zero-shot specialization which successfully specializes a full target distributional space without any lexical knowledge in the target language and without any bilingual data

Specializing distributional vectors of allwords for lexical entailment

Semantic specialization methods fine-tune distributional word vectors using lexical knowledge from external resources (e.g., WordNet) to accentuate a particular relation between words. However, such post-processing methods suffer from limited coverage as they affect only vectors of words seen in the external resources. We present the first postprocessing method that specializes vectors of all vocabulary words – including those unseen in the resources – for the asymmetric relation of lexical entailment (LE) (i.e., hyponymyhypernymy relation). Leveraging a partially LE-specialized distributional space, our POSTLE (i.e., post-specialization for LE) model learns an explicit global specialization function, allowing for specialization of vectors of unseen words, as well as word vectors from other languages via cross-lingual transfer. We capture the function as a deep feedforward neural network: its objective re-scales vector norms to reflect the concept hierarchy while simultaneously attracting hyponymyhypernymy pairs to better reflect semantic similarity. An extended model variant augments the basic architecture with an adversarial discriminator. We demonstrate the usefulness and versatility of POSTLE models with different input distributional spaces in different scenarios (monolingual LE and zero-shot cross-lingual LE transfer) and tasks (binary and graded LE). We report consistent gains over state-of-the-art LE-specialization methods, and successfully LE-specialize word vectors for languages without any external lexical knowledge

On the relation between linguistic typology and (limitations of) multilingual language modeling

A key challenge in cross-lingual NLP is developing general language-independent architectures that are equally applicable to any language. However, this ambition is largely hampered by the variation in structural and semantic properties, i.e. the typological profiles of the world's languages. In this work, we analyse the implications of this variation on the language modeling (LM) task. We present a large-scale study of state-of-the art n-gram based and neural language models on 50 typologically diverse languages covering a wide variety of morphological systems. Operating in the full vocabulary LM setup focused on word-level prediction, we demonstrate that a coarse typology of morphological systems is predictive of absolute LM performance. Moreover, fine-grained typological features such as exponence, flexivity, fusion, and inflectional synthesis are borne out to be responsible for the proliferation of low-frequency phenomena which are organically difficult to model by statistical architectures, or for the meaning ambiguity of character n-grams. Our study strongly suggests that these features have to be taken into consideration during the construction of next-level language-agnostic LM architectures, capable of handling morphologically complex languages such as Tamil or Korean.ERC grant Lexica