Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling H2 and its effects on star formation using a joint implementation of gadget-3 and KROME

We present P-GADGET3-K, an updated version of GADGET3, that incorporates the chemistry package KROME. P-GADGET3-K follows the hydrodynamical and chemical evolution of cosmic structures, incorporating the chemistry and cooling ofH2 andmetal cooling in non-equilibrium. We performed different runs of the same ICs to assess the impact of various physical parameters and prescriptions, namely gasmetallicity,molecular hydrogen formation on dust, star formation recipes including or not H2 dependence, and the effects of numerical resolution. We find that the characteristics of the simulated systems, both globally and at kpc-scales, are in good agreement with several observable properties of molecular gas in star-forming galaxies. The surface density profiles of SFR and H2 are found to vary with the clumping factor and resolution. In agreement with previous results, the chemical enrichment of the gas component is found to be a key ingredient to model the formation and distribution of H2 as a function of gas density and temperature. A SF algorithm that takes into account the H2 fraction together with a treatment for the local stellar radiation field improves the agreement with observed H2 abundances over a wide range of gas densities and with the molecular Kennicutt-Schmidt law, implying a more realistic modelling of the star formation process.
Olá, Bonjour, Salve! XFORMAL: A Benchmark for Multilingual Formality Style Transfer

We take the first step towards multilingual style transfer by creating and releasing XFORMAL, a benchmark of multiple formal reformulations of informal text in Brazilian Portuguese, French, and Italian. Results on XFORMAL suggest that state-of-the-art style transfer approaches perform close to simple baselines, indicating that style transfer is even more challenging when moving multilingual.
Parton rescattering and gluon saturation in dijet production at EIC

Large angle gluon radiations induced by multiple parton scatterings contribute to dijet production in deeply inelastic scattering off a large nucleus at the Electron-Ion Collider. Within the generalized high-twist approach to multiple parton scattering, such contributions at the leading order in perturbative QCD and large Bjorken momentum fraction $x_B$ can be expressed as a convolution of the multiple parton scattering amplitudes and the transverse momentum dependent (TMD) two-parton correlation matrix elements. We study this medium-induced dijet spectrum and its azimuthal angle correlation under the approximation of small longitudinal momentum transfer in the secondary scattering and the factorization of two-parton correlation matrix elements as a product of quark and gluon TMD parton distribution function (PDF). Using a simple model for gluon saturation based on the parametrized gluon TMD PDF, we can calculate the $x_B$ and $Q^2$ dependence of the saturation scale and parton transport coefficient $\hat q$. Contributions to dijet cross section from double scattering are power-suppressed and only become sizable for mini-jets at small transverse momentum. We find that the total dijet correlation for these mini-jets, which also includes the contribution from single scattering, is sensitive to the transverse momentum broadening in the quark TMD PDF at large $x$ and saturation in the gluon TMD PDF at small $x$ inside the nucleus. The correlation from double scattering is also found to increase with the dijet rapidity gap and have a quadratic nuclear-size dependence because of the Landau-Pomeranchuk-Migdal (LPM) interference in gluon emission induced by multiple scattering. Experimental measurements of such unique features in the dijet correlation can shed light on the LPM interference in strong interaction and gluon saturation in large nuclei.
Faster than real-time simulation: methods, tools, and applications

Real-time simulation enables the understanding of system operating conditions by evaluating simulation models of physical components running synchronized at the real-time wall clock. Leveraging the real-time measurements of comprehensive system models, faster than real-time (FTRT) simulation allows the evaluation of system architectures at speeds faster than real-time. FTRT simulation can assist in predicting the system's behavior efficiently, thus assisting the operation of system processes. Namely, the provided acceleration can be used for improving system scheduling, assessing system vulnerabilities, and predicting system disruptions in real-time systems. The acceleration of simulation times can be achieved by utilizing digital real-time simulators (RTS) and high-performance computing (HPC) architectures. FTRT simulation has been widely used, among others, for the operation, design, and investigation of power system events, building emergency management plans, wildfire prediction, etc. In this paper, we review the existing literature on FTRT simulation and its applications in different disciplines, with a particular focus on power systems. We present existing system modeling approaches, simulation tools and computing frameworks, and stress the importance of FTRT accuracy.
Auditing for Discrimination in Algorithms Delivering Job Ads

Ad platforms such as Facebook, Google and LinkedIn promise value for advertisers through their targeted advertising. However, multiple studies have shown that ad delivery on such platforms can be skewed by gender or race due to hidden algorithmic optimization by the platforms, even when not requested by the advertisers. Building on prior work measuring skew in ad delivery, we develop a new methodology for black-box auditing of algorithms for discrimination in the delivery of job advertisements. Our first contribution is to identify the distinction between skew in ad delivery due to protected categories such as gender or race, from skew due to differences in qualification among people in the targeted audience. This distinction is important in U.S. law, where ads may be targeted based on qualifications, but not on protected categories. Second, we develop an auditing methodology that distinguishes between skew explainable by differences in qualifications from other factors, such as the ad platform’s optimization for engagement or training its algorithms on biased data. Our method controls for job qualification by comparing ad delivery of two concurrent ads for similar jobs, but for a pair of companies with different de facto gender distributions of employees. We describe the careful statistical tests that establish evidence of non-qualification skew in the results. Third, we apply our proposed methodology to two prominent targeted advertising platforms for job ads: Facebook and LinkedIn. We confirm skew by gender in ad delivery on Facebook, and show that it cannot be justified by differences in qualifications. We fail to find skew in ad delivery on LinkedIn. Finally, we suggest improvements to ad platform practices that could make external auditing of their algorithms in the public interest more feasible and accurate.
Bright ab initio photoluminescence of NV+ in diamond

Akib Karim, ∗ Igor Lyskov, 3 Salvy P. Russo, 3 and Alberto Peruzzo † Quantum Photonics Laboratory and Centre for Quantum Computation and Communication Technology, School of Engineering, RMIT University, Melbourne, Victoria 3000, Australia ARC Centre of Excellence in Exciton Science, School of Science, RMIT University, Melbourne, VIC 3001 Australia Chemical and Quantum Physics, School of Science, RMIT University, Melbourne VIC 3001, Australia
Evaluating participants' experience of extended interaction with cutting-edge physics research through the PRiSE “research in schools” programme

Physics in schools is distinctly different from, and struggles to capture the excitement of, university researchlevel work. Initiatives where students engage in independent research linked to cutting-edge physics within their school over several months might help mitigate this, potentially facilitating the uptake of science in higher education. However, how such initiatives are best supported remains unclear and understudied. This paper evaluates a provision framework, Physics Research in School Environments (PRiSE), using survey data from participating 14–18-year-old students and their teachers to understand their experience of the programme. The results show that PRiSE appears to provide much more positive experiences than typical university outreach initiatives due to the nature of the opportunities afforded over several months, which schools would not be able to provide without external input. The intensive support offered is deemed necessary, with all elements appearing equally important. Based on additional feedback from independent researchers and engagement professionals, we also suggest the framework could be adopted at other institutions and applied to their own areas of scientific research, something which has already started to occur.
Multi-scale perturbation theory II: Solutions and leading-order bispectrum in the ΛCDM universe

Two-parameter perturbation theory (2PPT) is a framework designed to include the relativistic gravitational effects of small-scale nonlinear structures on the large-scale properties of the Universe. In this paper we use the 2PPT framework to calculate and study the bispectrum of matter in a spatially-flat ΛCDM cosmology. This is achieved by deploying Newtonian perturbation theory to model the gravitational fields of quasi-nonlinear structures, and then subsequently using them as source terms for the large-scale cosmological perturbations. We find that our approach reproduces some of the expected relativistic effects from second-order cosmological perturbation theory, but not all. This work therefore provides a first step in deploying a formalism that can simultaneously model the weak gravitational fields of both linear and nonlinear structures in a realistic model of the Universe.
Flavored Tacotron: Conditional Learning for Prosodic-linguistic Features

Neural sequence-to-sequence text-to-speech synthesis (TTS), such as Tacotron-2, transforms text into high-quality speech. However, generating speech with natural prosody still remains a challenge. Yasuda et. al. show that unlike natural speech, Tacotron-2's encoder doesn't fully represent prosodic features (e.g. syllable stress in English) from characters, and result in flat fundamental frequency variations. In this work, we propose a novel carefully designed strategy for conditioning Tacotron-2 on two fundamental prosodic features in English -- stress syllable and pitch accent, that help achieve more natural prosody. To this end, we use of a classifier to learn these features in an end-to-end fashion, and apply feature conditioning at three parts of Tacotron-2's Text-To-Mel Spectrogram: pre-encoder, post-encoder, and intra-decoder. Further, we show that jointly conditioned features at pre-encoder and intra-decoder stages result in prosodically natural synthesized speech (vs. Tacotron-2), and allows the model to produce speech with more accurate pitch accent and stress patterns. Quantitative evaluations show that our formulation achieves higher fundamental frequency contour correlation, and lower Mel Cepstral Distortion measure between synthesized and natural speech. And subjective evaluation shows that the proposed method's Mean Opinion Score of 4.14 fairs higher than baseline Tacotron-2, 3.91, when compared against natural speech (LJSpeech corpus), 4.28.
Weak Liouville quantum gravity metrics with matter central charge $\mathbf{c} \in (-\infty, 25)$

Physics considerations suggest that a theory of Liouville quantum gravity (LQG) should exist for all values of matter central charge $\mathbf{c} \in (-\infty,25)$. Probabilists have rigorously defined LQG as a random metric measure space for $\mathbf{c}<1$; however, they have only very recently begun to explore LQG in the $\mathbf{c} \in (1,25)$ phase. We define a random metric associated to LQG for all $\mathbf{c}<25$ by a collection of axioms analogous to axioms stated in the $\mathbf{c}<1$ setting. We show that such a metric exists for each $\mathbf{c}$ by considering an approximating metric known as Liouville first passage percolation. Ding and Gwynne proved that these approximating metrics are tight in a suitably chosen topology; we show that every subsequential limit satisfies our axioms. In particular, our result defines a metric associated to LQG in the critical case $\mathbf{c} =1$. The metrics we define for $\mathbf{c} \in (1,25)$ exhibit geometric behavior that sharply contrasts with the $\mathbf{c}<1$ regime. We show that, for $\mathbf{c} \in (1,25)$, the metrics do not induce the Euclidean topology since they a.s. have a dense (measure zero) set of singular points, points at infinite distance from all other points. We use this fact to prove that a.s. the metric ball is not compact and its boundary has infinite Hausdorff dimension. Despite these differences, we demonstrate that many properties of LQG metrics for $\mathbf{c}<1$ extend in some form to the entire range $(-\infty, 25)$. We show that the metrics are a.s. reverse H\"older continuous with respect to the Euclidean metric, are a.s. complete and geodesic away from the set of singular points, and satisfy the bounds for set-to-set distances that hold in the $\mathbf{c}<1$ phase. Finally, we prove that the metrics satisfy a version of the (geometric) Knizhnik-Polyakov-Zamolodchikov (KPZ) formula.
How rotational invariance of common kernels prevents generalization in high dimensions

Kernel ridge regression is well-known to achieve minimax optimal rates in low-dimensional settings. However, its behavior in high dimensions is much less understood. Recent work establishes consistency for kernel regression under certain assumptions on the ground truth function and the distribution of the input data. In this paper, we show that the rotational invariance property of commonly studied kernels (such as RBF, inner product kernels and fully-connected NTK of any depth) induces a bias towards low-degree polynomials in high dimensions. Our result implies a lower bound on the generalization error for a wide range of distributions and various choices of the scaling for kernels with different eigenvalue decays. This lower bound suggests that general consistency results for kernel ridge regression in high dimensions require a more refined analysis that depends on the structure of the kernel beyond its eigenvalue decay.
A new mapped WENO scheme using order-preserving mapping

Existing mapped WENO schemes can hardly prevent spurious oscillations while preserving high resolutions at long output times. We reveal in this paper the essential reason for such phenomena. It is actually caused by that the mapping function in these schemes can not preserve the order of the nonlinear weights of the stencils. The nonlinear weights may be increased for non-smooth stencils and be decreased for smooth stencils. It is then indicated to require the set of mapping functions to be Order-Preserving in mapped WENO schemes. Therefore, we propose a new mapped WENO scheme with a set of mapping functions to be order-preserving which exhibits a remarkable advantage over the mapped WENO schemes in references. For long output time simulations, the new scheme has the capacity to attain high resolutions and avoid spurious oscillations near discontinuities meanwhile.
Compatible structures on unary binary nonsymmetric operads with quadratic and cubic relations

Various compatibility conditions among replicated copies of operations in a given algebraic structure have appeared in broad contexts in recent years. Taking an uniform approach, this paper gives an operadic study of compatibility conditions for nonsymmetric operads with unary and binary operations, and homogeneous quadratic and cubic relations. This generalizes the previous studies for binary quadratic operads. We consider three compatibility conditions, namely the linear compatibility, matching compatibility and total compatibility, with increasingly strict restraints among the replicated copies. The linear compatibility is in Koszul dual to the total compatibility, while the matching compatibility is self dual. Further, each compatibility can be expressed in terms of either one or both of the two Manin square products.
A Few Observations About State-Centric Online Propaganda

This paper presents a few observations about pro-Kremlin propaganda between 2015 and early 2021 with a dataset from the East Stratcom Task Force (ESTF), which is affiliated with the European Union (EU) but working independently from it. Instead of focusing on misinformation and disinformation, the observations are motivated by classical propaganda research and the ongoing transformation of media systems. According to the tentative results, (i) the propaganda can be assumed to target both domestic and foreign audiences. Of the countries and regions discussed, (ii) Russia, Ukraine, the United States, and within Europe, Germany, Poland, and the EU have been the most frequently discussed. Also other conflict regions such as Syria have often appeared in the propaganda. In terms of longitudinal trends, however, (iii) most of these discussions have decreased in volume after the digital tsunami in 2016, although the conflict in Ukraine seems to have again increased the intensity of pro-Kremlin propaganda. Finally, (iv) the themes discussed align with state-centric war propaganda and conflict zones, although also post-truth themes frequently appear;from conspiracy theories via COVID-19 to fascism -- anything goes, as is typical to propaganda.
Bayesian Method for Spatial Change-Point Detection of Propagating Event

—Rapid detection of spatial events that propagate across a sensor network is of wide interest in many modern applications. In particular, in communications, radar, environmental monitoring, and biosurveillance, we may observe propagating ﬁelds or particles. In this paper, we propose Bayesian single and multiple change-point detection procedures for the rapid detection of propagating spatial events. It is assumed that the spatial event propagates across a network of sensors according to the physical properties of the source causing the event. The multisensor system conﬁguration is arbitrary and sensors may be mobile. We begin by considering a single spatial event and are interested in detecting this event as quickly as possible, while statistically controlling the probability of false alarm. Using a dynamic programming framework we derive the structure of the optimal procedure, which minimizes the average detection delay (ADD) subject to a false alarm probability upper bound. In the rare event regime, the optimal procedure converges to a more practical threshold test on the posterior probability of the change point. A convenient recursive computation of this posterior probability is derived by using the propagation pattern of the spatial event. The ADD of the posterior probability threshold test is analyzed in the asymptotic regime. Then, we take a multiple hypothesis testing (MHT) approach and develop a procedure for the detection of multiple propagating spatial events in parallel. The proposed parallel procedure controls the overall false discovery rate (FDR) under prespeciﬁed upper bound. The FDR is a commonly used criterion in MHT for quantifying the rate of false alarms. Simulations are conducted to verify the theoretical ﬁndings. It is shown that exploiting the spatial properties of the event improves the ADD compared to procedures that do not properly take advantage of the spatial information.
Population genetics in microchannels

Significance Many microbial populations proliferate in small channels. In such environments, reproducing cells organize in parallel lanes. Reproducing cells shift these lanes, potentially expelling other cells from the channel. In this paper, we combine theory and experiments to understand how these dynamics affects the diversity of a microbial population. We theoretically predict that genetic diversity is quickly lost along lanes of cells. Our experiments confirm that a population of proliferating Escherichia coli in a microchannel organizes into lanes of genetically identical cells within a few generations. Our findings elucidate the effect of lane formation on populations evolution, with potential applications ranging from microbial ecology in soil to dynamics of epithelial tissues in higher organisms.
The relationship between fasting-induced torpor, sleep, and wakefulness in laboratory mice

Abstract Study Objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG), and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of non-rapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.
Hashing Techniques

With the rapid development of information storage and networking technologies, quintillion bytes of data are generated every day from social networks, business transactions, sensors, and many other domains. The increasing data volumes impose significant challenges to traditional data analysis tools in storing, processing, and analyzing these extremely large-scale data. For decades, hashing has been one of the most effective tools commonly used to compress data for fast access and analysis, as well as information integrity verification. Hashing techniques have also evolved from simple randomization approaches to advanced adaptive methods considering locality, structure, label information, and data security, for effective hashing. This survey reviews and categorizes existing hashing techniques as a taxonomy, in order to provide a comprehensive view of mainstream hashing techniques for different types of data and applications. The taxonomy also studies the uniqueness of each method and therefore can serve as technique references in understanding the niche of different hashing mechanisms for future development.