Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating multiple merger pathways to the central kinematics of early-type galaxies

Two-dimensional integral field surveys such as ATLAS^3D are producing rich observational data sets yielding insights into galaxy formation. These new kinematic observations have highlighted the need to understand the evolutionary mechanisms leading to a spectrum of fast rotators and slow rotators in early-type galaxies. We address the formation of slow and fast rotators through a series of controlled, comprehensive hydrodynamical simulations, sampling idealized galaxy merger scenarios constructed from model spiral galaxies. Idealized and controlled simulations of this sort complement the more ‘realistic’ cosmological simulations by isolating and analysing the effects of specific parameters, as we do in this paper. We recreate minor and major binary mergers, binary merger trees with multiple progenitors, and multiple sequential mergers. Within each of these categories of formation history, we correlate progenitor gas fraction, mass ratio, orbital pericentre, orbital ellipticity, and spin with remnant kinematic properties. We create kinematic profiles of these 95 simulations comparable to ATLAS^3D data. By constructing remnant profiles of the projected specific angular momentum ($\lambda _R= \langle R|V|\rangle / \langle R \sqrt{V^2+\sigma ^2}\rangle$), triaxiality, and measuring the incidences of kinematic twists and kinematically decoupled cores, we distinguish between varying formation scenarios. We find that binary mergers nearly always form fast rotators. Slow rotators can be formed from zero initial angular momentum configurations and gas-poor mergers, but are not as round as the ATLAS^3D galaxies. Remnants of binary merger trees are triaxial slow rotators. Sequential mergers form round slow rotators that most resemble the ATLAS^3D rotators.
Finest light curve details, physical parameters, and period fluctuations of CoRoT RR Lyrae stars

The CoRoT satellite supplied the scientific community with a huge data base of variable stars. Among them the RR Lyrae stars have intensively been discussed in numerous papers in the last few years, but the latest runs have not been checked to find RR Lyrae stars up to now. Our main goal was to fill this gap and complete the CoRoT RR Lyrae sample. We found nine unstudied RR Lyrae stars. Seven of them are new discoveries. We identified three new Blazhko stars. The Blazhko effect shows non-strictly repetitive nature for all stars. The frequency spectrum of the Blazhko star CoRoT 104948132 contains second overtone frequency with the highest known period ratio. The harmonic amplitude and phase declines with the harmonic order were studied for non-Blazhko stars. We found a period dependent but similar shape amplitude decline for all stars. We discovered significant random period fluctuation for one of the two oversampled target, CM Ori. After a successful transformation of the CoRoT band parameters to the Johnson V values we estimated the basic physical properties such as mass, luminosity, metallicity. The sample can be divided into two subgroups with respect to the metallicity but otherwise the physical parameters are in the canonical range of RR Lyrae stars.
Marbles and Bottles-or Boxes illustrate Irreversibility and Recurrence

Imaginary assemblies of intercommunicating bottles-or boxes, in which marbles circulate performing random walks, can help modeling (and hence understanding) slow and long-lasting diffusion processes and enable easy evaluations of typical times involved in their dynamics. Compared to the more traditional approaches to explaining diffusion inspired by the Ehrenfest's urn problem, these simple random walk models offer a more straightforward way to illustrate irreversibility/recurrence issues.
DUST AROUND R CORONAE BOREALIS STARS. II. INFRARED EMISSION FEATURES IN AN H-POOR ENVIRONMENT

Residual Spitzer/Infrared Spectrograph spectra for a sample of 31 R Coronae Borealis (RCB) stars are presented and discussed in terms of narrow emission features superimposed on the quasi-blackbody continuous infrared emission. A broad ∼6–10 μm dust emission complex is seen in the RCBs showing an extreme H-deficiency. A secondary and much weaker ∼11.5–15 μm broad emission feature is detected in a few RCBs with the strongest ∼6–10 μm dust complex. The Spitzer infrared spectra reveal for the first time the structure within the ∼6–10 μm dust complex, showing the presence of strong C-C stretching modes at ∼6.3 and 8.1 μm as well as of other dust features at ∼5.9, 6.9, and 7.3 μm, which are attributable to amorphous carbonaceous solids with little or no hydrogen. The few RCBs with only moderate H-deficiencies display the classical “unidentified infrared bands (UIRs)” and mid-infrared features from fullerene-related molecules. In general, the characteristics of the RCB infrared emission features are not correlated with the stellar and circumstellar properties, suggesting that the RCB dust features may not be dependent on the present physical conditions around RCB stars. The only exception seems to be the central wavelength of the 6.3 μm feature, which is blueshifted in those RCBs showing also the UIRs, i.e., the RCBs with the smallest H deficiency.
Collaborative dictionary learning with structured incoherence for target detection in hyperspectral imagery

Although sparse representation based classification (SRC) has gained great success, doubts on the necessity of sparse constraint come in recent years. And collaborative representation based classification (CRC) has attracted much attention from researchers in fields of signal processing, image processing and pattern recognition. In this paper, an algorithm called collaborative dictionary learning with structured incoherence (CDLSI) is proposed for collaborative representation based detection (CRD), which can be viewed as a binary classification problem, in hyperspectral imagery (HSI). An inter-class incoherence term is added to make sub-dictionaries to be as independent as possible. During the optimizing procedure, sub-dictionaries are updated atoms-by-atoms with metaface method. Specifically, considering the non-sparse representation of CRC, the coefficients are iteratively optimized with l2 -norm regularization during the coding procedure in CDLSI. Once the sub-dictionaries are obtained, the collaborative representation based technique is then used for detection. The proposed algorithm is applied to several real hyperspectral images for detection. Experimental results confirm the effectiveness of the proposed approach, and prove the superiority to the traditional algorithms.
Interim Design Report

The International Design Study for the Neutrino Factory (the IDS-NF) was established by the community at the ninth "International Workshop on Neutrino Factories, super-beams, and beta- beams" which was held in Okayama in August 2007. The IDS-NF mandate is to deliver the Reference Design Report (RDR) for the facility on the timescale of 2012/13. In addition, the mandate for the study [3] requires an Interim Design Report to be delivered midway through the project as a step on the way to the RDR. This document, the IDR, has two functions: it marks the point in the IDS-NF at which the emphasis turns to the engineering studies required to deliver the RDR and it documents baseline concepts for the accelerator complex, the neutrino detectors, and the instrumentation systems. The IDS-NF is, in essence, a site-independent study. Example sites, CERN, FNAL, and RAL, have been identified to allow site-specific issues to be addressed in the cost analysis that will be presented in the RDR. The choice of example sites should not be interpreted as implying a preferred choice of site for the facility.
Evolutionary aspects of reservoir computing

Reservoir computing (RC) is a powerful computational paradigm that allows high versatility with cheap learning. While other artificial intelligence approaches need exhaustive resources to specify their inner workings, RC is based on a reservoir with highly nonlinear dynamics that does not require a fine tuning of its parts. These dynamics project input signals into high-dimensional spaces, where training linear readouts to extract input features is vastly simplified. Thus, inexpensive learning provides very powerful tools for decision-making, controlling dynamical systems, classification, etc. RC also facilitates solving multiple tasks in parallel, resulting in a high throughput. Existing literature focuses on applications in artificial intelligence and neuroscience. We review this literature from an evolutionary perspective. RC’s versatility makes it a great candidate to solve outstanding problems in biology, which raises relevant questions. Is RC as abundant in nature as its advantages should imply? Has it evolved? Once evolved, can it be easily sustained? Under what circumstances? (In other words, is RC an evolutionarily stable computing paradigm? ) To tackle these issues, we introduce a conceptual morphospace that would map computational selective pressures that could select for or against RC and other computing paradigms. This guides a speculative discussion about the questions above and allows us to propose a solid research line that brings together computation and evolution with RC as test model of the proposed hypotheses. This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.
PRECISE TULLY–FISHER RELATIONS WITHOUT GALAXY INCLINATIONS

Power-law relations between tracers of baryonic mass and rotational velocities of disk galaxies, so-called Tully–Fisher relations (TFRs), offer a wealth of applications in galaxy evolution and cosmology. However, measurements of rotational velocities require galaxy inclinations, which are difficult to measure, thus limiting the range of TFR studies. This work introduces a maximum likelihood estimation (MLE) method for recovering the TFR in galaxy samples with limited or no information on inclinations. The robustness and accuracy of this method is demonstrated using virtual and real galaxy samples. Intriguingly, the MLE reliably recovers the TFR of all test samples, even without using any inclination measurements—that is, assuming a random sin i-distribution for galaxy inclinations. Explicitly, this “inclination-free MLE” recovers the three TFR parameters (zero-point, slope, scatter) with statistical errors only about 1.5 times larger than the best estimates based on perfectly known galaxy inclinations with zero uncertainty. Thus, given realistic uncertainties, the inclination-free MLE is highly competitive. If inclination measurements have mean errors larger than 10°, it is better not to use any inclinations than to consider the inclination measurements to be exact. The inclination-free MLE opens interesting perspectives for future H i surveys by the Square Kilometer Array and its pathfinders.
IGRINS NEAR-IR HIGH-RESOLUTION SPECTROSCOPY OF MULTIPLE JETS AROUND LkHα 234

We present the results of high-resolution near-IR spectroscopy toward the multiple outflows around the Herbig Be star LkHα 234 using the Immersion Grating Infrared Spectrograph. Previous studies indicate that the region around LkHα 234 is complex, with several embedded young stellar objects and the outflows associated with them. In simultaneous H- and K-band spectra from HH 167, we detected 5 [Fe ii] and 14 H2 emission lines. We revealed a new [Fe ii] jet driven by radio continuum source VLA 3B. Position–velocity diagrams of the H2 1−0 S(1) λ2. 122 μm line show multiple velocity peaks. The kinematics may be explained by a geometrical bow shock model. We detected a component of H2 emission at the systemic velocity (VLSR = −10.2 km s−1) along the whole slit in all slit positions, which may arise from the ambient photodissociation region. Low-velocity gas dominates the molecular hydrogen emission from knots A and B in HH 167, which is close to the systemic velocity; [Fe ii] emission lines are detected farther from the systemic velocity, at VLSR = −100–−130 km s−1. We infer that the H2 emission arises from shocked gas entrained by a high-velocity outflow. Population diagrams of H2 lines imply that the gas is thermalized at a temperature of 2500–3000 K and the emission results from shock excitation.
A diversity of starburst-triggering mechanisms in interacting galaxies and their signatures in CO emission

The physical origin of enhanced star formation activity in interacting galaxies remains an open question. Knowing whether starbursts are triggered by an increase in the quantity of dense gas or an increase in the star formation efficiency therein would improve our understanding of galaxy evolution and make it possible to transfer the results obtained in the local Universe to high-redshift galaxies. In this paper, we analyze a parsec-resolution simulation of a model of interacting galaxies similar to the Antennae Galaxies. We find that the interplay of physical processes such as tides, shear, and turbulence shows complex and important variations in time and space, but that different combinations of these processes can produce similar signatures in observable quantities such as the depletion time and CO emission. Some clouds within the interacting galaxies exhibit an excess of dense gas (> 104 cm−3), while others only attain similarly high densities in the tail of their density distribution. The clouds with an excess of dense gas are found across all regions of the galaxies, but their number density varies between regions due to different cloud assembly mechanisms. This translates into variations in the scale dependence of quantities related to cloud properties and star formation. The super-linearity of the relationship between the star formation rate and gas density implies that the dense gas excess corresponds to a decrease in the depletion time, and thus leads to a deviation from the classical star formation regime that is visible up to galactic scales. We find that the αCO conversion factor between the CO luminosity and molecular gas mass exhibits stronger spatial than temporal variations in a system like the Antennae. Our results raise several caveats for the interpretation of observations of unresolved star-forming regions, but also predict that the diversity of environments for star formation will be better captured by the future generations of instruments.
ECG Signal Processing, Classification and Interpretation: A Comprehensive Framework of Computational Intelligence

The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; andPart III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.
Research on Method of Concept Semantic Similarity Based on Ontology

This paper proposes a different ontology concept semantic similarity algorithm,which uses entities similarity to get the initial concept semantic similarity,and integrates two coefficients which influence concept semantic similarity to get the final concept semantic similarity.Comparing with probability statistic,experiments prove that this method is valid.The research can be applied in the field of knowledge searching.
WATER VAPOR IN THE SPECTRUM OF THE EXTRASOLAR PLANET HD 189733b. II. THE ECLIPSE

Spectroscopic observations of exoplanets are crucial to infer the composition and properties of their atmospheres. HD 189733b is one of the most extensively studied exoplanets and is a cornerstone for hot Jupiter models. In this paper, we report the dayside emission spectrum of HD 189733b in the wavelength range 1.1–1.7 μm obtained with the Hubble Space Telescope Wide Field Camera 3 (WFC3) in spatial scan mode. The quality of the data is such that even a straightforward analysis yields a high-precision Poisson noise-limited spectrum: the median 1σ uncertainty is 57 ppm per 0.02 μm bin. We also build a white-light curve correcting for systematic effects and derive an absolute eclipse depth of 96 ± 39 ppm. The resulting spectrum shows marginal evidence for water vapor absorption, but can also be well explained by a blackbody spectrum. However, the combination of these WFC3 data with previous Spitzer photometric observations is best explained by a dayside atmosphere of HD 189733b with no thermal inversion and a nearly solar or subsolar H2O abundance in a cloud-free atmosphere. Alternatively, this apparent subsolar abundance may be the result of clouds or hazes that future studies need to investigate.
The Density Structure of Simulated Stellar Streams

Star particles in a set of dense clusters are self-consistently evolved within an LCDM dark matter distribution with an n-body code. The clusters are started on nearly circular orbits in the more massive sub-halos. Each cluster develops a stellar tidal stream, initially within its original sub-halo. When a sub-halo merges into the main halo the early time stream is dispersed as a somewhat chaotic thick stream, roughly the width of the orbit of the cluster in the sub-halo. Once the cluster orbits freely in the main halo the star stream forms a thin stream again, usually resulting in a thin stream surrounded by a wider distribution of star particles lost at earlier times. To examine the role of the lower-mass dark matter sub-halos in the creation of density variations along the thin tidal star streams two realizations of the simulation are run with and without a normal cold dark matter sub-halo population below 4 × 108 . About 70(40)% of thin streams show density variations that are 2(5) times the star count noise level, irrespective of the presence or absence of low-mass sub-halos. A counts-in-cells analysis (related to the two-point correlation function and power spectrum) of the density along nearly 8000° of streams in the two well matched models finds that the full sub-halo population leads to slightly larger, but statistically significant, density fluctuations on scales of 2°–6°.
Photometry of two DQ white dwarfs. Search for spots

Swan bands in cool DQ white dwarfs cannot be adequately ﬁtted with models that otherwisesuccesfully reproduce spectral features of the molecule CH in these stars. Initial modelling showed that a two-component atmospherein the style of a spot might be able to solve the problem.Methods. We photometrically observed the two cool DQ white dwarfs GJ1117 and EGGR78 to search for variability caused by stellarspots.Results. We have not found any such variability, but we estimate the eﬀects of hypothetical spots on lightcurves. We also estimatedetection probabilities for spots in diﬀerent conﬁgurations. Alternative explanations of the prob lem are needed and brieﬂy discussed.Key words. white dwarfs – stars: atmosphere – stars: spots
A Hierarchical Self-Organizing Approach for Learning the Patterns of Motion Trajectories

This paper presents a hierarchical self organizing neural network model and its application in the learning of the trajectory distribution patterns for event recognition. By linking the side neurons, some lines are formed. Each line becomes an internal net of the hierarchical self organizing neural network. Corresponding to the hierarchical self organizing neural network model, the authors define two neighborhoods, namely the neuron neighborhood and the internal net neighborhood. The neurons in both neighborhoods will update their weights to different extent. In this way, the trajectory distribution patterns can be learned. Using the learned patterns, the authors consider both local and global anomaly detection as well as object behavior prediction. Experimental results demonstrate the effectiveness of the approach to trajectory analysis.
Approach for data streams clustering over dynamic sliding windows

The clustering of data streams is an important problem for clustering analysis.In order to address the data streams with varying speed,an efficient data streams clustering algorithm over dynamic sliding windows is proposed,which based on the two-phased framework.In the online component,the novel micro-cluster feature is introduced to store the important statistical information of data streams.Through computing the distances from data points to the center of each micro-cluster,and adjusting the sizes of sliding windows,the corresponding clustering features are maintained dynamically.In the offline component,by employing the mean values of the micro-clusters in online component,k-means algorithm is adopted to generate the final clustering results.Experimental results show that this approach has higher clustering purity and better scalability.
Stellar populations of Lyα emitters at z= 3–4 based on deep large area surveys in the Subaru-SXDS/UKIDSS-UDS Field

We investigate the stellar populations of Lyα emitters (LAEs) at z = 3.1 and 3.7 in 0.65 deg 2 of the Subaru/XMM-Newton Deep Field, based on rest-frame ultraviolet-to-optical photometry obtained from the Subaru/XMM-Newton Deep Survey, the UKIRT Infrared Deep Sky Survey/ Ultra Deep Survey (UKIDSS/UDS), and the Spitzer legacy survey of the UKIDSS/UDS. Among a total of 302 LAEs (224 for z = 3.1 and 78 for z = 3.7), only 11 are detected in the K band, i.e. brighter than K(3σ) = 24.1 mag. Eight of the 11 K-detected LAEs are spectroscopically confirmed. In our stellar population analysis, we treat K-detected objects individually, while K-undetected objects are stacked at each redshift. We find that the K-undetected objects, which should closely represent the LAE population as a whole, have low stellar masses of ~10 8 -10 8. 5 M ⊙ , modest star formation rates (SFRs) of 1-100 M ⊙ yr -1 , and modest dust extinction of E(B - V) * < 0.2. The K-detected objects are massive, M star ~ 10 9 -10 10.5 M ⊙ , and have significant dust extinction with a median of E(B — V) * ≃ 0.3. Four K-detected objects with the reddest spectral energy distributions, two of which are spectroscopically confirmed, are heavily obscured with E(B — V) * ~ 0.65, and their continua resemble those of some local ultraluminous infrared galaxies (ULIRGs). Interestingly, they have large Lyα equivalent widths ≃ 70-250 A. If these four are excluded, our sample has a weak anticorrelation between Lyα equivalent width and M star . We compare the stellar masses and the specific SFRs (sSFRs) of LAEs with those of Lyman-break galaxies (LBGs), distant red galaxies, submillimetre galaxies, and I- or K-selected galaxies with photometric redshifts of z phot ~ 3. We find that the LAE population is the least massive among all the galaxy populations in question, but with relatively high sSFRs, while near-infrared (NIR)-detected LAEs have M star and sSFR similar to LBGs. Our reddest four LAEs have very high sSFRs in spite of large M star , thus occupying a unique region in the M star versus sSFR space.