1902.00030
The three causes of low-mass assembly bias
Mansfield, Kravtsov
We present a detailed analysis of the physical processes that cause halo assembly bias -- the dependence of halo clustering on proxies of halo formation time. We focus on the origin of assembly bias in the mass range corresponding to the hosts of typical galaxies and use halo concentration as our chief proxy of halo formation time. We also repeat our key analyses across a broad range of halo masses and for alternative formation time definitions. We show that splashback subhaloes are responsible for two thirds of the assembly bias signal, but do not account for the entire effect. After splashback subhaloes have been removed, we find that the remaining assembly bias signal is due to a relatively small fraction ($\lesssim 10\%$) of haloes in dense regions. We test a number of additional physical processes thought to contribute to assembly bias and demonstrate that the two key processes are the slowing of mass growth by large-scale tidal fields and by the high velocities of ambient matter in sheets and filaments. We also rule out several other proposed physical causes of halo assembly bias. Based on our results, we argue that there are three processes that contribute to assembly bias of low-mass halos: large-scale tidal fields, gravitational heating due to the collapse of large-scale structures, and splashback subhaloes located outside the virial radius.
The three causes of low-mass assembly bias
Mansfield, Kravtsov
We present a detailed analysis of the physical processes that cause halo assembly bias -- the dependence of halo clustering on proxies of halo formation time. We focus on the origin of assembly bias in the mass range corresponding to the hosts of typical galaxies and use halo concentration as our chief proxy of halo formation time. We also repeat our key analyses across a broad range of halo masses and for alternative formation time definitions. We show that splashback subhaloes are responsible for two thirds of the assembly bias signal, but do not account for the entire effect. After splashback subhaloes have been removed, we find that the remaining assembly bias signal is due to a relatively small fraction ($\lesssim 10\%$) of haloes in dense regions. We test a number of additional physical processes thought to contribute to assembly bias and demonstrate that the two key processes are the slowing of mass growth by large-scale tidal fields and by the high velocities of ambient matter in sheets and filaments. We also rule out several other proposed physical causes of halo assembly bias. Based on our results, we argue that there are three processes that contribute to assembly bias of low-mass halos: large-scale tidal fields, gravitational heating due to the collapse of large-scale structures, and splashback subhaloes located outside the virial radius.
1902.00044
Euclid prepration IV. Impact of undetected galaxies on weak lensing shear measurements
Euclid Collaboration, Martinet, Schrabback, Hoekstra, Tewes, et al
In modern weak lensing surveys, shape measurement algorithms are calibrated using simulations in order to correct for any residual systematic bias in the shear. These simulations must fully capture the complexity of the observations to avoid introducing any additional bias. In this paper we study the importance of faint galaxies below the observational detection limit of a survey. We simulate simplified Euclid VIS images with and without including this faint population, and measure the shift in the multiplicative shear bias between the two sets of simulations. We measure the shear with three different algorithms: a moment-based approach, model fitting, and machine learning. We find that for all methods, a spatially uniform random distribution of faint galaxies introduces a shear multiplicative bias of the order of a few times $10^{-3}$. This value increases to the order of $10^{-2}$ when including the clustering of the faint galaxies, as measured in the Hubble Space Telescope Ultra Deep Field. The magnification of the faint background galaxies due to the brighter galaxies along the line of sight is found to have a negligible impact on the multiplicative bias. We conclude that the undetected galaxies must be included in the calibration simulations with proper clustering properties down to magnitude 28 in order to reach a residual uncertainty on the multiplicative shear bias calibration of a few times $10^{-4}$, in line with the $2\times10^{-3}$ total accuracy budget required by the scientific objectives of the Euclid survey. We propose two complementary methods for including faint galaxy clustering in the calibration simulations.
1902.00354
Rare cosmological events recorded in muscovite mica
Russel
A study of fossil tracks of charged particles recorded in crystals of muscovite has revealed evidence of rare events of cosmological origin. The events are not compatible with known particle interactions with matter. They were recorded during a period when the crystals were in a metastable state during cooling after growth 13km water equivalent underground. In this state a phase transition can be triggered by low energy events in the range 1eV to 10keV, when the crystals effectively behave as solid-state bubble chambers. At higher energies the chemical etching technique can be used to reveal massive damage to the lattice. The rare events show evidence of interaction with the crystal over a great range of energies. They leave a distinctive record that is easily recognised.
1902.00522
Deep learning for multi-messenger astrophysics: a gateway for discovery in the big data era
Allen, et al
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at the National Center for Supercomputing Applications, October 17-19, 2018. Highlights of this report include unanimous agreement that it is critical to accelerate the development and deployment of novel, signal-processing algorithms that use the synergy between artificial intelligence (AI) and high performance computing to maximize the potential for scientific discovery with Multi-Messenger Astrophysics. We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.
Deep learning for multi-messenger astrophysics: a gateway for discovery in the big data era
Allen, et al
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at the National Center for Supercomputing Applications, October 17-19, 2018. Highlights of this report include unanimous agreement that it is critical to accelerate the development and deployment of novel, signal-processing algorithms that use the synergy between artificial intelligence (AI) and high performance computing to maximize the potential for scientific discovery with Multi-Messenger Astrophysics. We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.
1902.00534
The neutrino puzzle: anomalies, interactions, and cosmological tensions
Kreisch, Cyr-Racing, Doré
New physics in the neutrino sector might be necessary to address anomalies between different neutrino oscillation experiments. Intriguingly, it also offers a possible solution to the discrepant cosmological measurements of $H_0$ and $\sigma_8$. We show here that delaying the onset of neutrino free-streaming until close to the epoch of matter-radiation equality can naturally accommodate a larger value for the Hubble constant $H_0=72.3 \pm 1.4$ km/s/Mpc and a lower value of the matter fluctuations $\sigma_8=0.786\pm 0.020$, while not degrading the fit to the cosmic microwave background (CMB) damping tail. We achieve this by introducing neutrino self-interactions in the presence of a non-vanishing sum of neutrino masses. This strongly interacting neutrino cosmology prefers $N_{\rm eff} = 4.02 \pm 0.29$, which has interesting implications for particle model-building and neutrino oscillation anomalies. We show that the absence of the neutrino free-streaming phase shift on the CMB can be compensated by shifting the value of other cosmological parameters, hence providing an important caveat to the detections made in the literature. Due to their impact on the evolution of the gravitational potential at early times, self-interacting neutrinos and their subsequent decoupling leave a rich structure on the matter power spectrum. In particular, we point out the existence of a novel localized feature appearing on scales entering the horizon at the onset of neutrino free-streaming. While the interacting neutrino cosmology provides a better global fit to current cosmological data, we find that traditional Bayesian analyses penalize the model as compared to the standard cosmological. Our analysis shows that it is possible to find radically different cosmological models that nonetheless provide excellent fits to the data, hence providing an impetus to thoroughly explore alternate cosmological scenarios.
1902.00709
Debiasing inference with approximate covariance matrices and other unidentified biases
Sellentin, Starck
When a posterior peaks in unexpected regions of parameter space, new physics has either been discovered, or a bias has not been identified yet. To tell these two cases apart is of paramount importance. We therefore present a method to indicate and mitigate unrecognized biases: Our method runs any pipeline with possibly unknown biases on both simulations and real data. It computes the coverage probability of posteriors, which measures whether posterior volume is a faithful representation of probability or not. If found to be necessary, the posterior is then corrected. This is a non-parametric debiasing procedure which complies with objective Bayesian inference. We use the method to debias inference with approximate covariance matrices and redshift uncertainties. We demonstrate why approximate covariance matrices bias physical constraints, and how this bias can be mitigated. We show that for a Euclid-like survey, if a traditional likelihood exists, then 25 end-to-end simulations suffice to guarantee that the figure of merit deteriorates maximally by 22 percent, or by 10 percent for 225 simulations. Thus, even a pessimistic analysis of Euclid-like data will still constitute an 25-fold increase in precision on the dark energy parameters in comparison to the state of the art (2018) set by KiDS and DES. We provide a public code of our method.
1902.01260
Turning gravitationally lensed supernovae into cosmological probes
Pierre, Rodney
Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, ``Refsdal'', and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the separate images. These measurements provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Over the next decade, accurate time delay measurements will be needed for the tens to hundreds of lensed SNe to be found by wide-field time-domain surveys such as LSST and WFIRST. We have developed an open source software package for simulations and time delay measurements of multiply-imaged SNe, including an improved characterization of the uncertainty caused by microlensing. We describe simulations using the package that suggest a before-peak detection of the leading image enables a more accurate time delay measurement by ~4 days compared to an after-peak detection. We also conclude that fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data, but that employing a Gaussian Process Regression (GPR) technique is sufficient for determining the uncertainty due to microlensing.
1902.01274
The golden era of neutron stars: from hadrons to quarks
Baym
Neutron stars were first posited in the early thirties, and discovered as pulsars in late sixties; however, only recently are we beginning to understand the matter they contain. This talk describes the continuing development of a consistent picture of the liquid interiors of neutron stars, driven by four advances: observations of two heavy neutron stars with masses $\simeq$ 2.0 solar masses; inferences of masses and radii simultaneously for an increasing number of neutron stars in low mass X-ray binaries, and future determinations via the NICER observatory; the observation of the binary neutron star merger, GW170817, through gravitational waves as well as across the electromagnetic spectrum; and an emerging understanding in QCD of how nuclear matter can turn into deconfined quark matter in the interior. We describe the modern quark-hadron crossover equation of state, QHC18, and the corresponding neutron stars, which agree well with current observations.
We present the data-driven reconstruction of gravitational theories and Dark Energy models on cosmological scales. We showcase the power of present cosmological probes at constraining these models and quantify the knowledge of their properties that can be acquired through state of the art data. This reconstruction exploits the power of the Effective Field Theory approach to Dark Energy and Modified Gravity phenomenology, which compresses the freedom in defining such models into a finite set of functions that can be reconstructed across cosmic times using cosmological data. We consider several model classes described within this framework and thoroughly discuss their phenomenology and data implications. We find that some models can alleviate the present discrepancy in the determination of the Hubble constant as inferred from the cosmic microwave background and as directly measured. This results in a statistically significant preference for the reconstructed theories over the standard cosmological model.
1902.01401
We investigate the lowest-mass quiescent galaxies known to exist in isolated environments ($\mathrm{M^* = 10^{9.0-9.5} \ M_\odot}$; 1.5 Mpc from a more massive galaxy). This population may represent the lowest stellar mass galaxies in which internal feedback quenches galaxy-wide star formation. We present Keck/ESI long-slit spectroscopy for 27 isolated galaxies in this regime: 20 quiescent galaxies and 7 star-forming galaxies. We measure emission line strengths as a function of radius and place galaxies on the Baldwin Phillips Terlevich (BPT) diagram. Remarkably, 16 of 20 quiescent galaxies in our sample host central AGN-like line ratios. Only 5 of these quiescent galaxies were identified as AGN-like in SDSS due to lower spatial resolution and signal-to-noise. We find that many of the quiescent galaxies in our sample have spatially-extended emission across the non-SF regions of BPT-space. When considering only the central 1$^{\prime\prime}$, we identify a tight relationship between distance from the BPT star-forming sequence and host galaxy stellar age as traced by $\mathrm{D_n4000}$, such that older stellar ages are associated with larger distances from the star-forming locus. Our results suggest that the presence of hard ionizing radiation (AGN-like line ratios) is intrinsically tied to the quenching of what may be the lowest-mass self-quenched galaxies.
We characterize the occurrence rate of planets, ranging in size from 0.5-16 R$_\oplus$, orbiting FGK stars with orbital periods from 0.5-500 days. Our analysis is based on results from the `DR25' catalog of planet candidates produced by NASA's Kepler mission and stellar radii from Gaia `DR2'. We incorporate additional Kepler data products to accurately characterize the the efficiency of planets being recognized as a `threshold crossing events' (TCE) by Kepler's Transiting Planet Search pipeline and labeled as a planet candidate by the robovetter. Using a hierarchical Bayesian model, we derive planet occurrence rates for a wide range of planet sizes and orbital periods. For planets with sizes 1-1.75 R$_\oplus$ and orbital periods of 237-500 days, we find a rate of planets per FGK star of $ 0.24^{+0.11}_{-0.10}$ ($68.3\%$ credible interval). While the true rate of such planets could be lower by a factor of $\sim~2$ (primarily due to potential contamination of planet candidates by false alarms), the upper limits on the occurrence rate of such planets are robust to $\sim~10\%$. We recommend that mission concepts aiming to characterize potentially rocky planets in or near the habitable zone of sun-like stars prepare compelling science programs that would be robust for a true rate in the range $f_{R,P} = 0.05-0.51$ for $1-1.75$ R$_\oplus$ planets with orbital periods in 237-500 days, or a differential rate of $\Gamma_\oplus \equiv (d^2 f)/[d(\ln P)~d(\ln R_{p})] = 0.11-1.2$.
1902.01274
The golden era of neutron stars: from hadrons to quarks
Baym
Neutron stars were first posited in the early thirties, and discovered as pulsars in late sixties; however, only recently are we beginning to understand the matter they contain. This talk describes the continuing development of a consistent picture of the liquid interiors of neutron stars, driven by four advances: observations of two heavy neutron stars with masses $\simeq$ 2.0 solar masses; inferences of masses and radii simultaneously for an increasing number of neutron stars in low mass X-ray binaries, and future determinations via the NICER observatory; the observation of the binary neutron star merger, GW170817, through gravitational waves as well as across the electromagnetic spectrum; and an emerging understanding in QCD of how nuclear matter can turn into deconfined quark matter in the interior. We describe the modern quark-hadron crossover equation of state, QHC18, and the corresponding neutron stars, which agree well with current observations.
1902.01366
Reconstructing gravity on cosmological scales
Raveri
1902.01401
AGN all the way down? AGN-like line ratios are common in the lowest-mass isolated quiescent galaxies
Dickey, Geha, Wetzel, El-Badry
1902.01417
Occurrence rates of planets orbiting FGK stars: combining Kepler DR25, Gaia DR2 and Bayesian inference
Hsu, et al
1902.01503
Environmental effects on halo abundance and weak lensing peak statistics toward large underdone regions
Higuchi, Inoue
The cosmic microwave background (CMB) contains an anomalous cold spot with a surrounding hot ring, known as the Cold Spot. Inoue & Silk (2006) proposed that this feature could be explained by postulating a supervoid: if such a large underdense region exists, then the growth of matter perturbing around the spot might differ from the average value in the Universe and the differences might affect weak lensing analysis of peak statistics. To investigate environmental effects on halo number count and peak statistics, we used a publicly available ray-tracing simulation for a box size of 2250$h^{-1}$Mpc on a side (Takahashi et al. 2017). We found that the number counts for massive haloes toward the largest underdense region in the simulation decreases and the corresponding significance of the difference, based on a cosmic average, is $\geq3\sigma$. On the basis of the results of peak statistics analysis, the number of high peaks decreases with the decrement of massive haloes, but the number of low peaks increases with the lack of matter in the line of sight. The highest significance of the decrement in peak counts in large underdense regions is $10\sigma$ in the total signal-to-noise ratio. Our result implies that environmental effects on halo abundance and weak lensing peak statistic can be used to probe the presence and properties of supervoids.
1902.01665
What shapes a galaxy? - Unraveling the role of mass, environment and star formation in forming galactic structure
Bluck, et al
We investigate the dependence of galaxy structure on a variety of galactic and environmental parameters for ~500,000 galaxies at z<0.2, taken from the Sloan Digital Sky Survey data release 7 (SDSS-DR7). We utilise bulge-to-total stellar mass ratio, (B/T)_*, as the primary indicator of galactic structure, which circumvents issues of morphological dependence on waveband. We rank galaxy and environmental parameters in terms of how predictive they are of galaxy structure, using an artificial neural network approach. We find that distance from the star forming main sequence (Delta_SFR), followed by stellar mass (M_*), are the most closely connected parameters to (B/T)_*, and are significantly more predictive of galaxy structure than global star formation rate (SFR), or any environmental metric considered (for both central and satellite galaxies). Additionally, we make a detailed comparison to the Illustris hydrodynamical simulation and the LGalaxies semi-analytic model. In both simulations, we find a significant lack of bulge-dominated galaxies at a fixed stellar mass, compared to the SDSS. This result highlights a potentially serious problem in contemporary models of galaxy evolution.
1902.01775
Low-redshift lowest-metallicity star-forming galaxies in the SDSS DR14
Izotov, Guseva, Fricke, Henkel
We present a sample of low-redshift (z<0.133) candidates for extremely low-metallicity star-forming galaxies with oxygen abundances 12+logO/H<7.4 selected from the Data Release 14 (DR14) of the Sloan Digital Sky Survey (SDSS). Three methods are used to derive their oxygen abundances. Among these methods two are based on strong [OII]3727, [OIII]4959, and [OIII]5007 emission lines, which we call strong-line and semi-empirical methods. These were applied for all galaxies. We have developed one of these methods, the strong-line method, in this paper. This method is specifically focused on the accurate determination of metallicity in extremely low-metallicity galaxies and may not be used at higher metallicities with12+logO/H>7.5. The third, the direct Te method, was applied for galaxies with detected [OIII]4363 emission lines. All three methods give consistent abundances and can be used in combination or separately for selection of lowest-metallicity candidates. However, the strong-line method is preferable for spectra with a poorly detected or undetected [OIII]4363 emission line. In total, our list of selected candidates for extremely low-metallicity galaxies includes 66 objects.
What shapes a galaxy? - Unraveling the role of mass, environment and star formation in forming galactic structure
Bluck, et al
We investigate the dependence of galaxy structure on a variety of galactic and environmental parameters for ~500,000 galaxies at z<0.2, taken from the Sloan Digital Sky Survey data release 7 (SDSS-DR7). We utilise bulge-to-total stellar mass ratio, (B/T)_*, as the primary indicator of galactic structure, which circumvents issues of morphological dependence on waveband. We rank galaxy and environmental parameters in terms of how predictive they are of galaxy structure, using an artificial neural network approach. We find that distance from the star forming main sequence (Delta_SFR), followed by stellar mass (M_*), are the most closely connected parameters to (B/T)_*, and are significantly more predictive of galaxy structure than global star formation rate (SFR), or any environmental metric considered (for both central and satellite galaxies). Additionally, we make a detailed comparison to the Illustris hydrodynamical simulation and the LGalaxies semi-analytic model. In both simulations, we find a significant lack of bulge-dominated galaxies at a fixed stellar mass, compared to the SDSS. This result highlights a potentially serious problem in contemporary models of galaxy evolution.
1902.01775
Low-redshift lowest-metallicity star-forming galaxies in the SDSS DR14
Izotov, Guseva, Fricke, Henkel
We present a sample of low-redshift (z<0.133) candidates for extremely low-metallicity star-forming galaxies with oxygen abundances 12+logO/H<7.4 selected from the Data Release 14 (DR14) of the Sloan Digital Sky Survey (SDSS). Three methods are used to derive their oxygen abundances. Among these methods two are based on strong [OII]3727, [OIII]4959, and [OIII]5007 emission lines, which we call strong-line and semi-empirical methods. These were applied for all galaxies. We have developed one of these methods, the strong-line method, in this paper. This method is specifically focused on the accurate determination of metallicity in extremely low-metallicity galaxies and may not be used at higher metallicities with12+logO/H>7.5. The third, the direct Te method, was applied for galaxies with detected [OIII]4363 emission lines. All three methods give consistent abundances and can be used in combination or separately for selection of lowest-metallicity candidates. However, the strong-line method is preferable for spectra with a poorly detected or undetected [OIII]4363 emission line. In total, our list of selected candidates for extremely low-metallicity galaxies includes 66 objects.
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