Showing papers by "York University published in 2019"

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Abstract: This paper presents a comprehensive literature review on applications of deep reinforcement learning (DRL) in communications and networking. Modern networks, e.g., Internet of Things (IoT) and unmanned aerial vehicle (UAV) networks, become more decentralized and autonomous. In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment. Reinforcement learning has been efficiently used to enable the network entities to obtain the optimal policy including, e.g., decisions or actions, given their states when the state and action spaces are small. However, in complex and large-scale networks, the state and action spaces are usually large, and the reinforcement learning may not be able to find the optimal policy in reasonable time. Therefore, DRL, a combination of reinforcement learning with deep learning, has been developed to overcome the shortcomings. In this survey, we first give a tutorial of DRL from fundamental concepts to advanced models. Then, we review DRL approaches proposed to address emerging issues in communications and networking. The issues include dynamic network access, data rate control, wireless caching, data offloading, network security, and connectivity preservation which are all important to next generation networks, such as 5G and beyond. Furthermore, we present applications of DRL for traffic routing, resource sharing, and data collection. Finally, we highlight important challenges, open issues, and future research directions of applying DRL.

The Simons Observatory : Science goals and forecasts

Abstract: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s. We describe the scientific goals of the experiment, motivate the design, and forecast its performance. SO will measure the temperature and polarization anisotropy of the cosmic microwave background in six frequency bands centered at: 27, 39, 93, 145, 225 and 280 GHz. The initial configuration of SO will have three small-aperture 0.5-m telescopes and one large-aperture 6-m telescope, with a total of 60,000 cryogenic bolometers. Our key science goals are to characterize the primordial perturbations, measure the number of relativistic species and the mass of neutrinos, test for deviations from a cosmological constant, improve our understanding of galaxy evolution, and constrain the duration of reionization. The small aperture telescopes will target the largest angular scales observable from Chile, mapping ≈ 10% of the sky to a white noise level of 2 μK-arcmin in combined 93 and 145 GHz bands, to measure the primordial tensor-to-scalar ratio, r, at a target level of σ(r)=0.003. The large aperture telescope will map ≈ 40% of the sky at arcminute angular resolution to an expected white noise level of 6 μK-arcmin in combined 93 and 145 GHz bands, overlapping with the majority of the Large Synoptic Survey Telescope sky region and partially with the Dark Energy Spectroscopic Instrument. With up to an order of magnitude lower polarization noise than maps from the Planck satellite, the high-resolution sky maps will constrain cosmological parameters derived from the damping tail, gravitational lensing of the microwave background, the primordial bispectrum, and the thermal and kinematic Sunyaev-Zel'dovich effects, and will aid in delensing the large-angle polarization signal to measure the tensor-to-scalar ratio. The survey will also provide a legacy catalog of 16,000 galaxy clusters and more than 20,000 extragalactic sources.

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

Abstract: The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.

A deep learning framework for neuroscience

Abstract: Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In artificial neural networks, the three components specified by design are the objective functions, the learning rules and the architectures. With the growing success of deep learning, which utilizes brain-inspired architectures, these three designed components have increasingly become central to how we model, engineer and optimize complex artificial learning systems. Here we argue that a greater focus on these components would also benefit systems neuroscience. We give examples of how this optimization-based framework can drive theoretical and experimental progress in neuroscience. We contend that this principled perspective on systems neuroscience will help to generate more rapid progress.

Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation

Abstract: We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). RSP is a new functionality in MESAstar that models the nonlinear radial stellar pulsations that characterize RR Lyrae, Cepheids, and other classes of variable stars. We significantly enhance numerical energy conservation capabilities, including during mass changes. For example, this enables calculations through the He flash that conserve energy to better than 0.001%. To improve the modeling of rotating stars in MESA, we introduce a new approach to modifying the pressure and temperature equations of stellar structure, as well as a formulation of the projection effects of gravity darkening. A new scheme for tracking convective boundaries yields reliable values of the convective core mass and allows the natural emergence of adiabatic semiconvection regions during both core hydrogen- and helium-burning phases. We quantify the parallel performance of MESA on current-generation multicore architectures and demonstrate improvements in the computational efficiency of radiative levitation. We report updates to the equation of state and nuclear reaction physics modules. We briefly discuss the current treatment of fallback in core-collapse supernova models and the thermodynamic evolution of supernova explosions. We close by discussing the new MESA Testhub software infrastructure to enhance source code development.

The IllustrisTNG simulations: public data release

Abstract: We present the full public release of all data from the TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG is a suite of large volume, cosmological, gravo-magnetohydrodynamical simulations run with the moving-mesh code Arepo. TNG includes a comprehensive model for galaxy formation physics, and each TNG simulation self-consistently solves for the coupled evolution of dark matter, cosmic gas, luminous stars, and supermassive black holes from early time to the present day, $z=0$ . Each of the flagship runs—TNG50, TNG100, and TNG300—are accompanied by halo/subhalo catalogs, merger trees, lower-resolution and dark-matter only counterparts, all available with 100 snapshots. We discuss scientific and numerical cautions and caveats relevant when using TNG. The data volume now directly accessible online is ∼750 TB, including 1200 full volume snapshots and ∼80,000 high time-resolution subbox snapshots. This will increase to ∼1.1 PB with the future release of TNG50. Data access and analysis examples are available in IDL, Python, and Matlab. We describe improvements and new functionality in the web-based API, including on-demand visualization and analysis of galaxies and halos, exploratory plotting of scaling relations and other relationships between galactic and halo properties, and a new JupyterLab interface. This provides an online, browser-based, near-native data analysis platform enabling user computation with local access to TNG data, alleviating the need to download large datasets.

SIMBA: Cosmological simulations with black hole growth and feedback

Abstract: We introduce the Simba simulations, the next generation of the Mufasa cosmological galaxy formation simulations run with Gizmo's meshless finite mass hydrodynamics. Simba includes updates to Mufasa's sub-resolution star formation and feedback prescriptions, and introduces black hole growth via the torque-limited accretion model of Angles-Alcazar et al. (2017) from cold gas and Bondi accretion from hot gas, along with black hole feedback via kinetic bipolar outflows and X-ray energy. Ejection velocities are taken to be ~10^3 km/s at high Eddington ratios, increasing to ~8000 km/s at Eddington ratios below 2%, with a constant momentum input of 20L/c. Simba further includes an on-the-fly dust production, growth, and destruction model. Our Simba run with (100 Mpc/h)^3 and 1024^3 gas elements reproduces numerous observables, including galaxy stellar mass functions at z=0-6, the stellar mass--star formation rate main sequence, HI and H2 fractions, the mass-metallicity relation at z=0 and z=2, star-forming galaxy sizes, hot gas fractions in massive halos, and z=0 galaxy dust properties. However, Simba also yields an insufficiently sharp truncation of the z=0 mass function, and too-large sizes for low-mass quenched galaxies. We show that Simba's jet feedback is primarily responsible for quenching massive galaxies.

Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data

Abstract: We measure cosmic weak lensing shear power spectra with the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalog covering 137 deg^2 of the sky. Thanks to the high effective galaxy number density of ∼17 arcmin^−2, even after conservative cuts such as a magnitude cut of i < 24.5 and photometric redshift cut of 0.3 ≤ z ≤ 1.5, we obtain a high-significance measurement of the cosmic shear power spectra in four tomographic redshift bins, achieving a total signal-to-noise ratio of 16 in the multipole range 300 ≤ l ≤ 1900. We carefully account for various uncertainties in our analysis including the intrinsic alignment of galaxies, scatters and biases in photometric redshifts, residual uncertainties in the shear measurement, and modeling of the matter power spectrum. The accuracy of our power spectrum measurement method as well as our analytic model of the covariance matrix are tested against realistic mock shear catalogs. For a flat Λ cold dark matter model, we find |$S\,_{8}\equiv \sigma _8(\Omega _{\rm m}/0.3)^\alpha =0.800^{+0.029}_{-0.028}$| for α = 0.45 (⁠|$S\,_8=0.780^{+0.030}_{-0.033}$| for α = 0.5) from our HSC tomographic cosmic shear analysis alone. In comparison with Planck cosmic microwave background constraints, our results prefer slightly lower values of S_8, although metrics such as the Bayesian evidence ratio test do not show significant evidence for discordance between these results. We study the effect of possible additional systematic errors that are unaccounted for in our fiducial cosmic shear analysis, and find that they can shift the best-fit values of S_8 by up to ∼0.6 σ in both directions. The full HSC survey data will contain several times more area, and will lead to significantly improved cosmological constraints.

Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the Global Burden of Disease Study 2016

Abstract: Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7% (95% uncertainty interval 0.4% to 15.6%) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7% (27.2% to 36.6%) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6%. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0%, 95% uncertainty interval 42.6% to 54.6%) than men (23.8%, 15.6% to 32.7%). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates.

First results from the TNG50 simulation: galactic outflows driven by supernovae and black hole feedback

Abstract: We present the new TNG50 cosmological, magnetohydrodynamical simulation -- the third and final volume of the IllustrisTNG project. This simulation occupies a unique combination of large volume and high resolution, with a 50 Mpc box sampled by 2160^3 gas cells (baryon mass of 8x10^4 Msun). The median spatial resolution of star-forming ISM gas is ~100-140 parsecs. This resolution approaches or exceeds that of modern 'zoom' simulations of individual massive galaxies, while the volume contains ~20,000 resolved galaxies with M*>10^7 Msun. Herein we show first results from TNG50, focusing on galactic outflows driven by supernovae as well as supermassive black hole feedback. We find that the outflow mass loading is a non-monotonic function of galaxy stellar mass, turning over and rising rapidly above 10^10.5 Msun due to the action of the central black hole. Outflow velocity increases with stellar mass, and at fixed mass is faster at higher redshift. The TNG model can produce high velocity, multi-phase outflows which include cool, dense components. These outflows reach speeds in excess of 3000 km/s out to 20 kpc with an ejective, BH-driven origin. Critically, we show how the relative simplicity of model inputs (and scalings) at the injection scale produces complex behavior at galactic and halo scales. For example, despite isotropic wind launching, outflows exhibit natural collimation and an emergent bipolarity. Furthermore, galaxies above the star-forming main sequence drive faster outflows, although this correlation inverts at high mass with the onset of quenching, whereby low luminosity, slowly accreting, massive black holes drive the strongest outflows.

Recommendations for performing, interpreting and reporting hydrogen deuterium exchange mass spectrometry (HDX-MS) experiments.

Abstract: Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a powerful biophysical technique being increasingly applied to a wide variety of problems. As the HDX-MS community continues to grow, adoption of best practices in data collection, analysis, presentation and interpretation will greatly enhance the accessibility of this technique to nonspecialists. Here we provide recommendations arising from community discussions emerging out of the first International Conference on Hydrogen-Exchange Mass Spectrometry (IC-HDX; 2017). It is meant to represent both a consensus viewpoint and an opportunity to stimulate further additions and refinements as the field advances.

The Seventh Visual Object Tracking VOT2019 Challenge Results

Abstract: The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website.

First results from the TNG50 simulation: the evolution of stellar and gaseous discs across cosmic time

Abstract: We present a new cosmological, magnetohydrodynamical simulation for galaxy formation: TNG50, the third and final instalment of the Illustris TNG project. TNG50 evolves 2 x 2160(3) dark matter particles and gas cells in a volume 50 comoving Mpc across. It hence reaches a numerical resolution typical of zoom-in simulations, with a baryonic element mass of 8.5 x 10(4) M-circle dot and an average cell size of 70-140 pc in the star-forming regions of galaxies. Simultaneously, TNG50 samples similar to 700 (6500) galaxies with stellar masses above 10(10) (10(8)) M-circle dot at z = 1. Here we investigate the structural and kinematical evolution of star-forming galaxies across cosmic time (0 less than or similar to z less than or similar to 6). We quantify their sizes, disc heights, 3D shapes, and degree of rotational versus dispersion-supported motions as traced by rest-frame V-band light (i.e. roughly stellar mass) and by H alpha light (i.e. star-forming and dense gas). The unprecedented resolution of TNG50 enables us to model galaxies with sub-kpc half-light radii and with less than or similar to 300-pc disc heights. Coupled with the large-volume statistics, we characterize a diverse, redshift- and mass-dependent structural and kinematical morphological mix of galaxies all the way to early epochs. Our model predicts that for star-forming galaxies the fraction of disc-like morphologies, based on 3D stellar shapes, increases with both cosmic time and galaxy stellar mass. Gas kinematics reveal that the vast majority of 10(9-11.5) M-circle dot star-forming galaxies are rotationally supported discs for most cosmic epochs (V-rot/sigma > 2-3, z less than or similar to 5), being dynamically hotter at earlier epochs (z greater than or similar to 1.5). Despite large velocity dispersion at high redshift, cold and dense gas in galaxies predominantly arranges in disky or elongated shapes at all times and masses; these gaseous components exhibit rotationally dominated motions far exceeding the collisionless stellar bodies.

Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation

Abstract: We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). RSP is a new functionality in MESAstar that models the non-linear radial stellar pulsations that characterize RR Lyrae, Cepheids, and other classes of variable stars. We significantly enhance numerical energy conservation capabilities, including during mass changes. For example, this enables calculations through the He flash that conserve energy to better than 0.001 %. To improve the modeling of rotating stars in MESA, we introduce a new approach to modifying the pressure and temperature equations of stellar structure, and a formulation of the projection effects of gravity darkening. A new scheme for tracking convective boundaries yields reliable values of the convective-core mass, and allows the natural emergence of adiabatic semiconvection regions during both core hydrogen- and helium-burning phases. We quantify the parallel performance of MESA on current generation multicore architectures and demonstrate improvements in the computational efficiency of radiative levitation. We report updates to the equation of state and nuclear reaction physics modules. We briefly discuss the current treatment of fallback in core-collapse supernova models and the thermodynamic evolution of supernova explosions. We close by discussing the new MESA Testhub software infrastructure to enhance source-code development.

AMASS: Archive of Motion Capture As Surface Shapes

Abstract: Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion. While there are many different datasets available, they each use a different parameterization of the body, making it difficult to integrate them into a single meta dataset. To address this, we introduce AMASS, a large and varied database of human motion that unifies 15 different optical marker-based mocap datasets by representing them within a common framework and parameterization. We achieve this using a new method, MoSh++, that converts mocap data into realistic 3D human meshes represented by a rigged body model. Here we use SMPL [Loper et al., 2015], which is widely used and provides a standard skeletal representation as well as a fully rigged surface mesh. The method works for arbitrary marker sets, while recovering soft-tissue dynamics and realistic hand motion. We evaluate MoSh++ and tune its hyperparameters using a new dataset of 4D body scans that are jointly recorded with markerbased mocap. The consistent representation of AMASS makes it readily useful for animation, visualization, and generating training data for deep learning. Our dataset is significantly richer than previous human motion collections, having more than 40 hours of motion data, spanning over 300 subjects, more than 11000 motions, and will be publicly available to the research community.

Identifying a First-Order Phase Transition in Neutron-Star Mergers through Gravitational Waves.

Abstract: We identify an observable imprint of a first-order hadron-quark phase transition at supranuclear densities on the gravitational-wave (GW) emission of neutron-star mergers. Specifically, we show that the dominant postmerger GW frequency fpeak may exhibit a significant deviation from an empirical relation between fpeak and the tidal deformability if a strong first-order phase transition leads to the formation of a gravitationally stable extended quark matter core in the postmerger remnant. A comparison of the GW signatures from a large, representative sample of microphysical, purely hadronic equations of state indicates that this imprint is only observed in those systems which undergo a strong first-order phase transition. Such a shift of the dominant postmerger GW frequency can be revealed by future GW observations, which would provide evidence for the existence of a strong first-order phase transition in the interior of neutron-stars.

AMASS: Archive of Motion Capture as Surface Shapes

Abstract: Large datasets are the cornerstone of recent advances in computer vision using deep learning In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion While there are many different datasets available, they each use a different parameterization of the body, making it difficult to integrate them into a single meta dataset To address this, we introduce AMASS, a large and varied database of human motion that unifies 15 different optical marker-based mocap datasets by representing them within a common framework and parameterization We achieve this using a new method, MoSh++, that converts mocap data into realistic 3D human meshes represented by a rigged body model; here we use SMPL [doi:101145/28167952818013], which is widely used and provides a standard skeletal representation as well as a fully rigged surface mesh The method works for arbitrary marker sets, while recovering soft-tissue dynamics and realistic hand motion We evaluate MoSh++ and tune its hyperparameters using a new dataset of 4D body scans that are jointly recorded with marker-based mocap The consistent representation of AMASS makes it readily useful for animation, visualization, and generating training data for deep learning Our dataset is significantly richer than previous human motion collections, having more than 40 hours of motion data, spanning over 300 subjects, more than 11,000 motions, and will be publicly available to the research community

The International Pulsar Timing Array: second data release

Abstract: In this paper, we describe the International Pulsar Timing Array second data release, which includes recent pulsar timing data obtained by three regional consortia: the European Pulsar Timing Array, the North American Nanohertz Observatory for Gravitational Waves, and the Parkes Pulsar Timing Array. We analyse and where possible combine high-precision timing data for 65 millisecond pulsars which are regularly observed by these groups. A basic noise analysis, including the processes which are both correlated and uncorrelated in time, provides noise models and timing ephemerides for the pulsars. We find that the timing precisions of pulsars are generally improved compared to the previous data release, mainly due to the addition of new data in the combination. The main purpose of this work is to create the most up-to-date IPTA data release. These data are publicly available for searches for low-frequency gravitational waves and other pulsar science.

Widespread loss of lake ice around the Northern Hemisphere in a warming world

Abstract: Ice provides a range of ecosystem services—including fish harvest1, cultural traditions2, transportation3, recreation4 and regulation of the hydrological cycle5—to more than half of the world’s 117 million lakes. One of the earliest observed impacts of climatic warming has been the loss of freshwater ice6, with corresponding climatic and ecological consequences7. However, while trends in ice cover phenology have been widely documented2,6,8,9, a comprehensive large-scale assessment of lake ice loss is absent. Here, using observations from 513 lakes around the Northern Hemisphere, we identify lakes vulnerable to ice-free winters. Our analyses reveal the importance of air temperature, lake depth, elevation and shoreline complexity in governing ice cover. We estimate that 14,800 lakes currently experience intermittent winter ice cover, increasing to 35,300 and 230,400 at 2 and 8 °C, respectively, and impacting up to 394 and 656 million people. Our study illustrates that an extensive loss of lake ice will occur within the next generation, stressing the importance of climate mitigation strategies to preserve ecosystem structure and function, as well as local winter cultural heritage. Up to 35,000 lakes in the Northern Hemisphere may be at risk of intermittent winter ice cover at 2 °C warming, reveals an observation-based study. This would affect 394 million people reliant on lake ice for ecosystem services.

Testing the no-hair theorem with GW150914

Abstract: We analyze gravitational-wave data from the first LIGO detection of a binary black-hole merger (GW150914) in search of the ringdown of the remnant black hole. Using observations beginning at the peak of the signal, we find evidence of the fundamental quasinormal mode and at least one overtone, both associated with the dominant angular mode (l=m=2), with 3.6σ confidence. A ringdown model including overtones allows us to measure the final mass and spin magnitude of the remnant exclusively from postinspiral data, obtaining an estimate in agreement with the values inferred from the full signal. The mass and spin values we measure from the ringdown agree with those obtained using solely the fundamental mode at a later time, but have smaller uncertainties. Agreement between the postinspiral measurements of mass and spin and those using the full waveform supports the hypothesis that the GW150914 merger produced a Kerr black hole, as predicted by general relativity, and provides a test of the no-hair theorem at the ∼10% level. An independent measurement of the frequency of the first overtone yields agreement with the no-hair hypothesis at the ∼20% level. As the detector sensitivity improves and the detected population of black-hole mergers grows, we can expect that using overtones will provide even stronger tests.

The Belle II Physics Book

Abstract: The Belle II detector will provide a major step forward in precision heavy flavor physics, quarkonium and exotic states, searches for dark sectors, and many other areas. The sensitivity to a large number of key observables can be improved by about an order of magnitude compared to the current measurements, and up to two orders in very clean search measurements. This increase in statistical precision arises not only due to the increased luminosity, but also from improved detector efficiency and precision for many channels. Many of the most interesting observables tend to have very small theoretical uncertainties that will therefore not limit the physics reach. This book has presented many new ideas for measurements, both to elucidate the nature of current anomalies seen in flavor, and to search for new phenomena in a plethora of observables that will become accessible with the Belle II dataset. The simulation used for the studiesinthis book was state ofthe artat the time, though weare learning a lot more about the experiment during the commissioning period. The detector is in operation, and working spectacularly well.

Maintenance of Skeletal Muscle Mitochondria in Health, Exercise, and Aging.

Abstract: Mitochondria are critical organelles responsible for regulating the metabolic status of skeletal muscle These organelles exhibit remarkable plasticity by adapting their volume, structure, and function in response to chronic exercise, disuse, aging, and disease A single bout of exercise initiates signaling to provoke increases in mitochondrial biogenesis, balanced by the onset of organelle turnover carried out by the mitophagy pathway This accelerated turnover ensures the presence of a high functioning network of mitochondria designed for optimal ATP supply, with the consequence of favoring lipid metabolism, maintaining muscle mass, and reducing apoptotic susceptibility over the longer term Conversely, aging and disuse are associated with reductions in muscle mass that are in part attributable to dysregulation of the mitochondrial network and impaired mitochondrial function Therefore, exercise represents a viable, nonpharmaceutical therapy with the potential to reverse and enhance the impaired mitochondrial function observed with aging and chronic muscle disuse

The Circular Velocity Curve of the Milky Way from 5 to 25 kpc

Abstract: We measure the circular velocity curve $v_{\rm c}(R)$ of the Milky Way with the highest precision to date across Galactocentric distances of $5\leq R \leq 25$ kpc. Our analysis draws on the $6$-dimensional phase-space coordinates of $\gtrsim 23,000$ luminous red-giant stars, for which we previously determined precise parallaxes using a data-driven model that combines spectral data from APOGEE with photometric information from WISE, 2MASS, and Gaia. We derive the circular velocity curve with the Jeans equation assuming an axisymmetric gravitational potential. At the location of the Sun we determine the circular velocity with its formal uncertainty to be $v_{\rm c}(R_{\odot}) = (229.0\pm0.2)\rm\,km\,s^{-1}$ with systematic uncertainties at the $\sim 2-5\%$ level. We find that the velocity curve is gently but significantly declining at $(-1.7\pm0.1)\rm\,km\,s^{-1}\,kpc^{-1}$, with a systematic uncertainty of $0.46\rm\,km\,s^{-1}\,kpc^{-1}$, beyond the inner $5$ kpc. We exclude the inner $5$ kpc from our analysis due to the presence of the Galactic bar, which strongly influences the kinematic structure and requires modeling in a non-axisymmetric potential. Combining our results with external measurements of the mass distribution for the baryonic components of the Milky Way from other studies, we estimate the Galaxy's dark halo mass within the virial radius to be $M_{\rm vir} = (7.25\pm0.26)\cdot 10^{11}M_{\odot}$ and a local dark matter density of $\rho_{\rm dm}(R_{\odot}) = 0.30\pm0.03\,\rm GeV\,cm^{-3}$.

Cloud/Fog Computing Resource Management and Pricing for Blockchain Networks

Abstract: Public blockchain networks using proof of work (PoW)-based consensus protocols are considered as a promising platform for decentralized resource management with financial incentive mechanisms. In order to maintain a secured, universal state of the blockchain, PoW-based consensus protocols financially incentivize the nodes in the network to compete for the privilege of block generation through cryptographic puzzle solving. For rational consensus nodes, i.e., miners with limited local computational resources, offloading the computation load for PoW to the cloud/fog providers (CFPs) becomes a viable option. In this paper, we study the interaction between the CFPs and the miners in a PoW-based blockchain network using a game theoretic approach. In particular, we propose a lightweight infrastructure of the PoW-based blockchains, where the computation-intensive part of the consensus process is offloaded to the cloud/fog. We formulate the computation resource management in the blockchain consensus process as a two-stage Stackelberg game, where the profit of the CFP and the utilities of the individual miners are jointly optimized. In the first stage of the game, the CFP sets the price of offered computing resource. In the second stage, the miners decide on the amount of service to purchase accordingly. We apply backward induction to analyze the subgame perfect equilibria in each stage for both uniform and discriminatory pricing schemes. For uniform pricing where the same price applies to all miners, the uniqueness of the Stackelberg equilibrium is validated by identifying the best response strategies of the miners. For discriminatory pricing where the different prices are applied, the uniqueness of the Stackelberg equilibrium is proved by capitalizing on the variational inequality theory. Further, the real experimental results are employed to justify our proposed model.

Combination of searches for invisible Higgs boson decays with the ATLAS experiment

Abstract: Dark matter particles, if sufficiently light, may be produced in decays of the Higgs boson. This Letter presents a statistical combination of searches for H→invisible decays where H is produced according to the standard model via vector boson fusion, Z(ll)H, and W/Z(had)H, all performed with the ATLAS detector using 36.1 fb^{-1} of pp collisions at a center-of-mass energy of sqrt[s]=13 TeV at the LHC. In combination with the results at sqrt[s]=7 and 8 TeV, an exclusion limit on the H→invisible branching ratio of 0.26(0.17_{-0.05}^{+0.07}) at 95% confidence level is observed (expected).

A measurement of the atomic hydrogen Lamb shift and the proton charge radius.

Abstract: The surprising discrepancy between results from different methods for measuring the proton charge radius is referred to as the proton radius puzzle. In particular, measurements using electrons seem to lead to a different radius compared with those using muons. Here, a direct measurement of the n = 2 Lamb shift of atomic hydrogen is presented. Our measurement determines the proton radius to be rp = 0.833 femtometers, with an uncertainty of ±0.010 femtometers. This electron-based measurement of rp agrees with that obtained from the analogous muon-based Lamb shift measurement but is not consistent with the larger radius that was obtained from the averaging of previous electron-based measurements.

Electron and photon performance measurements with the ATLAS detector using the 2015-2017 LHC proton-proton collision data

Abstract: This paper describes the reconstruction of electrons and photons with the ATLAS detector, employed for measurements and searches exploiting the complete LHC Run 2 dataset. An improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail. Corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies, and the measurement of the charge of reconstructed electron candidates are determined using up to 81 fb−1 of proton-proton collision data collected at √s=13 TeV between 2015 and 2017.

The optical morphologies of galaxies in the IllustrisTNG simulation: A comparison to Pan-STARRS observations

Abstract: We have generated synthetic images of $\sim$27,000 galaxies from the IllustrisTNG and the original Illustris hydrodynamic cosmological simulations, designed to match Pan-STARRS observations of $\log_{10}(M_{\ast}/{\rm M}_{\odot}) \approx 9.8$-$11.3$ galaxies at $z \approx 0.05$. Most of our synthetic images were created with the SKIRT radiative transfer code, including the effects of dust attenuation and scattering, and performing the radiative transfer directly on the Voronoi mesh used by the simulations themselves. We have analysed both our synthetic and real Pan-STARRS images with the newly developed $\tt{statmorph}$ code, which calculates non-parametric morphological diagnostics -- including the Gini-$M_{20}$ and concentration-asymmetry-smoothness (CAS) statistics -- and performs two-dimensional Sersic fits. Overall, we find that the optical morphologies of IllustrisTNG galaxies are in good agreement with observations, and represent a substantial improvement compared to the original Illustris simulation. In particular, the locus of the Gini-$M_{20}$ diagram is consistent with that inferred from observations, while the median trends with stellar mass of all the morphological, size and shape parameters considered in this work lie within the $\sim$1$\sigma$ scatter of the observational trends. However, the IllustrisTNG model has some difficulty with more stringent tests, such as producing a strong morphology-colour relation. This results in a somewhat higher fraction of red discs and blue spheroids compared to observations. Similarly, the morphology-size relation is problematic: while observations show that discs tend to be larger than spheroids at a fixed stellar mass, such a trend is not present in IllustrisTNG.