arXiv subjects

Yu Feng

Publications and source records attributed to Yu Feng.

At least 199 records · Page 11Linked to original sources

arXiv2020

Mocking Faint Black Holes during Reionization

To investigate the potential abundance and impact of nuclear black holes (BHs) during reionization, we generate a neural network that estimates their masses and accretion rates by training it on 23 properties of galaxies harbouring them at $z=6$ in the cosmological hydrodynamical simulation Massive-Black II. We then populate all galaxies in the simulation from $z=18$ to $z=5$ with BHs from this network. As the network allows to robustly extrapolate to BH masses below those of the BH seeds, we predict a population of faint BHs with a turnover-free luminosity function, while retaining the bright (and observed) BHs, and together they predict a Universe in which intergalactic hydrogen is $15\%$ ionized at $z=6$ for a clumping factor of 5. Faint BHs may play a stronger role in H reionization without violating any observational constraints. This is expected to have an impact also on pre-heating and -ionization, which is relevant to observations of the 21 cm line from neutral H. We also find that BHs grow more efficiently at higher $z$, but mainly follow a redshift-independent galaxy-BH relation. We provide a power law parametrisation of the hydrogen ionizing emissivity of BHs.

astro-ph.GA↗

arXiv2020

Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: a case study of Hurricane Harvey

With increasing urbanization, in recent years there has been a growing interest and need in monitoring and analyzing urban flood events. Social media, as a new data source, can provide real-time information for flood monitoring. The social media posts with locations are often referred to as Volunteered Geographic Information (VGI), which can reveal the spatial pattern of such events. Since more images are shared on social media than ever before, recent research focused on the extraction of flood-related posts by analyzing images in addition to texts. Apart from merely classifying posts as flood relevant or not, more detailed information, e.g. the flood severity, can also be extracted based on image interpretation. However, it has been less tackled and has not yet been applied for flood severity mapping. In this paper, we propose a novel three-step process to extract and map flood severity information. First, flood relevant images are retrieved with the help of pre-trained convolutional neural networks as feature extractors. Second, the images containing people are further classified into four severity levels by observing the relationship between body parts and their partial inundation, i.e. images are classified according to the water level with respect to different body parts, namely ankle, knee, hip, and chest. Lastly, locations of the Tweets are used for generating a map of estimated flood extent and severity. This process was applied to an image dataset collected during Hurricane Harvey in 2017, as a proof of concept. The results show that VGI can be used as a supplement to remote sensing observations for flood extent mapping and is beneficial, especially for urban areas, where the infrastructure is often occluding water. Based on the extracted water level information, an integrated overview of flood severity can be provided for the early stages of emergency response.

cs.CV↗

arXiv2020

Large scale simulations of H and He reionization and heating driven by stars and more energetic sources

We present simulations of cosmic reionization and reheating from $z=18$ to $z=5$, investigating the role of stars (emitting soft UV-photons), nuclear black holes (BHs, with power-law spectra), X-ray binaries (XRBs, with hard X-ray dominated spectra), and the supernova-associated thermal bremsstrahlung of the diffuse interstellar medium (ISM, with soft X-ray spectra). We post-process the hydrodynamical simulation Massive-Black II (MBII) with multifrequency ionizing radiative transfer. The source properties are directly derived from the physical environment of MBII, and our only real free parameter is the ionizing escape fraction $f_{\rm esc}$. We find that, among the models explored here, the one with an escape fraction that decreases with decreasing redshift yields results most in line with observations, such as of the neutral hydrogen fraction and the Thomson scattering optical depth. Stars are the main driver of hydrogen reionization and consequently of the thermal history of the intergalactic medium (IGM). We obtain $\langle x_{\rm HII} \rangle = 0.99998$ at $z=6$ for all source types, with volume averaged temperatures $\langle T \rangle \sim 20,000~{\rm K}$. BHs are rare and negligible to hydrogen reionization, but conversely they are the only sources which can fully ionize helium, increasing local temperatures by $\sim 10^4~{\rm K}$. The thermal and ionization state of the neutral and lowly ionized hydrogen differs significantly with different source combinations, with ISM and (to a lesser extent) XRBs, playing a significant role and, as a consequence, determining the transition from absorption to emission of the 21 cm signal from neutral hydrogen.

astro-ph.CO↗

arXiv2020

The complete study on polarization of $Υ(nS)$ hadroproduction at QCD next-to-leading order

Applying the nonrelativistic quantum chromodynamics factorization formalism to the $Υ(1S,2S,3S)$ hadroproduction, a complete analysis on the polarization parameters $λ_θ$, $λ_{θϕ}$, $λ_ϕ$ for the production are presented at QCD next-to-leading order. With the long-distance matrix elements extracted from experimental data for the production rate and polarization parameter $λ_θ$ of $Υ$ hadroproduction, our results provide a good description for the measured parameters $λ_{θϕ}$ and $λ_ϕ$ in both the helicity and the Collins-Soper frames. In our calculations the frame invariant parameter $\tildeλ$ is consistent in the two frames. Finally, it is pointed out that there are discrepancies for $\tildeλ$ between available experimental data and corresponding theoretical predictions.

hep-ph↗

arXiv2020

Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation

Point cloud analytics is poised to become a key workload on battery-powered embedded and mobile platforms in a wide range of emerging application domains, such as autonomous driving, robotics, and augmented reality, where efficiency is paramount. This paper proposes Mesorasi, an algorithm-architecture co-designed system that simultaneously improves the performance and energy efficiency of point cloud analytics while retaining its accuracy. Our extensive characterizations of state-of-the-art point cloud algorithms show that, while structurally reminiscent of convolutional neural networks (CNNs), point cloud algorithms exhibit inherent compute and memory inefficiencies due to the unique characteristics of point cloud data. We propose delayed-aggregation, a new algorithmic primitive for building efficient point cloud algorithms. Delayed-aggregation hides the performance bottlenecks and reduces the compute and memory redundancies by exploiting the approximately distributive property of key operations in point cloud algorithms. Delayed-aggregation let point cloud algorithms achieve 1.6x speedup and 51.1% energy reduction on a mobile GPU while retaining the accuracy (-0.9% loss to 1.2% gains). To maximize the algorithmic benefits, we propose minor extensions to contemporary CNN accelerators, which can be integrated into a mobile Systems-on-a-Chip (SoC) without modifying other SoC components. With additional hardware support, Mesorasi achieves up to 3.6x speedup.

cs.CV↗

arXiv2020

Real-Time Spatio-Temporal LiDAR Point Cloud Compression

Compressing massive LiDAR point clouds in real-time is critical to autonomous machines such as drones and self-driving cars. While most of the recent prior work has focused on compressing individual point cloud frames, this paper proposes a novel system that effectively compresses a sequence of point clouds. The idea to exploit both the spatial and temporal redundancies in a sequence of point cloud frames. We first identify a key frame in a point cloud sequence and spatially encode the key frame by iterative plane fitting. We then exploit the fact that consecutive point clouds have large overlaps in the physical space, and thus spatially encoded data can be (re-)used to encode the temporal stream. Temporal encoding by reusing spatial encoding data not only improves the compression rate, but also avoids redundant computations, which significantly improves the compression speed. Experiments show that our compression system achieves 40x to 90x compression rate, significantly higher than the MPEG's LiDAR point cloud compression standard, while retaining high end-to-end application accuracies. Meanwhile, our compression system has a compression speed that matches the point cloud generation rate by today LiDARs and out-performs existing compression systems, enabling real-time point cloud transmission.

eess.IV↗

arXiv2020

Imaging Systematics and Clustering of DESI Main Targets

We evaluate the impact of imaging systematics on the clustering of luminous red galaxies (LRG), emission-line galaxies (ELG) and quasars (QSO) targeted for the upcoming Dark Energy Spectroscopic Instrument (DESI) survey. Using Data Release 7 of the DECam Legacy Survey, we study the effects of astrophysical foregrounds, stellar contamination, differences between north galactic cap and south galactic cap measurements, and variations in imaging depth, stellar density, galactic extinction, seeing, airmass, sky brightness, and exposure time before presenting survey masks and weights to mitigate these effects. With our sanitized samples in hand, we conduct a preliminary analysis of the clustering amplitude and evolution of the DESI main targets. From measurements of the angular correlation functions, we determine power law fits $r_0 = 7.78 \pm 0.26$ $h^{-1}$Mpc, $γ= 1.98 \pm 0.02$ for LRGs and $r_0 = 5.45 \pm 0.1$ $h^{-1}$Mpc, $γ= 1.54 \pm 0.01$ for ELGs. Additionally, from the angular power spectra, we measure the linear biases and model the scale dependent biases in the weakly nonlinear regime. Both sets of clustering measurements show good agreement with survey requirements for LRGs and ELGs, attesting that these samples will enable DESI to achieve precise cosmological constraints. We also present clustering as a function of magnitude, use cross-correlations with external spectroscopy to infer $dN/dz$ and measure clustering as a function of luminosity, and probe higher order clustering statistics through counts-in-cells moments.

astro-ph.CO↗

arXiv2020

Cosmic variance of $z>7$ galaxies: Prediction from BlueTides

In the coming decade, a new generation of telescopes, including JWST and WFIRST, will probe the period of the formation of first galaxies and quasars, and open up the last frontier for structure formation. Recent simulations as well as observations have suggested that these galaxies are strongly clustered (with large scale bias $\gtrsim6$), and therefore have significant cosmic variance. In this work, we use \texttt{BlueTides}, the largest volume cosmological simulation of galaxy formation, to directly estimate the cosmic variance for current and upcoming surveys. Given its resolution and volume, \texttt{BlueTides} can probe the bias and cosmic variance of $z>7$ galaxies between magnitude $M_{UV}\sim-16$ to $M_{UV}\sim-22$ over survey areas $\sim0.1\ \mathrm{arcmin}^2$ to $\sim 10~\mathrm{deg}^2$. Within this regime, the cosmic variance decreases with survey area/ volume as a power law with exponents between $\sim-0.25$ to $\sim-0.45$. For the planned $10~\mathrm{deg}^2$ field of WFIRST, the cosmic variance is between $3\%$ to $10\%$. Upcoming JWST medium/ deep surveys with areas up to $A\sim100\ \mathrm{arcmin}^2$ will have cosmic variance ranging from $\sim 20-50\%$. Lensed surveys have the highest cosmic variance $\gtrsim 40\%$; the cosmic variance of $M_{UV}\lesssim-16$ galaxies is $\lesssim100\%$ up to $z\sim11$. At higher redshifts such as $z\sim12~(14)$, effective volumes of $\gtrsim(8~\mathrm{Mpc}/h)^3$ ($\gtrsim(12\ \mathrm{Mpc}/h)^3$) are required to limit the cosmic variance to within $100\%$. Finally, we find that cosmic variance is larger than Poisson variance and forms the dominant component of the overall uncertainty in all current and upcoming surveys. We present our calculations in the form of simple fitting functions and an online cosmic variance calculator (CV_AT_COSMIC_DAWN) which we publicly release.

astro-ph.CO↗

arXiv2020

Phase separation in the advective Cahn-Hilliard equation

The Cahn--Hilliard equation is a classic model of phase separation in binary mixtures that exhibits spontaneous coarsening of the phases. We study the Cahn--Hilliard equation with an imposed advection term in order to model the stirring and eventual mixing of the phases. The main result is that if the imposed advection is sufficiently mixing then no phase separation occurs, and the solution instead converges exponentially to a homogeneous mixed state. The mixing effectiveness of the imposed drift is quantified in terms of the dissipation time of the associated advection-hyperdiffusion equation, and we produce examples of velocity fields with a small dissipation time. We also study the relationship between this quantity and the dissipation time of the standard advection-diffusion equation.

math.AP↗

arXiv2020

More accurate simulations with separate initial conditions for baryons and dark matter

We revisit techniques for performing cosmological simulations with both baryons and cold dark matter when each fluid has different initial conditions, as is the case at the end of the radiation era. Most simulations do not reproduce the linear prediction for the difference between the cold dark matter and baryon perturbations. We show that this is due to the common use of offset regular grids when setting up the particle initial conditions. The correct behaviour can be obtained without any loss of simulation resolution by using a Lagrangian glass for the baryon particles. We further show that the difference between cold dark matter and baryons may affect predictions for the Lyman-alpha forest flux power spectrum at the 5% level, potentially impacting current cosmological constraints.

astro-ph.CO↗

arXiv2020

The early growth of supermassive black holes in cosmological hydrodynamic simulations with constrained Gaussian realizations

The paper examines the early growth of supermassive black holes (SMBHs) in cosmological hydrodynamic simulations with different BH seeding scenarios. Employing the constrained Gaussian realization, we reconstruct the initial conditions in the large-volume BlueTides simulation and run them to $z=6$ to cross-validate that the method reproduces the first quasars and their environments. Our constrained simulations in a volume of $(15\, h^{-1}{\rm Mpc})^3$ successfully recover the evolution of large-scale structure and the stellar and BH masses in the vicinity of a $\sim10^{12}\, M_{\odot}$ halo which we identified in BlueTides at $z\sim7$ hosting a $\sim10^9\, M_{\odot}$ SMBH. Among our constrained simulations, only the ones with a low-tidal field and high-density peak in the initial conditions induce the fastest BH growth required to explain the $z>6$ quasars. We run two sets of simulations with different BH seed masses of $5\times10^3$, $5\times10^4$, and $5\times10^5\, h^{-1}M_{\odot}$, (a) with the same ratio of halo to BH seed mass and (b) with the same halo threshold mass. At $z=6$, all the SMBHs converge in mass to $\sim10^9\, M_{\odot}$ except for the one with the smallest seed in (b) undergoing critical BH growth and reaching $10^8$ -- $10^9\, M_{\odot}$, albeit with most of the growth in (b) delayed compared to set (a). The finding of eight BH mergers in the small-seed scenario (four with masses $10^4$ -- $10^6\, M_{\odot}$ at $z>12$), six in the intermediate-seed scenario, and zero in the large-seed scenario suggests that the vast BHs in the small-seed scenario merge frequently during the early phases of the growth of SMBHs. The increased BH merger rate for the low-mass BH seed and halo threshold scenario provides an exciting prospect for discriminating BH formation mechanisms with the advent of multi-messenger astrophysics and next-generation gravitational wave facilities.

astro-ph.GA↗

arXiv2020

Exclusive quarkonium production or decay in soft gluon factorization

In this paper, we study the application of the recently proposed soft gluon factorization (SGF) to exclusive quarkonium production or decay. We find that in the nonrelativistic QCD factorization framework there are too many nonperturbative parameters. Thanks to the factorization of kinematical physics from dynamical physics, the SGF significantly reduces the number of nonperturbative parameters. Therefore, the SGF can improve our predictive power of exclusive quarkonium production or decay. By applying to $η_c+γ$ production at B-factories, our result is the closest one to data among all theoretical calculations.

hep-ph↗

arXiv2020

Singular hyperbolic metrics and negative subharmonic functions

We propose a conjecture that the monodromy group of a singular hyperbolic metric on a non-hyperbolic Riemann surface is {\it Zariski dense} in ${\rm PSL}(2,\,{\Bbb R})$. By using meromorphic differentials and affine connections, we obtain an evidence of the conjecture that the monodromy group of the singular hyperbolic metric can not be contained in four classes of one-dimensional Lie subgroups of ${\rm PSL}(2,\,{\Bbb R})$. Moreover, we confirm the conjecture if the Riemann surface is either one of the once punctured Riemann sphere, the twice punctured Riemann sphere, a once punctured torus and a compact Riemann surface.

math.DG↗

arXiv2020

Nebular Line Emission During the Epoch of Reionization

Nebular emission lines associated with galactic HII regions carry information about both physical properties of the ionised gas and the source of ionising photons as well as providing the opportunity of measuring accurate redshifts and thus distances once a cosmological model is assumed. While nebular line emission has been extensively studied at lower redshift there are currently only few constraints within the epoch of reionisation (EoR, $z>6$), chiefly due to the lack of sensitive near-IR spectrographs. However, this will soon change with the arrival of the Webb Telescope providing sensitive near-IR spectroscopy covering the rest-frame UV and optical emission of galaxies in the EoR. In anticipation of Webb we combine the large cosmological hydrodynamical simulation Bluetides with photoionisation modelling to predict the nebular emission line properties of galaxies at $z=8\to 13$. We find good agreement with the, albeit limited, existing direct and indirect observational constraints on equivalent widths though poorer agreement with luminosity function constraints.

astro-ph.GA↗

arXiv2020

How neural networks find generalizable solutions: Self-tuned annealing in deep learning

Despite the tremendous success of Stochastic Gradient Descent (SGD) algorithm in deep learning, little is known about how SGD finds generalizable solutions in the high-dimensional weight space. By analyzing the learning dynamics and loss function landscape, we discover a robust inverse relation between the weight variance and the landscape flatness (inverse of curvature) for all SGD-based learning algorithms. To explain the inverse variance-flatness relation, we develop a random landscape theory, which shows that the SGD noise strength (effective temperature) depends inversely on the landscape flatness. Our study indicates that SGD attains a self-tuned landscape-dependent annealing strategy to find generalizable solutions at the flat minima of the landscape. Finally, we demonstrate how these new theoretical insights lead to more efficient algorithms, e.g., for avoiding catastrophic forgetting.

physics.data-an↗

arXiv2019

Data-Driven Robust Stabilization with Robust DOA Enlargement for Nonlinear Systems

Most of nonlinear robust control methods just consider the affine nonlinear nominal model. When the nominal model is assumed to be affine nonlinear, available information about existing non-affine nonlinearities is ignored. For non-affine nonlinear system, Li et al. (2019) proposes a new nonlinear control method to solve the robust stabilization problem with estimation of the robust closed-loop DOA (Domain of attraction). However, Li et al. (2019) assumes that the Lyapunov function is given and does not consider the problem of finding a good Lyapunov function to enlarge the estimate of the robust closed-loop DOA. The motivation of this paper is to enlarge the estimate of the closed-loop DOA by selecting an appropriate Lyapunov function. To achieve this goal, a solvable optimization problem is formulated to select an appropriate Lyapunov function from a parameterized positive-definite function set. The effectiveness of proposed method is verified by numerical results.

eess.SY↗

arXiv2019

Neutron Spin Resonance in the Heavily Hole-doped KFe$_{2}$As$_{2}$ Superconductor

We report high-resolution neutron scattering measurements of the low energy spin fluctuations of KFe$_{2}$As$_{2}$, the end member of the hole-doped Ba$_{1-x}$K$_x$Fe$_2$As$_2$ family with only hole pockets, above and below its superconducting transition temperature $T_c$ ($\sim$ 3.5 K). Our data reveals clear spin fluctuations at the incommensurate wave vector ($0.5\pmδ$, 0, $L$), ($δ$ = 0.2)(1-Fe unit cell), which exhibit $L$-modulation peaking at $L=0.5$. Upon cooling to the superconducting state, the incommensurate spin fluctuations gradually open a spin-gap and form a sharp spin resonance mode. The incommensurability ($2δ$ = 0.4) of the resonance mode ($\sim1.2$ meV) is considerably larger than the previously reported value ($2δ$ $\approx0.32$) at higher energies ($\ge\sim6$ meV). The determination of the momentum structure of spin fluctuation in the low energy limit allows a direct comparison with the realistic Fermi surface and superconducting gap structure. Our results point to an $s$-wave pairing with a reversed sign between the hole pockets near the zone center in KFe$_{2}$As$_{2}$.

cond-mat.supr-con↗

arXiv2019

QSO obscuration at high redshift ($z \gtrsim 7$): Predictions from the BlueTides simulation

High-$z$ AGNs hosted in gas rich galaxies are expected to grow through significantly obscured accretion phases. This may limit or bias their observability. In this work, we use \textsc{BlueTides}, a large volume cosmological simulation of galaxy formation to examine quasar obscuration for the highest-redshift ($z \geq 7$) supermassive black holes residing in the center of galaxies. We find that for the bright quasars, most of the high column density gas ($>90\%$) resides in the innermost regions of the host galaxy, (typically within $< 10$ ckpc), while the gas in the outskirts is a minor contributor to the $N_\mathrm H$. The brightest quasars can have large angular variations in galactic obscuration, over 2 orders of magnitude, where the lines of sight with the lowest obscuration are those formed via strong gas outflows driven by AGN feedback. We find that for the overall AGN population, the mean $N_\mathrm H$ is generally larger for high luminosity and BH mass, while the $N_\mathrm H$ distribution is significantly broadened, developing a low $N_\mathrm H $ wing due to the angular variations driven by the AGN outflows/feedback. The obscured fraction P($N_{\rm H} > 10^{23} {\rm cm}^{-2}$) typically range from 0.6 to 1.0 for increasing $L_{X}$ (with $L_X > 10^{43} \rm{ergs/s}$), with no clear trend of redshift evolution. With respect to the galaxy host property, we find a linear relation between $N_{\rm H}$, $M_*$ and $M_{\rm H_2}$ with $\log N_{\rm H} = (0.24 \pm 0.03) \log M_{*} + (20.7 \pm 0.3)$ and $\log N_{\rm H} = (0.47 \pm 0.03) \log M_{\rm H_2} + (18.4 \pm 0.3)$. The dust optical depth in the UV band $τ_{\mathrm UV}$ has tight positive correlation with $N_{\rm H}$. Our dust extincted UVLF is about 1.5 dex lower than the intrinsic UVLF, implying that more than 99\% of the $z \sim 7$ AGNs are heavily dust extincted and therefore would be missed by the UV band observation.

astro-ph.GA↗