Cosmological HII Bubble Growth During Reionization

We present general properties of ionized hydrogen (HII) bubbles and their growth based on a state-of-the-art large-scale (100 Mpc/h) cosmological radiative transfer simulation. The simulation resolves all halos with atomic cooling at the relevant redshifts and simultaneously performs radiative transfer and dynamical evolution of structure formation. Our major conclusions include: (1) for significant HII bubbles, the number distribution is peaked at a volume of $\sim 0.6 {\rm Mpc^{3}/h^{3}}$ at all redshifts. But, at $z\le 10$, one large, connected network of bubbles dominates the entire HII volume. (2) HII bubbles are highly non-spherical. (3) The HII regions are highly biased with respect to the underlying matter distribution with the bias decreasing with time. (4) The non-gaussianity of the HII region is small when the universe becomes 50% ionized. The non-gaussianity reaches its maximal near the end of the reionization epoch $z\sim 6$. But at all redshifts of interest there is a significant non-gaussianity in the HII field. (5) Population III galaxies may play a significant role in the reionization process. Small bubbles are initially largely produced by Pop III stars. At $z\ge 10$ even the largest HII bubbles have a balanced ionizing photon contribution from Pop II and Pop III stars, while at $z\le 8$ Pop II stars start to dominate the overall ionizing photon production for large bubbles, although Pop III stars continue to make a non-negligible contribution. (6) The relationship between halo number density and bubble size is complicated but a strong correlation is found between halo number density and bubble size for large bubbles.Comment: 10 pages, 14 figures; accepted version; higher resolution figures and supplementary material can be found at http://www.astro.princeton.edu/~msshin/reionization/web.ht

The EPOCH Project: I. Periodic variable stars in the EROS-2 LMC database

The EPOCH (EROS-2 periodic variable star classification using machine learning) project aims to detect periodic variable stars in the EROS-2 light curve database. In this paper, we present the first result of the classification of periodic variable stars in the EROS-2 LMC database. To classify these variables, we first built a training set by compiling known variables in the Large Magellanic Cloud area from the OGLE and MACHO surveys. We crossmatched these variables with the EROS-2 sources and extracted 22 variability features from 28 392 light curves of the corresponding EROS-2 sources. We then used the random forest method to classify the EROS-2 sources in the training set. We designed the model to separate not only $\delta$ Scuti stars, RR Lyraes, Cepheids, eclipsing binaries, and long-period variables, the superclasses, but also their subclasses, such as RRab, RRc, RRd, and RRe for RR Lyraes, and similarly for the other variable types. The model trained using only the superclasses shows 99% recall and precision, while the model trained on all subclasses shows 87% recall and precision. We applied the trained model to the entire EROS-2 LMC database, which contains about 29 million sources, and found 117 234 periodic variable candidates. Out of these 117 234 periodic variables, 55 285 have not been discovered by either OGLE or MACHO variability studies. This set comprises 1 906 $\delta$ Scuti stars, 6 607 RR Lyraes, 638 Cepheids, 178 Type II Cepheids, 34 562 eclipsing binaries, and 11 394 long-period variables. A catalog of these EROS-2 LMC periodic variable stars will be available online at http://stardb.yonsei.ac.kr and at the CDS website (http://vizier.u-strasbg.fr/viz-bin/VizieR).Comment: 18 pages, 20 figures, suggseted language-editing by the A&A editorial office is applie

Optimal Multiuser Diversity in Multi-Cell MIMO Uplink Networks: User Scaling Law and Beamforming Design

We introduce a distributed protocol to achieve multiuser diversity in a multicell multiple-input multiple-output (MIMO) uplink network, referred to as a MIMO interfering multiple-access channel (IMAC). Assuming both no information exchange among base stations (BS) and local channel state information at the transmitters for the MIMO IMAC, we propose a joint beamforming and user scheduling protocol, and then show that the proposed protocol can achieve the optimal multiuser diversity gain, i.e., KM log (SNR log N), as long as the number of mobile stations (MSs) in a cell, N, scales faster than SNRKM-L/1-epsilon for a small constant epsilon > 0, where M, L, K, and SNR denote the number of receive antennas at each BS, the number of transmit antennas at each MS, the number of cells, and the signal-to-noise ratio, respectively. Our result indicates that multiuser diversity can be achieved in the presence of intra-cell and inter-cell interference even in a distributed fashion. As a result, vital information on how to design distributed algorithms in interference-limited cellular environments is provided

Detecting Variability in Massive Astronomical Time-series Data. II. Variable Candidates in the Northern Sky Variability Survey

We present variability analysis of data from the Northern Sky Variability Survey (NSVS). Using the clustering method, which defines variable candidates as outliers from large clusters, we cluster 16,189,040 light curves having data points at more than 15 epochs as variable and non-variable candidates in 638 NSVS fields. Variable candidates are selected depending on how strongly they are separated from the largest cluster and how rarely they are grouped together in eight-dimensional space spanned by variability indices. All NSVS light curves are also cross-correlated with IRAS , AKARI, Two Micron All Sky Survey, Sloan Digital Sky Survey (SDSS), and GALEX objects, as well as known objects in the SIMBAD database. The variability analysis and cross-correlation results are provided in a public online database, which can be used to select interesting objects for further investigation. Adopting conservative selection criteria for variable candidates, we find about 1.8 million light curves as possible variable candidates in the NSVS data, corresponding to about 10% of our entire NSVS sample. Multi-wavelength colors help us find specific types of variability among the variable candidates. Moreover, we also use morphological classification from other surveys such as SDSS to suppress spurious cases caused by blending objects or extended sources due to the low angular resolution of the NSVS.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98631/1/1538-3881_143_3_65.pd

Scaling Law for Recommendation Models: Towards General-purpose User Representations

Recent advancement of large-scale pretrained models such as BERT, GPT-3, CLIP, and Gopher, has shown astonishing achievements across various task domains. Unlike vision recognition and language models, studies on general-purpose user representation at scale still remain underexplored. Here we explore the possibility of general-purpose user representation learning by training a universal user encoder at large scales. We demonstrate that the scaling law is present in user representation learning areas, where the training error scales as a power-law with the amount of computation. Our Contrastive Learning User Encoder (CLUE), optimizes task-agnostic objectives, and the resulting user embeddings stretch our expectation of what is possible to do in various downstream tasks. CLUE also shows great transferability to other domains and companies, as performances on an online experiment shows significant improvements in Click-Through-Rate (CTR). Furthermore, we also investigate how the model performance is influenced by the scale factors, such as training data size, model capacity, sequence length, and batch size. Finally, we discuss the broader impacts of CLUE in general.Comment: Accepted at AAAI 2023. This version includes the technical appendi

The Magnetohydrodynamics of Shock-Cloud Interaction in Three Dimensions

The magnetohydrodynamic evolution of a dense spherical cloud as it interacts with a strong planar shock is studied, as a model for shock interactions with density inhomogeneities in the interstellar medium. The cloud is assumed to be small enough that radiative cooling, thermal conduction, and self-gravity can be ignored. A variety of initial orientations (including parallel, perpendicular, and oblique to the incident shock normal) and strengths for the magnetic field are investigated. During the early stages of the interaction (less than twice the time taken for the transmitted shock to cross the interior of the cloud) the structure and dynamics of the shocked cloud is fairly insensitive to the magnetic field strength and orientation. However, at late times strong fields substantially alter the dynamics of the cloud, suppressing fragmentation and mixing by stabilizing the interface at the cloud surface. Even weak magnetic fields can drastically alter the evolution of the cloud compared to the hydrodynamic case. Weak fields of different geometries result in different distributions and amplifications of the magnetic energy density, which may affect the thermal and non-thermal x-ray emission expected from shocked clouds associated with, for example, supernovae remnants.Comment: Accepted for publication in Astrophysical Journal; a higher resolution file can be found at http://www.astro.princeton.edu/~msshin/science/shock_cloud.pdf.g

Highly sensitive colorimetric detection of allergies based on an immunoassay using peroxidase-mimicking nanozymes

Nanomaterials that exhibit enzyme-like characteristics, which are called nanozymes, have recently attracted significant attention due to their potential to overcome the intrinsic limitations of natural enzymes, such as low stability and relatively high cost for preparation and purification. In this study, we report a highly efficient colorimetric allergy detection system based on an immunoassay utilizing the peroxidase- mimicking activity of hierarchically structured platinum nanoparticles (H-Pt NPs). The H-Pt NPs had a diameter of 30 nm, and were synthesized by a seed-mediated growth method, which led to a significant amount of peroxidase-like activity. This activity mainly occurs because of the high catalytic power of the Pt element, and the fact that the H-Pt NPs have a large surface area available for catalytic events. The H-Pt NPs were conjugated to an antibody for the detection of immunoglobulin E (IgE) in the analytes; IgE is a representative marker for the diagnosis of allergies. They were then successfully integrated into a conventionally used allergy diagnostic test, the ImmunoCAP diagnostic test, as a replacement for natural signaling enzymes. Using this strategy, total and specific IgE levels were detected within 5 min at room temperature, with high specificity and sensitivity. The practical utility of the immunoassay was also successfully verified by correctly determining the levels of both total and specific IgE in real human serum samples with high precision and reproducibility. The present H-Pt NP-based immunoassay system would serve as a platform for rapid, robust, and convenient analysis of IgE, and can be extended to the construction of diagnostic systems for a variety of clinically important target molecules.11Ysciescopu