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Preferred axion models are minimal realizations of the Peccei-Quinn solution to the strong CP problem while providing a dark matter candidate. These models invoke new heavy quarks that interact strongly with the Standard Model bringing them into thermal equilibrium in the early Universe. We show that for a number of these models, the heavy quarks will decay after axions have decoupled from the Standard Model thermal bath. As a consequence, any axion products in the decay form a component of dark radiation. This provides the potential to differentiate between preferred axion models through measurements of the number of relativistic degrees of freedom. The most sensitive of which comes from the Planck collaboration's measurements of the Cosmic Microwave Background. We find that existing constraints allow us to rule out regions of parameter space for 40% of preferred axion models., Comment: 22 pages, 3 figures, 1 table

We propose practical ways of differentiating the various (Breit-Wigner, theoretical, and energy-dependent) resonance schemes of unstable particles at lepton colliders. First, the energy-dependent scheme can be distinguished from the other two by fitting the $Z$ lineshape scan and forward-backward asymmetries at LEP and future lepton colliders with the $Z$ mass $m_Z$, decay width $\Gamma_Z$, and coupling strength as fitting parameters. Although the Breit-Wigner and theoretical schemes work equally well, the scheme conversion requires the decay width $\Gamma_Z$ to scale inversely with $m_Z$ rather than the usual linear dependence from theoretical calculation. These contradicting behaviors can be used to distinguish the Breit-Wigner and theoretical schemes by the precision $Z$ measurements with single parameter ($m_Z$) fit at future lepton colliders. For the $WW$ threshold scan, its combination with the precise Fermi constant provides another way of distinguishing the Breit-Wigner and theoretical schemes., Comment: 6 pages, 1 table

In the early universe, strong large scale random flows prevail, and when these flows collide it produces sheets and filaments for the conventional particle dark matter model. However, for wave dark matter, the sheets and filaments are parallelly modulated by fine-scale and large-amplitude interference fringes. These long fine fringes tend to be unstable initially and subsequently deform and collapse to form halos of various sizes, perhaps down to proto-globular cluster scales. This work aims to investigate the instability of such fringes. Two colliding streams of quantum waves result in a standing density wave. By contrast, two colliding beams in classical collisionless fluid systems often give rise to beam instability, characterized by unstable oscillations with a complex frequency. Will the quantum standing density wave be subject to a similar instability? In fact, such unstable oscillations have never been observed in conventional quantum mechanical systems. This study discovers that periodic fringes can indeed undergo unstable oscillations or beam instability. The presence of any local density null in the background density that fails the Madelung formulation is shown to be the necessary condition for unstable oscillations. We establish a phase diagram to distinguish between beam instability, Jeans instability, and stable oscillation through theoretical calculations and computer simulations. Roughly speaking, Jeans instability almost always occurs for long-wave density perturbations; beam instability on the other hand always occurs when the density wave is aligned with the beam direction and moreover the period of the density wave is twice the period of background density; lastly, both instabilities diminish for a very low background density. We have engaged in Blocks theorem extensively in the analysis., Comment: 34 pages, 4 figures, 1 table

As wireless networks evolve towards open architectures like O-RAN, testing, and integration platforms are crucial to address challenges like interoperability. This paper describes ARA-O-RAN, a novel O-RAN testbed established through the NSF Platforms for Advanced Wireless Research (PAWR) ARA platform. ARA provides an at-scale rural wireless living lab focused on technologies for digital agriculture and rural communities. As an O-RAN Alliance certified Open Testing and Integration Centre (OTIC), ARA launched ARA-O-RAN -- the first public O-RAN testbed tailored to rural and agriculture use cases, together with the end-to-end, whole-stack programmability. ARA-O-RAN uniquely combines support for outdoor testing across a university campus, surrounding farmlands, and rural communities with a 50-node indoor sandbox. The testbed facilitates vital R\&D to implement open architectures that can meet rural connectivity needs. The paper outlines ARA-O-RAN's hardware system design, software architecture, and enabled research experiments. It also discusses plans aligned with national spectrum policy and rural spectrum innovation. ARA-O-RAN exemplifies the value of purpose-built wireless testbeds in accelerating impactful wireless research.

In speech separation, time-domain approaches have successfully replaced the time-frequency domain with latent sequence feature from a learnable encoder. Conventionally, the feature is separated into speaker-specific ones at the final stage of the network. Instead, we propose a more intuitive strategy that separates features earlier by expanding the feature sequence to the number of speakers as an extra dimension. To achieve this, an asymmetric strategy is presented in which the encoder and decoder are partitioned to perform distinct processing in separation tasks. The encoder analyzes features, and the output of the encoder is split into the number of speakers to be separated. The separated sequences are then reconstructed by the weight-shared decoder, which also performs cross-speaker processing. Without relying on speaker information, the weight-shared network in the decoder directly learns to discriminate features using a separation objective. In addition, to improve performance, traditional methods have extended the sequence length, leading to the adoption of dual-path models, which handle the much longer sequence effectively by segmenting it into chunks. To address this, we introduce global and local Transformer blocks that can directly handle long sequences more efficiently without chunking and dual-path processing. The experimental results demonstrated that this asymmetric structure is effective and that the combination of proposed global and local Transformer can sufficiently replace the role of inter- and intra-chunk processing in dual-path structure. Finally, the presented model combining both of these achieved state-of-the-art performance with much less computation in various benchmark datasets., Comment: Accepted to NeurIPS 2024; Project Page: https://dmlguq456.github.io/SepReformer_Demo

This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs. For this, we use a diverse test set containing a variety of 4K images ranging from digital art to gaming and photography. The images are compressed using the modern AVIF codec, instead of JPEG. All the proposed methods improve PSNR fidelity over Lanczos interpolation, and process images under 10ms. Out of the 160 participants, 25 teams submitted their code and models. The solutions present novel designs tailored for memory-efficiency and runtime on edge devices. This survey describes the best solutions for real-time SR of compressed high-resolution images., Comment: CVPR 2024, AI for Streaming (AIS) Workshop

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. HyperCLOVA X was trained on a balanced mix of Korean, English, and code data, followed by instruction-tuning with high-quality human-annotated datasets while abiding by strict safety guidelines reflecting our commitment to responsible AI. The model is evaluated across various benchmarks, including comprehensive reasoning, knowledge, commonsense, factuality, coding, math, chatting, instruction-following, and harmlessness, in both Korean and English. HyperCLOVA X exhibits strong reasoning capabilities in Korean backed by a deep understanding of the language and cultural nuances. Further analysis of the inherent bilingual nature and its extension to multilingualism highlights the model's cross-lingual proficiency and strong generalization ability to untargeted languages, including machine translation between several language pairs and cross-lingual inference tasks. We believe that HyperCLOVA X can provide helpful guidance for regions or countries in developing their sovereign LLMs., Comment: 44 pages; updated authors list and fixed author names

The analysis of large population economies with incomplete information often entails the integration of a continuum of random variables. We showcase the usefulness of the integral notion \`a la Pettis (1938) to study such models. We present several results on Pettis integrals, including convenient sufficient conditions for Pettis integrability and Fubini-like exchangeability formulae, illustrated through a running example. Building on these foundations, we conduct a unified analysis of Bayesian games with arbitrarily many heterogeneous agents. We provide a sufficient condition on payoff structures, under which the equilibrium uniqueness is guaranteed across all signal structures. Our condition is parsimonious, as it turns out necessary when strategic interactions are undirected. We further identify the moment restrictions, imposed on the equilibrium action-state joint distribution, which have crucial implications for information designer's problem of persuading a population of strategically interacting agents. To attain these results, we introduce and develop novel mathematical tools, built on the theory of integral kernels and reproducing kernel Hilbert spaces in functional analysis.

In this paper, we first present the character texture generation system \textit{Minecraft-ify}, specified to Minecraft video game toward in-game application. Ours can generate face-focused image for texture mapping tailored to 3D virtual character having cube manifold. While existing projects or works only generate texture, proposed system can inverse the user-provided real image, or generate average/random appearance from learned distribution. Moreover, it can be manipulated with text-guidance using StyleGAN and StyleCLIP. These features provide a more extended user experience with enlarged freedom as a user-friendly AI-tool. Project page can be found at https://gh-bumsookim.github.io/Minecraft-ify/, Comment: 2 pages, 2 figures. Accepted as Spotlight to NeurIPS 2023 Workshop on Machine Learning for Creativity and Design

This paper addresses information design with linear best responses of agents, quadratic objective functions of an information designer, and a payoff state distributed according to a Gaussian distribution. We formulate the problem as semidefinite programming (SDP) and use the duality principle to characterize an optimal information structure. There exists a Gaussian information structure that is optimal among all information structures. A necessary and sufficient condition for optimality is that the realizations of the induced action profile and a state satisfy linear constraints derived from the primal and dual SDP. As a result, an observed action profile typically reveals the true state even if individual agents have only partial knowledge. In symmetric network games, an optimal information structure inherits this symmetry, which facilitates the computation of an optimal information structure.

In speaker verification, ECAPA-TDNN has shown remarkable improvement by utilizing one-dimensional(1D) Res2Net block and squeeze-and-excitation(SE) module, along with multi-layer feature aggregation (MFA). Meanwhile, in vision tasks, ConvNet structures have been modernized by referring to Transformer, resulting in improved performance. In this paper, we present an improved block design for TDNN in speaker verification. Inspired by recent ConvNet structures, we replace the SE-Res2Net block in ECAPA-TDNN with a novel 1D two-step multi-scale ConvNeXt block, which we call TS-ConvNeXt. The TS-ConvNeXt block is constructed using two separated sub-modules: a temporal multi-scale convolution (MSC) and a frame-wise feed-forward network (FFN). This two-step design allows for flexible capturing of inter-frame and intra-frame contexts. Additionally, we introduce global response normalization (GRN) for the FFN modules to enable more selective feature propagation, similar to the SE module in ECAPA-TDNN. Experimental results demonstrate that NeXt-TDNN, with a modernized backbone block, significantly improved performance in speaker verification tasks while reducing parameter size and inference time. We have released our code for future studies., Comment: Accepted by ICASSP 2024

Axions and dark photons are common in many extensions of the Standard Model. The dark axion portal -- an axion coupling to the dark photon and photon -- can significantly modify their phenomenology. We study the cosmological constraints on the dark axion portal from Cosmic Microwave Background (CMB) bounds on the energy density of dark radiation, $\Delta N_\text{eff}$. By computing the axion-photon-dark photon collision terms and solving the Boltzmann equations including their effects, we find that light axions are generally more constrained by $\Delta N_\text{eff}$ than from supernova cooling or collider experiments. However, with dark photons at the MeV scale, a window of parameter space is opened up above the supernova limits and below the experimental exclusion, allowing for axion decay constants as low as $f_a \sim 10^4$ GeV. This region also modifies indirectly the neutrino energy density, thus relaxing the cosmological upper bound on the sum of neutrino masses. Future CMB measurements could detect a signal or close this open window on the dark axion portal., Comment: 31 pages, 13 figures. v2: Added section on BBN constraints and extended discussions, figures, and references. Version accepted for publication in JHEP

This work studies the net sum-rate performance of a distributed reconfigurable intelligent surfaces (RISs)-assisted multi-user multiple-input-single-output (MISO) downlink communication system under imperfect instantaneous-channel state information (I-CSI) to implement precoding at the base station (BS) and statistical-CSI (S-CSI) to design the RISs phase-shifts. Two channel estimation (CE) protocols are considered for I-CSI acquisition: (i) a full CE protocol that estimates all direct and RISs-assisted channels over multiple training sub-phases, and (ii) a low-overhead direct estimation (DE) protocol that estimates the end-to-end channel in a single sub-phase. We derive the asymptotic equivalents of signal-to-interference-plus-noise ratio (SINR) and ergodic net sum-rate under both protocols for given RISs phase-shifts, which are then optimized based on S-CSI. Simulation results reveal that the low-complexity DE protocol yields better net sum-rate than the full CE protocol when used to obtain CSI for precoding. A benchmark full I-CSI based RISs design is also outlined and shown to yield higher SINR but lower net sum-rate than the S-CSI based RISs design.

In recent years, badminton analytics has drawn attention due to the advancement of artificial intelligence and the efficiency of data collection. While there is a line of effective applications to improve and investigate player performance, there are only a few public badminton datasets that can be used by researchers outside the badminton domain. Existing badminton singles datasets focus on specific matchups; however, they cannot provide comprehensive studies on different players and various matchups. In this paper, we provide a badminton singles dataset, ShuttleSet22, which is collected from high-ranking matches in 2022. ShuttleSet22 consists of 30,172 strokes in 2,888 rallies in the training set, 1,400 strokes in 450 rallies in the validation set, and 2,040 strokes in 654 rallies in the testing set, with detailed stroke-level metadata within a rally. To benchmark existing work with ShuttleSet22, we hold a challenge, Track 2: Forecasting Future Turn-Based Strokes in Badminton Rallies, at CoachAI Badminton Challenge @ IJCAI 2023, to encourage researchers to tackle this real-world problem through innovative approaches and to summarize insights between the state-of-the-art baseline and improved techniques, exchanging inspiring ideas. The baseline codes and the dataset are made available at https://github.com/wywyWang/CoachAI-Projects/tree/main/CoachAI-Challenge-IJCAI2023., Comment: IJCAI-24 Demo, IT4PSS @ IJCAI-23, and CoachAI Badminton Challenge Track 2 @ IJCAI-23. Challenge website: https://sites.google.com/view/coachai-challenge-2023/

In this paper, we present a statistical beamforming algorithm as a pre-processing step for robust automatic speech recognition (ASR). By modeling the target speech as a non-stationary Laplacian distribution, a mask-based statistical beamforming algorithm is proposed to exploit both its output and masked input variance for robust estimation of the beamformer. In addition, we also present a method for steering vector estimation (SVE) based on a noise power ratio obtained from the target and noise outputs in independent component analysis (ICA). To update the beamformer in the same ICA framework, we derive ICA with distortionless and null constraints on target speech, which yields beamformed speech at the target output and noises at the other outputs, respectively. The demixing weights for the target output result in a statistical beamformer with the weighted spatial covariance matrix (wSCM) using a weighting function characterized by a source model. To enhance the SVE, the strict null constraints imposed by the Lagrange multiplier methods are relaxed by generalized penalties with weight parameters, while the strict distortionless constraints are maintained. Furthermore, we derive an online algorithm based on an optimization technique of recursive least squares (RLS) for practical applications. Experimental results on various environments using CHiME-4 and LibriCSS datasets demonstrate the effectiveness of the presented algorithm compared to conventional beamforming and blind source extraction (BSE) based on ICA on both batch and online processing., Comment: Accepted by TASLP

With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance quality and fan engagement. This is attributed to the availability of public ground-truth datasets. While there are a few available datasets for turn-based sports for action detection, these datasets severely lack structured source data and stroke-level records since these require high-cost labeling efforts from domain experts and are hard to detect using automatic techniques. Consequently, the development of artificial intelligence approaches is significantly hindered when existing models are applied to more challenging structured turn-based sequences. In this paper, we present ShuttleSet, the largest publicly-available badminton singles dataset with annotated stroke-level records. It contains 104 sets, 3,685 rallies, and 36,492 strokes in 44 matches between 2018 and 2021 with 27 top-ranking men's singles and women's singles players. ShuttleSet is manually annotated with a computer-aided labeling tool to increase the labeling efficiency and effectiveness of selecting the shot type with a choice of 18 distinct classes, the corresponding hitting locations, and the locations of both players at each stroke. In the experiments, we provide multiple benchmarks (i.e., stroke influence, stroke forecasting, and movement forecasting) with baselines to illustrate the practicability of using ShuttleSet for turn-based analytics, which is expected to stimulate both academic and sports communities. Over the past two years, a visualization platform has been deployed to illustrate the variability of analysis cases from ShuttleSet for coaches to delve into players' tactical preferences with human-interactive interfaces, which was also used by national badminton teams during multiple international high-ranking matches., Comment: KDD 2023. Project page: https://github.com/wywyWang/CoachAI-Projects

In games with incomplete and ambiguous information, rational behavior depends not only on fundamental ambiguity (ambiguity about states) but also on strategic ambiguity (ambiguity about others' actions), which further induces hierarchies of ambiguous beliefs. We study the impacts of strategic ambiguity in global games and demonstrate the distinct effects of ambiguous-quality and low-quality information. Ambiguous-quality information makes more players choose an action yielding a constant payoff, whereas (unambiguous) low-quality information makes more players choose an ex-ante best response to the uniform belief over the opponents' actions. If the ex-ante best-response action yields a constant payoff, sufficiently ambiguous-quality information induces a unique equilibrium, whereas sufficiently low-quality information generates multiple equilibria. In applications to financial crises, we show that news of more ambiguous quality triggers a debt rollover crisis, whereas news of less ambiguous quality triggers a currency crisis.

We study the electroweak dilepton production with two forward jets at the LHC, aiming to measure the anomalous triple gauge couplings in the Effective Field Theory (EFT) approach. This process exhibits a distinctive feature, namely, the interference between Standard Model (SM) and beyond the SM is resurrected in the inclusive cross section of the full amplitude, including two forward jets. As a concrete illustration, we perform the detailed analytic and numerical study of the interference using a simpler toy process, and discuss the subtlety of the effective W approximation. We propose a new kinematic variable, VBFhardness, that controls the amount of energy flowing into the dilepton subprocess. We show that an appropriate cut on VBFhardness makes the interference resurrection manifest. Finally, we use the invariant mass of the dilepton system as well as the transverse momentum, as done in the literature, to derive the sensitivity to anomalous triple gauge couplings at the LHC and the high luminosity LHC. Our result is compared with the existing limits from the experiments., Comment: 46 pages, 21 figures, typos corrected, references added, extended discussion

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper.

Compression plays an important role on the efficient transmission and storage of images and videos through band-limited systems such as streaming services, virtual reality or videogames. However, compression unavoidably leads to artifacts and the loss of the original information, which may severely degrade the visual quality. For these reasons, quality enhancement of compressed images has become a popular research topic. While most state-of-the-art image restoration methods are based on convolutional neural networks, other transformers-based methods such as SwinIR, show impressive performance on these tasks. In this paper, we explore the novel Swin Transformer V2, to improve SwinIR for image super-resolution, and in particular, the compressed input scenario. Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data. We conduct experiments on three representative tasks: JPEG compression artifacts removal, image super-resolution (classical and lightweight), and compressed image super-resolution. Experimental results demonstrate that our method, Swin2SR, can improve the training convergence and performance of SwinIR, and is a top-5 solution at the "AIM 2022 Challenge on Super-Resolution of Compressed Image and Video"., Comment: European Conference on Computer Vision (ECCV 2022) Workshops

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track~2 targets the super-resolution of compressed video. In Track 1, we use the popular dataset DIV2K as the training, validation and test sets. In Track 2, we propose the LDV 3.0 dataset, which contains 365 videos, including the LDV 2.0 dataset (335 videos) and 30 additional videos. In this challenge, there are 12 teams and 2 teams that submitted the final results to Track 1 and Track 2, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution on compressed image and video. The proposed LDV 3.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge is at https://github.com/RenYang-home/AIM22_CompressSR., Comment: Camera-ready version

It is easier to hear birds than see them. However, they still play an essential role in nature and are excellent indicators of deteriorating environmental quality and pollution. Recent advances in Deep Neural Networks allow us to process audio data to detect and classify birds. This technology can assist researchers in monitoring bird populations and biodiversity. We propose a sound detection and classification pipeline to analyze complex soundscape recordings and identify birdcalls in the background. Our method learns from weak labels and few data and acoustically recognizes the bird species. Our solution achieved 18th place of 807 teams at the BirdCLEF 2022 Challenge hosted on Kaggle., Comment: LifeCLEF2022 (best paper award)

Interacting agents receive public information at no cost and flexibly acquire private information at a cost proportional to entropy reduction. When a policymaker provides more public information, agents acquire less private information, thus lowering information costs. Does more public information raise or reduce uncertainty faced by agents? Is it beneficial or detrimental to welfare? To address these questions, we examine the impacts of public information on flexible information acquisition in a linear-quadratic-Gaussian game with arbitrary quadratic material welfare. More public information raises uncertainty if and only if the game exhibits strategic complementarity, which can be harmful to welfare. However, when agents acquire a large amount of information, more provision of public information increases welfare through a substantial reduction in the cost of information. We give a necessary and sufficient condition for welfare to increase with public information and identify optimal public information disclosure, which is either full or partial disclosure depending upon the welfare function and the slope of the best response.

A policymaker discloses public information to interacting agents who also acquire costly private information. More precise public information reduces the precision and cost of acquired private information. Considering this effect, what disclosure rule should the policymaker adopt? We address this question under two alternative assumptions using a linear quadratic Gaussian game with arbitrary quadratic material welfare and convex information costs. First, the policymaker knows the cost of private information and adopts an optimal disclosure rule to maximize the expected welfare. Second, the policymaker is uncertain about the cost and adopts a robust disclosure rule to maximize the worst-case welfare. Depending on the elasticity of marginal cost, an optimal rule is qualitatively the same as that in the case of either a linear information cost or exogenous private information. The worst-case welfare is strictly increasing if and only if full disclosure is optimal under some information costs, which provides a new rationale for central bank transparency.

We study scalar and fermionic crossing two-component dark matter (C2CDM) models with $ U(1)_X $ dark gauge symmetry. This $ U(1)_X $ gauge symmetry is broken via the dark Higgs mechanism of a dark Higgs field $\Phi$ and the dark photon becomes massive. On the other hand, the same dark Higgs field $\Phi$ also serves as a bridge between each component of two DM sectors such that the dark flavor-changing neutral current (DFCNC) interaction between them is induced. Moreover, the mass splitting between these two DM sectors is generated after $ U(1)_X $ gauge symmetry breaking by nonzero $\langle \Phi \rangle$. We discuss the stability of DM candidates and allowed parameter space from the relic density and other constraints in C2CDM models. Some novel signatures with displaced vertices at Belle II are studied. Finally, the possible explanations of 511 keV $\gamma$-ray line and XENON1T excess in C2CDM models are discussed., Comment: 41 pages, 12 figures

Quasi-isometries are mappings on graphs, with distance-distortions parameterized by a multiplicative factor and an additive constant. The distance-distortions of quasi-isometries are in a general form that captures a wide range of distance-approximating graph simplifications. This paper introduces quasi-isometries into the field of graph simplifications, which is becoming increasingly important as large-scale graphs gain more and more prevalence. We discuss some general goals of graph simplification under the framework of quasi-isometries, and investigate several constructions of quasi-isometric graph simplifications, namely one based on maximal independent sets and one based on grouping vertices. For the latter construction, we prove that it preserves the centers and medians of trees., Comment: 31 pages, 7 figures, to be submitted to "Discrete Mathematics and Theoretical Computer Science"

We propose a new approach to constant-roll warm inflation as a generalization of constant-roll inflation. Based on the $\beta$-function formalism, it is shown that constant-roll warm inflation models with a natural end fall into universality classes defined by three different types of $\beta$-functions, under the assumption that radiation energy density is quasi-stable. Given that warm inflation is completely specified by the $\beta$-function and dissipation coefficient ratio, we investigate whether or not the inflation can physically be realized for enough number of e-foldings at the background level for some combinations of the $\beta$-functions and non-trivial dissipation coefficient ratios., Comment: 10 pages, 5 figures

We report the enhanced superconducting properties of double-chain based superconductor Pr$_{2}$Ba$_{4}$Cu$_{7}$O$_{15-\delta}$ synthesized by the citrate pyrolysis technique. %In spite of the polycrystalline bulk samples, we obtained the higher residual resistivity ratios (10-12). The reduction heat treatment in vacuum results in the appearance of superconducting state with $T_\mathrm{c}$=22-24 K, accompanied by the higher residual resistivity ratios. The superconducting volume fractions are estimated from the ZFC data to be 50$\sim55\%$, indicating the bulk superconductivity. We evaluate from the magneto-transport data the temperature dependence of the superconducting critical field, to establish the superconducting phase diagram. The upper critical magnetic field is estimated to be about 35 T at low temperatures from the resistive transition data using the Werthamer-Helfand-Hohenberg formula. The Hall coefficient $R_{H}$ of the 48-h-reduced superconducting sample is determined to be -0.5$\times10^{-3}$ cm$^{3}$/C at 30 K, suggesting higher electron concentration. These findings have a close relationship with homogeneous distributions of the superconducting grains and improved weak links between their superconducting grains in the present synthesis process., Comment: 7 pages, 6 figures, 1 table. arXiv admin note: substantial text overlap with arXiv:1609.00125, arXiv:1512.01300

We document the activities performed during the second MadAnalysis 5 workshop on LHC recasting, that was organised in KIAS (Seoul, Korea) on February 12-20, 2020. We detail the implementation of 12 new ATLAS and CMS searches in the MadAnalysis 5 Public Analysis Database, and the associated validation procedures. Those searches probe the production of extra gauge and scalar/pseudoscalar bosons, supersymmetry, seesaw models and deviations from the Standard Model in four-top production., Comment: 119 pages, 37 figures, 48 tables and 12 new analyses added to the MadAnalysis 5 Public Analysis Database. More information available from https://indico.cern.ch/event/873524/ and http://madanalysis.irmp.ucl.ac.be/wiki/PublicAnalysisDatabase

Anomalous activity recognition deals with identifying the patterns and events that vary from the normal stream. In a surveillance paradigm, these events range from abuse to fighting and road accidents to snatching, etc. Due to the sparse occurrence of anomalous events, anomalous activity recognition from surveillance videos is a challenging research task. The approaches reported can be generally categorized as handcrafted and deep learning-based. Most of the reported studies address binary classification i.e. anomaly detection from surveillance videos. But these reported approaches did not address other anomalous events e.g. abuse, fight, road accidents, shooting, stealing, vandalism, and robbery, etc. from surveillance videos. Therefore, this paper aims to provide an effective framework for the recognition of different real-world anomalies from videos. This study provides a simple, yet effective approach for learning spatiotemporal features using deep 3-dimensional convolutional networks (3D ConvNets) trained on the University of Central Florida (UCF) Crime video dataset. Firstly, the frame-level labels of the UCF Crime dataset are provided, and then to extract anomalous spatiotemporal features more efficiently a fine-tuned 3D ConvNets is proposed. Findings of the proposed study are twofold 1)There exist specific, detectable, and quantifiable features in UCF Crime video feed that associate with each other 2) Multiclass learning can improve generalizing competencies of the 3D ConvNets by effectively learning frame-level information of dataset and can be leveraged in terms of better results by applying spatial augmentation., Comment: 25 pages, 7, figures, 8 Tables, Under Review in Multimedia Tools and Applications

This paper studies the differences between different types of newspapers in expressing temporal information, which is a topic that has not received much attention. Techniques from the fields of temporal processing and pattern mining are employed to investigate this topic. First, a corpus annotated with temporal information is created by the author. Then, sequences of temporal information tags mixed with part-of-speech tags are extracted from the corpus. The TKS algorithm is used to mine skip-gram patterns from the sequences. With these patterns, the signatures of the four newspapers are obtained. In order to make the signatures uniquely characterize the newspapers, we revise the signatures by removing reference patterns. Through examining the number of patterns in the signatures and revised signatures, the proportion of patterns containing temporal information tags and the specific patterns containing temporal information tags, it is found that newspapers differ in ways of expressing temporal information., Comment: 19 pages

We investigate the post-bounce background dynamics in a certain class of single bounce scenarios studied in the literature, in which the cosmic bounce is driven by a scalar field with negative exponential potential such as the ekpyrotic potential. We show that those models can actually lead to cyclic evolutions with repeated bounces. These cyclic evolutions, however, do not account for the currently observed late-time accelerated expansion and hence are not cosmologically viable. In this respect we consider a new kind of cyclic model proposed recently and derive some cosmological constraints on this model., Comment: 26 pages, 15 figures. Significantly revised and accepted version for JHEP

We study the effective field theory sensitivity of an LHC analysis for the $\tau \nu$ final state with an associated b-jet. To illustrate the improvement due to the b-tagging, we first recast the recent CMS analysis in the $\tau\nu$ channel, using an integrated luminosity of 35.9 fb$^{-1}$ at $\sqrt{s}=13$ TeV, and provide limits on all the dimension-six effective operators which contribute to the process. The expected limits from the b-tagged analysis are then derived and compared. We find an improvement of approximately $\sim 30\%$ in the bounds for operators with a b quark. We also discuss in detail possible angular observables to be used as a discriminator between dimension-six operators with different Lorentz structure. Finally, we study the impact of these limits on some simplified scenarios aimed at addressing the observed deviations from the Standard Model in lepton flavor universality ratios of semileptonic B-meson decays. In particular, we compare the collider limits on those scenarios set by our analysis either with or without the b-tagging, assuming an integrated luminosity of 300 fb$^{-1}$, with relevant low-energy flavor measurements., Comment: 41 pages, 13 figures. The complete chi-square function for our CMS recast is shared in ancillary files. v2: references added, matches the version to be published in JHEP

PTFO 8-8695b (CVSO 30b) is a young planet candidate whose host star is a $\sim$ 2.6 Myr-old T-Tauri star, and there have been continuous discussions about the nature of this system. To unveil the mystery of this system, we observed PTFO8-8695 for around five years at optical and infrared bands simultaneously using Kanata telescope at the Higashi-Hiroshima Observatory. Through our observations, we found that the reported fading event split into two: deeper but phase-shifted "dip-A" and shallower but equiphase "dip-B". These dips disappeared at different epochs, and then, dip-B reappeared. Based on the observed wavelength dependence of dip depths, a dust clump and a precessing planet are likely origins of dip-A and B, respectively. Here we propose "a precessing planet associated with a dust cloud" scenario for this system. This scenario is consistent with the reported change in the depth of fading events, and even with the reported results, which were thought to be negative evidence to the planetary hypothesis, such as the past non-detection of the Rossiter-McLaughlin effect. If this scenario is correct, this is the third case of a young (<3 Myr) planet around a pre-main sequence star. This finding implies that a planet can be formed within a few Myr., Comment: 17 pages, 19 figures, 6 tables, accepted for publication in PASJ

We present a general and model-independent method to obtain an effective Markovian quantum kinetic equation for the expectation value of a slowly evolving scalar field in an adiabatically evolving background from first principles of nonequilibrium quantum field theory. The method requires almost no assumptions about the field's interactions and the composition of the background, except that 1) the coupling constants shall be small enough for perturbation theory to be applicable, 2) there is a clear separation between microphysical time scales and the rate at which bulk properties change, and 3) higher time derivatives of the field remain small. The resulting Markovian equation of motion is expressed in terms of an effective potential and friction coefficients. Motivated by cosmological applications we focus on spatially homogeneous and isotropic systems, but the approach could also be applied to spatial gradients., Comment: 20 pages, 2 figures; version accepted in JCAP

We consider the cosmological relaxation solution to the electroweak hierarchy problem using the fermion production as a dominant friction force. In our approach, neither super-Planckian field excursions nor a large number of e-folds arise, and scanning over thermal Higgs mass squared is avoided. The produced fermions from the relaxion source through the derivative coupling are SM-singlets, what we call dark fermions, and they can serve as the keV scale warm dark matter candidates., Comment: 40 pages, 9 figures; small modifications in the appendix: comments on the static Universe limit added, brief discussion about the shutdown of the backraction added; version accepted for publication in JHEP

Tele-wide camera system with different Field of View (FoV) lenses becomes very popular in recent mobile devices. Usually it is difficult to obtain full-FoV depth based on traditional stereo-matching methods. Pure Deep Neural Network (DNN) based depth estimation methods can obtain full-FoV depth, but have low robustness for scenarios which are not covered by training dataset. In this paper, to address the above problems we propose a hierarchical hourglass network for robust full-FoV depth estimation in tele-wide camera system, which combines the robustness of traditional stereo-matching methods with the accuracy of DNN. More specifically, the proposed network comprises three major modules: single image depth prediction module infers initial depth from input color image, depth propagation module propagates traditional stereo-matching tele-FoV depth to surrounding regions, and depth combination module fuses the initial depth with the propagated depth to generate final output. Each of these modules employs an hourglass model, which is a kind of encoder-decoder structure with skip connections. Experimental results compared with state-of-the-art depth estimation methods demonstrate that our method not only produces robust and better subjective depth quality on wild test images, but also obtains better quantitative results on standard datasets., Comment: 5 pages, 7 figures, 2 tables

Computer vision based object tracking has been used to annotate and augment sports video. For sports learning and training, video replay is often used in post-match review and training review for tactical analysis and movement analysis. For automatically and systematically competition data collection and tactical analysis, a project called CoachAI has been supported by the Ministry of Science and Technology, Taiwan. The proposed project also includes research of data visualization, connected training auxiliary devices, and data warehouse. Deep learning techniques will be used to develop video-based real-time microscopic competition data collection based on broadcast competition video. Machine learning techniques will be used to develop a tactical analysis. To reveal data in more understandable forms and to help in pre-match training, AR/VR techniques will be used to visualize data, tactics, and so on. In addition, training auxiliary devices including smart badminton rackets and connected serving machines will be developed based on the IoT technology to further utilize competition data and tactical data and boost training efficiency. Especially, the connected serving machines will be developed to perform specified tactics and to interact with players in their training.

Ball trajectory data are one of the most fundamental and useful information in the evaluation of players' performance and analysis of game strategies. Although vision-based object tracking techniques have been developed to analyze sport competition videos, it is still challenging to recognize and position a high-speed and tiny ball accurately. In this paper, we develop a deep learning network, called TrackNet, to track the tennis ball from broadcast videos in which the ball images are small, blurry, and sometimes with afterimage tracks or even invisible. The proposed heatmap-based deep learning network is trained to not only recognize the ball image from a single frame but also learn flying patterns from consecutive frames. TrackNet takes images with a size of $640\times360$ to generate a detection heatmap from either a single frame or several consecutive frames to position the ball and can achieve high precision even on public domain videos. The network is evaluated on the video of the men's singles final at the 2017 Summer Universiade, which is available on YouTube. The precision, recall, and F1-measure of TrackNet reach $99.7\%$, $97.3\%$, and $98.5\%$, respectively. To prevent overfitting, 9 additional videos are partially labeled together with a subset from the previous dataset to implement 10-fold cross-validation, and the precision, recall, and F1-measure are $95.3\%$, $75.7\%$, and $84.3\%$, respectively. A conventional image processing algorithm is also implemented to compare with TrackNet. Our experiments indicate that TrackNet outperforms conventional method by a big margin and achieves exceptional ball tracking performance. The dataset and demo video are available at https://nol.cs.nctu.edu.tw/ndo3je6av9/.

Using cosmological particle hydrodynamical simulations and uniform ultraviolet backgrounds, we compare Lyman-$\alpha$ forest flux spectra predicted by the conventional cold dark matter (CDM) model, the free-particle wave dark matter (FP$\psi$DM) model and extreme-axion wave dark matter (EA$\psi$DM) models of different initial axion field angles against the BOSS Lyman-$\alpha$ forest absorption spectra with a fixed boson mass $m_b\sim 10^{-22}$eV. We recover results reported previously (Ir\v{s}i\v{c} et al. 2017b; Armengaud et al. 2017) that the CDM model agrees better with the BOSS data than the FP$\psi$DM model by a large margin, and we find the difference of total $\chi^2$'s is $120$ for $420$ data bins. These previous results demand a larger boson mass by a factor $>10$ to be consistent with the date and are in tension with the favoured value determined from local satellite galaxies. We however find that such tension is removed as some EA$\psi$DM models predict Lyman-$\alpha$ flux spectra agreeing better with the BOSS data than the CDM model, and the difference of total $\chi^2$'s can be as large as $24$ for the same bin number. This finding arises with no surprise since EA$\psi$DM models have unique spectral shapes with spectral bumps in excess of the CDM power near the small-scale cutoff typical of $\psi$DM linear matter power spectra as well as more extended cutoffs than FP$\psi$DM (Zhang & Chiueh 2017a,b).

We present optical and near-infrared observations of the nearby Type Iax supernova (SN) 2014dt from 14 to 410 days after the maximum light. The velocities of the iron absorption lines in the early phase indicated that SN 2014dt showed slower expansion than the well-observed Type Iax SNe 2002cx, 2005hk and 2012Z. In the late phase, the evolution of the light curve and that of the spectra were considerably slower. The spectral energy distribution kept roughly the same shape after ~100 days, and the bolometric light curve flattened during the same period. These observations suggest the existence of an optically thick component that almost fully trapped the {\gamma}-ray energy from 56 Co decay. These findings are consistent with the predictions of the weak deflagration model, leaving a bound white dwarf remnant after the explosion., Comment: 39 pages, 14 figures, accepted for publication in PASJ

We propose a universal group theoretic description of the fermion production through any type of interaction to scalar or pseudo-scalar. Our group theoretic approach relies on the group $SU(2) \times U(1)$, corresponding to the freedom in choosing representations of the gamma matrices in Clifford algebra, under which a part of the Dirac spinor function transforms like a fundamental representation. In terms of a new $SO(3)$ ($\sim SU(2)$) vector constructed out of spinor functions, we show that fermion production mechanism can be analogous to the classical dynamics of a vector precessing with the angular velocity. In our group theoretic approach, the equation of motion takes a universal form for any system, and choosing a different type of interaction or a different basis amounts to selecting the corresponding angular velocity. The expression of the particle number density is greatly simplified, compared to the traditional approach, and it provides us with a simple geometric interpretation of the fermion production dynamics. For the purpose of the demonstration, we focus on the fermion production through the derivative coupling to the pseudo-scalar., Comment: 25 pages, 4 figures, v3: version accepted to JHEP. New Section V added

GAMER, a parallel Graphic-processing-unit-accelerated Adaptive-MEsh-Refinement hydrodynamic code, has been extended to support magnetohydrodynamics (MHD) with both the corner-transport-upwind (CTU) and MUSCL-Hancock schemes and the constraint transport (CT) technique. The divergent preserving operator for adaptive mesh refinement (AMR) has been applied to reinforce the divergence-free constraint on the magnetic field. GAMER-MHD has fully exploited the concurrent executions between the GPU MHD solver and other CPU computation pertinent to AMR. We perform various standard tests to demonstrate that GAMER-MHD is both second-order accurate and robust, producing results as accurate as those given by high-resolution uniform-grid runs. We also explore a new 3D MHD test, where the magnetic field assumes the Arnold-Beltrami-Childress (ABC) configuration, temporarily becomes turbulent with current sheets and finally settles to a lowest-energy equilibrium state. This 3D problem is adopted for the performance test of GAMER-MHD. The single-GPU performance reaches $1.2\times 10^8$ and $5.5\times 10^7$ cell-updates/sec for the single- and double-precision calculations, respectively, on Tesla P100. We also demonstrate a parallel efficiency of $\sim 70\%$ for both weak and strong scaling using $1,024$ XK nodes on the Blue Waters supercomputers., Comment: 29 pages, 22 figures, 1 table. GAMER-MHD will soon become available at https://github.com/gamer-project/gamer

We study reheating in $\alpha$-attractor models of inflation in which the inflaton couples to other scalars or fermions. We show that the parameter space contains viable regions in which the inflaton couplings to radiation can be determined from the properties of CMB temperature fluctuations, in particular the spectral index. This may be the only way to measure these fundamental microphysical parameters, which shaped the universe by setting the initial temperature of the hot big bang and contain important information about the embedding of a given model of inflation into a more fundamental theory of physics. The method can be applied to other models of single field inflation., Comment: 39 pages, 14 figures. Identical to the version that is to appear in JHEP

We present monitoring campaign observations at optical and near-infrared (NIR) wavelengths for a radio-loud active galactic nucleus (AGN) at z=0.840, SDSS~J110006.07+442144.3 (hereafter, J1100+4421), which was identified during a flare phase in late February, 2014. The campaigns consist of three intensive observing runs from the discovery to March, 2015, mostly within the scheme of the OISTER collaboration. Optical-NIR light curves and simultaneous spectral energy distributions (SEDs) are obtained. Our measurements show the strongest brightening in March, 2015. We found that the optical-NIR SEDs of J1100+4421 show an almost steady shape despite the large and rapid intranight variability. This constant SED shape is confirmed to extend to $\sim5~\mu$m in the observed frame using the archival WISE data. Given the lack of absorption lines and the steep power-law spectrum of $\alpha_{\nu}\sim-1.4$, where $f_{\nu}\propto\nu^{\alpha_{\nu}}$, synchrotron radiation by a relativistic jet with no or small contributions from the host galaxy and the accretion disk seems most plausible as an optical-NIR emission mechanism. The steep optical-NIR spectral shape and the large amplitude of variability are consistent with this object being a low $\nu_{\rm{peak}}$ jet-dominated AGN. In addition, sub-arcsec resolution optical imaging data taken with Subaru Hyper Suprime-Cam does not show a clear extended component and the spatial scales are significantly smaller than the large extensions detected at radio wavelengths. The optical spectrum of a possible faint companion galaxy does not show any emission lines at the same redshift and hence a merging hypothesis for this AGN-related activity is not supported by our observations., Comment: 22 pages, 7 figures, 2 tables. Accepted for publication in PASJ

Sub-horizon perturbations under the extreme initial condition of the axion model are investigated, where initial axion angles start near the potential maximum. This work focuses on a few new features found in the extreme axion model but absent in the free-particle model. A particularly novel new feature is the spectral excess relative to the CDM model in some wave number range, where the excess may be so large that landscapes of high-redshift universe beyond $z=10$ can be significantly altered. For axions of particle mass $10^{-22}$ eV, this range of wave number corresponds to first galaxies of few times $10^9-10^{10} M_\odot$. We demonstrate that sub-horizon perturbations are accurately described by Mathieu's equation and subject to parametric instability, which explains this novel feature. Actually the axion model is not a special one; perturbations in a wide range of scalar field models can share the similar characteristic., Comment: 11 pages, 3 figures

Linear perturbations of the wave dark matter, or $\psi$ dark matter ($\psi$DM), of particle mass $\sim 10^{-22}$eV in the radiation-dominant era are analyzed, and the matter power spectrum at the photon-matter equality is obtained. We identify four phases of evolution for $\psi$DM perturbations, where the dynamics can be vastly different from the counterparts of cold dark matter (CDM). While in late stages after mass oscillation long-wave $\psi$DM perturbations are almost identical to CDM perturbations, some subtle differences remain, let alone intermediate-to-short waves that bear no resemblance with those of CDM throughout the whole evolutionary history. The dissimilarity is due to quantum mechanical effects which lead to severe mode suppression. We also discuss the axion model with a cosine field potential. The power spectrum of axion models are generally almost identical to those of $\psi$DM, but in the extreme case when the initial axion angle is near the field potential top, this axion model predict a power excess over a range of wave number and a higher spectral cutoff than $\psi$DM as if $\psi$DM had a higher particle mass., Comment: 20 pages, 7 figures

Surface plasmon polariton, hyberbolic dispersion of energy and momentum, and emission interference provide opportunities to control photoluminescence properties. However, the interplays between these regimes need to be understood to take advantage of them in optoelectronic applications. Here, we investigate broadband variations induced by hyperbolic metamaterial (HMM) multilayer nanostructures on the spontaneous emission of selected organic chromophores. Experimental and calculated spontaneous emission lifetimes are shown to vary non-monotonously near HMM interfaces. With the SPP and interference dominant regimes. With the HMM number of pairs used as the analysis parameter, the lifetime is shown to be independent of the number of pairs in the surface plasmon polaritons, and emission interference dominant regimes, while it decreases in the Hyperbolic Dispersion dominant regime. We also show that the spontaneous emission lifetime is similarly affected by transverse positive and transverse negative HMMs. This work has broad implications on the rational design of functional photonic surfaces to control the luminescence of semiconductor chromophores., Comment: Manuscript: 8 pages, 5 figures ; SI: 13 pages, 17 figures

Blazars are highly variable active galactic nuclei which emit radiation at all wavelengths from radio to gamma-rays. Polarized radiation from blazars is one key piece of evidence for synchrotron radiation at low energies and it also varies dramatically. The polarization of blazars is of interest for understanding the origin, confinement, and propagation of jets. However, even though numerous measurements have been performed, the mechanisms behind jet creation, composition and variability are still debated. We performed simultaneous gamma-ray and optical photopolarimetry observations of 45 blazars between Jul. 2008 and Dec. 2014 to investigate the mechanisms of variability and search for a basic relation between the several subclasses of blazars. We identify a correlation between the maximum degree of optical linear polarization and the gamma-ray luminosity or the ratio of gamma-ray to optical fluxes. Since the maximum polarization degree depends on the condition of the magnetic field (chaotic or ordered), this result implies a systematic difference in the intrinsic alignment of magnetic fields in pc-scale relativistic jets between different types blazars (FSRQs vs. BL Lacs), and consequently between different types of radio galaxies (FR Is vs. FR IIs)., Comment: 17 pages, 30 figures, 6 tables. Accepted for publication in Astrophysical Journal

Here we report on the results of the WEBT photo-polarimetric campaign targeting the blazar S5~0716+71, organized in March 2014 to monitor the source simultaneously in BVRI and near IR filters. The campaign resulted in an unprecedented dataset spanning $\sim 110$\,h of nearly continuous, multi-band observations, including two sets of densely sampled polarimetric data mainly in R filter. During the campaign, the source displayed pronounced variability with peak-to-peak variations of about $30\%$ and "bluer-when-brighter" spectral evolution, consisting of a day-timescale modulation with superimposed hourlong microflares characterized by $\sim 0.1$\,mag flux changes. We performed an in-depth search for quasi-periodicities in the source light curve; hints for the presence of oscillations on timescales of $\sim 3$\,h and $\sim 5$\,h do not represent highly significant departures from a pure red-noise power spectrum. We observed that, at a certain configuration of the optical polarization angle relative to the positional angle of the innermost radio jet in the source, changes in the polarization degree led the total flux variability by about 2\,h; meanwhile, when the relative configuration of the polarization and jet angles altered, no such lag could be noted. The microflaring events, when analyzed as separate pulse emission components, were found to be characterized by a very high polarization degree ($> 30\%$) and polarization angles which differed substantially from the polarization angle of the underlying background component, or from the radio jet positional angle. We discuss the results in the general context of blazar emission and energy dissipation models., Comment: 16 pages, 17 Figures; ApJ accepted