Search

This paper presents a 610 MHz radio survey covering 1.94 square degrees around the North Ecliptic Pole (NEP), which includes parts of the AKARI (ADF-N) and Euclid, Deep Fields North. The median 5-sigma sensitivity is 28 microJy beam per beam, reaching as low as 19 microJy per beam, with a synthesised beam of 3.6 x 4.1 arcsec. The catalogue contains 1675 radio components, with 339 grouped into multi-component sources and 284 isolated components likely part of double radio sources. Imaging, cataloguing, and source identification are presented, along with preliminary scientific results. From a non-statistical sub-set of 169 objects with multi-wavelength AKARI and other detections, luminous infrared galaxies (LIRGs) represent 66 percent of the sample, ultra-luminous infrared galaxies (ULIRGs) 4 percent, and sources with L_IR < 1011 L_sun 30 percent. In total, 56 percent of sources show some AGN presence, though only seven are AGN-dominated. ULIRGs require three times higher AGN contribution to produce high-quality SED fits compared to lower luminosity galaxies, and AGN presence increases with AGN fraction. The PAH mass fraction is insignificant, although ULIRGs have about half the PAH strength of lower IR-luminosity galaxies. Higher luminosity galaxies show gas and stellar masses an order of magnitude larger, suggesting higher star formation rates. For LIRGs, AGN presence increases with redshift, indicating that part of the total luminosity could be contributed by AGN activity rather than star formation. Simple cross-matching revealed 13 ROSAT QSOs, 45 X-ray sources, and 61 sub-mm galaxies coincident with GMRT radio sources.

This study aims to evaluate the sentiment of financial texts using large language models~(LLMs) and to empirically determine whether LLMs exhibit company-specific biases in sentiment analysis. Specifically, we examine the impact of general knowledge about firms on the sentiment measurement of texts by LLMs. Firstly, we compare the sentiment scores of financial texts by LLMs when the company name is explicitly included in the prompt versus when it is not. We define and quantify company-specific bias as the difference between these scores. Next, we construct an economic model to theoretically evaluate the impact of sentiment bias on investor behavior. This model helps us understand how biased LLM investments, when widespread, can distort stock prices. This implies the potential impact on stock prices if investments driven by biased LLMs become dominant in the future. Finally, we conduct an empirical analysis using Japanese financial text data to examine the relationship between firm-specific sentiment bias, corporate characteristics, and stock performance., Comment: Acceped IEEE BigData 2024 Special Sessionon Understanding New Markets by Data Science, Social Science, and Economics

This paper studies stable learning methods for generative models that enable high-quality data generation. Noise injection is commonly used to stabilize learning. However, selecting a suitable noise distribution is challenging. Diffusion-GAN, a recently developed method, addresses this by using the diffusion process with a timestep-dependent discriminator. We investigate Diffusion-GAN and reveal that data scaling is a key component for stable learning and high-quality data generation. Building on our findings, we propose a learning algorithm, Scale-GAN, that uses data scaling and variance-based regularization. Furthermore, we theoretically prove that data scaling controls the bias-variance trade-off of the estimation error bound. As a theoretical extension, we consider GAN with invertible data augmentations. Comparative evaluations on benchmark datasets demonstrate the effectiveness of our method in improving stability and accuracy.

Out-of-distribution (OOD) detection is a critical issue for the stable and reliable operation of systems using a deep neural network (DNN). Although many OOD detection methods have been proposed, it remains unclear how the differences between in-distribution (ID) and OOD samples are generated by each processing step inside DNNs. We experimentally clarify this issue by investigating the layer dependence of feature representations from multiple perspectives. We find that intrinsic low dimensionalization of DNNs is essential for understanding how OOD samples become more distinct from ID samples as features propagate to deeper layers. Based on these observations, we provide a simple picture that consistently explains various properties of OOD samples. Specifically, low-dimensional weights eliminate most information from OOD samples, resulting in misclassifications due to excessive attention to dataset bias. In addition, we demonstrate the utility of dimensionality by proposing a dimensionality-aware OOD detection method based on alignment of features and weights, which consistently achieves high performance for various datasets with lower computational cost., Comment: This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this contribution is published in ECML PKDD 2024, and is available online at https://doi.org/10.1007/978-3-031-70341-6_9

We derive a robust bound on dark photon dark matter scenarios where the dark photon mass is generated through the Higgs mechanism, based on the requirement that symmetry breaking must occur sufficiently early in the universe. We emphasize that dark photon production occurs successfully when the dark Higgs field remains in the symmetric phase due to non-thermal trapping effects. For renormalizable Higgs potentials, our bound reads $$\frac{m_{\gamma'}}{q_H e_H}\; \gg \;60\,{\rm eV}\left(\frac{2\pi}{\lambda}\right)^{1/4}$$ where $m_{\gamma'}$ is the dark photon mass, $e_H$ is the gauge coupling, $q_H$ is the charge of the dark Higgs boson, and $\lambda$ is the Higgs quartic coupling. This constraint holds independently of any complications arising from the Schwinger effect and vortex formation in the Higgsed phase. For more general Higgs potentials such as the Coleman-Weinberg type potential, our bound yields different forms. We argue that late-time symmetry breaking of the dark U(1) symmetry satisfying the bound has only a mild impact on both the abundance and momentum distribution of dark photon dark matter, and therefore does not pose any serious problem for the dark photon dark matter scenario., Comment: v2: 7 pages, 2 figures, References added. Dynamics of dark Higgs further clarified. Conclusions unchanged

A measure of asymmetry is a quantification method that allows for the comparison of categorical evaluations before and after treatment effects or among different target populations, irrespective of sample size. We focus on square contingency tables that summarize survey results between two time points or cohorts, represented by the same categorical variables. We propose a measure to evaluate the degree of departure from a symmetry model using cosine similarity. This proposal is based on the Fisher-Rao distance, allowing asymmetry to be interpreted as a geodesic distance between two distributions. Various measures of asymmetry have been proposed, but visualizing the relationship of these quantification methods on a two-dimensional plane demonstrates that the proposed measure provides the geometrically simplest and most natural quantification. Moreover, the visualized figure indicates that the proposed method for measuring departures from symmetry is less affected by very few cells with extreme asymmetry. A simulation study shows that for square contingency tables with an underlying asymmetry model, our method can directly extract and quantify only the asymmetric structure of the model, and can more sensitively detect departures from symmetry than divergence-type measures.

By coupling to both the Higgs and electroweak gauge sectors, an axion can generate the matter-antimatter asymmetry in the universe via electroweak baryogenesis when the axion decay constant lies within the range of approximately $10^5$ and $10^7$GeV, corresponding to axion masses between the MeV and GeV scales. In this work, we explore the intriguing possibility that the axion interacts with a dark sector, particularly with dark photons through anomalous couplings. Notably, axion-coupled dark photons can play multiple roles, including $(i)$ suppressing the branching ratio of axion decay to Standard Model (SM) particles, which would otherwise conflict with the constraints from supernovae explosions, Big Bang nucleosynthesis, and neutron star merger events, $(ii)$ serving as a candidate for cold dark matter if they are massive and stable, and $(iii)$ contributing to dark radiation if they are ultralight. The axion decouples from the SM thermal bath when it becomes non-relativistic, facilitating the production of dark matter dark photons through the freeze-in mechanism, while dark radiation dark photons are thermally generated prior to the electroweak phase transition., Comment: 12 pages, 3 figures

Rapid advancements in artificial intelligence (AI) have made it crucial to integrate moral reasoning into AI systems. However, existing models and datasets often overlook regional and cultural differences. To address this shortcoming, we have expanded the JCommonsenseMorality (JCM) dataset, the only publicly available dataset focused on Japanese morality. The Extended JCM (eJCM) has grown from the original 13,975 sentences to 31,184 sentences using our proposed sentence expansion method called Masked Token and Label Enhancement (MTLE). MTLE selectively masks important parts of sentences related to moral judgment and replaces them with alternative expressions generated by a large language model (LLM), while re-assigning appropriate labels. The model trained using our eJCM achieved an F1 score of 0.857, higher than the scores for the original JCM (0.837), ChatGPT one-shot classification (0.841), and data augmented using AugGPT, a state-of-the-art augmentation method (0.850). Specifically, in complex moral reasoning tasks unique to Japanese culture, the model trained with eJCM showed a significant improvement in performance (increasing from 0.681 to 0.756) and achieved a performance close to that of GPT-4 Turbo (0.787). These results demonstrate the validity of the eJCM dataset and the importance of developing models and datasets that consider the cultural context.

Determining the inner structure of the molecular torus around an active galactic nucleus is essential for understanding its formation mechanism. However, spatially resolving the torus is difficult because of its small size. To probe the clump conditions in the torus, we therefore perform the systematic velocity-decomposition analyses of the gaseous CO rovibrational absorption lines ($v=0\to 1,\Delta J=\pm 1$) at $\lambda\sim 4.67 \mathrm{\mu{m}}$ observed toward four (ultra)luminous infrared galaxies using the high-resolution ($R\sim 5000\text{--}10000$) spectroscopy from the Subaru Telescope. We find that each transition has two to five distinct velocity components with different line-of-sight (LOS) velocities ($V_\mathrm{LOS}\sim -240\text{--}+100\mathrm{km\,s^{-1}}$) and dispersions ($\sigma_V\sim 15\text{--}190\mathrm{km\,s^{-1}}$); i.e., the components (a), (b), ..., beginning with the broadest one in each target, indicating that the tori have clumpy structures. By assuming a hydrostatic disk ($\sigma_V\propto R_\mathrm{rot}^{-0.5}$), we find that the tori have dynamic inner structures, with the innermost component (a) outflowing with velocity $|V_\mathrm{LOS}|\sim 160\text{--}240\mathrm{km\,s^{-1}}$, and the outer components (b) and (c) outflowing more slowly or infalling with $|V_\mathrm{LOS}|\lesssim 100\mathrm{km\,s^{-1}}$. In addition, we find that the innermost component (a) can be attributed to collisionally excited hot ($\gtrsim 530$K) and dense ($n_\mathrm{H_2}\gtrsim 10^6\mathrm{cm^{-3}}$) clumps, based on the level populations. Conversely, the outer component (b) can be attributed to cold ($\sim 30\text{--}140$K) clumps radiatively excited by a far-infrared-to-submillimeter background with a brightness temperature higher than $\sim 20\text{--}400$K. These observational results demonstrate the clumpy and dynamic structure of tori in the presence of background radiation., Comment: 43 pages, 15 figures, accepted for publication in ApJ

When the row and column variables consist of the same category in a two-way contingency table, it is specifically called a square contingency table. Since it is clear that the square contingency tables have an association structure, a primary objective is to examine symmetric relationships and transitions between variables. While various models and measures have been proposed to analyze these structures understanding changes between two variables in behavior at two-time points or cohorts, it is also necessary to require a detailed investigation of individual categories and their interrelationships, such as shifts in brand preferences. This paper proposes a novel approach to correspondence analysis (CA) for evaluating departures from symmetry in square contingency tables with nominal categories, using a power-divergence-type measure. The approach ensures that well-known divergences can also be visualized and, regardless of the divergence used, the CA plot consists of two principal axes with equal contribution rates. Additionally, the scaling is independent of sample size, making it well-suited for comparing departures from symmetry across multiple contingency tables. Confidence regions are also constructed to enhance the accuracy of the CA plot.

We investigated the temperature (T) dependence of the irreversibility field Hirr(T) in high-critical-temperature cuprate Bi2+xSr2-xCa1-yYyCu2O8+d (Bi-2212) single crystals over a wide range of hole doping level (p). Hirr(T) was evaluated by measuring the magnetization hysteresis loop. The value of Hirr(T) extrapolated to T = 0 K [Hirr(0)], is either equal to or sets the lower boundary for the upper critical field at T = 0 K [Hc2(0)]. Tc shows a parabolic p-dependence (peak at p = 0.16), whereas Hirr(0) increases monotonically with p by approximately one order of magnitude, from 19 T for the most underdoped sample (p = 0.065, Tc = 24 K) to 209 T for the most overdoped sample (p = 0.200, Tc = 75 K). The present results qualitatively agree with Hc2(0) values evaluated from the specific heat measurements. The observed p-dependence of Hirr(0) in Bi-2212 is distinct from those in YBa2Cu3O7-d and HgBa2CuO6+d, in which a pronounced dip structure appears in the underdoped region. Considering that the dip structures observed in these two systems are likely associated with the formation of competing orders (most likely field-induced charge orders), the present results indicate that the influence of the competing order in Bi-2212 is less prominent than that in the other two systems., Comment: 32 pages, 9 figures, 1 table

We report the first measurement of the azimuthal anisotropy of J$/\psi$ at forward rapidity ($1.2<|\eta|<2.2$) in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV at the Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The second Fourier coefficient ($v_2$) of the azimuthal distribution of $J/\psi$ is determined as a function of the transverse momentum ($p_T$) using the event-plane method. The measurements were performed for several selections of collision centrality: 0\%--50\%, 10\%--60\%, and 10\%-40\%. We find that in all cases the values of $v_2(p_T)$, which quantify the elliptic flow of J$/\psi$, are consistent with zero. The results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the J$/\psi$ within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{_{NN}}}=200$ GeV., Comment: 369 authors from 72 institutions, 12 pages, 7 figures, 5 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We present the first forward-rapidity measurements of elliptic anisotropy of open-heavy-flavor muons at the BNL Relativistic Heavy Ion Collider. The measurements are based on data samples of Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The measurements are performed in the pseudorapidity range $1.2<|\eta|<2$ and cover transverse momenta $1

The AI traders in financial markets have sparked significant interest in their effects on price formation mechanisms and market volatility, raising important questions for market stability and regulation. Despite this interest, a comprehensive model to quantitatively assess the specific impacts of AI traders remains undeveloped. This study aims to address this gap by modeling the influence of AI traders on market price formation and volatility within a multi-agent framework, leveraging the concept of microfoundations. Microfoundations involve understanding macroeconomic phenomena, such as market price formation, through the decision-making and interactions of individual economic agents. While widely acknowledged in macroeconomics, microfoundational approaches remain unexplored in empirical finance, particularly for models like the GARCH model, which captures key financial statistical properties such as volatility clustering and fat tails. This study proposes a multi-agent market model to derive the microfoundations of the GARCH model, incorporating three types of agents: noise traders, fundamental traders, and AI traders. By mathematically aggregating the micro-structure of these agents, we establish the microfoundations of the GARCH model. We validate this model through multi-agent simulations, confirming its ability to reproduce the stylized facts of financial markets. Finally, we analyze the impact of AI traders using parameters derived from these microfoundations, contributing to a deeper understanding of their role in market dynamics., Comment: Accepted PRIMA2024

Band gap energy of an organic molecule can be reduced by intermolecular interaction enhancement, and thus, certain polycyclic aromatic hydrocarbons (PAHs), which are insulators with wide band gaps, are expected to undergo insulator-metal transitions by simple compression. Such a pressure-induced electronic transition can be exploited to transform non-metallic organic materials into states featuring intriguing electronic characteristics such as high-temperature superconductivity. Numerous attempts have been made to metalize various small PAHs, but so far only pressure-induced amorphization well below the megabar region was observed. The wide band gap energy of the small PAHs and low chemical stability under simple compression are the bottlenecks. We have investigated the band gap energy evolution and the crystal structural compression of the large PAH molecules, where the band gap energy is significantly reduced by increasing the number of {\pi}-electrons and improved chemical stability with fully benzenoid molecular structure. Herein, we present a pressure-induced transition in dicoronylene, C48H20, an insulator at ambient conditions that transforms into a semi-metallic state above 23.0 GPa with a three-order-of-magnitude reduction in resistivity. In-situ UV-visible absorption, transport property measurement, Raman spectroscopy, X-ray diffraction and density functional theory calculations were performed to provide tentative explanations to the alterations in its electronic structure at high pressure. The discovery of an electronic transition at pressures well below the megabar is a promising step towards realization of a single component purely hydrocarbon molecular metal in the near future., Comment: 22 pages, 5 figures

Simulating thermal-equilibrium properties at finite temperature is crucial for studying quantum many-body systems. Quantum computers are expected to enable us to simulate large systems at finite temperatures, overcoming challenges faced by classical computers, like the sign problem of the quantum Monte-Carlo technique. Conventional methods suitable for fault-tolerant quantum computing (FTQC) devices are designed for studying large-scale quantum many-body systems but require a large number of ancilla qubits and a deep quantum circuit with many basic gates, making them unsuitable for the early stage of the FTQC era, at which the availability of qubits and quantum gates is limited. In this paper, we propose a method suitable for quantum devices in this early stage to calculate the thermal-equilibrium expectation value of an observable at finite temperatures. Our proposal, named the Markov-chain Monte Carlo with sampled pairs of unitaries (MCMC-SPU) algorithm, involves sampling simple quantum circuits and generating the corresponding statistical ensembles. This approach addresses the issues of resource demand and the decay in probability associated with postselection of measurement outcomes on ancilla qubits. We validate our proposal with numerical simulation on the one-dimensional transverse-field Ising model as an illustrative example., Comment: 22 pages, 11 figures

This paper evaluated the effects of the Tokyo 2020 Olympic and Paralympic Games on traffic demand on the Metropolitan expressway. We constructed panel data for both passenger and freight vehicles' demand using longitudinal disaggregated trip records from the Metropolitan expressway. Subsequently, we established a demand function and used a difference-in-differences method to individually estimate the impacts of toll surcharges and other Olympics-related factors by leveraging the fact that the toll surcharges were not applied to freight vehicles. The results indicate that toll surcharges resulted in a decrease of 25.0 % for weekdays and 36.8 % for weekends/holidays in passenger vehicle demand on the Metropolitan expressway. The estimated toll elasticities are 0.345 for weekdays and 0.615 for weekends/holidays, respectively. Notably, analysis of the Olympics-related factor demonstrated that travel demand management (TDM) strategies effectively curbed demand on weekends/holidays with a reduction of 2.9 % in traffic demand. However, on weekdays, induced demand surpassed the reduction of demand by other TDM strategies than tolling, resulting in a 4.6 % increase in traffic demand. Additionally, We developed a zone-based demand function and investigate the spatial heterogeneity in toll elasticity. Our findings revealed small heterogeneity for weekdays (0.283 to 0.509) and large heterogeneity for weekends/holidays (0.484 to 0.935).

The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

A novel method was developed to detect double-$\Lambda$ hypernuclear events in nuclear emulsions using machine learning techniques. The object detection model, the Mask R-CNN, was trained using images generated by Monte Carlo simulations, image processing, and image-style transformation based on generative adversarial networks. Despite being exclusively trained on $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ events, the model achieved a detection efficiency of 93.8$\%$ for $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ and 82.0$\%$ for $\prescript{5\ }{\Lambda\Lambda}{\rm{H}}$ events in the produced images. In addition, the model demonstrated its ability to detect the $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ event named the Nagara event, which is the only uniquely identified double-$\Lambda$ hypernuclear event reported to date. It also exhibited a proper segmentation of the event topology. Furthermore, after analyzing 0.2$\%$ of the entire emulsion data from the J-PARC E07 experiment utilizing the developed approach, six new candidates for double-$\Lambda$ hypernuclear events were detected, suggesting that more than 2000 double-strangeness hypernuclear events were recorded in the entire dataset. This method is sufficiently effective for mining more latent double-$\Lambda$ hypernuclear events recorded in nuclear emulsion sheets by reducing the time required for manual visual inspection by a factor of five hundred.

We present a detailed study of the MASTER OT J030227.28+191754.5 outburst in 2021-2022, reaching an amplitude of 10.2 mag and a duration of 60 d. The detections of (1) the double-peaked optical emission lines, and (2) the early and ordinary superhumps, established that MASTER OT J030227.28+191754.5 is an extremely energetic WZ Sge-type dwarf nova (DN). Based on the superhump observations, we obtained its orbital period and mass ratio as 0.05986(1) d and 0.063(1), respectively. These are within a typical range of low-mass-ratio DNe. According to the binary parameters derived based on the thermal-tidal instability model, our analyses showed that (1) the standard disk model requires an accretion rate $\simeq$ 10$^{20}$ g s$^{-1}$ to explain its peak optical luminosity and (2) large mass was stored in the disk at the outburst onset. These cannot be explained solely by the impact of its massive ($\gtrsim$ 1.15 M$_\odot$) primary white dwarf implied by Kimura et al. (2023). Instead, we propose that the probable origin of this enormously energetic DN outburst is the even lower quiescence viscosity than other WZ Sge-type DNe. This discussion is qualitatively valid for most possible binary parameter spaces unless the inclination is low ($\lesssim 40^\circ$) enough for the disk to be bright explaining the outburst amplitude. Such low inclinations, however, would not allow detectable amplitude of early superhumps in the current thermal-tidal instability model. The optical spectra at outburst maximum showed the strong emission lines of Balmer, He I, and He II series whose core is narrower than $\sim 800$ km s$^{-1}$. Considering its binary parameters, a Keplerian disk cannot explain this narrow component, but the presumable origin is disk winds., Comment: 23 pages, 13 figures, 2 tables. Accepted by PASJ. Part of the online supplemental information is included

In recent years, metal hydride research has become one of the driving forces of the high-pressure community, as it is believed to hold the key to superconductivity close to ambient temperature. While numerous novel metal hydride compounds have been reported and extensively investigated for their superconducting properties, little attention has been focused on the atomic and electronic states of hydrogen, the main ingredient in these novel compounds. Here, we present combined $^{1}H$- and $^{139}La$-NMR data on lanthanum superhydrides, $LaH_{x}$, ($x = 10.2 - 11.1$), synthesized after laser heating at pressures above 160 GPa. Strikingly, we found hydrogen to be in a highly diffusive state at room temperature, with diffusion coefficients in the order of $10^{-6}~cm^2s^{-1}$. We found that this diffusive state of hydrogen results in a dynamic de-hydrogenation of the sample over the course of several weeks, approaching a composition similar to its precursor materials. Quantitative measurements demonstrate that the synthesized superhydrides continuously decompose over time. Transport measurements underline this conclusion as superconducting critical temperatures were found to decrease significantly over time as well. This observation sheds new light on formerly unanswered questions on the long-term stability of metal superhydrides.

An experimental investigation of collisionless shock ion acceleration is presented using a multicomponent plasma and a high-intensity picosecond duration laser pulse. Protons are the only accelerated ions when a near-critical-density plasma is driven by a laser with a modest normalized vector potential. The results of particle-in-cell simulations imply that collisionless shock may accelerate protons alone selectively, which can be an important tool for understanding the physics of inaccessible collisionless shocks in space and astrophysical plasma.

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Azide functionalization produced luminescent sp2-type defects on single-walled carbon nanotubes, by which defect photoluminescence appeared in near infrared regions (1116 nm). Changes in exciton properties were induced by localization effects at the defect sites, creating exciton-engineered nanomaterials based on the defect structure design.

We analyze the competition between strong correlations and dissipation in quantum impurity systems from the Kondo regime to the valence fluctuation regime by developing a slave-boson theory for a non-Hermitian Anderson impurity model with one-body loss. Notably, in the non-Hermitian Kondo regime, strong correlations qualitatively change the nature of dissipation through renormalization effects, where the effective one-body loss is suppressed and emergent many-body dissipation characterized by the complex-valued hybridization is generated. We unveil the mechanism of a dissipative quantum phase transition of the Kondo state on the basis of this renormalization effect, which counterintuitively enhances the lifetime of the impurity against loss. We also find a crossover from the non-Hermitian Kondo regime to the valence fluctuation regime dominated by one-body dissipation. Our results can be tested in a wide variety of setups such as quantum dots coupled to electronic leads and quantum point contacts in ultracold Fermi gases., Comment: 8+14 pages, 3+4 figures

Image-generative artificial intelligence (AI) has garnered significant attention in recent years. In particular, the diffusion model, a core component of generative AI, produces high-quality images with rich diversity. In this study, we proposed a novel computed tomography (CT) reconstruction method by combining the denoising diffusion probabilistic model with iterative CT reconstruction. In sharp contrast to previous studies, we optimized the fidelity loss of CT reconstruction with respect to the latent variable of the diffusion model, instead of the image and model parameters. To suppress the changes in anatomical structures produced by the diffusion model, we shallowed the diffusion and reverse processes and fixed a set of added noises in the reverse process to make it deterministic during the inference. We demonstrated the effectiveness of the proposed method through the sparse-projection CT reconstruction of 1/10 projection data. Despite the simplicity of the implementation, the proposed method has the potential to reconstruct high-quality images while preserving the patient's anatomical structures and was found to outperform existing methods, including iterative reconstruction, iterative reconstruction with total variation, and the diffusion model alone in terms of quantitative indices such as the structural similarity index and peak signal-to-noise ratio. We also explored further sparse-projection CT reconstruction using 1/20 projection data with the same trained diffusion model. As the number of iterations increased, the image quality improved comparable to that of 1/10 sparse-projection CT reconstruction. In principle, this method can be widely applied not only to CT but also to other imaging modalities., Comment: 20 pages, 10 figures

Conclusive crystal structure determination of the high pressure phases of hydrogen remains elusive due to lack of core electrons and vanishing wave vectors, rendering standard high-pressure experimental methods moot. Ab-initio DFT calculations have shown that structural polymorphism might be solely resolvable using high-resolution nuclear magnetic resonance (NMR) spectroscopy at mega-bar pressures, however technical challenges have precluded such experiments thus far. Here, we present in-situ high-pressure high-resolution NMR experiments in hydrogen phase III between 181 GPa and 208 GPa at room temperature. Our spectra suggest that at lower pressures phase III adopts a hexagonal P6122 crystal structure, transitioning into a monoclinic C2/c phase at about 197 GPa. The high resolution spectra are in excellent agreement with earlier structural and spectral predictions and underline the possibility of a subtle P6122 to C2/c phase transition in hydrogen phase III. These experiments show the importance of a combination of ab-initio calculations and low-Z sensitive spectral probes in high-pressure science in elucidating the structural complexity of the most abundant element in our universe.

Advancing defensive mechanisms against adversarial attacks in generative models is a critical research topic in machine learning. Our study focuses on a specific type of generative models - Variational Auto-Encoders (VAEs). Contrary to common beliefs and existing literature which suggest that noise injection towards training data can make models more robust, our preliminary experiments revealed that naive usage of noise augmentation technique did not substantially improve VAE robustness. In fact, it even degraded the quality of learned representations, making VAEs more susceptible to adversarial perturbations. This paper introduces a novel framework that enhances robustness by regularizing the latent space divergence between original and noise-augmented data. Through incorporating a paired probabilistic prior into the standard variational lower bound, our method significantly boosts defense against adversarial attacks. Our empirical evaluations demonstrate that this approach, termed Robust Augmented Variational Auto-ENcoder (RAVEN), yields superior performance in resisting adversarial inputs on widely-recognized benchmark datasets.

Simulation of quantum many-body systems is a promising application of quantum computers. However, implementing the time-evolution operator as a quantum circuit efficiently on near-term devices with limited resources is challenging. Standard approaches like Trotterization often require deep circuits, making them impractical. This paper proposes a hybrid quantum-classical algorithm called Local Subspace Variational Quantum Compilation (LSVQC) for compiling the time-evolution operator. The LSVQC uses variational optimization to reproduce the action of the target time-evolution operator within a physically reasonable subspace. Optimization is performed on small local subsystems based on the Lieb-Robinson bound, allowing for cost function evaluation using small-scale quantum devices or classical computers. Numerical simulations on a spin-lattice model and an $\mathit{\text{ab initio}}$ effective model of strongly correlated material Sr$_2$CuO$_3$ demonstrate the algorithm's effectiveness. It is shown that the LSVQC achieves a 95% reduction in circuit depth compared to Trotterization while maintaining accuracy. The subspace restriction also reduces resource requirements and improves accuracy. Furthermore, we estimate the gate count needed to execute the quantum simulations using the LSVQC on near-term quantum computing architectures in the noisy intermediate-scale or early fault-tolerant quantum computing era. Our estimation suggests that the acceptable physical gate error rate for the LSVQC can be significantly larger than for Trotterization., Comment: 29 pages, 14 figures

Liquid-gas phase coexistence in a boundary-driven diffusive system is studied by analyzing fluctuating hydrodynamics of a density field defined on a one-dimensional lattice with a space interval $\Lambda$. When an interface width $\ell$ is much larger than $\Lambda$, the discrete model becomes the standard fluctuating hydrodynamics, where the phase coexistence condition is given by the local equilibrium thermodynamics. In contrast, when $\ell < \Lambda$, the most probable density profile is determined by a new variational principle, where the chemical potential at the interface is found to deviate from the equilibrium coexistence chemical potential. This means that metastable states at equilibrium stably appear near the interface as the influence of the particle current. The variational function derived in the theoretical analysis is also found to be equivalent to the variational function formulated in an extended framework of thermodynamics called global thermodynamics. Finally, the validity of the theoretical result is confirmed by numerical simulations., Comment: 29 pages, 8 figures. Revised version

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The strength distributions of the Isoscalar Giant Monopole Resonance (ISGMR) and Isoscalar Giant Quadrupole Resonance (ISGQR) in 142,146-150Nd have been determined via inelastic alpha-particle scattering with the Grand Raiden (GR) Spectrometer at the Research Center for Nuclear Physics (RCNP), Japan. In the deformed nuclei 146-150Nd, the ISGMR strength distributions exhibit a splitting into two components, while the nearly spherical nucleus 142Nd displays a single peak in the ISGMR strength distribution. A noteworthy achievement in this study is the first-time detection of overtones in the Isoscalar Giant Quadrupole Resonance (ISGQR) strength distributions within Nd isotopes at an excitation energy around 25 MeV obtained through Multipole Decomposition Analysis (MDA)., Comment: Accepted for publication in Physics Letters B

Motivated by recent experimental realization of a Bose-Einstein condensate (BEC) of dipolar molecules, we develop superfluid transport theory for a dissipative BEC to show that a weak uniform two-body loss can induce phase rigidity, leading to superfluid transport of bosons. A generalized f-sum rule is shown to hold for a dissipative superfluid as a consequence of weak U(1) symmetry. It is also demonstrated that dissipation enhances the stability of a molecular BEC with dipolar interactions. Possible experimental situations for measuring the superfluid fraction and the spectral function are discussed., Comment: 6 pages, 1 figure+27 pages 2 figures

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We investigate a composite model of spontaneous CP violation based on a new supersymmetric QCD as a solution to the strong CP problem. The scalar components of the meson chiral superfields obtain complex vacuum expectation values to break CP symmetry spontaneously. Then, wavefunction renormalization for the quark kinetic terms provides the Cabibbo-Kobayashi-Maskawa (CKM) phase, while the strong CP phase $\bar{\theta}$ is protected by nonrenormalization of the superpotential and hermiticity of the wavefunction renormalization factor. In our model, the right-handed down-type quark multiplets are given by composite states, enhancing their couplings to CP breaking fields, which is essential to realize the observed CKM phase. The non-perturbative dynamics generates the scale of spontaneous CP violation hierarchically lower than the Planck scale. We discuss potential corrections to $\bar{\theta}$ and find a viable parameter space of the model to solve the strong CP problem without fine-tuning., Comment: 10 pages, 1 figure

There has been an attempt to revive the visible QCD axion at the 10 MeV scale assuming that it exclusively couples to the first-generation quarks and the electron. This variant of the QCD axion is claimed to remain phenomenologically viable, partly due to a clever model construction that induces tree-level pion-phobia and exploits uncertainties inherent in the chiral perturbation theory. We confront this model with the cosmological domain wall problem, the quality issue and constraints arising from the electron electric dipole moment. It is also pointed out that the gluon loop-generated axion-top coupling can provide a very large contribution to rare $B$-meson decays, such that the present LHCb data for $B^0 \to K^{*0} e^+ e^-$ rule out the model for the axion mass larger than 30 MeV. There is a strong motivation for pushing the experimental analysis of $B \to K^{(*)} e^+ e^-$ to a lower $e^+ e^-$ invariant mass window, which will conclusively determine the fate of the model, as its contribution to this branching ratio significantly exceeds the Standard Model prediction., Comment: 10 pages, 3 figures, matches published version

We investigate a novel scenario involving asymmetric keV-range dark matter (DM) in the form of right-handed (sterile) neutrinos. Based on the Fermi-Dirac distribution, we demonstrate that asymmetric fermionic DM forms a Fermi degenerate gas, making it potentially colder than symmetric fermionic DM. This setup simultaneously accounts for the Universe's baryon asymmetry through tiny Yukawa interactions with Standard Model leptons and the Higgs field, and the homochirality of amino acids via decay into circularly polarized photons. This scenario can be investigated through soft X-ray searches conducted by current and upcoming space missions. The helical X-rays is a smoking-gun signal of our scenario. Additionally, we propose a new mechanism to suppress DM thermal production by introducing a light modulus, which may also benefit cosmology involving generic right-handed neutrinos with large mixing., Comment: 22pages, 3figures, comments are welcome

Motivated by the notion of multiplier Hermitian-Einstein metric of type $\sigma$ introduced by Mabuchi, we introduce the notion of $\sigma$-extremal K\"{a}hler metrics on compact K\"{a}hler manifolds, which generalizes Calabi's extremal K\"{a}hler metrics. We characterize the existence of this metric in terms of the coercivity of a certain functional on the space of K\"{a}hler metrics to show that, on a Fano manifold, the existence of a multiplier Hermitian-Einstein metric of type $\sigma$ implies the existence of a $\sigma$-extremal K\"{a}hler metric., Comment: 25 pages, fixed a mistake in the abstract, added some sentences in the article

The local Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) quantum master equation is a powerful tool for the study of open quantum many-body systems. However, its microscopic derivation applicable to many-body systems is available only in limited cases of weak internal couplings, and it has yet to be fully understood under what microscopic conditions the local GKSL equation is valid. We derive the local GKSL equation on the basis of the Lieb-Robinson bound, which provides an upper bound of the propagation of information in quantum many-body systems. We numerically test the validity of the derived local GKSL equation for a one-dimensional tight-binding fermion chain., Comment: 16 pages, 7 figures

For chiral liquid crystals that express topologically protected defects and thermally driven mechanical rotation, the size- and temperature-driven reversal of the rotational direction of their droplets was demonstrated even under a fixed temperature gradient. This unconventional reversal indicates the dependence of thermomechanical coupling on the molecular orientational order, this dependence is justified through an examination of the size, temperature, and molecular structure as well as by phenomenological arguments on the order parameter.

We present Ir $4f$ core-level hard-x-ray photoemission spectroscopy (HAXPES) experiments conducted across antiferromagnetic (AFM) ordering transition in Ruddlesden-Popper iridates Sr$_2$IrO$_4$ and Sr$_3$Ir$_2$O$_7$. The Ir $4f$ spectra exhibit distinct changes between the AFM and paramagnetic (PM) phases, with the spectral difference $I_\text{PM}-I_\text{AFM}$ showing a contrasting behavior in the two compounds. By employing computational simulations using the local-density approximation combined with the dynamical mean-field theory method, we elucidate that $I_\text{PM}-I_\text{AFM}$ primary reflects the Slater or Mott-Hubbard character of the AFM insulating state rather than material specific details. This sensitivity to fine low-energy electronic structure arises from the dependence of charge-transfer responses to the sudden creation of a localized core hole on both metal-insulator transitions and long-range AFM ordering. Our result broadens the applications of core-level HAXPES as a tool for characterization of electronic structure., Comment: Main: 7 pages, 3 figures ; SM: 4 pages, 4 figures

In observational studies, the propensity score plays a central role in estimating causal effects of interest. The inverse probability weighting (IPW) estimator is commonly used for this purpose. However, if the propensity score model is misspecified, the IPW estimator may produce biased estimates of causal effects. Previous studies have proposed some robust propensity score estimation procedures. However, these methods require considering parameters that dominate the uncertainty of sampling and treatment allocation. This study proposes a novel Bayesian estimating procedure that necessitates probabilistically deciding the parameter, rather than deterministically. Since the IPW estimator and propensity score estimator can be derived as solutions to certain loss functions, the general Bayesian paradigm, which does not require the considering the full likelihood, can be applied. Therefore, our proposed method only requires the same level of assumptions as ordinary causal inference contexts. The proposed Bayesian method demonstrates equal or superior results compared to some previous methods in simulation experimentss, and is also applied to real data, namely the Whitehall dataset., Comment: covariate balancing, general Bayes, inverse probability weighting, M-estimator, propensity score

Unlike typical video action recognition, Dynamic Facial Expression Recognition (DFER) does not involve distinct moving targets but relies on localized changes in facial muscles. Addressing this distinctive attribute, we propose a Multi-Scale Spatio-temporal CNN-Transformer network (MSSTNet). Our approach takes spatial features of different scales extracted by CNN and feeds them into a Multi-scale Embedding Layer (MELayer). The MELayer extracts multi-scale spatial information and encodes these features before sending them into a Temporal Transformer (T-Former). The T-Former simultaneously extracts temporal information while continually integrating multi-scale spatial information. This process culminates in the generation of multi-scale spatio-temporal features that are utilized for the final classification. Our method achieves state-of-the-art results on two in-the-wild datasets. Furthermore, a series of ablation experiments and visualizations provide further validation of our approach's proficiency in leveraging spatio-temporal information within DFER., Comment: Accepted to 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024)