Search

We leverage gravitational wave observations to explore physics beyond the Standard Model, focusing on axion-like particles (ALPs). This study investigates the resonant effects of ALPs with binary black hole systems, where their oscillatory nature induces time-dependent forces on the black holes. By employing a detailed Fisher matrix analysis, we not only probe a new parameter space for ALPs, characterized by their mass and decay constants, but also assess how these parameters affect gravitational waveforms during black hole mergers. Our approach is distinct as it does not assume interactions of ALPs with photons or nucleons. We demonstrate that as binary black holes spiral inward and lose energy, their orbital frequencies may resonate with those of ALPs, producing distinct oscillatory patterns in gravitational waves detectable by upcoming experiments such as the Laser Interferometer Space Antenna (LISA). This work broadens the potential of gravitational wave astronomy as a tool for dark matter searches, offering a promising avenue for studying elusive components of the universe., Comment: 11 pages, 9 figures

We consider multipartite quantum state discrimination and provide a specific relation between the properties of entanglement witness and quantum nonlocality inherent in the confidence of measurements. We first provide the definition of the confidence of measurements as well as its useful properties for various types of multipartite measurements. We show that globally maximum confidence that cannot be achieved by local operations and classical communication strongly depends on the existence of entanglement witness. We also provide conditions for an upper bound on maximum of locally-achievable confidences. Finally, we establish a method in terms of entanglement witness to construct quantum state ensemble with nonlocal maximum confidences., Comment: 12 pages, no figure

We present a new simulation suite for the star-forming interstellar medium (ISM) in galactic disks using the TIGRESS-NCR framework. Distinctive aspects of our simulation suite are: (1) sophisticated and comprehensive numerical treatments of essential physical processes including magnetohydrodynamics, self-gravity, and galactic differential rotation, as well as photochemistry, cooling, and heating coupled with ray-tracing UV radiation transfer and resolved supernova feedback and (2) wide parameter coverage including metallicity over $Z'\equiv Z/Z_\odot\sim0.1-3$, gas surface density $\Sigma_{\rm gas}\sim5-150 M_{\odot}{\rm pc^{-2}}$, and stellar surface density $\Sigma_{\rm star}\sim 1-50 M_{\odot}{\rm pc^{-2}}$. The range of emergent star formation rate surface density is $\Sigma_{\rm SFR}\sim 10^{-4}-0.5 M_{\odot}{\rm kpc^{-2}yr^{-1}}$ and ISM total midplane pressure is $P_{\rm tot}/k_B=10^3-10^6{\rm cm^{-3}K}$, with $P_{\rm tot}$ equal to the ISM weight $W$. For given $\Sigma_{\rm gas}$ and $\Sigma_{\rm star}$, we find $\Sigma_{\rm SFR} \propto Z'^{0.3}$. We provide an interpretation based on the pressure-regulated feedback-modulated (PRFM) star formation theory. We characterize feedback modulation in terms of the yield $\Upsilon$, defined as the ratio of each stress to $\Sigma_{\rm SFR}$. The thermal feedback yield varies sensitively with both weight and metallicity as $\Upsilon_{\rm th}\propto W^{-0.46}Z'^{-0.53}$, while the combined turbulent and magnetic feedback yield shows weaker dependence $\Upsilon_{\rm turb+mag}\propto W^{-0.22}Z'^{-0.18}$. The reduction in $\Sigma_{\rm SFR}$ at low metallicity is due mainly to enhanced thermal feedback yield, resulting from reduced attenuation of UV radiation. With the metallicity-dependent calibrations we provide, PRFM theory can be used for a new subgrid star formation prescription in cosmological simulations where the ISM is unresolved., Comment: Resubmitted to ApJ after minor revision

This paper presents a novel manipulation strategy that uses keypoint correspondences extracted from visuo-tactile sensor images to facilitate precise object manipulation. Our approach uses the visuo-tactile feedback to guide the robot's actions for accurate object grasping and placement, eliminating the need for post-grasp adjustments and extensive training. This method provides an improvement in deployment efficiency, addressing the challenges of manipulation tasks in environments where object locations are not predefined. We validate the effectiveness of our strategy through experiments demonstrating the extraction of keypoint correspondences and their application to real-world tasks such as block alignment and gear insertion, which require millimeter-level precision. The results show an average error margin significantly lower than that of traditional vision-based methods, which is sufficient to achieve the target tasks.

Bubbles driven by energy and mass injection from small scales are ubiquitous in astrophysical fluid systems and essential to feedback across multiple scales. In particular, O stars in young clusters produce high velocity winds that create hot bubbles in the surrounding gas. We demonstrate that the dynamical evolution of these bubbles is critically dependent upon the geometry of their interfaces with their surroundings and the nature of heat transport across these interfaces. These factors together determine the amount of energy that can be lost from the interior through cooling at the interface, which in turn determines the ability of the bubble to do work on its surroundings. We further demonstrate that the scales relevant to physical dissipation across this interface are extremely difficult to resolve in global numerical simulations of bubbles for parameter values of interest. This means the dissipation driving evolution of these bubbles in numerical simulations is often of a numerical nature. We describe the physical and numerical principles that determine the level of dissipation in these simulations; we use this, along with a fractal model for the geometry of the interfaces, to explain differences in convergence behavior between hydrodynamical and magneto-hydrodynamical simulations presented here. We additionally derive an expression for momentum as a function of bubble radius expected when the relevant dissipative scales are resolved and show that it still results in efficiently-cooled solutions as postulated in previous work., Comment: 41 pages, 20 figures, submitted to ApJ, comments welcome

In this paper, we propose a method to improve the accuracy of speech emotion recognition (SER) by using vision transformer (ViT) to attend to the correlation of frequency (y-axis) with time (x-axis) in spectrogram and transferring positional information between ViT through knowledge transfer. The proposed method has the following originality i) We use vertically segmented patches of log-Mel spectrogram to analyze the correlation of frequencies over time. This type of patch allows us to correlate the most relevant frequencies for a particular emotion with the time they were uttered. ii) We propose the use of image coordinate encoding, an absolute positional encoding suitable for ViT. By normalizing the x, y coordinates of the image to -1 to 1 and concatenating them to the image, we can effectively provide valid absolute positional information for ViT. iii) Through feature map matching, the locality and location information of the teacher network is effectively transmitted to the student network. Teacher network is a ViT that contains locality of convolutional stem and absolute position information through image coordinate encoding, and student network is a structure that lacks positional encoding in the basic ViT structure. In feature map matching stage, we train through the mean absolute error (L1 loss) to minimize the difference between the feature maps of the two networks. To validate the proposed method, three emotion datasets (SAVEE, EmoDB, and CREMA-D) consisting of speech were converted into log-Mel spectrograms for comparison experiments. The experimental results show that the proposed method significantly outperforms the state-of-the-art methods in terms of weighted accuracy while requiring significantly fewer floating point operations (FLOPs). Overall, the proposed method offers an promising solution for SER by providing improved efficiency and performance.

We provide multi-player quantum data hiding based on nonlocal quantum state ensembles arising from multi-party quantum state discrimination. Using bounds on local minimum-error discrimination of multi-party quantum states, we construct a multi-player quantum data-hiding scheme. Our data-hiding scheme can be used to hide multiple bits, asymptotically, unless all the players collaborate. We also illustrate our results by examples of nonlocal quantum state ensembles., Comment: 11 pages, 3 figures. arXiv admin note: text overlap with arXiv:2311.06029

The Extreme Universe Space Observatory on a Super Pressure Balloon 1 (EUSO-SPB1) was launched in 2017 April from Wanaka, New Zealand. The plan of this mission of opportunity on a NASA super pressure balloon test flight was to circle the southern hemisphere. The primary scientific goal was to make the first observations of ultra-high-energy cosmic-ray extensive air showers (EASs) by looking down on the atmosphere with an ultraviolet (UV) fluorescence telescope from suborbital altitude (33~km). After 12~days and 4~hours aloft, the flight was terminated prematurely in the Pacific Ocean. Before the flight, the instrument was tested extensively in the West Desert of Utah, USA, with UV point sources and lasers. The test results indicated that the instrument had sensitivity to EASs of approximately 3 EeV. Simulations of the telescope system, telescope on time, and realized flight trajectory predicted an observation of about 1 event assuming clear sky conditions. The effects of high clouds were estimated to reduce this value by approximately a factor of 2. A manual search and a machine-learning-based search did not find any EAS signals in these data. Here we review the EUSO-SPB1 instrument and flight and the EAS search., Comment: 18 pages, 19 figures

We explore extensive N-body simulations with two-component cold dark matter candidates. We delve into the temperature evolution, power spectrum, density perturbation, and maximum circular velocity functions. We find that the substantial mass difference between the two candidates and the annihilation of the heavier components to the lighter ones effectively endow the latter with warm dark matter-like behavior, taking advantage of all distinct features that warm dark matter candidates offer, without observational bounds on the warm dark matter mass. Moreover, we demonstrate that the two-component dark matter model aligns well with observational data, providing valuable insights into where and how to search for the elusive dark matter candidates in terrestrial experiments., Comment: 7 pages, 5 figures

We consider the discrimination of bipartite quantum states and establish a relation between nonlocal quantum state ensemble and quantum data hiding processing. Using a bound on optimal local discrimination of bipartite quantum states, we provide a sufficient condition for a bipartite quantum state ensemble to be used to construct a quantum data-hiding scheme. Our results are illustrated by examples in multidimensional bipartite quantum systems., Comment: 11 pages, 4 figures

Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. Low ON-state resistance of filamentary RRAM devices further increases the energy consumption due to high-current read and write operations, and limits the array size and parallel multiply & accumulate operations. High-forming voltages needed for filamentary RRAM are not compatible with advanced CMOS technology nodes. To address all these challenges, we developed a forming-free and bulk switching RRAM technology based on a trilayer metal-oxide stack. We systematically engineered a trilayer metal-oxide RRAM stack and investigated the switching characteristics of RRAM devices with varying thicknesses and oxygen vacancy distributions across the trilayer to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching operation at megaohm regime with high current nonlinearity and programmed up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform based on trilayer bulk RRAM crossbars by combining energy-efficient switched-capacitor voltage sensing circuits with differential encoding of weights to experimentally demonstrate high-accuracy matrix-vector multiplication. We showcased the computational capability of bulk RRAM crossbars by implementing a spiking neural network model for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints.

The nearby radio galaxy M87 offers a unique opportunity to explore the connections between the central supermassive black hole and relativistic jets. Previous studies of the inner region of M87 revealed a wide opening angle for the jet originating near the black hole. The Event Horizon Telescope resolved the central radio source and found an asymmetric ring structure consistent with expectations from General Relativity. With a baseline of 17 years of observations, there was a shift in the jet's transverse position, possibly arising from an eight to ten-year quasi-periodicity. However, the origin of this sideways shift remains unclear. Here we report an analysis of radio observations over 22 years that suggests a period of about 11 years in the position angle variation of the jet. We infer that we are seeing a spinning black hole that induces the Lense-Thirring precession of a misaligned accretion disk. Similar jet precession may commonly occur in other active galactic nuclei but has been challenging to detect owing to the small magnitude and long period of the variation., Comment: 41 pages, 7 figures, 7 tables

We have carried out ALMA observations of the massive star-forming region W75N(B), which contains the massive protostars VLA1, VLA2, and VLA3. Particularly, VLA2 is an enigmatic protostar associated with a wind-driven H$_2$O maser shell, which has evolved from an almost isotropic outflow to a collimated one in just 20 years. The shell expansion seemed to be halted by an obstacle located to the northeast of VLA2. Here we present our findings from observing the 1.3 mm continuum and H$_2$CO and SiO emission lines. Within a region of $\sim 30"$ ($\sim 39,000$ au) diameter, we have detected 40 compact mm-continuum sources, three of them coinciding with VLA1, VLA2, and VLA3. While the H$_2$CO emission is mainly distributed in a fragmented structure around the three massive protostars, but without any of the main H$_2$CO clumps spatially coinciding with them, the SiO is highly concentrated on VLA2, indicating the presence of very strong shocks generated near this protostar. The SiO emission is clearly resolved into an elongated structure ($\sim 0.6"\times0.3"$; $\sim 780$ au$\times$390 au) perpendicular to the major axis of the wind-driven maser shell. The structure and kinematics of the SiO emission are consistent with a toroid and a wide-angle outflow surrounding a central mass of $\sim 10$ M$_{\odot}$, thus supporting previous theoretical predictions regarding the evolution of the outflow. Additionally, we have identified the expected location and estimated the gas density of the obstacle that is hindering the expansion of the maser shell., Comment: To be published in The Astrophysical Journal Letters. Sixteen pages, seven figures. Updated metadata

The presence of dark matter overdensities surrounding a black hole can influence the evolution of a binary system. The gravitational wave signals emitted by a black hole binary offer a promising means to probe the dark matter environments near a black hole. The dense region of dark matter can lead to the dephasing of gravitational waveforms, which can be detected by upcoming experiments such as the Laser Interferometer Space Antenna (LISA). The dark matter density profile around the black hole can vary for different dark matter models. Our study specifically investigates the impact of the ultralight self-interacting scalar dark matter (SIDM) on the gravitational wave signals emitted by black hole binaries. A distinctive characteristic of SIDM surrounding a black hole, as opposed to collisionless dark matter, is the formation of a soliton core. We perform a Fisher matrix analysis to estimate the size of the soliton and the corresponding SIDM parameter space that future LISA-like gravitational wave experiments can explore., Comment: 12 pages, 7 figures, 1 table; matches the published version

Chemistry plays a key role in many aspects of astrophysical fluids. Atoms and molecules are agents for heating and cooling, determine the ionization fraction, serve as observational tracers, and build the molecular foundation of life. We present the implementation of a chemistry module in the publicly available magneto-hydrodynamic code Athena++. We implement several chemical networks and heating and cooling processes suitable for simulating the interstellar medium (ISM). A general chemical network framework in the KIDA format is also included, allowing the user to easily implement their own chemistry. Radiation transfer and cosmic-ray ionization are coupled with chemistry and solved with the simple six-ray approximation. The chemical and thermal processes are evolved as a system of coupled ODEs with an implicit solver from the CVODE library. We perform and present a series of tests to ensure the numerical accuracy and convergence of the code. Many tests combine chemistry with gas dynamics, including comparisons with analytic solutions, 1D problems of the photo-dissociation regions and shocks, and realistic 3D simulations of the turbulent ISM. We release the code with the new public version of Athena++, aiming to provide a robust and flexible code for the astrochemical simulation community.

We propose a deep learning-based search strategy for pair production of doubly charged scalars undergoing three-body decays to $W^+ t\bar b$ in the same-sign lepton plus multi-jet final state. This process is motivated by composite Higgs models with an underlying fermionic UV theory. We demonstrate that for such busy final states, jet image classification with convolutional neural networks outperforms standard fully connected networks acting on reconstructed kinematic variables. We derive the expected discovery reach and exclusion limit at the high-luminosity LHC., Comment: 16 pages, 14 figures, 2 technical appendices

Let $\mathbf{R}_d$ be the space of stable sheaves $F$ which satisfy the Hilbert polynomial $\chi(F(m))=dm+1$ and are supported on rational curves in the projective plane $\mathbb{P}^2$. Then $\mathbf{R}_1$ (resp. $\mathbf{R}_2$) is isomorphic to $\mathbf{R}_1\cong\mathbb{P}^2$ (resp. $\mathbf{R}_2\cong \mathbb{P}^5$). Also it is very well-known that $\mathbf{R}_3$ is isomorphic to a $\mathbb{P}^6$-bundle over $\mathbb{P}^2$. In special $\mathbf{R}_d$ is smooth for $d\leq 3$. But for $d\geq4$ case, one can imagine that the space $\mathbf{R}_d$ is no more smooth because of the complexity of boundary curves. In this paper, we obtain an $\mathrm{SL}(3,\mathbb{C})$-equivariant smooth resolution of $\mathbf{R}_4$ for $d=4$, which is a $\mathbb{P}^5$-bundle over the blow-up of a Kronecker modules space., Comment: Comments are welcome

Particles with masses much larger than the inflationary Hubble scale, $H_I$, can be pair-produced non-adiabatically during inflation. Due to their large masses, the produced particles modify the curvature perturbation around their locations. These localized perturbations eventually give rise to localized signatures on the Cosmic Microwave Background (CMB), in particular, pairwise hotspots (PHS). In this work, we show that Convolutional Neural Networks (CNN) provide a powerful tool for identifying PHS on the CMB. While for a given hotspot profile a traditional Matched Filter Analysis is known to be optimal, a Neural Network learns to effectively detect the large variety of shapes that can arise in realistic models of particle production. Considering an idealized situation where the dominant background to the PHS signal comes from the standard CMB fluctuations, we show that a CNN can isolate the PHS with $\mathcal{O}(10)\%$ efficiency even if the hotspot temperature is $\mathcal{O}(10)$ times smaller than the average CMB fluctuations. Overall, the CNN search is sensitive to heavy particle masses $M_0/H_I=\mathcal{O}(200)$, and constitutes one of the unique probes of very high energy particle physics.

Because of its proximity and the large size of its black hole, M87 is one of the best targets for studying the launching mechanism of active galactic nucleus jets. Currently, magnetic fields are considered to be an essential factor in the launching and accelerating of the jet. However, current observational estimates of the magnetic field strength of the M87 jet are limited to the innermost part of the jet or to HST-1. No attempt has yet been made to measure the magnetic field strength in between. We aim to infer the magnetic field strength of the M87 jet out to a distance of several thousand $r_s$ by tracking the distance-dependent changes in the synchrotron spectrum of the jet from high-resolution very long baseline interferometry observations. In order to obtain high-quality spectral index maps, quasi-simultaneous observations at 22 and 43 GHz were conducted using the KVN and VERA Array (KaVA) and the VLBA. We compared the spectral index distributions obtained from the observations with a model and placed limits on the magnetic field strengths as a function of distance. The overall spectral morphology is broadly consistent over the course of these observations. The observed synchrotron spectrum rapidly steepens from $\alpha_{22-43 GHz}$ ~ -0.7 at ~ 2 mas to $\alpha_{22-43 GHz}$ ~ -2.5 at ~ 6 mas. A spectral index model in which nonthermal electron injections inside the jet decrease with distance can adequately reproduce the observed trend. This suggests the magnetic field strength of the jet at a distance of 2 - 10 mas (~ 900 $r_s$ - ~ 4500 $r_s$ in the deprojected distance) has a range of $B=(0.3 - 1.0 G)(z/2 mas)^{-0.73}$. Extrapolating to the EHT scale yields consistent results, suggesting that the majority of the magnetic flux of the jet near the black hole is preserved out to ~ 4500 $r_s$ without significant dissipation., Comment: 16 pages, 9 figures. Accepted for publication in Astronomy & Astrophysics

We consider multipartite quantum state discrimination and show that the minimum-error discrimination by separable measurements is closely related to the concept of entanglement witness. Based on the properties of entanglement witness, we establish some necessary and/or sufficient conditions on minimum-error discrimination by separable measurements. We also provide some conditions on the upper bound of the maximum success probability over all possible separable measurements. Our results are illustrated by examples of multidimensional multipartite quantum states. Finally, we provide a systematic way in terms of the entanglement witness to construct multipartite quantum state ensembles showing nonlocality in state discrimination., Comment: 13 pages, 1 figure. arXiv admin note: substantial text overlap with arXiv:2212.10799

We consider bipartite quantum state discrimination using positive-partial-transpose measurements and show that minimum-error discrimination by positive-partial-transpose measurements is closely related to entanglement witness. By using the concept of decomposable entanglement witness, we establish conditions on minimum-error discrimination by positive-partial-transpose measurements. We also provide conditions on the upper bound of the maximum success probability over all possible positive-partial-transpose measurements. Finally, we illustrate our results using examples of multidimensional bipartite quantum states., Comment: 14 pages, 1 figure

The East Asian VLBI Network (EAVN) is an international VLBI facility in East Asia and is operated under mutual collaboration between East Asian countries, as well as part of Southeast Asian and European countries. EAVN currently consists of 16 radio telescopes and three correlators located in China, Japan, and Korea, and is operated mainly at three frequency bands, 6.7, 22, and 43 GHz with the longest baseline length of 5078 km, resulting in the highest angular resolution of 0.28 milliarcseconds at 43 GHz. One of distinct capabilities of EAVN is multi-frequency simultaneous data reception at nine telescopes, which enable us to employ the frequency phase transfer technique to obtain better sensitivity at higher observing frequencies. EAVN started its open-use program in the second half of 2018, providing a total observing time of more than 1100 hours in a year. EAVN fills geographical gap in global VLBI array, resulting in enabling us to conduct contiguous high-resolution VLBI observations. EAVN has produced various scientific accomplishments especially in observations toward active galactic nuclei, evolved stars, and star-forming regions. These activities motivate us to initiate launch of the 'Global VLBI Alliance' to provide an opportunity of VLBI observation with the longest baselines on the earth., Comment: 27 pages, appeared in Galaxies special issue 'Challenges in Understanding Black Hole Powered Jets with VLBI' as an invited review

Massive, young stars are the main source of energy that maintains multiphase structure and turbulence in the interstellar medium (ISM), and without this "feedback" the star formation rate (SFR) would be much higher than is observed. Rapid energy loss in the ISM and efficient energy recovery by stellar feedback lead to co-regulation of SFRs and the ISM state. Realistic approaches to this problem should solve the dynamical evolution of the ISM, including star formation, and the input of feedback energy self-consistently and accurately. Here, we present the TIGRESS-NCR numerical framework, in which UV radiation, supernovae, cooling and heating processes, and gravitational collapse are modeled explicitly. We use an adaptive ray tracing method for UV radiation transfer from star clusters represented by sink particles, accounting for attenuation by dust and gas. We solve photon-driven chemical equations to determine the abundances of H (time-dependent) and C/O-bearing species (steady-state), which then set cooling and heating rates self-consistently. Applying these methods, we present high-resolution magnetohydrodynamics simulations of differentially rotating local galactic disks representing typical conditions of nearby star-forming galaxies. We analyze ISM properties and phase distributions and show good agreement with existing multiwavelength galactic observations. We measure midplane pressure components (turbulent, thermal, and magnetic) and the weight, demonstrating that vertical dynamical equilibrium holds. We quantify the ratios of pressure components to the SFR surface density, which we call the feedback yields. The TIGRESS-NCR framework will allow for a wide range of parameter exploration, including low metallicity system., Comment: ApJ accepted

We aim to reveal the structure and kinematics of the Outer-Scutum-Centaurus (OSC) arm located on the far side of the Milky Way through very long baseline interferometry (VLBI) astrometry using KaVA, which is composed of KVN (Korean VLBI Network) and VERA (VLBI Exploration of Radio Astrometry). We report the proper motion of a 22 GHz H$_{2}$O maser source, which is associated with the star-forming region G034.84$-$00.95, to be ($\mu_{\alpha} \rm{cos}\delta$, $\mu_{\delta}$) = ($-$1.61$\pm$0.18, $-$4.29$\pm$0.16) mas yr$^{-1}$ in equatorial coordinates (J2000). We estimate the 2D kinematic distance to the source to be 18.6$\pm$1.0 kpc, which is derived from the variance-weighted average of kinematic distances with LSR velocity and the Galactic-longitude component of the measured proper motion. Our result places the source in the OSC arm and implies that G034.84$-$00.95 is moving away from the Galactic plane with a vertical velocity of $-$38$\pm$16 km s$^{-1}$. Since the H I supershell GS033+06$-$49 is located at a kinematic distance roughly equal to that of G034.84$-$00.95, it is expected that gas circulation occurs between the outer Galactic disk around G034.84$-$00.95 with a Galactocentric distance of 12.8$^{+1.0}_{-0.9}$ kpc and halo. We evaluate possible origins of the fast vertical motion of G034.84$-$00.95, which are (1) supernova explosions and (2) cloud collisions with the Galactic disk. However, neither of the possibilities are matched with the results of VLBI astrometry as well as spatial distributions of H II regions and H I gas., Comment: Accepted for publication in PASJ. 14 figures; 8 tables

We present an efficient heating/cooling method coupled with chemistry and ultraviolet (UV) radiative transfer, which can be applied to numerical simulations of the interstellar medium (ISM). We follow the time-dependent evolution of hydrogen species (H$_2$, H, H$^+$), assume carbon/oxygen species (C, C$^+$, CO, O, and O$^+$) are in formation-destruction balance given the non-steady hydrogen abundances, and include essential heating/cooling processes needed to capture thermodynamics of all ISM phases. UV radiation from discrete point sources and the diffuse background is followed through adaptive ray tracing and a six-ray approximation, respectively, allowing for H$_2$ self-shielding; cosmic ray (CR) heating and ionization are also included. To validate our methods and demonstrate their application for a range of density, metallicity, and radiation field, we conduct a series of tests, including the equilibrium curves of thermal pressure vs. density, the chemical and thermal structure in photo-dissociation regions, H I-to-H$_2$ transitions, and the expansion of H II regions and radiative supernova remnants. Careful treatment of photochemistry and CR ionization is essential for many aspects of ISM physics, including identifying the thermal pressure at which cold and warm neutral phases co-exist. We caution that many current heating and cooling treatments used in galaxy formation simulations do not reproduce the correct thermal pressure and ionization fraction in the neutral ISM. Our new model is implemented in the MHD code Athena and incorporated in the TIGRESS simulation framework, for use in studying the star-forming ISM in a wide range of environments., Comment: 57 pages, 22 figures; accepted for publication in ApJS

Hund's rule coupling ($\textit{J}$) has attracted much attention recently for its role in the description of the novel quantum phases of multi orbital materials. Depending on the orbital occupancy, $\textit{J}$ can lead to various intriguing phases. However, experimental confirmation of the orbital occupancy dependency has been difficult as controlling the orbital degrees of freedom normally accompanies chemical inhomogeneities. Here, we demonstrate a method to investigate the role of orbital occupancy in $\textit{J}$ related phenomena without inducing inhomogeneities. By growing SrRuO$_3$ monolayers on various substrates with symmetry-preserving interlayers, we gradually tune the crystal field splitting and thus the orbital degeneracy of the Ru $\textit{t$_2$$_g$}$ orbitals. It effectively varies the orbital occupancies of two-dimensional (2D) ruthenates. Via in-situ angle-resolved photoemission spectroscopy, we observe a progressive metal-insulator transition (MIT). It is found that the MIT occurs with orbital differentiation: concurrent opening of a band insulating gap in the $\textit{d$_x$$_y$}$ band and a Mott gap in the $\textit{d$_x$$_z$$_/$$_y$$_z$}$ bands. Our study provides an effective experimental method for investigation of orbital-selective phenomena in multi-orbital materials.

We develop a discrete-time version of the blended dynamics theorem for the use of designing distributed computation algorithms. The blended dynamics theorem enables to predict the behavior of heterogeneous multi-agent systems. Therefore, once we get a blended dynamics for a particular computational task, design idea of node dynamics for individual heterogeneous agents can easily occur. In the continuous-time case, prediction by blended dynamics was enabled by high coupling gain among neighboring agents. In the discrete-time case, we propose an equivalent action, which we call multi-step coupling in this paper. Compared to the continuous-time case, the blended dynamics can have more variety depending on the coupling matrix. This benefit is demonstrated with three applications; distributed estimation of network size, distributed computation of the PageRank, and distributed computation of the degree sequence of a graph, which correspond to the coupling by doubly-stochastic, column-stochastic, and row-stochastic matrices, respectively.

Magnetic fields ($\textbf{B}$) are an important factor that controls the star formation process. The leading method to observe $\textbf{B}$ is using polarized thermal emission from dust grains aligned with $\textbf{B}$. However, in dense environments such as protostellar cores, dust grains may have inefficient alignment due to strong gas randomizations, so that using dust polarization to trace $\textbf{B}$ is uncertain. Hoang $\&$ Lazarian (2016) demonstrated that the grain alignment by RAdiative Torques is enhanced if dust grains contain embedded iron inclusions. Here we extend POLARIS code to study the effect of iron inclusions on grain alignment and thermal dust polarization toward a protostellar core, assuming uniform magnetic fields. We found that paramagnetic grains produce a low polarization degree of $p \sim 1\%$ in the envelope and negligible $p \ll 1\%$ in the central region due to the loss of grain alignment. In contrast, grains with a high level of iron inclusions can have perfect alignment and produce high $p \sim 40\%$ in the envelope and low $p \leq 10\%$ in the central region. Grains with a moderate level of iron inclusions induce the polarization flipping from $\textbf{P}$ $\parallel$ $\textbf{B}$ at millimeter to $\textbf{P}$ $\perp$ $\textbf{B}$ at submillimeter due to the change in the internal alignment caused by slow internal relaxation. The weak alignment of very large grains of $a \geq 10\mu m$ reduces the polarization by dichroic extinction at submillimeter wavelengths. We found a positive correlation between p and the level of iron inclusions, which opens a new window to constrain the abundance of irons locked in dust through dust polarimetry., Comment: 39 pages, 27 figures

Power analysis poses a significant threat to the security of cryptographic algorithms, as it can be leveraged to recover secret keys. While various software-based countermeasures exist to mitigate this non-invasive attack, they often involve a trade-off between time and space constraints. Techniques such as masking and shuffling, while effective, can noticeably impact execution speed and rely heavily on run-time random number generators. On the contrary, internally encoded implementations of block ciphers offer an alternative approach that does not rely on run-time random sources, but it comes with the drawback of requiring substantial memory space to accommodate lookup tables. Internal encoding, commonly employed in white-box cryptography, suffers from a significant security limitation as it does not effectively protect the secret key against statistical analysis. To overcome this weakness, this paper introduces a secure internal encoding method for an AES implementation. By addressing the root cause of vulnerabilities found in previous encoding methods, we propose a balanced encoding technique that aims to minimize the problematic correlation with key-dependent intermediate values. We analyze the potential weaknesses associated with the balanced encoding and present a method that utilizes complementary sets of lookup tables. In this approach, the size of the lookup tables is approximately 512KB, and the number of table lookups is 1,024. This is comparable to the table size of non-protected white-box AES-128 implementations, while requiring only half the number of lookups. By adopting this method, our aim is to introduce a non-masking technique that mitigates the vulnerability to statistical analysis present in current internally-encoded AES implementations., Comment: 60 pages, 25 figures, submitted

There have been several attempts to use deep learning based on brain fMRI signals to classify cognitive impairment diseases. However, deep learning is a hidden black box model that makes it difficult to interpret the process of classification. To address this issue, we propose a novel analytical framework that interprets the classification result from deep learning processes. We first derive the region of interest (ROI) functional connectivity network (FCN) by embedding functions based on their similar signal patterns. Then, using the self-attention equipped deep learning model, we classify diseases based on their FCN. Finally, in order to interpret the classification results, we employ a latent space item-response interaction network model to identify the significant functions that exhibit distinct connectivity patterns when compared to other diseases. The application of this proposed framework to the four types of cognitive impairment shows that our approach is valid for determining the significant ROI functions., Comment: 38 pages,12 figures,3 tables

In this short article, we determine the bigness of the tangent bundle $T_X$ of the projective bundle $X=\mathbb{P}_C(E)$ associated to a vector bundle $E$ on a smooth projective curve $C$., Comment: 9 pages, error fixed