Search

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