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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