1,836 research outputs found

    First detection of 22 GHz H2O masers in TX Camelopardalis

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    Simultaneous time monitoring observations of H2_{2}O 616−5236_{16}-5_{23}, SiO JJ = 1--0, 2--1, 3--2, and 29^{29}SiO vv = 0, JJ = 1--0 lines were carried out in the direction of the Mira variable star TX Cam with the Korean VLBI Network single dish radio telescopes. For the first time, the H2_{2}O maser emission from TX Cam was detected near the stellar velocity at five epochs from April 10, 2013 (ϕ\phi = 3.13) to June 4, 2014 (ϕ\phi = 3.89) including minimum optical phases. The intensities of H2_{2}O masers are very weak compared to SiO masers. The variation of peak antenna temperature ratios among SiO vv = 1, JJ = 1--0, JJ = 2--1, and JJ = 3--2 masers is investigated according to their phases. The shift of peak velocities of H2_{2}O and SiO masers with respect to the stellar velocity is also investigated according to observed optical phases. The H2_{2}O maser emission occurs around the stellar velocity during our monitoring interval. On the other hand, the peak velocities of SiO masers show a spread compared to the stellar velocity. The peak velocities of SiO JJ = 2--1, and JJ = 3--2 masers show a smaller spread with respect to the stellar velocity than those of SiO JJ = 1--0 masers. These simultaneous observations of multi-frequencies will provide a good constraint for maser pumping models and a good probe for investigating the stellar atmosphere and envelope according to their different excitation conditions.Comment: 10 page

    Superfluid-like spin transport in the dynamic states of easy-axis magnets

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    The existing proposals for superfluid-like spin transport have been based on easy-plane magnets where the U(1) spin-rotational symmetry is spontaneously broken in equilibrium, and this has been limiting material choices for realizing superfluid-like spin transport to restricted class of magnets. In this work, we lift this limitation by showing that superfluid-like spin transport can also be realized based on easy-axis magnets, where the U(1) spin-rotational symmetry is intact in equilibrium but can be broken in non-equilibrium. Specifically, we find the condition to engender a non-equilibrium easy-cone state by applying a spin torque to easy-axis magnets, which dynamically induces the spontaneous breaking of the U(1) spin-rotational symmetry and thereby can support superfluid-like spin transport. By exploiting this dynamic easy-cone state, we show theoretically that superfluid-like spin transport can be achieved in easy-axis magnets under suitable conditions and confirmed the prediction by micromagnetic simulations. We envision that our work broadens material library for realizing superfluid-like spin transport, showing the potential utility of dynamic states of magnets as venue to look for spin-transport phenomena that do not occur in static magnetic backgrounds.Comment: 7 pages and 2 figure

    Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation

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    Transformer-based speech self-supervised learning (SSL) models, such as HuBERT, show surprising performance in various speech processing tasks. However, huge number of parameters in speech SSL models necessitate the compression to a more compact model for wider usage in academia or small companies. In this study, we suggest to reuse attention maps across the Transformer layers, so as to remove key and query parameters while retaining the number of layers. Furthermore, we propose a novel masking distillation strategy to improve the student model's speech representation quality. We extend the distillation loss to utilize both masked and unmasked speech frames to fully leverage the teacher model's high-quality representation. Our universal compression strategy yields the student model that achieves phoneme error rate (PER) of 7.72% and word error rate (WER) of 9.96% on the SUPERB benchmark.Comment: Interspeech 2023. Code URL: https://github.com/sungnyun/ARMHuBER

    Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

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    We study contextual linear bandit problems under uncertainty on features; they are noisy with missing entries. To address the challenges from the noise, we analyze Bayesian oracles given observed noisy features. Our Bayesian analysis finds that the optimal hypothesis can be far from the underlying realizability function, depending on noise characteristics, which is highly non-intuitive and does not occur for classical noiseless setups. This implies that classical approaches cannot guarantee a non-trivial regret bound. We thus propose an algorithm aiming at the Bayesian oracle from observed information under this model, achieving O~(dT)\tilde{O}(d\sqrt{T}) regret bound with respect to feature dimension dd and time horizon TT. We demonstrate the proposed algorithm using synthetic and real-world datasets.Comment: 30 page

    Rotting infinitely many-armed bandits

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    We consider the infinitely many-armed bandit problem with rotting rewards, where the mean reward of an arm decreases at each pull of the arm according to an arbitrary trend with maximum rotting rate ϱ=o(1). We show that this learning problem has an Ω(max{ϱ1/3T,T−−√}) worst-case regret lower bound where T is the time horizon. We show that a matching upper bound O~(max{ϱ1/3T,T−−√}), up to a poly-logarithmic factor, can be achieved by an algorithm that uses a UCB index for each arm and a threshold value to decide whether to continue pulling an arm or remove the arm from further consideration, when the algorithm knows the value of the maximum rotting rate ϱ. We also show that an O~(max{ϱ1/3T,T3/4}) regret upper bound can be achieved by an algorithm that does not know the value of ϱ, by using an adaptive UCB index along with an adaptive threshold value

    A candidate LiBH4 for hydrogen storage: Crystal structures and reaction mechanisms of intermediate phases

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    First-principles calculation and x-ray diffraction simulation methods have been used to explore crystal structures and reaction mechanisms of the intermediate phases involved in dehydriding of LiBH4. LiBH4 was found to dehydride via two sequential steps: first dehydriding through LiBH, followed by the dehydriding of LiBH through LiB. The first step, which releases 13.1 wt. % hydrogen, was calculated to have an activation barrier of 2.33 eV per formula unit and was endothermic by 1.28 eV per formula unit, while the second step was endothermic by 0.23 eV per formula unit. On the other hand, if LiBH4 and LiBH each donated one electron, possibly to the catalyst doped on their surfaces, it was found that the barrier for the first step was reduced to 1.50 eV. This implies that the development of the catalyst to induce charge migration from the bulk to the surface is essential to make LiBH4 usable as a hydrogen storage material in a moderate temperature range, which is also important to stabilize the low-temperature structure of Pnma (no. 62) LiBH on dehydrogenation. Consequently, the high 13.1 wt. % hydrogen available from the dehydriding of LiBH4 and LiBH and their phase stability on Pnma when specific catalysts were used suggest that LiBH4 has good potential to be developed as the hydrogen storage medium capable of releasing the Department of Energy target of 6.5 wt. % for a hydrogen fuel cell car in a moderate temperature range
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