1,241 research outputs found

    Forbidden Channels and SIMP Dark Matter

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    In this review, we focus on dark matter production from thermal freeze-out with forbidden channels and SIMP processes. We show that forbidden channels can be dominant to produce dark matter depending on the dark photon and / or dark Higgs mass compared to SIMP.Comment: 5 pages, Prepared for the proceedings of the 13th International Conference on Gravitation, 3-7 July 201

    On thermal production of self-interacting dark matter

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    We consider thermal production mechanisms of self-interacting dark matter in models with gauged Z3Z_3 symmetry. A complex scalar dark matter is stabilized by the Z3Z_3, that is the remnant of a local dark U(1)dU(1)_d. Light dark matter with large self-interaction can be produced from thermal freeze-out in the presence of SM-annihilation, SIMP and/or forbidden channels. We show that dark photon and/or dark Higgs should be relatively light for unitarity and then assist the thermal freeze-out. We identify the constraints on the parameter space of dark matter self-interaction and mass in cases that one or some of the channels are important in determining the relic density.Comment: 26 pages, 11 figures, Version to appear in Journal of High Energy Physic

    Aging effects and working memory in garden-path sentence comprehension

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    The current study examined whether older adults exhibit difficulty in recovering from syntactically ambiguous garden-path sentences, and whether this difficulty is predicted by working memory capacity (WM). This study found several points. First, there was a garden-path effect regardless of age group. Second, there were age-related differences between young and elderly adults for the sentences with temporary syntactic ambiguity, in on- and off-line measures. Third, the age-related effects were predicted by WM. These points indicate that syntactic ambiguity resolution is affected by healthy cognitive aging, and suggest that age-related WM changes may be responsible for these differences

    Unitary inflaton as decaying dark matter

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    We consider the inflation model of a singlet scalar field (sigma field) with both quadratic and linear non-minimal couplings where unitarity is ensured up to the Planck scale. We assume that a Z2Z_2 symmetry for the sigma field is respected by the scalar potential in Jordan frame but it is broken explicitly by the linear non-minimal coupling due to quantum gravity. We discuss the impacts of the linear non-minimal coupling on various dynamics from inflation to low energy, such as a sizable tensor-to-scalar ratio, a novel reheating process with quartic potential dominance, and suppressed physical parameters in the low energy, etc. In particular, the linear non-minimal coupling leads to the linear couplings of the sigma field to the Standard Model through the trace of the energy-momentum tensor in Einstein frame. Thus, regarding the sigma field as a decaying dark matter, we consider the non-thermal production mechanisms for dark matter from the decays of Higgs and inflaton condensate and show the parameter space that is compatible with the correct relic density and cosmological constraints.Comment: 36 pages, 7 figures, v2: minor corrections made and references added, v3: discussion on preheating added, accepted for Journal of High Energy Physics, v4: Lyman-alpha bound included and inflationary predictions refined for perturbative reheatin

    A minimal flavored U(1)U(1)' for BB-meson anomalies

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    We consider an anomaly-free U(1)U(1)' model with favorable couplings to heavy flavors in the Standard Model(SM), as motivated by BB-meson anomalies at LHCb. Taking the U(1)U(1)' charge to be Q=y(LμLτ)+x(B3L3)Q'=y(L_\mu-L_\tau)+ x(B_3-L_3), we can explain the BB-meson anomalies without invoking extra charged fermions or flavor violation beyond the SM. We show that there is a viable parameter space with a small xx that is compatible with other meson decays, tau lepton and neutrino experiments as well as the LHC dimuon searches. We briefly discuss the prospects of discovering the ZZ' gauge boson at the LHC in the proposed model.Comment: 20 pages, 4 figures, v2: references and discussion on electroweak precision test added, v3: Version to appear in Physical Review

    Evaluation formulas for a conditional Feynman integral over Wiener paths in abstract Wiener space

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    summary:In this paper, we introduce a simple formula for conditional Wiener integrals over C0(B)C_0(\mathbb{B}), the space of abstract Wiener space valued continuous functions. Using this formula, we establish various formulas for a conditional Wiener integral and a conditional Feynman integral of functionals on C0(B)C_0(\mathbb{B}) in certain classes which correspond to the classes of functionals on the classical Wiener space introduced by Cameron and Storvick. We also evaluate the conditional Wiener integral and conditional Feynman integral for functionals of the form exp{0Tθ(s,x(s))dη(s)} \exp \biggl \lbrace \int _0^T \theta (s, x(s))\mathrm{d}\eta (s) \biggr \rbrace which are of interest in Feynman integration theories and quantum mechanics

    Improving Neural Radiance Field using Near-Surface Sampling with Point Cloud Generation

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    Neural radiance field (NeRF) is an emerging view synthesis method that samples points in a three-dimensional (3D) space and estimates their existence and color probabilities. The disadvantage of NeRF is that it requires a long training time since it samples many 3D points. In addition, if one samples points from occluded regions or in the space where an object is unlikely to exist, the rendering quality of NeRF can be degraded. These issues can be solved by estimating the geometry of 3D scene. This paper proposes a near-surface sampling framework to improve the rendering quality of NeRF. To this end, the proposed method estimates the surface of a 3D object using depth images of the training set and sampling is performed around there only. To obtain depth information on a novel view, the paper proposes a 3D point cloud generation method and a simple refining method for projected depth from a point cloud. Experimental results show that the proposed near-surface sampling NeRF framework can significantly improve the rendering quality, compared to the original NeRF and a state-of-the-art depth-based NeRF method. In addition, one can significantly accelerate the training time of a NeRF model with the proposed near-surface sampling framework.Comment: 13 figures, 2 table
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