668 research outputs found

    Stochastic dynamics of multi-waterfall hybrid inflation and formation of primordial black holes

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    We show that a hybrid inflation model with multiple waterfall fields can result in the formation of primordial black hole (PBH) with an astrophysical size, by using an advanced algorithm to follow the stochastic dynamics of the waterfall fields. This is in contrast to the case with a single waterfall field, where the wavelength of density perturbations is usually too short to form PBHs of the astrophysical scale (or otherwise PBH are overproduced and the model is ruled out) unless the inflaton potential is tuned. In particular, we demonstrate that PBHs with masses of order 1020g10^{20}\, {\rm g} can form after hybrid inflation consistently with other cosmological observations if the number of waterfall fields is about 5 for the case of instantaneous reheating. Observable gravitational waves are produced from the second-order effect of large curvature perturbations as well as from the dynamics of texture or global defects that form after the waterfall phase transition.Comment: 23 pages, 5 figure

    On the primordial black hole formation in hybrid inflation

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    We revisit the scenario of primordial black hole (PBH) formation from large curvature perturbations generated during the waterfall phase transition in hybrid inflation models. In a minimal setup considered in the literature, the mass and abundance of PBHs are correlated and astrophysical size PBHs tend to be overproduced. This is because a longer length scale for curvature perturbations (or a larger PBH mass) requires a longer waterfall regime with a flatter potential, which results in overproduction of curvature perturbations. However, in this paper, we discuss that the higher-dimensional terms for the inflaton potential affect the dynamics during the waterfall phase transition and show that astrophysical size PHBs of order 101723g10^{17\text{--}23} \, {\rm g} (which can explain the whole dark matter) can form in some parameter space consistently with any existing constraints. The scenario can be tested by observing the induced gravitational waves from scalar perturbations by future gravitational wave experiments, such as LISA.Comment: 14 pages, 8 figures; v2: minor corrections, figures updated, conclusions unchange

    Dynamics of Superconformal Axion: Quality and Scalegenesis

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    We explore a dynamical mechanism to realize the emergence of a global U(1)PQU(1)_{\rm PQ} symmetry and its spontaneous breaking at an intermediate scale for an axion solution to the strong CP problem. Such a dynamics is provided by a new supersymmetric QCD near the middle of conformal window that couples to fields spontaneously breaking the U(1)PQU(1)_{\rm PQ} symmetry. A large anomalous dimension of the U(1)PQU(1)_{\rm PQ} breaking fields leads to the suppression of explicit U(1)PQU(1)_{\rm PQ}-violating higher dimensional operators. The U(1)PQU(1)_{\rm PQ} breaking vacuum is generated at a scale hierarchically smaller than the Planck scale by a non-perturbative effect. The U(1)PQU(1)_{\rm PQ} breaking drives the conformal breaking, and all the new quarks become massive. The axion potential is generated by the ordinary color SU(3)CSU(3)_C effect as the U(1)PQU(1)_{\rm PQ} symmetry is only anomalous under the SU(3)CSU(3)_C. The saxion direction is stabilized by supersymmetry breaking and cosmologically harmless.Comment: 8 pages, 3 figure

    Effectiveness of spatial analysis in Cryptomeria japonica D. Don (sugi) forward selection revealed by validation using progeny and clonal tests

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    International audienceAbstractKey messageAccurate evaluation of genetic performances of trees is crucial in order to improve the efficiency of forest tree breeding. We revealed that spatial analysis is effective for predicting individual tree breeding values at the forward selection stage ofCryptomeria japonicaD. Don (sugi) breeding program by using a novel validation approach.ContextIn the process of selecting genetically superior trees for breeding, appropriate handling of environmental effects is important in order to precisely evaluate candidate trees. Spatial analysis has been an effective statistical approach for genetic evaluation at sites with heterogeneous microenvironments. However, the efficiency of spatial analysis on forward selection has not been validated on a practical scale to date.AimsThis study aimed to reveal the effectiveness of spatial analysis, which incorporates spatially autocorrelated residuals into mixed models, for the prediction of breeding values at the forward selection stage by validation using progeny or clonal tests of forward-selected individuals.MethodsTree height was analyzed by ordinary randomized complete block design models and spatial models incorporating spatially autocorrelated residuals in a linear mixed model framework, and model selection was conducted at thirty Cryptomeria japonica D. Don breeding population sites having various topographical ruggedness. For validation, three clonal tests and one progeny test of individuals selected from three and four breeding populations, respectively, were used. The effectiveness of forward selection using the two models was evaluated based on the correlation between individual breeding values at the stage of forward selection and genotypic and breeding values that were estimated by clonal and progeny tests.ResultsSpatial models were more predictive than ordinary models in all cases. Spatial correlation parameters tend to increase with the topographical ruggedness index of each site. The correlation coefficients between breeding values at the time of forward selection and genotypic or breeding values evaluated in succeeding clonal and progeny tests were significantly higher in spatial models than in ordinary models in six out of nine cases.ConclusionValidation using progeny and clonal tests of forward-selected individual trees revealed that spatial analysis is more effective for the evaluation of genetic performance of individuals at the stage of forward selection in Cryptomeria japonica

    Titer estimation for quality control (TEQC) method: A practical approach for optimal production of protein complexes using the baculovirus expression vector system

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    The baculovirus expression vector system (BEVS) is becoming the method of choice for expression of many eukaryotic proteins and protein complexes for biochemical, structural and pharmaceutical studies. Significant technological advancement has made generation of recombinant baculoviruses easy, efficient and user-friendly. However, there is a tremendous variability in the amount of proteins made using the BEVS, including different batches of virus made to express the same proteins. Yet, what influences the overall production of proteins or protein complexes remains largely unclear. Many downstream applications, particularly protein structure determination, require purification of large quantities of proteins in a repetitive manner, calling for a reliable experimental set-up to obtain proteins or protein complexes of interest consistently. During our investigation of optimizing the expression of the Mediator Head module, we discovered that the 'initial infectivity' was an excellent indicator of overall production of protein complexes. Further, we show that this initial infectivity can be mathematically described as a function of multiplicity of infection (MOI), correlating recombinant protein yield and virus titer. All these findings led us to develop the Titer Estimation for Quality Control (TEQC) method, which enables researchers to estimate initial infectivity, titer/MOI values in a simple and affordable way, and to use these values to quantitatively optimize protein expressions utilizing BEVS in a highly reproducible fashion
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