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Closing the Gap on $R_{D^*}$ by including longitudinal effects

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 Added by Genaro Toledo
 Publication date 2018
  fields
and research's language is English




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Measurements of the $R_{D^*}equivmathrm{Br}(Brightarrow tau u D^*)/mathrm{Br}(Brightarrow e u D^*)$ parameter remain in tension with the standard model prediction, despite recent results helping to close the gap. The standard model prediction it is compared with considers the $D^*$ as an external particle, even though what is detected in experiments is a $Dpi$ pair it decays into, from which it is reconstructed. We argue that the experimental result must be compared with the theoretical prediction considering the full 4-body decay $(Brightarrow l u D^* to l u Dpi)$. We show that the longitudinal degree of freedom of the off-shell $D^*$ helps to further close the disagreement gap with experimental data. We find values for the ratio $R_{Dpi}^l equiv {mathrm{Br}(Brightarrow tau u_tau D pi)}/mathrm{Br}(Brightarrow l u_l Dpi)$ of $R_{Dpi}^e=0.274pm0.003$ and $R_{Dpi}^mu=0.275pm0.003$, where the uncertainty comes from the uncertainty of the form factors parameters. Comparing against $R_{Dpi}$ reduces the gap with the latest LHCb result from $1.1sigma$ to $0.48sigma$, while the gap with the latest Belle result is reduced from $0.42sigma$ to just $0.10sigma$ and with the world average results from $3.7sigma$ to $2.1sigma$. Erratum added at the end of the file.

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Measurements of the $R_{D^*}$ parameter remain in tension with the standard model prediction, despite recent results helping to close the gap. In this work, we revisit the standard model considerations for the prediction. We pay particular attention to the theoretical prediction considering the full 4-body decay $(Brightarrow l u D^* to l u Dpi)$, which introduces the longitudinal degree of freedom of the $D^*$. We show that this does not introduce sizeable effects at the current precision. This modifies our previous finding (Phys. Rev. D 98 056014 (2018)) where a numerical bug led us to a different conclusion. Thus, the results on $R_{Dpi}$ are consistent with $R_{D^*}$, and the difference between the several values can be traced back to the form factor used and the restrictions incorporated to determine their parameters. There is still tension between the experimental world average and the most accurate theoretical estimate, leaving the possibility of presence of new physics scenarios open.
There has been persistent disagreement between the Standard Model (SM) prediction and experimental measurements of $R_{D^{(*)}}=mathcal{B}(bar B rightarrow D^{(*)} tau bar u_tau)/mathcal{B}(bar B rightarrow D^{(*)} l bar u_l)$ $(l=e,mu)$. This anomaly may be addressed by introducing interactions beyond the Standard Model involving new states, such as leptoquarks. Since the processes involved are quark flavor changing, any new states would need to couple to at least two different generations of quarks, requiring a non-trivial flavor structure in the quark sector while avoiding stringent constraints from flavor-changing neutral current processes. In this work, we look at scalar leptoquarks as a possible solution for the $R_{D^{(*)}}$ anomaly under the assumption of $it{minimal~flavor~violation}$ (MFV). We investigate all possible representations for the leptoquarks under the SM quark flavor symmetry group, consistent with asymptotic freedom. We consider constraints on their parameter space from self-consistency of the MFV scenario, perturbativity, the FCNC decay $bto sbar u u$ and precision electroweak observables. We find that none of the scalar leptoquarks can explain the $R_{D^{(*)}}$ anomaly while simultaneously avoiding all constraints within this scenario. Thus scalar leptoquarks with MFV-generated quark couplings do not work as a solution to the $R_{D^{(*)}}$ anomaly.
259 - Ryoutaro Watanabe 2018
Recent theoretical developments on $R_D$ and $R_{D^*}$ -- discrepancies between experimental data and the Standard Model predictions have been reported (B anomaly) -- are reviewed. New Physics explanations for the B anomaly and other relevant observables to obtain additional bounds on New Physics are also summarized. This is the proceedings for the talk at CIPANP2018 which was held on May 29 2018.
The $R_{D^{(*)}}$ anomalies are among the longest-standing and most statistically significant hints of physics beyond the Standard Model. Many models have been proposed to explain these anomalies, including the interesting possibility that right-handed neutrinos could be involved in the $B$ decays. In this paper, we investigate future measurements at Belle II that can be used to tell apart the various new physics scenarios. Focusing on a number of $tau$ asymmetry observables (forward-backward asymmetry and polarization asymmetries) which can be reconstructed at Belle II, we calculate the contribution of the most general dimension 6 effective Hamiltonian (including right-handed neutrinos) to all of these asymmetries. We show that Belle II can use these asymmetries to distinguish between new-physics scenarios that use right- and left-handed neutrinos, and in most cases can likely distinguish the specific model itself.
AI researchers employ not only the scientific method, but also methodology from mathematics and engineering. However, the use of the scientific method - specifically hypothesis testing - in AI is typically conducted in service of engineering objectives. Growing interest in topics such as fairness and algorithmic bias show that engineering-focused questions only comprise a subset of the important questions about AI systems. This results in the AI Knowledge Gap: the number of unique AI systems grows faster than the number of studies that characterize these systems behavior. To close this gap, we argue that the study of AI could benefit from the greater inclusion of researchers who are well positioned to formulate and test hypotheses about the behavior of AI systems. We examine the barriers preventing social and behavioral scientists from conducting such studies. Our diagnosis suggests that accelerating the scientific study of AI systems requires new incentives for academia and industry, mediated by new tools and institutions. To address these needs, we propose a two-sided marketplace called TuringBox. On one side, AI contributors upload existing and novel algorithms to be studied scientifically by others. On the other side, AI examiners develop and post machine intelligence tasks designed to evaluate and characterize algorithmic behavior. We discuss this markets potential to democratize the scientific study of AI behavior, and thus narrow the AI Knowledge Gap.
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