arXiv subjects

Shenshen Yang

Publications and source records attributed to Shenshen Yang.

4 recordsLinked to original sources

arXiv2024

Dark Matter Physics in General NMSSM

In the General Next-to-Minimal Supersymmetric Standard Model (GNMSSM), singlet particles may form a secluded sector of dark matter (DM), in which Singlino-like DM could achieve the observed relic abundance through various channels such as $\tilde{\chi}_1^0 \tilde{\chi}_1^0 \to h_s h_s, A_s A_s, h_s A_s$, where $h_s$ and $A_s$ represent singlet-dominated CP-even and CP-odd Higgs bosons. We provide analytical formulas for both the spin-independent and spin-dependent cross sections of Singlino DM scattering with nucleons, illustrating their dependence on the model's parameters in a clear manner. We also present analytic expressions for the annihilation cross sections of these three important channels. Based on these preparations, we conducted Bayesian analyses of the GNMSSM and concluded that the theory significantly favored Singlino-dominated DM over Bino-like DM across a much broader range of parameters. The combined results from our numerical analyses and the formulas distinctly highlight crucial aspects of DM physics within the GNMSSM.

hep-ph↗

arXiv2023

A Computational Approach to Identification of Treatment Effects for Policy Evaluation

For counterfactual policy evaluation, it is important to ensure that treatment parameters are relevant to policies in question. This is especially challenging under unobserved heterogeneity, as is well featured in the definition of the local average treatment effect (LATE). Being intrinsically local, the LATE is known to lack external validity in counterfactual environments. This paper investigates the possibility of extrapolating local treatment effects to different counterfactual settings when instrumental variables are only binary. We propose a novel framework to systematically calculate sharp nonparametric bounds on various policy-relevant treatment parameters that are defined as weighted averages of the marginal treatment effect (MTE). Our framework is flexible enough to fully incorporate statistical independence (rather than mean independence) of instruments and a large menu of identifying assumptions beyond the shape restrictions on the MTE that have been considered in prior studies. We apply our method to understand the effects of medical insurance policies on the use of medical services.

econ.EM↗

arXiv2023

The Phenomenological Research on Higgs and dark matter in the Next-to-Minimal Supersymmetric Standard Model

The $Z_3$-invariant next-to-minimal supersymmetric standard model (NMSSM) can provide a candidate for dark matter (DM). It can also be used to explain the hypothesis that the Higgs signal observed on the Large Hadron Collider (LHC) comes from the contribution of the two lightest CP-even Higgs bosons, whose masses are near 125 GeV. At present, XENON1T, LUX, and PandaX experiments have imposed very strict restrictions on direct collision cross sections of {dark matter}. In this paper, we consider a scenario that the observed Higgs signal is the superposition of two mass-degenerate Higgs in the $Z_3$-invariant NMSSM and scan the seven-dimension parameter space composing of $λ, κ, \tanβ, μ, A_k, A_t, M_1$ via the Markov chain Monte Carlo (MCMC) method. We find that the DM relic density, as well as the LHC searches for sparticles, especially the DM direct detections, has provided a strong limit on the parameter space. %Please check intended meaning has been retained. The allowed parameter space is featured by a relatively small $μ\le 300$ GeV and about $\tanβ\in(10,20)$. In addition, the DM is Higgsino-dominated because of $|\frac{2κ}λ|>1$. Moreover, the co-annihilation between $\tildeχ_1^0$ and $\tildeχ_1^\pm$ must be taken into account to obtain the reasonable DM relic density.

hep-ph↗

arXiv2022

A Doubly Robust GMM Estimator for Sequential Non-monotone Missingness

We study moment-based estimation with two sequentially collected variables subject to non-monotone missingness. The commonly used Missing at Random (MAR) assumption requiring all missingness mechanisms to depend on the same fully observed covariates often fails in such cases. We introduce a sequential MAR assumption that allows asymmetric missingness mechanisms across stages. Based on this assumption, we construct an Augmented Inverse-Probability-Weighted GMM (AIPW-GMM) estimator. The estimator features an asymmetric structure for the augmentation term, guarantees double robustness, and achieves the closed-form semiparametric efficiency bound. An application to two-period survey data from the Oregon Health Insurance Experiment supports the observable implications of the new assumption. The proposed approach reduces the standard errors by more than 50% for the estimated effects of the Oregon Health Plan among older adults, "driving" previously statistically insignificant estimates significant.

econ.EM↗