Emission of photon echoes in a strongly scattering medium

We observe the two- and three-pulse photon echo emission from a scattering powder, obtained by grinding a Pr$^{3+}$:Y$_2$SiO$_5$ rare earth doped single crystal. We show that the collective emission is coherently constructed over several grains. A well defined atomic coherence can therefore be created between randomly placed particles. Observation of photon echo on powders as opposed to bulk materials opens the way to faster material development. More generally, time-domain resonant four-wave mixing offers an attractive approach to investigate coherent propagation in scattering media

Heavy fermions and two loop electroweak corrections to b→s+γb\rightarrow s+\gamma

Applying effective Lagrangian method and on-shell scheme, we analyze the electroweak corrections to the rare decay $b\rightarrow s+\gamma$ from some special two loop diagrams in which a closed heavy fermion loop is attached to the virtual charged gauge bosons or Higgs. At the decoupling limit where the virtual fermions in inner loop are much heavier than the electroweak scale, we verify the final results satisfying the decoupling theorem explicitly when the interactions among Higgs and heavy fermions do not contain the nondecoupling couplings. Adopting the universal assumptions on the relevant couplings and mass spectrum of new physics, we find that the relative corrections from those two loop diagrams to the SM theoretical prediction on the branching ratio of $B\rightarrow X_{_s}\gamma$ can reach 5% as the energy scale of new physics $\Lambda_{_{\rm NP}}=200$ GeV.Comment: 30 pages,4 figure

Evolution of Iron Kα_{\alpha} Line Emission in the Black Hole Candidate GX 339-4

GX 339-4 was regularly monitored with RXTE during a period (in 1999) when its X-ray flux decreased significantly (from 4.2$\times 10^{-10}$ erg cm$^{-2} s^{-1}$ to 7.6$\times 10^{-12}$ erg cm$^{-2}$s$^{-1}$ in the 3--20 keV band), as the source settled into the ``off state''. Our spectral analysis revealed the presence of a prominent iron K$_{\alpha}$ line in the observed spectrum of the source for all observations. The line shows an interesting evolution: it is centered at $\sim$6.4 keV when the measured flux is above 5$\times 10^{-11}$ erg cm$^{-2} s^{-1}$, but is shifted to $\sim$6.7 keV at lower fluxes. The equivalent width of the line appears to increase significantly toward lower fluxes, although it is likely to be sensitive to calibration uncertainties. While the fluorescent emission of neutral or mildly ionized iron atoms in the accretion disk can perhaps account for the 6.4 keV line, as is often invoked for black hole candidates, it seems difficult to understand the 6.7 keV line with this mechanism, because the disk should be less ionized at lower fluxes (unless its density changes drastically). On the other hand, the 6.7 keV line might be due to recombination cascade of hydrogen or helium like iron ions in an optically thin, highly ionized plasma. We discuss the results in the context of proposed accretion models.Comment: 18 pages, 2 figures, accepted for publication in the ApJ in v552n2p May 10, 2001 issu

LHC Searches for Non-Chiral Weakly Charged Multiplets

Because the TeV-scale to be probed at the Large Hadron Collider should shed light on the naturalness, hierarchy, and dark matter problems, most searches to date have focused on new physics signatures motivated by possible solutions to these puzzles. In this paper, we consider some candidates for new states that although not well-motivated from this standpoint are obvious possibilities that current search strategies would miss. In particular we consider vector representations of fermions in multiplets of $SU(2)_L$ with a lightest neutral state. Standard search strategies would fail to find such particles because of the expected small one-loop-level splitting between charged and neutral states.Comment: 16 pages, 9 figure

Two loop electroweak corrections to Bˉ→Xsγ\bar B\rightarrow X_s\gamma and Bs0→μ+μ−B_s^0\rightarrow \mu^+\mu^- in the B-LSSM

The rare decays $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$ are important to research new physics beyond standard model. In this work, we investigate two loop electroweak corrections to $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$ in the minimal supersymmetric extension of the SM with local $B-L$ gauge symmetry (B-LSSM), under a minimal flavor violating assumption for the soft breaking terms. In this framework, new particles and new definition of squarks can affect the theoretical predictions of these two processes, with respect to the MSSM. Considering the constraints from updated experimental data, the numerical results show that the B-LSSM can fit the experimental data for the branching ratios of $\bar B\rightarrow X_s\gamma$ and $B_s^0\rightarrow \mu^+\mu^-$. The results of the rare decays also further constrain the parameter space of the B-LSSM.Comment: 33 pages, 9 figures, Published in EPJ

Global microRNA depletion suppresses tumor angiogenesis

MicroRNAs delicately regulate the balance of angiogenesis. Here we show that depletion of all microRNAs suppresses tumor angiogenesis. We generated microRNA-deficient tumors by knocking out Dicer1. These tumors are highly hypoxic but poorly vascularized, suggestive of deficient angiogenesis signaling. Expression profiling revealed that angiogenesis genes were significantly down-regulated as a result of the microRNA deficiency. Factor inhibiting hypoxia-inducible factor 1 (HIF-1), FIH1, is derepressed under these conditions and suppresses HIF transcription. Knocking out FIH1 using CRISPR/Cas9-mediated genome engineering reversed the phenotypes of microRNA-deficient cells in HIF transcriptional activity, VEGF production, tumor hypoxia, and tumor angiogenesis. Using multiplexed CRISPR/Cas9, we deleted regions in FIH1 3′ untranslated regions (UTRs) that contain microRNA-binding sites, which derepresses FIH1 protein and represses hypoxia response. These data suggest that microRNAs promote tumor responses to hypoxia and angiogenesis by repressing FIH1.Swedish Research CouncilHoward Hughes Medical Institute (International Student Research Fellowship)National Institutes of Health (U.S.) (grant number R01-CA133404)MIT-Harvard Center of Cancer Nanotechnology Excellence (grant no. U54-CA151884)David H. Koch Institute for Integrative Cancer Research at MIT (Marie D. and Pierre Casimir-Lambert Fund)National Cancer Institute (U.S.) (Koch Institute Support (core) Grant P30-CA14051))National Institutes of Health (U.S.) (grant EB016101-01A1)Damon Runyon Cancer Research Foundation (Research Fellow (DRG-2117-12)

Color Octet Contribution to J/psi Photoproduction Asymmetries

We investigate $J/\psi$ photoproduction asymmetries in the framework of the NRQCD factorization approach. It is shown that the color octet contribution leads to large uncertainties in the predicted asymmetries which rules out the possibility to precisely measure the gluon polarization in the nucleon through this final state. For small values of the color octet parameters being compatible with $J/\psi$ photoproduction data it appears possible that a measurement of $J/\psi$ asymmetries could provide a new test for the NRQCD factorization approach, on one hand, or a measurement of the polarized gluon distribution from low inelasticity events $(z<0.7)$, on the otherComment: 12 pages, LaTeX, with 6 figs. Final version published in Phys.Rev.

Essays on Causal Inference with Endogeneity and Missing Data

This dissertation strives to devise novel yet easy-to-implement estima- tion and inference procedures for economists to solve complicated real world problems. It provides by far the most optimal solutions in situations when sample selection is entangled with missing data problems and when treatment effects are heterogenous but instruments only have limited variations. In the first chapter, we investigate the problem of missing instruments and create the generated instrument approach to address it. Specifically, When the missingness of instruments is endogenous, dropping observations can cause biased estimation. This chapter proposes a methodology which uses all the data to do instrumental variables (IV) estimation. The methodology provides consistent estimation with endogenous missingness of instruments. It firstly forms a generated instrument for every observation in the data sample that: a) for observations without instruments, the new instrument is an imputation; b) for observations with instruments, the new instrument is an inverse propensity score weighted combination of the original instrument and an imputation. The estimation then proceeds by using the generated instruments. Asymptotic theorems are established. The new estimator attains the semiparametric efficiency bound. It is also less biased compared to existing procedures in the simulations. As an illustrative example, we use the NLSYM data set in which IQ scores are partially missing, and demonstrate that by adopting the new methodology the return to education is larger and more precisely estimated compared to standard complete case methods. In the second chapter, we provide Lasso-type of procedures for reduced form regression with many missing instruments. The methodology takes two steps. In the first step, we generate a rich instrument set from the many missing instruments and other observed data. In the second step, IV estimation is conduced based on the generated instrument set. Specifically, the (very) many generated instruments are used to approximate a “pseudo” optimal instrument in the reduced form regression. The approach has been shown to have efficiency gains compared to the generated instrument estimator developed in the first chapter. We also compare the finite sample behavior of the new estimator with other Lasso estimator and demonstrate the good performance of the proposed estimator in the Monte Carlo experiments. The third chapter estimates individual treatment effects in a triangular model with binary–valued endogenous treatments. This chapter is based on the previous joint work with Quang Vuong and Haiqing Xu. Following the identification strategy established in (Vuong and Xu, forthcoming), we propose a two-stage estimation approach. First, we estimate the counterfactual outcome and hence the individual treatment effect (ITE) for every observational unit in the sample. Second, we estimate the density of individual treatment effects in the population. Our estimation method does not suffer from the ill-posed inverse problem associated with inverting a non–linear functional. Asymptotic properties of the proposed method are established. We study its finite sample properties in Monte Carlo experiments. We also illustrate our approach with an empirical application assessing the effects of 401(k) retirement programs on personal savings. Our results show that there exists a small but statistically significant proportion of individuals who experience negative effects, although the majority of ITEs is positive.Economic

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations