Density-Dependent Response of an Ultracold Plasma to Few-Cycle Radio-Frequency Pulses

Ultracold neutral plasmas exhibit a density-dependent resonant response to applied radio-frequency (RF) fields in the frequency range of several MHz to hundreds of MHz for achievable densities. We have conducted measurements where short bursts of RF were applied to these plasmas, with pulse durations as short as two cycles. We still observed a density-dependent resonant response to these short pulses. However, the too rapid timescale of the response, the dependence of the response on the sign of the driving field, the response as the number of pulses was increased, and the difference in plasma response to radial and axially applied RF fields are inconsistent with the plasma response being due to local resonant heating of electrons in the plasma. Instead, our results are consistent with rapid energy transfer from collective motion of the entire electron cloud to electrons in high-energy orbits. In addition to providing a potentially more robust way to measure ultracold neutral plasma densities, these measurements demonstrate the importance of collective motion in the energy transport in these systems.Comment: 5 pages, 4 figure

Does SN 1987A contain a rapidly vibrating neutron star

If the recently reported 0.5 ms-period pulsed optical signal from the direction of Supernova 1987A originated in a young neutron star, its interpretation as a rotational period has difficulties. The surface magnetic field would have to be much lower than expected, and the high rotation rate may rule out preferred nuclear equations of state. It is pointed out here that a remnant radial vibration of a neutron star, excited in the supernova event, may survive for several years with about the observed (gravitationally redshifted) period. Heavy ions at the low-density stellar surface, periodically shocked by the vibration, may efficiently produce narrow pulses of optical cyclotron radiation in a surface field of about a trillion gauss

Causal Inference With Outcome-Dependent Missingness And Self-Censoring

We consider missingness in the context of causal inference when the outcome of interest may be missing. If the outcome directly affects its own missingness status, i.e., it is "self-censoring", this may lead to severely biased causal effect estimates. Miao et al. [2015] proposed the shadow variable method to correct for bias due to self-censoring; however, verifying the required model assumptions can be difficult. Here, we propose a test based on a randomized incentive variable offered to encourage reporting of the outcome that can be used to verify identification assumptions that are sufficient to correct for both self-censoring and confounding bias. Concretely, the test confirms whether a given set of pre-treatment covariates is sufficient to block all backdoor paths between the treatment and outcome as well as all paths between the treatment and missingness indicator after conditioning on the outcome. We show that under these conditions, the causal effect is identified by using the treatment as a shadow variable, and it leads to an intuitive inverse probability weighting estimator that uses a product of the treatment and response weights. We evaluate the efficacy of our test and downstream estimator via simulations.Comment: 15 pages. In proceedings of the 39th Conference on Uncertainty in Artificial Intelligenc

A reluctant additive model framework for interpretable nonlinear individualized treatment rules

Individualized treatment rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Interpretability is a desirable property of ITRs, as it helps practitioners make sense of treatment decisions, yet there is a need for ITRs to be flexible to effectively model complex biomedical data for treatment decision making. Many ITR approaches either focus on linear ITRs, which may perform poorly when true optimal ITRs are nonlinear, or black-box nonlinear ITRs, which may be hard to interpret and can be overly complex. This dilemma indicates a tension between interpretability and accuracy of treatment decisions. Here we propose an additive model-based nonlinear ITR learning method that balances interpretability and flexibility of the ITR. Our approach aims to strike this balance by allowing both linear and nonlinear terms of the covariates in the final ITR. Our approach is parsimonious in that the nonlinear term is included in the final ITR only when it substantially improves the ITR performance. To prevent overfitting, we combine cross-fitting and a specialized information criterion for model selection. Through extensive simulations, we show that our methods are data-adaptive to the degree of nonlinearity and can favorably balance ITR interpretability and flexibility. We further demonstrate the robust performance of our methods with an application to a cancer drug sensitive study

The InfraRed Imaging Spectrograph (IRIS) for TMT: Reflective ruled diffraction grating performance testing and discussion

We present the efficiency of near-infrared reflective ruled diffraction gratings designed for the InfraRed Imaging Spectrograph (IRIS). IRIS is a first light, integral field spectrograph and imager for the Thirty Meter Telescope (TMT) and narrow field infrared adaptive optics system (NFIRAOS). We present our experimental setup and analysis of the efficiency of selected reflective diffraction gratings. These measurements are used as a comparison sample against selected candidate Volume Phase Holographic (VPH) gratings (see Chen et al., this conference). We investigate the efficiencies of five ruled gratings designed for IRIS from two separate vendors. Three of the gratings accept a bandpass of 1.19-1.37 {\mu}m (J band) with ideal spectral resolutions of R=4000 and R=8000, groove densities of 249 and 516 lines/mm, and blaze angles of 9.86 and 20.54 degrees, respectively. The other two gratings accept a bandpass of 1.51-1.82 {\mu}m (H Band) with an ideal spectral resolution of R=4000, groove density of 141 lines/mm, and blaze angle of 9.86{\deg}. We measure the efficiencies off blaze angle for all gratings and the efficiencies between the polarization transverse magnetic (TM) and transverse electric (TE) states. The peak reflective efficiencies are 98.90 +/- 3.36% (TM) and 84.99 +/- 2.74% (TM) for the H-band R=4000 and J-band R=4000 respectively. The peak reflective efficiency for the J-band R=8000 grating is 78.78 +/- 2.54% (TE). We find that these ruled gratings do not exhibit a wide dependency on incident angle within +/-3{\deg}. Our best-manufactured gratings were found to exhibit a dependency on the polarization state of the incident beam with a ~10-20% deviation, consistent with the theoretical efficiency predictions.Comment: Proceedings of the SPIE, 9147-34

Metamaterial Coatings for Broadband Asymmetric Mirrors

We report on design and fabrication of nano-composite metal-dielectric thin film coatings with high reflectance asymmetries. Applying basic dispersion engineering principles to model a broadband and large reflectance asymmetry, we obtain a model dielectric function for the metamaterial film, closely resembling the effective permittivity of disordered metal-dielectric nano-composites. Coatings realized using disordered nanocrystalline silver films deposited on glass substrates confirm the theoretical predictions, exhibiting symmetric transmittance, large reflectance asymmetries and a unique flat reflectance asymmetry.Comment: 4 pages, 4 figures, submitted to Optics Letter

Climatic effects of 1950-2050 changes in US anthropogenic aerosols - Part 2: Climate response

We investigate the climate response to changing US anthropogenic aerosol sources over the 1950–2050 period by using the NASA GISS general circulation model (GCM) and comparing to observed US temperature trends. Time-dependent aerosol distributions are generated from the GEOS-Chem chemical transport model applied to historical emission inventories and future projections. Radiative forcing from US anthropogenic aerosols peaked in 1970–1990 and has strongly declined since due to air quality regulations. We find that the regional radiative forcing from US anthropogenic aerosols elicits a strong regional climate response, cooling the central and eastern US by 0.5–1.0 °C on average during 1970–1990, with the strongest effects on maximum daytime temperatures in summer and autumn. Aerosol cooling reflects comparable contributions from direct and indirect (cloud-mediated) radiative effects. Absorbing aerosol (mainly black carbon) has negligible warming effect. Aerosol cooling reduces surface evaporation and thus decreases precipitation along the US east coast, but also increases the southerly flow of moisture from the Gulf of Mexico resulting in increased cloud cover and precipitation in the central US. Observations over the eastern US show a lack of warming in 1960–1980 followed by very rapid warming since, which we reproduce in the GCM and attribute to trends in US anthropogenic aerosol sources. Present US aerosol concentrations are sufficiently low that future air quality improvements are projected to cause little further warming in the US (0.1 °C over 2010–2050). We find that most of the warming from aerosol source controls in the US has already been realized over the 1980–2010 period

AtomSim: web-deployed atomistic dynamics simulator

AtomSim, a collection of interfaces for computational crystallography simulations, has been developed. It uses forcefield-based dynamics through physics engines such as the General Utility Lattice Program, and can be integrated into larger computational frameworks such as the Virtual Neutron Facility for processing its dynamics into scattering functions, dynamical functions etc. It is also available as a Google App Engine-hosted web-deployed interface. Examples of a quartz molecular dynamics run and a hafnium dioxide phonon calculation are presented