Generalization of the Darboux transformation and generalized harmonic oscillators

The Darbroux transformation is generalized for time-dependent Hamiltonian systems which include a term linear in momentum and a time-dependent mass. The formalism for the $N$-fold application of the transformation is also established, and these formalisms are applied for a general quadratic system (a generalized harmonic oscillator) and a quadratic system with an inverse-square interaction up to N=2. Among the new features found, it is shown, for the general quadratic system, that the shape of potential difference between the original system and the transformed system could oscillate according to a classical solution, which is related to the existence of coherent states in the system

Wide-bandwidth, tunable, multiple-pulse-width optical delays using slow light in cesium vapor

We demonstrate an all-optical delay line in hot cesium vapor that tunably delays 275 ps input pulses up to 6.8 ns and 740 input ps pulses up to 59 ns (group index of approximately 200) with little pulse distortion. The delay is made tunable with a fast reconfiguration time (hundreds of ns) by optically pumping out of the atomic ground states.Comment: 4 pages, 6 figure

Machine Learning, Human Factors and Security Analysis for the Remote Command of Driving: An MCity Pilot

Conducted under the U.S. DOT Office of the Assistant Secretary for Research and Technology’s (OST-R) University Transportation Centers (UTC) program.Both human drivers and autonomous vehicles are able to drive relatively well in frequently encountered settings, but fail in exceptional cases. These exceptional cases often arise suddenly, leaving human drivers with a few seconds at best to react—exactly the setting that people perform worst in. Autonomous systems also fail in exceptional cases, because ambiguous situations preceding crashes are not effectively captured in training datasets. This work introduces new methods for leveraging groups of people to provide on-demand assistance by coordinating responses and using collective answer distributions to generate responses to ambiguous scenarios using minimal time and effort. Unlike prior approaches, we introduce collective workflows that enable groups of people to significantly outperform any of the constituent individuals in terms of time and accuracy. First, we examine the latency and accuracy of crowd workers in a future state prediction task in visual driving scenes, and find that more than 50% of workers could provide accurate answers within one second. We found that using crowd predictions is a viable approach for determining critical future states to inform rapid decision making. Additionally, we characterize different estimation techniques that can be used to efficiently create collective answer distributions from crowd workers for visual tasks containing ambiguity. Surprisingly, we discovered that the most fine-grained and time-consuming methods were not the most accurate. Instead, having annotators choose all relevant responses they thought other annotators would select led to more accurate aggregate outcomes. This approach reduced human time required by 21.4% while maintaining the same level of accuracy as the baseline approach. These research results can inform the development of hybrid intelligence systems that accurately and rapidly address sudden and rare critical events, even when they are ambiguous or subjective.United States Department of Transportation Office of the Assistant Secretary for Research and TechnologyCenter for Connected and Automated Transportationhttp://deepblue.lib.umich.edu/bitstream/2027.42/156392/4/Machine Learning Human Factors and Security Analysis for the Remote Command of Driving - An Mcity Pilot.pd

Nature of the spin resonance mode in CeCoIn5_5

Spin-fluctuation-mediated unconventional superconductivity can emerge at the border of magnetism, featuring a superconducting order parameter that changes sign in momentum space. Detection of such a sign-change is experimentally challenging, since most probes are not phase-sensitive. The observation of a spin resonance mode (SRM) from inelastic neutron scattering is often seen as strong phase-sensitive evidence for a sign-changing superconducting order parameter, by assuming the SRM is a spin-excitonic bound state. Here, we show that for the heavy fermion superconductor CeCoIn$_5$, its SRM defies expectations for a spin-excitonic bound state, and is not a manifestation of sign-changing superconductivity. Instead, the SRM in CeCoIn$_5$ likely arises from a reduction of damping to a magnon-like mode in the superconducting state, due to its proximity to magnetic quantum criticality. Our findings emphasize the need for more stringent tests of whether SRMs are spin-excitonic, when using their presence to evidence sign-changing superconductivity.Comment: accepted for publication in Communications Physic

Robust Upward Dispersion of the Neutron Spin Resonance in the Heavy Fermion Superconductor Ce1−x_{1-x}Ybx_{x}CoIn5_5

The neutron spin resonance is a collective magnetic excitation that appears in copper oxide, iron pnictide, and heavy fermion unconventional superconductors. Although the resonance is commonly associated with a spin-exciton due to the $d$($s^{\pm}$)-wave symmetry of the superconducting order parameter, it has also been proposed to be a magnon-like excitation appearing in the superconducting state. Here we use inelastic neutron scattering to demonstrate that the resonance in the heavy fermion superconductor Ce$_{1-x}$Yb$_{x}$CoIn$_5$ with $x=0,0.05,0.3$ has a ring-like upward dispersion that is robust against Yb-doping. By comparing our experimental data with random phase approximation calculation using the electronic structure and the momentum dependence of the $d_{x^2-y^2}$-wave superconducting gap determined from scanning tunneling microscopy for CeCoIn$_5$, we conclude the robust upward dispersing resonance mode in Ce$_{1-x}$Yb$_{x}$CoIn$_5$ is inconsistent with the downward dispersion predicted within the spin-exciton scenario.Comment: Supplementary Information available upon reques

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Cone-beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However, the excessive x-ray imaging dose from serial CBCT scans raises a clinical concern in most IGRT procedures. The excessive imaging dose can be effectively reduced by reducing the number of x-ray projections and/or lowering mAs levels in a CBCT scan. The goal of this work is to develop a fast GPU-based algorithm to reconstruct high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose. The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. We developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multi-grid technique is also employed. We test our CBCT reconstruction algorithm on a digital NCAT phantom and a head-and-neck patient case. The performance under low mAs is also validated using a physical Catphan phantom and a head-and-neck Rando phantom. It is found that 40 x-ray projections are sufficient to reconstruct CBCT images with satisfactory quality for IGRT patient alignment purpose. Phantom experiments indicated that CBCT images can be successfully reconstructed with our algorithm under as low as 0.1 mAs/projection level. Comparing with currently widely used full-fan head-and-neck scanning protocol of about 360 projections with 0.4 mAs/projection, it is estimated that an overall 36 times dose reduction has been achieved with our algorithm. Moreover, the reconstruction time is about 130 sec on an NVIDIA Tesla C1060 GPU card, which is estimated ~100 times faster than similar iterative reconstruction approaches.Comment: 20 pages, 10 figures, Paper was revised and more testing cases were added

3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

Recently we have developed an algorithm for reconstructing volumetric images and extracting 3D tumor motion information from a single x-ray projection. We have demonstrated its feasibility using a digital respiratory phantom with regular breathing patterns. In this work, we present a detailed description and a comprehensive evaluation of the improved algorithm. The algorithm was improved by incorporating respiratory motion prediction. The accuracy and efficiency were then evaluated on 1) a digital respiratory phantom, 2) a physical respiratory phantom, and 3) five lung cancer patients. These evaluation cases include both regular and irregular breathing patterns that are different from the training dataset. For the digital respiratory phantom with regular and irregular breathing, the average 3D tumor localization error is less than 1 mm. On an NVIDIA Tesla C1060 GPU card, the average computation time for 3D tumor localization from each projection ranges between 0.19 and 0.26 seconds, for both regular and irregular breathing, which is about a 10% improvement over previously reported results. For the physical respiratory phantom, an average tumor localization error below 1 mm was achieved with an average computation time of 0.13 and 0.16 seconds on the same GPU card, for regular and irregular breathing, respectively. For the five lung cancer patients, the average tumor localization error is below 2 mm in both the axial and tangential directions. The average computation time on the same GPU card ranges between 0.26 and 0.34 seconds

HST and Spitzer Observations of the HD 207129 Debris Ring

A debris ring around the star HD 207129 (G0V; d = 16.0 pc) has been imaged in scattered visible light with the ACS coronagraph on the Hubble Space Telescope and in thermal emission using MIPS on the Spitzer Space Telescope at 70 microns (resolved) and 160 microns (unresolved). Spitzer IRS (7-35 microns) and MIPS (55-90 microns) spectrographs measured disk emission at >28 microns. In the HST image the disk appears as a ~30 AU wide ring with a mean radius of ~163 AU and is inclined by 60 degrees from pole-on. At 70 microns it appears partially resolved and is elongated in the same direction and with nearly the same size as seen with HST in scattered light. At 0.6 microns the ring shows no significant brightness asymmetry, implying little or no forward scattering by its constituent dust. With a mean surface brightness of V=23.7 mag per square arcsec, it is the faintest disk imaged to date in scattered light.Comment: 28 pages, 8 figure

The Solar Neighborhood. XXVI. AP Col: The Closest (8.4 pc) Pre-Main-Sequence Star

We present the results of a multi-technique investigation of the M4.5Ve flare star AP Col, which we discover to be the nearest pre-main-sequence star. These include astrometric data from the CTIO 0.9m, from which we derive a proper motion of 342.0+/-0.5 mas yr^-1, a trigonometric parallax of 119.21+/-0.98 mas (8.39+/-0.07 pc), and photometry and photometric variability at optical wavelengths. We also provide spectroscopic data, including radial velocity (22.4+/-0.3 km s^-1), lithium Equivalent Width (EW) (0.28+/-0.02 A), H-alpha EW (-6.0 to -35 A), {\it vsini} (11+/-1 km s^-1), and gravity indicators from the Siding Spring 2.3-m WiFeS, Lick 3-m Hamilton echelle, and Keck-I HIRES echelle spectrographs. The combined observations demonstrate that AP Col is the closer of only two known systems within 10 pc of the Sun younger than 100 Myr. Given its space motion and apparent age of 12-50 Myr, AP Col is likely a member of the recently proposed ~40 Myr old Argus/IC 2391 association.Comment: 31 pages, 11 figure