Electrothermal feedback in superconducting nanowire single-photon detectors

We investigate the role of electrothermal feedback in the operation of superconducting nanowire single-photon detectors (SNSPDs). It is found that the desired mode of operation for SNSPDs is only achieved if this feedback is unstable, which happens naturally through the slow electrical response associated with their relatively large kinetic inductance. If this response is sped up in an effort to increase the device count rate, the electrothermal feedback becomes stable and results in an effect known as latching, where the device is locked in a resistive state and can no longer detect photons. We present a set of experiments which elucidate this effect, and a simple model which quantitatively explains the results

The new radiation-hard optical links for the ATLAS pixel detector

The ATLAS detector is currently being upgraded with a new layer of pixel based charged particle tracking and a new arrangement of the services for the pixel detector. These upgrades require the replacement of the opto-boards previously used by the pixel detector. In this report we give details on the design and production of the new opto-boards.Comment: Presentation at the DPF 2013 Meeting of the American Physical Society Division of Particles and Fields, Santa Cruz, California, August 13-17, 201

Differential neuroproteomic and systems biology analysis of spinal cord injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets

Electron-Energy Loss of Ultraviolet Plasmonic Modes in Aluminum Nanodisks

We theoretically investigated electron energy loss spectroscopy (EELS) of ultraviolet surface plasmon modes in aluminum nanodisks. Using full-wave simulations, we studied the impact of diameter on the resonant modes of the nanodisks. We found that the mode behavior can be separately classified for two distinct cases: (1) flat nanodisks where the diameter is much less than the thickness; and (2) thick nanodisks where the diameter is comparable to the thickness. While the multipolar edge modes and breathing modes of flat nanostructures have previously been interpreted using intuitive, analytical models based on surface plasmon polariton (SPP) modes of a thin-film stack, it has been found that the true dispersion relation of the multipolar edge modes deviates significantly from the SPP dispersion relation. Here, we developed a modified intuitive model that uses effective wavelength theory to accurately model this dispersion relation with significantly less computational overhead compared to full-wave electromagnetic simulations. However, for the case of thick nanodisks, this effective wavelength theory breaks down, and such intuitive models are no longer viable. We found that this is because some modes of the thick nanodisks carry a polar (i.e. out of the substrate plane, or along the electron beam direction) dependence and cannot be simply categorized as radial breathing modes or angular (azimuthal) multipolar edge modes. This polar dependence leads to radiative losses, motivating the use of simultaneous EELS and cathodoluminescence measurements when experimentally investigating the complex mode behavior of thick nanostructures

Excitations and benchmark ensemble density functional theory for two electrons

A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.Comment: 15 pages, supplemental material pd

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces

Mean Field Theory of the Localization Transition

A mean field theory of the localization transition for bosonic systems is developed. Localization is shown to be sensitive to the distribution of the random site energies. It occurs in the presence of a triangular distribution, but not a uniform one. The inverse participation ratio, the single site Green's function, the superfluid order parameter and the corresponding susceptibility are calculated, and the appropriate exponents determined. All of these quantities indicate the presence of a new phase, which can be identified as the {\it Bose-glass}.Comment: 4 pages, Revtex, 2 figures appende

Tolerance on sphere radius for the calibration of the transfer function of coherence scanning interferometry

Although coherence scanning interferometry (CSI) commonly achieves a sub-nanometre noise level in surface topography measurement, the absolute accuracy is difficult to determine when measuring a surface that contains varying local slope angles and curvatures. Recent research has shown that it is possible to use a single sphere with a radius much greater than the source wavelength to calibrate the three-dimensional transfer function of a CSI system. A major requirement is the accurate knowledge of the sphere radius, but the three-dimensional measurement of a sphere with nanometre level uncertainty is a highly challenging metrology problem, and is not currently feasible. Perfect spheres do not exist and every measurement has uncertainty. Without having a quantitative understanding of the tolerance of the sphere radius, the calibration method cannot be used confidently for calibration of the transfer function of a CSI system that may be used in research laboratories or industry. In this paper, the effects of the tolerance of the radius of the calibration sphere on surface topography measurements are quantitatively analysed through a computational approach. CSI measurements of spherical, sinusoidal and rough surfaces are investigated in the presence of various degrees of radius error. A lookup table that relates the surface height error as a function of the radius error and surface slope angle is provided. The users may estimate the required tolerances of the sphere radius for their specific surface measurements if this calibration approach is used. The output of this paper provides a feasibility analysis for this calibration method for further development and applications

Nanostructured-membrane electron phase plates

Electron beams can acquire designed phase modulations by passing through nanostructured material phase plates. These phase modulations enable electron wavefront shaping and benefit electron microscopy, spectroscopy, lithography, and interferometry. However, in the fabrication of electron phase plates, the typically used focused-ion-beam-milling method limits the fabrication throughput and hence the active area of the phase plates. Here, we fabricated large-area electron phase plates with electron-beam lithography and reactive-ion-etching. The phase plates are characterized by electron diffraction in transmission electron microscopes with various electron energies, as well as diffractive imaging in a scanning electron microscope. We found the phase plates could produce a null in the center of the bright-field based on coherent interference of diffractive beams. Our work adds capabilities to the fabrication of electron phase plates. The nullification of the direct beam and the tunable diffraction efficiency demonstrated here also paves the way towards novel dark-field electron-microscopy techniques and tunable electron phase plates