Wavefront shaping concepts for application in optical coherence tomography - a review

Optical coherence tomography (OCT) enables three-dimensional imaging with resolution on the micrometer scale. The technique relies on the time-of-flight gated detection of light scattered from a sample and has received enormous interest in applications as versatile as non-destructive testing, metrology and non-invasive medical diagnostics. However, in strongly scattering media such as biological tissue, the penetration depth and imaging resolution are limited. Combining OCT imaging with wavefront shaping approaches significantly leverages the capabilities of the technique by controlling the scattered light field through manipulation of the field incident on the sample. This article reviews the main concepts developed so far in the field and discusses the latest results achieved with a focus on signal enhancement and imaging. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Double Interferometer Design for Independent Wavefront Manipulation in Spectral Domain Optical Coherence Tomography

Spectral domain optical coherence tomography (SD-OCT) is a highly versatile method which allows for three dimensional optical imaging in scattering media. A number of recent publications demonstrated the technique to benefit from structured illumination and beam shaping approaches, e.g. to enhance the signal-to-noise ratio or the penetration depth with samples such as biological tissue. We present a compact and easy to implement design for independent wavefront manipulation and beam shaping at the reference and sample arm of the interferometric OCT device. The design requires a single spatial light modulator and can be integrated to existing free space SD-OCT systems by modifying the source arm only. We provide analytical and numerical discussion of the presented design as well as experimental data confirming the theoretical analysis. The system is highly versatile and lends itself for applications where independent phase or wavefront control is required. We demonstrate the system to be used for wavefront sensorless adaptive optics as well as for iterative optical wavefront shaping for OCT signal enhancement in strongly scattering media. © 2019, The Author(s)

Emergent statistical mechanics from properties of disordered random matrix product states

The study of generic properties of quantum states has led to an abundance of insightful results. A meaningful set of states that can be efficiently prepared in experiments are ground states of gapped local Hamiltonians, which are well approximated by matrix product states. In this work, we introduce a picture of generic states within the trivial phase of matter with respect to their non-equilibrium and entropic properties: We do so by rigorously exploring non-translation-invariant matrix product states drawn from a local i.i.d. Haar-measure. We arrive at these results by exploiting techniques for computing moments of random unitary matrices and by exploiting a mapping to partition functions of classical statistical models, a method that has lead to valuable insights on local random quantum circuits. Specifically, we prove that such disordered random matrix product states equilibrate exponentially well with overwhelming probability under the time evolution of Hamiltonians featuring a non-degenerate spectrum. Moreover, we prove two results about the entanglement Renyi entropy: The entropy with respect to sufficiently disconnected subsystems is generically extensive in the system-size, and for small connected systems the entropy is almost maximal for sufficiently large bond dimensions.Comment: 11 page

An Aliasing-Free Hybrid Digital-Analog Polyphonic Synthesizer

Analog subtractive synthesizers are generally considered to provide superior sound quality compared to digital emulations. However, analog circuitry requires calibration and suffers from aging, temperature instability, and limited flexibility in generating a wide variety of waveforms. Digital synthesis can mitigate many of these drawbacks, but generating arbitrary aliasing-free waveforms remains challenging. In this paper, we present the +-synth, a hybrid digital-analog eight-voice polyphonic synthesizer prototype that combines the best of both worlds. At the heart of the synthesizer is the big Fourier oscillator (BFO), a novel digital very-large scale integration (VLSI) design that utilizes additive synthesis to generate a wide variety of aliasing-free waveforms. Each BFO produces two voices, using four oscillators per voice. A single oscillator can generate up to 1024 freely configurable partials (harmonic or inharmonic), which are calculated using coordinate rotation digital computers (CORDICs). The BFOs were fabricated as 65nm CMOS custom application-specific integrated circuits (ASICs), which are integrated in the +-synth to simultaneously generate up to 32768 partials. Four 24-bit 96kHz stereo DACs then convert the eight voices into the analog domain, followed by digitally controlled analog low-pass filtering and amplification. Measurement results of the +-synth prototype demonstrate high fidelity and low latency.Comment: Presented at DAFx2

Sky View Factor footprints for urban climate modeling

Urban morphology is an important multidimensional variable to consider in climate modeling and observations, because it significantly drives the local and micro-scale climatic variability in cities. Urban form can be described through urban canopy parameters (UCPs) that resolve the spatial heterogeneity of cities by specifying the 3-dimensional geometry, arrangement, and materials of urban features. The sky view factor (SVF) is a dimension-reduced UCP capturing 3-dimensional form through horizon limitation fractions. SVF has become a popular metric to parameterize urban morphology, but current approaches are difficult to scale up to global coverage. This study introduces a Big-Data approach to calculate SVFs for urban areas from Google Street View (GSV). 90-degree field-of-view GSV photos are retrieved and converted into hemispherical views through equiangular projection. The fisheyes are segmented into sky and non-sky pixels using image processing, and the SVF is calculated using an annulus method. Results are compared to SVFs retrieved from GSV images segmented using deep learning. SVF footprints are presented for urban areas around the world tallying 15,938,172 GSV locations. Two use cases are introduced: (1) an evaluation of a Google Earth Engine classified Local Climate Zone map for Singapore; (2) hourly sun duration maps for New York and San Francisco

Modelling of the temperature distribution of spot-weldable composite/metal joints

Resistance spot welding is the most economical joining method for the production of automotive steel bodies. In modern car body construction, however, its future applicability is limited due to the growing mix of materials in multi-material design. In response to increasing weight reduction requirements to protect the environment and natural resources, lightweight materials, and fibre-reinforced plastics (FRP) in particular, are more and more used in modern vehicle bodies. To facilitate the future joining of FRP/steel structures with resistance spot welding, spot-weldable force-introduction elements may be embedded in the laminate as a joining interface. When welding the so-called inserts, thermal damage to the surrounding polymer should be avoided, as this is the only way to calculate the strength of the joint correctly. For this purpose, the paper presents a numerical model that allows the prediction of the temperature propagation during spot welding of FRP/steel joints with embedded inserts. The simulative approach is subsequently validated by comparison with experimentally determined temperature curves and in doing so, an excellent model prediction can be noted

Complementary tuning of Na+ and K+ channel gating underlies fast and energy-efficient action potentials in GABAergic interneuron axons

Fast-spiking, parvalbumin-expressing GABAergic interneurons (PV+-BCs) express a complex machinery of rapid signaling mechanisms, including specialized voltage-gated ion channels to generate brief action potentials (APs). However, short APs are associated with overlapping Na+ and K+ fluxes and are therefore energetically expensive. How the potentially vicious combination of high AP frequency and inefficient spike generation can be reconciled with limited energy supply is presently unclear. To address this question, we performed direct recordings from the PV+-BC axon, the subcellular structure where active conductances for AP initiation and propagation are located. Surprisingly, the energy required for the AP was, on average, only ∼1.6 times the theoretical minimum. High energy efficiency emerged from the combination of fast inactivation of Na+ channels and delayed activation of Kv3-type K+ channels, which minimized ion flux overlap during APs. Thus, the complementary tuning of axonal Na+ and K+ channel gating optimizes both fast signaling properties and metabolic efficiency. Hu et al. demonstrate that action potentials in parvalbumin-expressing GABAergic interneuron axons are energetically efficient, which is highly unexpected given their brief duration. High energy efficiency emerges from the combination of fast inactivation of voltage-gated Na+ channels and delayed activation of Kv3 channels in the axon

Semi-supervised LC/MS alignment for differential proteomics

Motivation: Mass spectrometry (MS) combined with high-performance liquid chromatography (LC) has received considerable attention for high-throughput analysis of proteomes. Isotopic labeling techniques such as ICAT [5,6] have been successfully applied to derive differential quantitative information for two protein samples, however at the price of significantly increased complexity of the experimental setup. To overcome these limitations, we consider a label-free setting where correspondences between elements of two samples have to be established prior to the comparative analysis. The alignment between samples is achieved by nonlinear robust ridge regression. The correspondence estimates are guided in a semi-supervised fashion by prior information which is derived from sequenced tandem mass spectra. Results: The semi-supervised method for finding correspondences was successfully applied to aligning highly complex protein samples, even if they exhibit large variations due to different biological conditions. A large-scale experiment clearly demonstrates that the proposed method bridges the gap between statistical data analysis and label-free quantitative differential proteomics. Availability: The software will be available on the website Contact: [email protected]

Efficient Unitary Designs with a System-Size Independent Number of Non-Clifford Gates

Many quantum information protocols require the implementation of random unitaries. Because it takes exponential resources to produce Haar-random unitaries drawn from the full n-qubit group, one often resorts to t-designs. Unitary t-designs mimic the Haar-measure up to t-th moments. It is known that Clifford operations can implement at most 3-designs. In this work, we quantify the non-Clifford resources required to break this barrier. We find that it suffices to inject O(t4log2(t)log(1/ε)) many non-Clifford gates into a polynomial-depth random Clifford circuit to obtain an ε-approximate t-design. Strikingly, the number of non-Clifford gates required is independent of the system size – asymptotically, the density of non-Clifford gates is allowed to tend to zero. We also derive novel bounds on the convergence time of random Clifford circuits to the t-th moment of the uniform distribution on the Clifford group. Our proofs exploit a recently developed variant of Schur-Weyl duality for the Clifford group, as well as bounds on restricted spectral gaps of averaging operators