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Auroral emissions are a reflection of magnetospheric processes, and, at Jupiter, it is not entirely certain how the morphology of the UV main emission (ME) varies with magnetospheric compression or the strength of the central current sheet. This work leverages the observations from Juno-UVS to link ME variability with magnetospheric states. Novel arc-detection techniques are used to determine new reference ovals for the ME from perijoves 1 through 54, in both hemispheres, and analyse how the size and shape of the ME vary compared to this reference oval. The morphology and brightness of the ME vary in local time: the dawn-side ME is typically expanded and the dusk-side ME typically contracted compared to the reference oval, and the dusk-side ME being typically twice as bright as the dawn-side ME. Both the northern and southern ME, and the day-side and night-side ME, expand and contract from their reference ovals synchronously, which indicates that the variable size of the ME is caused by a process occurring throughout the jovian magnetosphere. The poleward latitudinal shift of the auroral footprint of Ganymede correlates with the poleward motion of the ME, whereas a similar relation is not present for the footprint of Io. Additionally, the expansion of the ME correlates well with an increase in magnetodisc current. These two results suggest that a changing current-sheet magnetic field is partially responsible for the variable size of the ME. Finally, magnetospheric compression is linked to a global ME contraction and brightening, though this brightening occurs predominantly in the day-side ME. This observation, and the observation that the dusk-side ME is typically brighter than the dawn-side ME, stands in contrast to the modelled and observed behaviour of field-aligned currents and thus weakens the theoretical link between field-aligned currents and the generation of the auroral ME.

Even though research has repeatedly shown that non-cash incentives can be effective, cash incentives are the de facto standard in crowdsourcing contests. In this multi-study research, we quantify ideators' preferences for non-cash incentives and investigate how allowing ideators to self-select their preferred incentive -- offering ideators a choice between cash and non-cash incentives -- affects their creative performance. We further explore whether the market context of the organization hosting the contest -- social (non-profit) or monetary (for-profit) -- moderates incentive preferences and their effectiveness. We find that individuals exhibit heterogeneous incentive preferences and often prefer non-cash incentives, even in for-profit contexts. Offering ideators a choice of incentives can enhance creative performance. Market context moderates the effect of incentives, such that ideators who receive non-cash incentives in for-profit contexts tend to exert less effort. We show that heterogeneity of ideators' preferences (and the ability to satisfy diverse preferences with suitably diverse incentive options) is a critical boundary condition to realizing benefits from offering ideators a choice of incentives. We provide managers with guidance to design effective incentives by improving incentive-preference fit for ideators., Comment: Journal of Management Information Systems, forthcoming 2024

We demonstrate in a {\it proof-of-concept} experiment spectral-domain optical coherence tomography where steering of the optical beam that probes the sample in a transverse scan does not make use of any mechanical element. Steering is done with the help of a spatial light modulator, that introduces a spatially-dependent phase between the two orthogonal polarization components of an optical beam, and some optical elements that control the polarization of light. We demonstrate that making use of the non-mechanical steering system considered here, we can reproduce the main traits of imaging with standard OCT that makes use of mechanical-assisted optical beam steering.

Heat transport in two-dimensions is fundamentally different from that in three dimensions. As a consequence, the thermal properties of 2D materials are of great interest, both from scientific and application point of view. However, few techniques are available for accurate determination of these properties in ultrathin suspended membranes. Here, we present an optomechanical methodology for extracting the thermal expansion coefficient, specific heat and thermal conductivity of ultrathin membranes made of 2H-TaS2, FePS3, polycrystalline silicon, MoS2 and WSe2. The obtained thermal properties are in good agreement with values reported in the literature for the same materials. Our work provides an optomechanical method for determining thermal properties of ultrathin suspended membranes, that are difficult to measure otherwise. It can does provide a route towards improving our understanding of heat transport in the 2D limit and facilitates engineering of 2D structures with dedicated thermal performance., Comment: 14 pages, 10 figures

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 45 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations., Comment: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation

Artificial Intelligence methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new methods, but access to such data is often hindered by the lack of standards for sharing datasets. We brought together community experts in a workshop to develop guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are positive that the MIFA (Metadata, Incentives, Formats, and Accessibility) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high quality training data., Comment: 16 pages, 3 figures

Suspended drums made of 2D materials hold potential for sensing applications. However, the industrialization of these applications is hindered by significant device-to-device variations presumably caused by non-uniform stress distributions induced by the fabrication process. Here we introduce a new methodology to determine the stress distribution from their mechanical resonance frequencies and corresponding mode shapes as measured by a laser Doppler vibrometer (LDV). To avoid limitations posed by the optical resolution of the LDV, we leverage a unique manufacturing process to create ultra-large graphene drums with diameters of up to 1000 um. We solve the inverse problem of a F\"oppl--von K\'arm\'an plate model by an iterative procedure to obtain the stress distribution within the drums from the experimental data. Our results show that the generally used uniform pre-tension assumption overestimates the pre-stress value, exceeding the averaged stress obtained by more than 47%. Moreover, it is is found that the reconstructed stress distributions are bi-axial, which likely originates from the transfer process. The introduced metholodogy allows one to estimate the tension distribution in drum resonators from their mechanical response and thereby paves the way for linking the used fabrication processes to the resulting device performance.

We consider an interferometer based on the concept of induced coherence, where two photons that originate in different second-order nonlinear crystals can interfere. We derive a complementarity relationship that links the first-order coherence between the two interfering photons with a parameter that quantifies the distinguishing information regarding the nonlinear crystal where they originated. We show that the derived relationship goes beyond the single-photon regime and is valid for any photon-flux rate generated. We report experimental results in the low photon-flux regime that confirm the validity of the derived complementarity relationship., Comment: 8 pages, 6 figures

The high susceptibility of ultrathin two-dimensional (2D) material resonators to force and temperature makes them ideal systems for sensing applications and exploring thermomechanical coupling. Although the dynamics of these systems at high stress has been thoroughly investigated, their behavior near the buckling transition has received less attention. Here, we demonstrate that the force sensitivity and frequency tunability of 2D material resonators are significantly enhanced near the buckling bifurcation. This bifurcation is triggered by compressive displacement that we induce via thermal expansion of the devices, while measuring their dynamics via an optomechanical technique. We understand the frequency tuning of the devices through a mechanical buckling model, which allows to extract the central deflection and boundary compressive displacement of the membrane. Surprisingly, we obtain a remarkable enhancement of up to 14x the vibration amplitude attributed to a very low stiffness of the membrane at the buckling transition, as well as a high frequency tunability by temperature of more than 4.02 %/K. The presented results provide insights into the effects of buckling on the dynamics of free-standing 2D materials and thereby open up opportunities for the realization of 2D resonant sensors with buckling-enhanced sensitivity., Comment: 20 pages and 4 figures

Optically-active spin defects in hexagonal boron nitride (hBN) are promising quantum systems for the design of two-dimensional quantum sensing units offering optimal proximity to the sample being probed. In this work, we first demonstrate that the electron spin resonance frequencies of boron vacancy centres (V$_\text{B}^-$) can be detected optically in the limit of few-atomic-layer thick hBN flakes despite the nanoscale proximity of the crystal surface that often leads to a degradation of the stability of solid-state spin defects. We then analyze the variations of the electronic spin properties of V$_\text{B}^-$ centres with the hBN thickness with a focus on (i) the zero-field splitting parameters, (ii) the optically-induced spin polarization rate and (iii) the longitudinal spin relaxation time. This work provides important insights into the properties of V$_\text{B}^-$ centres embedded in ultrathin hBN flakes, which are valuable for future developments of foil-based quantum sensing technologies., Comment: 7 pages, 3 figures

We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e.g., seismic and medical ultrasound), regularization with learned priors, and learned neural surrogates for multiphase flow simulations. By integrating multiple layers of abstraction, our software is designed to be both readable and scalable. This allows researchers to easily formulate their problems in an abstract fashion while exploiting the latest developments in high-performance computing. We illustrate and demonstrate our design principles and their benefits by means of building a scalable prototype for permeability inversion from time-lapse crosswell seismic data, which aside from coupling of wave physics and multiphase flow, involves machine learning.

Until the mid 1960s, the UK experienced regular measles epidemics, with the vast majority of children being infected in early childhood. The introduction of a measles vaccine substantially reduced its incidence. The first part of this paper examines the long-term human capital and health effects of this change in the early childhood disease environment. The second part investigates interactions between the vaccination campaign and individuals' endowments as captured using molecular genetic data, shedding light on complementarities between public health investments and individual endowments. We use two identification approaches, based on the nationwide introduction of the vaccine in 1968 and local vaccination trials in 1966. Our results show that exposure to the vaccination in early childhood positively affects adult height, but only among those with high genetic endowments for height. We find no effects on years of education; neither a direct effect, nor evidence of complementarities.

Maternal sugar consumption in utero may have a variety of effects on offspring. We exploit the abolishment of the rationing of sweet confectionery in the UK on April 24, 1949, and its subsequent reintroduction some months later, in an era of otherwise uninterrupted rationing of confectionery (1942-1953), sugar (1940-1953) and many other foods, and we consider effects on late-life cardiovascular disease, BMI, height, type-2 diabetes and the intake of sugar, fat and carbohydrates, as well as cognitive outcomes and birth weight. We use individual-level data from the UK Biobank for cohorts born between April 1947-May 1952. We also explore whether one's genetic "predisposition" to the outcome can moderate the effects of prenatal sugar exposure. We find that prenatal exposure to derationing increases education and reduces BMI and sugar consumption at higher ages, in line with the "developmental origins" explanatory framework, and that the sugar effects are stronger for those who are genetically "predisposed" to sugar consumption.

Microphones exploit the motion of suspended membranes to detect sound waves. Since the microphone performance can be improved by reducing the thickness and mass of its sensing membrane, graphene-based microphones are expected to outperform state-of-the-art microelectromechanical (MEMS) microphones and allow further miniaturization of the device. Here, we present a laser vibrometry study of the acoustic response of suspended multilayer graphene membranes for microphone applications. We address performance parameters relevant for acoustic sensing, including mechanical sensitivity, limit of detection and nonlinear distortion, and discuss the trade-offs and limitations in the design of graphene microphones. We demonstrate superior mechanical sensitivities of the graphene membranes, reaching more than 2 orders of magnitude higher compliances than commercial MEMS devices, and report a limit of detection as low as 15 dBSPL, which is 10 - 15 dB lower than that featured by current MEMS microphones., Comment: 34 pages, 6 figures, 7 supplementary figures

Conoscopic interferometry is a promising detection technique for ultrafast acoustics. By focusing a probe beam through a birefringent crystal before passing it through a polarizer, conoscopic interferences sculpt the spatial profile of the beam. The use of these patterns for acoustic wave detection revealed a higher detection sensitivity over existing techniques, such as reflectometry and beam distortion detection. However, the physical origin of the increased sensitivity is unknown. In this work, we present a model, describing the sensitivity behaviour of conoscopic interferometry with respect to the quarter-wave plate orientation and the diaphragm aperture, which is validated experimentally. Using the model, we optimize the detection sensitivity of conoscopic interferometry. We obtain a maximal sensitivity of detection when placing the diaphragm edge on the dark fringes of the conoscopic interference patterns. In the configurations studied in this work, conoscopic interferometry can be 8x more sensitive to acoustic waves than beam distortion detection.

We report successful incorporation of an ensemble of G centers in silicon-on-insulator (SOI) microrings using ion implantation and conventional nanofabrication. The coupling between the emitters and the resonant modes of the microrings is studied using continuous-wave and time-resolved microphotoluminescence (PL) experiments. We observe the resonant modes of the microrings on PL spectra, on the wide spectral range that is covered by G centers emission. By finely tuning the size of the microrings, we match their zero-phonon line at 1278 nm with a resonant mode of quality factor around 3000 and volume 7.2 (lambda over n)^3. The zero-phonon line intensity is enhanced by a factor of 5, both in continuous-wave and time-resolved measurements. This is attributed to the Purcell enhancement of zero-phonon spontaneous emission into the resonant mode and quantitatively understood considering the distribution of the G centers dipoles. Despite the enhancement of the zero-phonon emission, we do not observe any sizeable decrease of the average lifetime of the G centers, which points at a low radiative yield (<10%). We reveal the detrimental impact of parasitic defects in heavily implanted silicon, and discuss the perspectives for quantum electrodynamics experiments with individual color centers in lightly implanted SOI rings. Our results provide key information for the development of deterministic single photon sources for integrated quantum photonics., Comment: 24 pages, 7 figures, submitted to an international journal with peer review

We theoretically and experimentally study the precision of a quantum clock near zero temperature, explicitly accounting for the effect of continuous measurement. The clock is created by a superconducting transmon qubit dispersively coupled to an open coplanar resonator. The cavity and qubit are driven by coherent fields, and the cavity output is monitored with a quantum-noise-limited amplifier. When the continuous measurement is weak, it induces persistent coherent oscillations (with fluctuating periods) in the conditional moments of the qubit's energy probability distribution, which are manifest in the output of the resonator. On the other hand, strong continuous measurement leads to an incoherent cycle of quantum jumps. We theoretically find an equality for the precision of the clock in each regime. Independently from the equalities, we derive a kinetic uncertainty relation for the precision, and find that both equalities satisfy this uncertainty relation. Finally, we experimentally verify that our quantum clock obeys the kinetic uncertainty relation for the precision, thus making an explicit link between the (kinetic) thermodynamic behavior of the clock and its precision, and achieving an experimental test of a kinetic uncertainty relation in the quantum domain., Comment: arXiv admin note: text overlap with arXiv:2109.05390

Canonical discrete quantum error correction (DQEC) schemes use projective von Neumann measurements on stabilizers to discretize the error syndromes into a finite set, and fast unitary gates are applied to recover the corrupted information. Quantum error correction (QEC) based on continuous measurement, known as continuous quantum error correction (CQEC), in principle, can be executed faster than DQEC and can also be resource efficient. However, CQEC requires meticulous filtering of noisy continuous measurement data to reliably extract error syndromes on the basis of which errors could be detected. In this paper, we show that by constructing a measurement-based estimator (MBE) of the logical qubit to be protected, which is driven by the noisy continuous measurement currents of the stabilizers, it is possible to accurately track the errors occurring on the physical qubits in real time. We use this MBE to develop a continuous quantum error correction (MBE-CQEC) scheme that can protect the logical qubit to a high degree, surpassing the performance of DQEC, and also allows QEC to be conducted either immediately or in delayed time with instantaneous feedbacks., Comment: 10 pages, 4 figures, journal article

The objective of the proposed MAQRO mission is to harness space for achieving long free-fall times, extreme vacuum, nano-gravity, and cryogenic temperatures to test the foundations of physics in macroscopic quantum experiments. This will result in the development of novel quantum sensors and a means to probe the foundations of quantum physics at the interface with gravity. Earlier studies showed that the proposal is feasible but that several critical challenges remain, and key technologies need to be developed. These new technologies will open up the potential for achieving additional science objectives. The proposed research campaign aims to advance the state of the art and to perform the first macroscopic quantum experiments in space. Experiments on the ground, in micro-gravity, and in space will drive the proposed research campaign during the current decade to enable the implementation of MAQRO within the subsequent decade., Comment: 9 pages, 2 figures, submitted as a Research Campaign Whitepaper for the BPS2023 Decadal Survey

We continuously interact with computerized systems to achieve goals and perform tasks in our personal and professional lives. Therefore, the ability to program such systems is a skill needed by everyone. Consequently, computational thinking skills are essential for everyone, which creates a challenge for the educational system to teach these skills at scale and allow students to practice these skills. To address this challenge, we present a novel approach to providing formative feedback to students on programming assignments. Our approach uses dynamic evaluation to trace intermediate results generated by student's code and compares them to the reference implementation provided by their teachers. We have implemented this method as a Python library and demonstrate its use to give students relevant feedback on their work while allowing teachers to challenge their students' computational thinking skills.

In wireless networks, an essential step for precise range-based localization is the high-resolution estimation of multipath channel delays. The resolution of traditional delay estimation algorithms is inversely proportional to the bandwidth of the training signals used for channel probing. Considering that typical training signals have limited bandwidth, delay estimation using these algorithms often leads to poor localization performance. To mitigate these constraints, we exploit the multiband and carrier frequency switching capabilities of wireless transceivers and propose to acquire channel state information (CSI) in multiple bands spread over a large frequency aperture. The data model of the acquired measurements has a multiple shift-invariance structure, and we use this property to develop a high-resolution delay estimation algorithm. We derive the Cram\'er-Rao Bound (CRB) for the data model and perform numerical simulations of the algorithm using system parameters of the emerging IEEE 802.11be standard. Simulations show that the algorithm is asymptotically efficient and converges to the CRB. To validate modeling assumptions, we test the algorithm using channel measurements acquired in real indoor scenarios. From these results, it is seen that delays (ranges) estimated from multiband CSI with a total bandwidth of 320 MHz show an average RMSE of less than 0.3 ns (10 cm) in 90% of the cases., Comment: 16 pages, 17 figures, 2 tables, journal

Although 2D materials hold great potential for next-generation pressure sensors, recent studies revealed that gases permeate along the membrane-surface interface that is only weakly bound by van der Waals interactions, necessitating additional sealing procedures. In this work, we demonstrate the use of free-standing complex oxides as self-sealing membranes that allow the reference cavity of pressure sensors to be sealed by a simple anneal. To test the hermeticity, we study the gas permeation time constants in nano-mechanical resonators made from SrRuO3 and SrTiO3 membranes suspended over SiO2/Si cavities which show an improvement up to 4 orders of magnitude in the permeation time constant after annealing the devices for 15 minutes. Similar devices fabricated on Si3N4/Si do not show such improvements, suggesting that the adhesion increase over SiO2 is mediated by oxygen bonds that are formed at the SiO2/complex oxide interface during the self-sealing anneal. We confirm the enhancement of adhesion by picosecond ultrasonics measurements which show an increase in the interfacial stiffness by 70% after annealing. Since it is straigthforward to apply, the presented self-sealing method is thus a promising route toward realizing ultrathin hermetic pressure sensors., Comment: 7 pages, 5 figures

Optical coherence tomography (OCT) is a 3D imaging technique that was introduced in 1991 [Science 254, 1178 (1991); Applied Optics 31, 919 (1992)]. Since 2018 there has been growing interest in a new type of OCT scheme based on the use of so-called nonlinear interferometers, interferometers that contain optical parametric amplifiers. Some of these OCT schemes are based on the idea of induced coherence [Physical Review A 97, 023824 (2018)], while others make use of an SU(1,1) interferometer [Quantum Science and Technology 3 025008 (2018)]. What are the differences and similarities between the output signals measured in standard OCT and in these new OCT schemes? Are there any differences between OCT schemes based on induced coherence and on an SU(1,1) interferometer? Differences can unveil potential advantages of OCT based on nonlinear interferometers when compared with conventional OCT schemes. Similarities might benefit the schemes based on nonlinear interferometers from the wealth of research and technology related to conventional OCT schemes. In all cases we will consider the scheme where the optical sectioning of the sample is obtained by measuring the output signal spectrum (spectral, or Fourier-domain OCT), since it shows better performance in terms of speed and sensitivity than its counterpart time-domain OCT.

Closed loop quantum control uses measurement to control the dynamics of a quantum system to achieve either a desired target state or target dynamics. In the case when the quantum Hamiltonian is quadratic in ${x}$ and ${p}$, there are known optimal control techniques to drive the dynamics towards particular states e.g. the ground state. However, for nonlinear Hamiltonians such control techniques often fail. We apply Deep Reinforcement Learning (DRL), where an artificial neural agent explores and learns to control the quantum evolution of a highly non-linear system (double well), driving the system towards the ground state with high fidelity. We consider a DRL strategy which is particularly motivated by experiment where the quantum system is continuously but weakly measured. This measurement is then fed back to the neural agent and used for training. We show that the DRL can effectively learn counter-intuitive strategies to cool the system to a nearly-pure `cat' state which has a high overlap fidelity with the true ground state., Comment: 5 pages, 2 figures, journal article with supplementary materials

Silicon p-n junction diodes emit low-intensity, broad-spectrum light near 1120 nm in forward bias and between 400-900 nm in reverse bias (avalanche). For the first time, we experimentally achieve optical absorption sensing of pigment in solution with silicon micro LEDs designed in a standard silicon-on-insulator CMOS technology. By driving a single LED in both forward and avalanche modes of operation, we steer its electroluminescent spectrum between visible and near-infrared (NIR). We then characterize the vertical optical transmission of both visible and NIR light from the LED through the same micro-droplet specimen to a vertically mounted discrete silicon photodiode. The effective absorption coefficient of carmine solution in glycerol at varying concentrations were extracted from the color ratio in optical coupling. By computing the LED-specific molar absorption coefficient of carmine, we estimate the concentration (0.040 mo/L) and validate the same with a commercial spectrophotometer (0.030 mol/L ). With a maximum observed sensitivity of 1260 /cm /mol L, the sensor is a significant step forward towards low-cost CMOS-integrated optical sensors with silicon LED as the light source intended for biochemical analyses in food sector and plant/human health., Comment: IEEE Sensors 2020, 4 pages, 5 figures (https://ieeexplore.ieee.org/document/9278700)

The presence of rich scattering in indoor and urban radio propagation scenarios may cause a high arrival density of multipath components (MPCs). Often the MPCs arrive in clusters at the receiver, where MPCs within one cluster have similar angles and delays. The MPCs arriving within a single cluster are typically unresolvable in the delay domain. In this paper, we analyze the effects of unresolved MPCs on the bias of the delay estimation with a multiband subspace fitting algorithm. We treat the unresolved MPCs as a model error that results in perturbed subspace estimation. Starting from the first-order approximation of the perturbations, we derive the bias of the delay estimate of the line-of-sight (LOS) component. We show that it depends on the power and relative delay of the unresolved MPCs in the first cluster compared to the LOS component. Numerical experiments are included to show that the derived expression for the bias well describes the effects of unresolved MPCs on the delay estimation., Comment: 6 pages, 4 figures, 54rd Asilomar Conference on Signals, Systems, and Computers 2020

We report the detection of individual emitters in silicon belonging to seven different families of optically-active point defects. These fluorescent centers are created by carbon implantation of a commercial silicon-on-insulator wafer usually employed for integrated photonics. Single photon emission is demonstrated over the [1.1,1.55]-$\mu$m range, spanning the O- and C-telecom bands. We analyse their photoluminescence spectrum, dipolar emission and optical relaxation dynamics at 10K. For a specific family, we show a constant emission intensity at saturation from 10K to temperatures well above the 77K-liquid nitrogen temperature. Given the advanced control over nanofabrication and integration in silicon, these novel artificial atoms are promising candidates for Si-based quantum technologies.

This paper proposes a new method that combines check-pointing methods with error-controlled lossy compression for large-scale high-performance Full-Waveform Inversion (FWI), an inverse problem commonly used in geophysical exploration. This combination can significantly reduce data movement, allowing a reduction in run time as well as peak memory. In the Exascale computing era, frequent data transfer (e.g., memory bandwidth, PCIe bandwidth for GPUs, or network) is the performance bottleneck rather than the peak FLOPS of the processing unit. Like many other adjoint-based optimization problems, FWI is costly in terms of the number of floating-point operations, large memory footprint during backpropagation, and data transfer overheads. Past work for adjoint methods has developed checkpointing methods that reduce the peak memory requirements during backpropagation at the cost of additional floating-point computations. Combining this traditional checkpointing with error-controlled lossy compression, we explore the three-way tradeoff between memory, precision, and time to solution. We investigate how approximation errors introduced by lossy compression of the forward solution impact the objective function gradient and final inverted solution. Empirical results from these numerical experiments indicate that high lossy-compression rates (compression factors ranging up to 100) have a relatively minor impact on convergence rates and the quality of the final solution.

The unique properties and atomic thickness of two-dimensional (2D) materials enable smaller and better nanoelectromechanical sensors with novel functionalities. During the last decade, many studies have successfully shown the feasibility of using suspended membranes of 2D materials in pressure sensors, microphones, accelerometers, and mass and gas sensors. In this review, we explain the different sensing concepts and give an overview of the relevant material properties, fabrication routes, and device operation principles. Finally, we discuss sensor readout and integration methods and provide comparisons against the state of the art to show both the challenges and promises of 2D material-based nanoelectromechanical sensing., Comment: Review paper

The concept of an embodied intelligent agent is a key concept in modern artificial intelligence and robotics. Physically, an agent is an open system embedded in an environment that it interacts with through sensors and actuators. It contains a learning algorithm that correlates the sensor and actuator results by learning features about its environment. In this article we present a simple optical agent that uses light to probe and learn components of its environment. In our scenario, the quantum agent outperforms a classical agent: The quantum agent probes the world using single photon pulses, where its classical counterpart uses a weak coherent state with an average photon number equal to one. We analyze the thermodynamic behavior of both agents, showing that improving the agent's estimate of the world corresponds to an increase in average work done on the sensor by the actuator pulse. Thus, our model provides a useful toy model for studying the interface between machine learning, optics, and statistical thermodynamics., Comment: 8 pages, 4 figures

We demonstrate optical coherence tomography based on an SU(1,1) nonlinear interferometer with high-gain parametric down-conversion. For imaging and sensing applications, this scheme promises to outperform previous experiments working at low parametric gain, since higher photon fluxes provide lower integration times for obtaining high-quality images. In this way one can avoid using single-photon detectors or CCD cameras with very high sensitivities, and standard spectrometers can be used instead. Other advantages are: higher sensitivity to small loss and amplification before detection, so that the detected light power considerably exceeds the probing one.

There is renewed interest in using the coherence between beams generated in separate down-converter sources for new applications in imaging, spectroscopy, microscopy and optical coherence tomography (OCT). These schemes make use of continuous wave (CW) pumping in the low parametric gain regime, which produces frequency correlations, and frequency entanglement, between signal-idler pairs generated in each single source. But can induced coherence still be observed if there is no frequency correlation, so the biphoton wavefunction is factorable? We will show that this is the case, and this might be an advantage for OCT applications. High axial resolution requires a large bandwidth. For CW pumping this requires the use of short nonlinear crystals. This is detrimental since short crystals generate small photon fluxes. We show that the use of ultrashort pump pulses allows improving axial resolution even for long crystal that produce higher photon fluxes.

In this paper, we focus on the problem of blind joint calibration of multiband transceivers and time-delay (TD) estimation of multipath channels. We show that this problem can be formulated as a particular case of covariance matching. Although this problem is severely ill-posed, prior information about radio-frequency chain distortions and multipath channel sparsity is used for regularization. This approach leads to a biconvex optimization problem, which is formulated as a rank-constrained linear system and solved by a simple group Lasso algorithm.Numerical experiments show that the proposed algorithm provides better calibration and higher resolution for TD estimation than current state-of-the-art methods., Comment: 4 pages, 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020)

Given its unrivaled potential of integration and scalability, silicon is likely to become a key platform for large-scale quantum technologies. Individual electron-encoded artificial atoms either formed by impurities or quantum dots have emerged as a promising solution for silicon-based integrated quantum circuits. However, single qubits featuring an optical interface needed for large-distance exchange of information have not yet been isolated in such a prevailing semiconductor. Here we show the isolation of single optically-active point defects in a commercial silicon-on-insulator wafer implanted with carbon atoms. These artificial atoms exhibit a bright, linearly polarized single-photon emission at telecom wavelengths suitable for long-distance propagation in optical fibers. Our results demonstrate that despite its small bandgap (~ 1.1 eV) a priori unfavorable towards such observation, silicon can accommodate point defects optically isolable at single scale, like in wide-bandgap semiconductors. This work opens numerous perspectives for silicon-based quantum technologies, from integrated quantum photonics to quantum communications and metrology.

The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multibranch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shift-invariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cramer Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT., Comment: 4 pages, 6 figures, (ACSSC 2019) 2019 Asilomar Conference on Signals, Systems, and Computers

Recent experiments have shown surprisingly large thermal time constants in suspended graphene ranging from 10 to 100 ns in drums with a diameter ranging from 2 to 7 microns. The large time constants and their scaling with diameter points towards a thermal resistance at the edge of the drum. However, an explanation of the microscopic origin of this resistance is lacking. Here, we show how phonon scattering at a kink in the graphene, e.g. formed by sidewall adhesion at the edge of the suspended membrane, can cause a large thermal time constant. This kink strongly limits the fraction of flexural phonons that cross the suspended graphene edge, which causes a thermal interface resistance at its boundary. Our model predicts thermal time constants that are of the same order of magnitude as experimental data, and shows a similar dependence on the circumference. Furthermore, the model predicts the relative in-plane and out-of-plane phonon contributions to graphene's thermal expansion force, in agreement with experiments. We thus show, that in contrast to conventional thermal (Kapitza) resistance which occurs between two different materials, in 2D materials another type of thermal interface resistance can be geometrically induced in a single material.

Recent theory has predicted large temperature differences between the in-plane (LA and TA) and out-of-plane (ZA) acoustic phonon baths in locally-heated suspended graphene. To verify these predictions, and their implications for understanding the nonequilibrium thermodynamics of 2D materials, experimental techniques are needed. Here, we present a method to determine the acoustic phonon bath temperatures from the frequency-dependent mechanical response of suspended graphene to a power modulated laser. The mechanical motion reveals two counteracting contributions to the thermal expansion force, that are attributed to fast positive thermal expansion by the in-plane phonons and slower negative thermal expansion by the out-of-plane phonons. The magnitude of the two forces reveals that the in-plane and flexural acoustic phonons are at very different temperatures in the steady-state, with typically observed values of the ratio $\Delta T_{\mathrm{LA+TA}}/\Delta T_{\mathrm{ZA}}$ between 0.2 and 3.7. These deviations from the generally used local thermal equilibrium assumption ($\Delta T_{\mathrm{LA+TA}}=\Delta T_{\mathrm{ZA}}$) can affect the experimental analysis of thermal properties of 2D materials.

We evaluate the performance of Devito, a domain specific language (DSL) for finite differences on Arm ThunderX2 processors. Experiments with two common seismic computational kernels demonstrate that Arm processors can deliver competitive performance compared to other Intel Xeon processors., Comment: 2 pages, one figure, 2 tables

In their IZA Discussion Paper 10247, Johansson and Lee claim that the main result (Proposition 3) in Abbring and Van den Berg (2003b) does not hold. We show that their claim is incorrect. At a certain point within their line of reasoning, they make a rather basic error while transforming one random variable into another random variable, and this leads them to draw incorrect conclusions. As a result, their paper can be discarded., Comment: 10 pages, IZA Discussion Paper 10248 with new appendix discussing files currently (July 20, 2019) posted on M.J. Lee's web site

Precise understanding of the dynamics of trapped particles is crucial for nascent quantum technologies, including atomic clocks and quantum simulators. Here we present a framework to systematically include quantum effects arising from the mass-energy equivalence in harmonically trapped systems. We find that the mass-energy equivalence leads to squeezing, displacement and frequency changes of harmonic modes associated with different internal energies. The framework predicts new phenomena, notably, the existence of a lower bound to the fractional frequency shift in atomic clocks arising from the interplay between gravitational effects and so-called time dilation shifts. Analogous effects will arise in other trapping potentials, especially in periodic lattices, and may play a role in correlation dynamics and thermalisation process in many-body systems and cold gases., Comment: 4+3.2 pages, 2 figures

Achieving high resolution time-of-arrival (TOA) estimation in multipath propagation scenarios from bandlimited observations of communication signals is challenging because the multipath channel impulse response (CIR) is not bandlimited. Modeling the CIR as a sparse sequence of Diracs, TOA estimation becomes a problem of parametric spectral inference from observed bandlimited signals. To increase resolution without arriving at unrealistic sampling rates, we consider multiband sampling approach, and propose a practical multibranch receiver for the acquisition. The resulting data model exhibits multiple shift invariance structures, and we propose a corresponding multiresolution TOA estimation algorithm based on the ESPRIT algorithm. The performance of the algorithm is compared against the derived Cram\'er Rao Lower Bound, using simulations with standardized ultra-wideband (UWB) channel models. We show that the proposed approach provides high-resolution estimates while reducing spectral occupancy and sampling costs compared to traditional UWB approaches., Comment: 5 pages, 5 figures, conference

Synchronization and ranging in internet of things (IoT) networks are challenging due to the narrowband nature of signals used for communication between IoT nodes. Recently, several estimators for range estimation using phase difference of arrival (PDoA) measurements of narrowband signals have been proposed. However, these estimators are based on data models which do not consider the impact of clock-skew on the range estimation. In this paper, clock-skew and range estimation are studied under a unified framework. We derive a novel and precise data model for PDoA measurements which incorporates the unknown clock-skew effects. We then formulate joint estimation of the clock-skew and range as a two-dimensional (2-D) frequency estimation problem of a single complex sinusoid. Furthermore, we propose: (i) a two-way communication protocol for collecting PDoA measurements and (ii) a weighted least squares (WLS) algorithm for joint estimation of clock-skew and range leveraging the shift invariance property of the measurement data. Finally, through numerical experiments, the performance of the proposed protocol and estimator is compared against the Cramer Rao lower bound demonstrating that the proposed estimator is asymptotically efficient., Comment: 52nd Annual Asilomar Conference on Signals, Systems, and Computers

The fundamental polarization singularities of monochromatic light are normally associated with invariance under coordinated rotations: symmetry operations that rotate the spatial dependence of an electromagnetic field by an angle $\theta$ and its polarization by a multiple $\gamma\theta$ of that angle. These symmetries are generated by mixed angular momenta of the form $J_\gamma = L + \gamma S$ and they generally induce M\"obius-strip topologies, with the coordination parameter $\gamma$ restricted to integer and half-integer values. In this work we construct beams of light that are invariant under coordinated rotations for arbitrary $\gamma$, by exploiting the higher internal symmetry of 'bicircular' superpositions of counter-rotating circularly polarized beams at different frequencies. We show that these beams have the topology of a torus knot, which reflects the subgroup generated by the torus-knot angular momentum $J_\gamma$, and we characterize the resulting optical polarization singularity using third-and higher-order field moment tensors, which we experimentally observe using nonlinear polarization tomography., Comment: Submitted Manuscript, including a subset of the figures from the published Supplementary Information

We introduce Devito, a new domain-specific language for implementing high-performance finite difference partial differential equation solvers. The motivating application is exploration seismology where methods such as Full-Waveform Inversion and Reverse-Time Migration are used to invert terabytes of seismic data to create images of the earth's subsurface. Even using modern supercomputers, it can take weeks to process a single seismic survey and create a useful subsurface image. The computational cost is dominated by the numerical solution of wave equations and their corresponding adjoints. Therefore, a great deal of effort is invested in aggressively optimizing the performance of these wave-equation propagators for different computer architectures. Additionally, the actual set of partial differential equations being solved and their numerical discretization is under constant innovation as increasingly realistic representations of the physics are developed, further ratcheting up the cost of practical solvers. By embedding a domain-specific language within Python and making heavy use of SymPy, a symbolic mathematics library, we make it possible to develop finite difference simulators quickly using a syntax that strongly resembles the mathematics. The Devito compiler reads this code and applies a wide range of analysis to generate highly optimized and parallel code. This approach can reduce the development time of a verified and optimized solver from months to days.