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We present a real-time method for calibrating the frequency of a resonantly driven qubit. The real-time processing capabilities of a controller dynamically compute adaptive probing sequences for qubit-frequency estimation. Each probing time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. We show the algorithm's efficacy by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. By feeding forward the updated qubit frequency, the FPGA-powered control electronics also mitigates non-Markovian noise in the system, which is detrimental to quantum error correction. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms., Comment: main text 10 pages, 4 figures, plus 10 supplementary pages, 6 supplementary figures

Compact laboratory-scale X-ray sources still rely on the same fundamental principles as in the first X-ray tubes developed more than a century ago. In recent years, significant research and development have focused on large-scale X-ray sources such as synchrotrons and free-electron lasers, leading to the generation of high-brightness coherent X-rays. However, the large size and high costs of such sources prevent their widespread use. The quest for a compact and coherent Xray source has long been a critical objective in modern physics, gaining further importance in recent years for industrial applications and fundamental scientific research. Here, we review the physical mechanisms governing compact coherent X-ray generation. Of current interest are coherent periodic interactions of free electrons in crystalline materials, creating hard X-rays via a mechanism known as parametric X-ray radiation (PXR). Over the past decade, X-ray sources leveraging this mechanism have demonstrated state-of-the-art tunability, directionality, and broad spatial coherence, enabling X-ray phase-contrast imaging on a compact scale. The coming years are expected to show substantial miniaturization of compact X-ray sources, facilitated by progress in electron beam technologies. This review compares the most promising mechanisms used for hard-X-ray generation, contrasting parametric X-ray radiation with inverse Compton scattering and characteristic radiation from a liquid-jet anode. We cover the most recent advancements, including the development of new materials, innovative geometrical designs, and specialized optimization techniques, aiming toward X-ray flux levels suitable for medical imaging and X-ray spectroscopy in compact scales.

We investigate automated in situ optimization of the potential landscape in a quantum point contact device, using a $3 \times 3$ gate array patterned atop the constriction. Optimization is performed using the covariance matrix adaptation evolutionary strategy, for which we introduce a metric for how "step-like" the conductance is as the channel becomes constricted. We first perform the optimization of the gate voltages in a tight-binding simulation and show how such in situ tuning can be used to mitigate a random disorder potential. The optimization is then performed in a physical device in experiment, where we also observe a marked improvement in the quantization of the conductance resulting from the optimization procedure., Comment: 8 pages, 4 figures (supplement: 6 pages, 3 figures)

Technology involving hybrid superconductor-semiconductor materials is a promising avenue for engineering quantum devices for information storage, manipulation, and transmission. Proximity-induced superconducting correlations are an essential part of such devices. While the proximity effect in the conduction band of common semiconductors is well understood, its manifestation in confined hole gases, realized for instance in germanium, is an active area of research. Lower-dimensional hole-based systems, particularly in germanium, are emerging as an attractive platform for a variety of solid-state quantum devices, due to their combination of efficient spin and charge control and long coherence times. The recent experimental realization of the proximity effect in germanium thus calls for a theoretical description that is tailored to hole gases. In this work, we propose a simple model to describe proximity-induced superconductivity in two-dimensional hole gases, incorporating both the heavy-hole (HH) and light-hole (LH) bands. We start from the Luttinger-Kohn model, introduce three parameters that characterize hopping across the superconductor-semiconductor interface, and derive explicit intraband and interband effective pairing terms for the HH and LH bands. Unlike previous approaches, our theory provides a quantitative relationship between induced pairings and interface properties. Restricting our general model to an experimentally relevant case where only the HH band crosses the chemical potential, we predict the coexistence of $s$-wave and $d$-wave singlet pairings, along with triplet-type pairings, and modified Zeeman and Rashba spin-orbit couplings. Our model thus presents a starting point for theoretical modeling of quantum devices based on proximitized hole gases, fueling further progress in quantum technology., Comment: 22 pages, 5 figures

Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or trans-national scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined., Comment: 25 pages, 3 figures, Accepted for publication at Knowledge Engineering Review (KER)

A Josephson diode is a superconducting circuit element that enables non-reciprocal transport, allowing a dissipationless supercurrent to preferentially flow in a single direction. Existing methods for achieving the required symmetry breaking mostly rely on specifically-designed materials or carefully-engineered circuits composed of multiple Josephson junctions. Here, we demonstrate that applying a biharmonic drive to a conventional superconducting tunnel-junction induces a diode effect through harmonic mixing processes that shift the supercurrent region. We show that, in a conventional tunnel junction, unity efficiency is achievable while maintaining a large supercurrent. Moreover, the relative phase between the two driving tones determines the directionality of the diode, which can be tuned in situ., Comment: 6 pages, 3 figures

Superconductor-semiconductor hybrid systems play a crucial role in realizing nanoscale quantum devices, including hybrid qubits, Majorana bound states, and Kitaev chains. For such hybrid devices, subgap states play a prominent role in their operation. In this work, we study such subgap states via Coulomb and tunneling spectroscopy through a superconducting island defined in a semiconductor nanowire fully coated by a superconductor. We systematically explore regimes ranging from an almost decoupled island to the open configuration. In the weak coupling regime, the experimental observations are very similar in the absence of a magnetic field and when one flux quantum is piercing the superconducting shell. Conversely, in the strong coupling regime, significant distinctions emerge between the two cases. We ascribe this different behavior to the existence of subgap states at one flux quantum, which become observable only for sufficiently strong coupling to the leads. We support our interpretation using a simple model to describe transport through the island. Our study highlights the importance of studying a broad range of tunnel couplings for understanding the rich physics of hybrid devices.

Virtual Try-On (VTON) is a highly active line of research, with increasing demand. It aims to replace a piece of garment in an image with one from another, while preserving person and garment characteristics as well as image fidelity. Current literature takes a supervised approach for the task, impairing generalization and imposing heavy computation. In this paper, we present a novel zero-shot training-free method for inpainting a clothing garment by reference. Our approach employs the prior of a diffusion model with no additional training, fully leveraging its native generalization capabilities. The method employs extended attention to transfer image information from reference to target images, overcoming two significant challenges. We first initially warp the reference garment over the target human using deep features, alleviating "texture sticking". We then leverage the extended attention mechanism with careful masking, eliminating leakage of reference background and unwanted influence. Through a user study, qualitative, and quantitative comparison to state-of-the-art approaches, we demonstrate superior image quality and garment preservation compared unseen clothing pieces or human figures., Comment: Project page available at https://nadavorzech.github.io/max4zero.github.io/

We demonstrate reliable machine-learned tuning of quantum-dot-based artificial Kitaev chains to Majorana sweet spots, using the covariance matrix adaptation algorithm. We show that a loss function based on local tunnelling-spectroscopy features of a chain with two additional sensor dots added at its ends provides a reliable metric to navigate parameter space and find points where crossed Andreev reflection and elastic cotunneling between neighbouring sites balance in such a way to yield near-zero-energy modes with very high Majorana quality. We simulate tuning of two- and three-site Kitaev chains, where the loss function is found from calculating the low-energy spectrum of a model Hamiltonian that includes Coulomb interactions and finite Zeeman splitting. In both cases, the algorithm consistently converges towards high-quality sweet spots. Since tunnelling spectroscopy provides one global metric for tuning all on-site potentials simultaneously, this presents a promising way towards tuning longer Kitaev chains, which are required for achieving topological protection of the Majorana modes.

Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strategy propagates a probability distribution inside the quantum controller according to the Fokker-Planck equation, appropriate for describing the effects of nuclear spin diffusion in gallium-arsenide. Evaluating and narrowing the anticipated distribution by a predetermined qubit probe sequence enables improved dynamical tracking of the uncontrolled magnetic field gradient within the singlet-triplet qubit. The adaptive strategy replaces the probe sequence by a small number of qubit probe cycles, with each probe time conditioned on the previous measurement outcomes, thereby further increasing the estimation efficiency. The combined real-time estimation strategy efficiently tracks low-frequency nuclear spin fluctuations in solid-state qubits, and can be applied to other qubit platforms by tailoring the appropriate update equation to capture their distinct noise sources., Comment: 21 pages, 10 figures, including 11-page 6-figure Supplemental Material

We investigate the impact of spin torque and spin pumping on the surface magnon polariton dispersion in a antiferromagnetic insulator-semiconductor heterostructure. In the bilayer system, the surface magnon polaritons conventionally couple to the plasma-oscillations in the semiconductor via electromagnetic fields. Additionally, magnons in the antiferromagnetic insulator layer may interact with the semiconductor layer via spin torques and their reciprocal phenomena of spin pumping. Due to the spin-to-charge conversion from the spin Hall and inverse spin Hall effects in the semiconductor layer with a strong spin-orbit coupling, this can couple the magnons to the plasmons in the semiconductor layer. Our research reveals that modifications in the mode frequency and the hybridization gap induced by these phenomena depend on the thickness of the antiferromagnetic layer. In thick layers, the spin-pumping contribution to the frequency shift and damping is inversely proportional to the wavelength, while in thin layers it is inversely proportional to the thickness. Furthermore, hybridization of the surface magnon polariton and dispersive magnons in the antiferromagnet is shown to depend on both the thickness and wavelength of the modes., Comment: 14 pages, 6 figures

We use a single-channel scattering formalism to derive general expressions for the Andreev bound-state energies and resulting current--phase relationship in a one-dimensional semiconductor-based SNS-junction, including arbitrarily oriented effective spin--orbit and Zeeman fields and taking into account disorder in the junction in by including a single scatterer with transmission probability $0 \leq T^2 \leq 1$, arbitrarily located in the normal region. We first corroborate our results by comparing them to the known analytic limiting-case expressions. Then we simplify our general result in several additional limits, including the case of the scatterer being at a specific location and the cases of small and large spin--orbit fields compared to the Zeeman splitting, assuming low transparency ($T\ll 1$). We believe that our results could be helpful for disentangling the main spin-mixing processes in experiments on low-dimensional semiconductor-based SNS-junctions.

Josephson diodes are superconducting elements that show an asymmetry in the critical current depending on the direction of the current. Here, we theoretically explore how an alternating current bias can tune the response of such a diode. We show that for slow driving there is always a regime where the system can only carry zero-voltage dc current in one direction, thus effectively behaving as an ideal Josephson diode. Under fast driving, the diode efficiency is also tunable, although the ideal regime cannot be reached in this case. We also investigate the residual dissipation due to the time-dependent current bias and show that it remains small. All our conclusions are solely based on the critical current asymmetry of the junction, and are thus compatible with any Josephson diode., Comment: 4 pages, 4 figures (+ 9 pages, 3 figures)

This paper assesses the reliability and validity of cognitive and socioemotional skills measures and investigates the correlation between schooling, skills acquisition, and labor earnings. The primary data from Pakistan incorporates two innovations related to measurement and sampling. On measurement, the paper develops and implements a battery of instruments intended to capture cognitive and socioemotional skills among young adults. On sampling, the paper uses a panel that follows respondents from their original rural locations in 2003 to their residences in 2018, a period over which 38 percent of the respondents left their native villages. In terms of their validity and reliability, our skills measures compare favorably to previous measurement attempts in low- and middle-income countries. The following are documented in the data: (a) more years of schooling are correlated with higher cognitive and socioemotional skills; (b) labor earnings are correlated with cognitive and socioemotional skills as well as years of schooling; and (c) the earnings-skills correlations depend on respondents' migration status. The magnitudes of the correlations between schooling and skills on the one hand and earnings and skills on the other are consistent with a widespread concern that such skills are under-produced in the schooling system. [This report was prepared by the World Bank Group's Development Research Group, Development Economics. Funding was provided by RISE and World Bank's Strategic Research Program Fund.]

Slow fluctuations of Overhauser fields are an important source for decoherence in spin qubits hosted in III-V semiconductor quantum dots. Focusing on the effect of the field gradient on double-dot singlet-triplet qubits, we present two adaptive Bayesian schemes to estimate the magnitude of the gradient by a series of free induction decay experiments. We concentrate on reducing the computational overhead, with a real-time implementation of the schemes in mind. We show how it is possible to achieve a significant improvement of estimation accuracy compared to more traditional estimation methods. We include an analysis of the effects of dephasing and the drift of the gradient itself., Comment: Submission to SciPost

Artificial Kitaev chains, formed by quantum dots coupled via superconductors, have emerged as a promising platform for realizing Majorana bound states. Even a minimal Kitaev chain (a quantum dot--superconductor--quantum dot setup) can host Majorana states at discrete sweet spots. However, unambiguously identifying Majorana sweet spots in such a system is still challenging. In this work, we propose an additional dot coupled to one side of the chain as a tool to identify good sweet spots in minimal Kitaev chains. When the two Majorana states in the chain overlap, the extra dot couples to both and thus splits an even--odd ground-state degeneracy when its level is on resonance. In contrast, a ground-state degeneracy will persist for well-separated Majorana states. This difference can be used to identify points in parameter space with spatially separated Majorana states, using tunneling spectroscopy measurements. We perform a systematic analysis of different relevant situations. We show that the additional dot can help distinguishing between Majorana sweet spots and other trivial zero-energy crossings. We also characterize the different conductance patterns, which can serve as a guide for future experiments aiming to study Majorana states in minimal Kitaev chains., Comment: 10 pages, 7 figures

The spin of a single electron confined in a semiconductor quantum dot is a natural qubit candidate. Fundamental building blocks of spin-based quantum computing have been demonstrated in double quantum dots with significant spin-orbit coupling. Here, we show that spin-orbit-coupled double quantum dots can be categorised in six classes, according to a partitioning of the multi-dimensional space of their $g$-tensors. The class determines physical characteristics of the double dot, i.e., features in transport, spectroscopy and coherence measurements, as well as qubit control, shuttling, and readout experiments. In particular, we predict that the spin physics is highly simplified due to pseudospin conservation, whenever the external magnetic field is pointing to special directions (`magic directions'), where the number of special directions is determined by the class. We also analyze the existence and relevance of magic loops in the space of magnetic-field directions, corresponding to equal local Zeeman splittings. These results present an important step toward precise interpretation and efficient design of spin-based quantum computing experiments in materials with strong spin-orbit coupling., Comment: 12 pages main text, +4 pages appendix and bibliography, 7 figures

The possibility to engineer artificial Kitaev chains in arrays of quantum dots coupled via narrow superconducting regions has emerged as an attractive way to overcome the disorder issues that complicate the realization and detection of topological superconducting phases in other platforms. Although a true topological phase would require long chains, already a two-site chain realized in a double quantum dot can be tuned to points in parameter space where it hosts zero-energy states that seem identical to the Majorana bound states that characterize a topological phase. These states were named "poor man's Majorana bound states" (PMMs) because they lack formal topological protection. In this work, we propose a roadmap for next-generation experiments on PMMs. The roadmap starts with experiments to characterize a single pair of PMMs by measuring the Majorana quality, then moves on to initialization and readout of the parity of a PMM pair, which allows measuring quasiparticle poisoning times. The next step is to couple two PMM systems to form a qubit. We discuss measurements of the coherence time of such a qubit, as well as a test of Majorana fusion rules in the same setup. Finally, we propose and analyse three different types of braiding-like experiments which require more complex device geometries. Our conclusions are supported by calculations based on a realistic model with interacting and spinful quantum dots, as well as by simpler models to gain physical insight. Our calculations show that it is indeed possible to demonstrate nonabelian physics in minimal two-site Kitaev chains despite the lack of a true topological phase. But our findings also reveal that doing so requires some extra care, appropriately modified protocols and awareness of the details of this particular platform., Comment: 24 pages, 8 figures

The spin degree of freedom is crucial for the understanding of any condensed matter system. Knowledge of spin-mixing mechanisms is not only essential for successful control and manipulation of spin-qubits, but also uncovers fundamental properties of investigated devices and material. For electrostatically-defined bilayer graphene quantum dots, in which recent studies report spin-relaxation times T1 up to 50ms with strong magnetic field dependence, we study spin-blockade phenomena at charge configuration $(1,2)\leftrightarrow(0,3)$. We examine the dependence of the spin-blockade leakage current on interdot tunnel coupling and on the magnitude and orientation of externally applied magnetic field. In out-of-plane magnetic field, the observed zero-field current peak could arise from finite-temperature co-tunneling with the leads; though involvement of additional spin- and valley-mixing mechanisms are necessary for explaining the persistent sharp side peaks observed. In in-plane magnetic field, we observe a zero-field current dip, attributed to the competition between the spin Zeeman effect and the Kane-Mele spin-orbit interaction. Details of the line shape of this current dip however, suggest additional underlying mechanisms are at play.

Superconductor--semiconductor hybrid devices are currently attracting much attention, fueled by the fact that strong spin--orbit interaction in combination with induced superconductivity can lead to exotic physics with potential applications in fault-tolerant quantum computation. The detailed nature of the spin dynamics in such systems is, however, often strongly dependent on device details and hard to access in experiment. In this paper we theoretically investigate a superconductor--normal--superconductor junction based on a two-dimensional hole gas with additional Rashba spin orbit--coupling, and we focus on the dependence of the critical current on the direction and magnitude of an applied in-plane magnetic field. We present a simple model, which allows us to systematically investigate different parameter regimes and obtain both numerical results and analytical expressions for all limiting cases. Our results could serve as a tool for extracting more information about the detailed spin physics in a two-dimensional hole gas based on a measured pattern of critical currents., Comment: 11 pages, 5 figures

Tyler's M-estimator is a well known procedure for robust and heavy-tailed covariance estimation. Tyler himself suggested an iterative fixed-point algorithm for computing his estimator however, it requires super-linear (in the size of the data) runtime per iteration, which maybe prohibitive in large scale. In this work we propose, to the best of our knowledge, the first Frank-Wolfe-based algorithms for computing Tyler's estimator. One variant uses standard Frank-Wolfe steps, the second also considers \textit{away-steps} (AFW), and the third is a \textit{geodesic} version of AFW (GAFW). AFW provably requires, up to a log factor, only linear time per iteration, while GAFW runs in linear time (up to a log factor) in a large $n$ (number of data-points) regime. All three variants are shown to provably converge to the optimal solution with sublinear rate, under standard assumptions, despite the fact that the underlying optimization problem is not convex nor smooth. Under an additional fairly mild assumption, that holds with probability 1 when the (normalized) data-points are i.i.d. samples from a continuous distribution supported on the entire unit sphere, AFW and GAFW are proved to converge with linear rates. Importantly, all three variants are parameter-free and use adaptive step-sizes., Comment: In Neural Information Processing Systems (NeurIPS) 2022

Spin--orbit interaction (SOI) plays a fundamental role in many low-dimensional semiconductor and hybrid quantum devices. In the rapidly evolving field of semiconductor spin qubits, SOI is an essential ingredient that can allow for ultrafast qubit control. The exact manifestation of SOI in a given device is, however, often both hard to predict theoretically and probe experimentally. Here, we develop a detailed theoretical connection between the leakage current through a double quantum dot in Pauli spin blockade and the underlying SOI in the system. We present a general analytic expression for the leakage current, which allows to connect experimentally observable features to both the magnitude and orientation of the effective spin--orbit field acting on the moving carriers. Motivated by the large recent interest in hole-based quantum devices, we further zoom in on the case of Pauli blockade of hole spins, assuming a strong transverse confinement potential. In this limit we also find an analytic expression for the current at low external magnetic field, that includes the effect of hyperfine coupling of the hole spins to randomly fluctuating nuclear spin baths. This result can be used to extract detailed information about both hyperfine and spin--orbit coupling parameters for hole spins in devices with a significant fraction of non-zero nuclear spins., Comment: 9 pages, 5 figures

Supervision for image-to-image translation (I2I) tasks is hard to come by, but bears significant effect on the resulting quality. In this paper, we observe that for many Unsupervised I2I (UI2I) scenarios, one domain is more familiar than the other, and offers in-domain prior knowledge, such as semantic segmentation. We argue that for complex scenes, figuring out the semantic structure of the domain is hard, especially with no supervision, but is an important part of a successful I2I operation. We hence introduce two techniques to incorporate this invaluable in-domain prior knowledge for the benefit of translation quality: through a novel Multi-Stream generator architecture, and through a semantic segmentation-based regularization loss term. In essence, we propose splitting the input data according to semantic masks, explicitly guiding the network to different behavior for the different regions of the image. In addition, we propose training a semantic segmentation network along with the translation task, and to leverage this output as a loss term that improves robustness. We validate our approach on urban data, demonstrating superior quality in the challenging UI2I tasks of converting day images to night ones. In addition, we also demonstrate how reinforcing the target dataset with our augmented images improves the training of downstream tasks such as the classical detection one.