Demonstration of Microwave Resonators and Double Quantum Dots on Optimized Reverse-Graded Ge/SiGe Heterostructures.

One of the most promising platforms for the realization of spin-based quantum computing are planar germanium quantum wells embedded between silicon-germanium barriers. To achieve comparably thin stacks with little surface roughness, this type of heterostructure can be grown using the so-called reverse linear grading approach, where the growth starts with a virtual germanium substrate followed by a graded silicon-germanium alloy with an increasing silicon content. However, the compatibility of such reverse-graded heterostructures with superconducting microwave resonators has not yet been demonstrated. Here, we report on the successful realization of well-controlled double quantum dots and high-quality coplanar waveguide resonators on the same reverse-graded Ge/SiGe heterostructure.

Production and Comprehension of Prosodic Boundary Marking in Persons With Unilateral Brain Lesions.

PURPOSE: Persons with unilateral brain damage in the right hemisphere (RH) or left hemisphere (LH) show limitations in processing linguistic prosody, with yet inconclusive results on their ability to process prosodically marked structural boundaries for syntactic ambiguity resolution. We aimed at systematically investigating production and comprehension of three prosodic cues (f 0 range, final lengthening, and pause) at structural boundaries in coordinate sequences in participants with right hemisphere brain damage (RHDP) and participants with left hemisphere brain damage (LHDP). METHOD: Twenty RHDP and 15 LHDP participated in our study. Comprehension experiment: Participants and a control group listened to coordinate name sequences with internal grouping by a prosodically marked structural boundary (grouped condition, e.g., "(Gabi und Leni) # und Nina") or without internal grouping (ungrouped condition, e.g., "Gabi und Leni und Nina") and had to identify the target condition. The strength and combinations of prosodic cues in the stimuli were manipulated. Production experiment: Participants were asked to produce coordinate sequences in the two conditions (grouped, ungrouped) in two different tasks: a Reading Aloud and a Repetition experiment. Accuracy of participants' productions was subsequently assessed in a rating study and productions were analyzed with respect to use of prosodic cues. RESULTS: In the Comprehension experiment, RHDP and LHDP had overall lower identification accuracies than unimpaired control participants and LHDP were found to have particular problems with boundary identification when the pause cue was reduced. In production, LHDP and RHDP employed all three prosodic cues for boundary marking, but struggled to clearly mark prosodic boundaries in 28% of all productions. Both groups showed better performance in reading aloud than in repetition. LHDP relied more on using f 0 range and pause duration to prosodically mark structural boundaries, whereas RHDP employed final lengthening more vigorously than LHDP in reading aloud. CONCLUSIONS: We conclude that processing of linguistic prosody is affected in RHDP and LHDP, but not completely impaired. Therefore, prosody can serve as a relevant communicative resource. However, it should also be considered as a target area for assessment and treatment in both groups. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21637505.

Majorana-like Coulomb spectroscopy in the absence of zero-bias peaks.

Hybrid semiconductor-superconductor devices hold great promise for realizing topological quantum computing with Majorana zero modes1-5. However, multiple claims of Majorana detection, based on either tunnelling6-10 or Coulomb blockade (CB) spectroscopy11,12, remain disputed. Here we devise an experimental protocol that allows us to perform both types of measurement on the same hybrid island by adjusting its charging energy via tunable junctions to the normal leads. This method reduces ambiguities of Majorana detections by checking the consistency between CB spectroscopy and zero-bias peaks in non-blockaded transport. Specifically, we observe junction-dependent, even-odd modulated, single-electron CB peaks in InAs/Al hybrid nanowires without concomitant low-bias peaks in tunnelling spectroscopy. We provide a theoretical interpretation of the experimental observations in terms of low-energy, longitudinally confined island states rather than overlapping Majorana modes. Our results highlight the importance of combined measurements on the same device for the identification of topological Majorana zero modes.

Dynamics of Hole Singlet-Triplet Qubits with Large g-Factor Differences.

The spin-orbit interaction permits to control the state of a spin qubit via electric fields. For holes it is particularly strong, allowing for fast all electrical qubit manipulation, and yet an in-depth understanding of this interaction in hole systems is missing. Here we investigate, experimentally and theoretically, the effect of the cubic Rashba spin-orbit interaction on the mixing of the spin states by studying singlet-triplet oscillations in a planar Ge hole double quantum dot. Landau-Zener sweeps at different magnetic field directions allow us to disentangle the effects of the spin-orbit induced spin-flip term from those caused by strongly site-dependent and anisotropic quantum dot g tensors. Our work, therefore, provides new insights into the hole spin-orbit interaction, necessary for optimizing future qubit experiments.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Children's Learning of Non-adjacent Dependencies Using a Web-Based Computer Game Setting.

Infants show impressive speech decoding abilities and detect acoustic regularities that highlight the syntactic relations of a language, often coded via non-adjacent dependencies (NADs, e.g., is singing). It has been claimed that infants learn NADs implicitly and associatively through passive listening and that there is a shift from effortless associative learning to a more controlled learning of NADs after the age of 2 years, potentially driven by the maturation of the prefrontal cortex. To investigate if older children are able to learn NADs, Lammertink et al. (2019) recently developed a word-monitoring serial reaction time (SRT) task and could show that 6-11-year-old children learned the NADs, as their reaction times (RTs) increased then they were presented with violated NADs. In the current study we adapted their experimental paradigm and tested NAD learning in a younger group of 52 children between the age of 4-8 years in a remote, web-based, game-like setting (whack-a-mole). Children were exposed to Italian phrases containing NADs and had to monitor the occurrence of a target syllable, which was the second element of the NAD. After exposure, children did a "Stem Completion" task in which they were presented with the first element of the NAD and had to choose the second element of the NAD to complete the stimuli. Our findings show that, despite large variability in the data, children aged 4-8 years are sensitive to NADs; they show the expected differences in r RTs in the SRT task and could transfer the NAD-rule in the Stem Completion task. We discuss these results with respect to the development of NAD dependency learning in childhood and the practical impact and limitations of collecting these data in a web-based setting.

Nontopological zero-bias peaks in full-shell nanowires induced by flux-tunable Andreev states.

A semiconducting nanowire fully wrapped by a superconducting shell has been proposed as a platform for obtaining Majorana modes at small magnetic fields. In this study, we demonstrate that the appearance of subgap states in such structures is actually governed by the junction region in tunneling spectroscopy measurements and not the full-shell nanowire itself. Short tunneling regions never show subgap states, whereas longer junctions always do. This can be understood in terms of quantum dots forming in the junction and hosting Andreev levels in the Yu-Shiba-Rusinov regime. The intricate magnetic field dependence of the Andreev levels, through both the Zeeman and Little-Parks effects, may result in robust zero-bias peaks-features that could be easily misinterpreted as originating from Majorana zero modes but are unrelated to topological superconductivity.

A singlet-triplet hole spin qubit in planar Ge.

Spin qubits are considered to be among the most promising candidates for building a quantum processor. Group IV hole spin qubits are particularly interesting owing to their ease of operation and compatibility with Si technology. In addition, Ge offers the option for monolithic superconductor-semiconductor integration. Here, we demonstrate a hole spin qubit operating at fields below 10 mT, the critical field of Al, by exploiting the large out-of-plane hole g-factors in planar Ge and by encoding the qubit into the singlet-triplet states of a double quantum dot. We observe electrically controlled g-factor difference-driven and exchange-driven rotations with tunable frequencies exceeding 100 MHz and dephasing times of 1 µs, which we extend beyond 150 µs using echo techniques. These results demonstrate that Ge hole singlet-triplet qubits are competing with state-of-the-art GaAs and Si singlet-triplet qubits. In addition, their rotation frequencies and coherence are comparable with those of Ge single spin qubits, but singlet-triplet qubits can be operated at much lower fields, emphasizing their potential for on-chip integration with superconducting technologies.

Algal Community Change in Mountain Lakes of the Alps Reveals Effects of Climate Warming and Shifting Treelines1.

The biological communities of mountain lakes are suspected to be highly sensitive to global warming and associated catchment changes. To identify the parameters determining algal community responses, subfossil pigments from 21 different mountain lakes in the Bavarian-Tyrolean Limestone Alps were investigated. Sediment cores were radio-isotopically dated, and their pigment preservation evaluated. General additive models (GAM) of pigment compositions were calculated with temperature as the explanatory variable and generalized linear models with several lake parameters explaining log-transformed GAM P-values. Lake depth and trophic state were identified as major control variables of the algal community and productivity changes. Shifts in a deep oligotrophic alpine lake (lg(P) = -1.04) were half as strong as in a shallow mesotrophic alpine lake (lg(P) = -1.86) with faster warming and higher productivity forcing the development of biomass. Phytoplankton and macrophyte pigments increased clearly with warming, at lower altitudes, and decreased at the treeline, so that periphytic pigments dominated alpine sediments. This pattern is probably the result of interactions of UV radiation and allochthonous inputs of DOM. Our findings suggest that (sub)alpine shallow lakes with higher nutrient levels are most vulnerable to climate change-driven changes whereas deep, nutrient-poor lakes appear more resilient.