Electric-field tuning of the valley splitting in silicon corner dots

We perform an excited state spectroscopy analysis of a silicon corner dot in a nanowire field-effect transistor to assess the electric field tunability of the valley splitting. First, we demonstrate a back-gate-controlled transition between a single quantum dot and a double quantum dot in parallel that allows tuning the device in to corner dot formation. We find a linear dependence of the valley splitting on back-gate voltage, from $880~\mu \text{eV}$ to $610~\mu \text{eV}$ with a slope of $-45\pm 3~\mu \text{eV/V}$ (or equivalently a slope of $-48\pm 3~\mu \text{eV/(MV/m)}$ with respect to the effective field). The experimental results are backed up by tight-binding simulations that include the effect of surface roughness, remote charges in the gate stack and discrete dopants in the channel. Our results demonstrate a way to electrically tune the valley splitting in silicon-on-insulator-based quantum dots, a requirement to achieve all-electrical manipulation of silicon spin qubits.Comment: 5 pages, 3 figures. In this version: Discussion of model expanded; Fig. 3 updated; Refs. added (15, 22, 32, 34, 35, 36, 37

Low-temperature tunable radio-frequency resonator for sensitive dispersive readout of nanoelectronic devices

We present a sensitive, tunable radio-frequency resonator designed to detect reactive changes in nanoelectronic devices down to dilution refrigerator temperatures. The resonator incorporates GaAs varicap diodes to allow electrical tuning of the resonant frequency and the coupling to the input line. We find a resonant frequency tuning range of 8.4 MHz at 55 mK that increases to 29 MHz at 1.5 K. To assess the impact on performance of different tuning conditions, we connect a quantum dot in a silicon nanowire field-effect transistor to the resonator, and measure changes in the device capacitance caused by cyclic electron tunneling. At 250 mK, we obtain an equivalent charge sensitivity of $43~\mu e / \sqrt{\text{Hz}}$ when the resonator and the line are impedance-matched and show that this sensitivity can be further improved to $31~\mu e / \sqrt{\text{Hz}}$ by re-tuning the resonator. We understand this improvement by using an equivalent circuit model and demonstrate that for maximum sensitivity to capacitance changes, in addition to impedance matching, a high-quality resonator with low parasitic capacitance is desired.Comment: Includes supplementary informatio

Large Anisotropic Thermal Expansion Anomaly near the Superconducting Transition Temperature in MgB2

An anisotropic lattice anomaly near the superconducting transition temperature, Tc, was observed in MgB2 by high-resolution neutron powder diffraction. The a-axis thermal expansion becomes negative near Tc, while the c-axis thermal expansion is unaffected. This is qualitatively consistent with a depletion of the boron-boron s-band as the superconducting gap opens, resulting in weaker bonding. However, the observed anomaly is much larger than predicted by the Ehrenfest relation, strongly suggesting that the phonon thermal expansion also changes sign, as commonly observed in hexagonal layered crystals. These two effects may be connected through subtle changes in the phonon spectrum at Tc.Comment: 11 pages, 4 figure

The genome of the jellyfish Aurelia and the evolution of animal complexity

We present the genome of the moon jellyfish Aurelia, a genome from a cnidarian with a medusa life stage. Our analyses suggest that gene gain and loss in Aurelia is comparable to what has been found in its morphologically simpler relatives—the anthozoan corals and sea anemones. RNA sequencing analysis does not support the hypothesis that taxonomically restricted (orphan) genes play an oversized role in the development of the medusa stage. Instead, genes broadly conserved across animals and eukaryotes play comparable roles throughout the life cycle. All life stages of Aurelia are significantly enriched in the expression of genes that are hypothesized to interact in protein networks found in bilaterian animals. Collectively, our results suggest that increased life cycle complexity in Aurelia does not correlate with an increased number of genes. This leads to two possible evolutionary scenarios: either medusozoans evolved their complex medusa life stage (with concomitant shifts into new ecological niches) primarily by re-working genetic pathways already present in the last common ancestor of cnidarians, or the earliest cnidarians had a medusa life stage, which was subsequently lost in the anthozoans. While we favour the earlier hypothesis, the latter is consistent with growing evidence that many of the earliest animals were more physically complex than previously hypothesized

Large dispersive interaction between a CMOS double quantum dot and microwave photons

We report a large coupling rate, $g_0/(2\pi)=183$ MHz, between the charge state of a double quantum dot in a CMOS split-gate silicon nanowire transistor and microwave photons in a lumped-element resonator formed by hybrid integration with a superconducting inductor. We enhance the coupling by exploiting the large interdot lever arm of an asymmetric split-gate device, $\alpha=0.72$, and by inductively coupling to the resonator to increase its impedance, $Z_\text{r}=560$ $\Omega$. In the dispersive regime, the large coupling strength at the DQD hybridisation point produces a frequency shift comparable to the resonator linewidth, the optimal setting for maximum state visibility. We exploit this regime to demonstrate rapid gate-based readout of the charge degree of freedom, with an SNR of 3.3 in 50 ns. In the resonant regime, the fast charge decoherence rate precludes reaching the strong coupling regime, but we show a clear route to spin-photon circuit quantum electrodynamics using hybrid CMOS systems.Comment: 9 pages, 7 figure

Rapid cryogenic characterisation of 1024 integrated silicon quantum dots

Quantum computers are nearing the thousand qubit mark, with the current focus on scaling to improve computational performance. As quantum processors grow in complexity, new challenges arise such as the management of device variability and the interface with supporting electronics. Spin qubits in silicon quantum dots are poised to address these challenges with their proven control fidelities and potential for compatibility with large-scale integration. Here, we demonstrate the integration of 1024 silicon quantum dots with on-chip digital and analogue electronics, all operating below 1 K. A high-frequency analogue multiplexer provides fast access to all devices with minimal electrical connections, enabling characteristic data across the quantum dot array to be acquired in just 5 minutes. We achieve this by leveraging radio-frequency reflectometry with state-of-the-art signal integrity, reaching a minimum integration time of 160 ps. Key quantum dot parameters are extracted by fast automated machine learning routines to assess quantum dot yield and understand the impact of device design. We find correlations between quantum dot parameters and room temperature transistor behaviour that may be used as a proxy for in-line process monitoring. Our results show how rapid large-scale studies of silicon quantum devices can be performed at lower temperatures and measurement rates orders of magnitude faster than current probing techniques, and form a platform for the future on-chip addressing of large scale qubit arrays.Comment: Main text: 14 pages, 8 figures, 1 table Supplementary: 8 pages, 6 figure

Multi-module microwave assembly for fast read-out and charge noise characterization of silicon quantum dots

Fast measurements of quantum devices is important in areas such as quantum sensing, quantum computing and nanodevice quality analysis. Here, we develop a superconductor-semiconductor multi-module microwave assembly to demonstrate charge state readout at the state-of-the-art. The assembly consist of a superconducting readout resonator interfaced to a silicon-on-insulator (SOI) chiplet containing quantum dots (QDs) in a high-$\kappa$ nanowire transistor. The superconducting chiplet contains resonant and coupling elements as well as $LC$ filters that, when interfaced with the silicon chip, result in a resonant frequency $f=2.12$~GHz, a loaded quality factor $Q=680$, and a resonator impedance $Z=470$~$\Omega$. Combined with the large gate lever arms of SOI technology, we achieve a minimum integration time for single and double QD transitions of 2.77~ns and 13.5~ns, respectively. We utilize the assembly to measure charge noise over 9 decades of frequency up to 500~kHz and find a 1/$f$ dependence across the whole frequency spectrum as well as a charge noise level of 4~$\mu$eV/$\sqrt{\text{Hz}}$ at 1~Hz. The modular microwave circuitry presented here can be directly utilized in conjunction with other quantum device to improve the readout performance as well as enable large bandwidth noise spectroscopy, all without the complexity of superconductor-semiconductor monolithic fabrication.Comment: Main: 7 pages, 4 figures. Supplementary: 6 pages, 5 figure

The genome of the jellyfish Aurelia and the evolution of animal complexity

We present the genome of the moon jellyfish Aurelia, a genome from a cnidarian with a medusa life stage. Our analyses suggest that gene gain and loss in Aurelia is comparable to what has been found in its morphologically simpler relatives—the anthozoan corals and sea anemones. RNA sequencing analysis does not support the hypothesis that taxonomically restricted (orphan) genes play an oversized role in the development of the medusa stage. Instead, genes broadly conserved across animals and eukaryotes play comparable roles throughout the life cycle. All life stages of Aurelia are significantly enriched in the expression of genes that are hypothesized to interact in protein networks found in bilaterian animals. Collectively, our results suggest that increased life cycle complexity in Aurelia does not correlate with an increased number of genes. This leads to two possible evolutionary scenarios: either medusozoans evolved their complex medusa life stage (with concomitant shifts into new ecological niches) primarily by re-working genetic pathways already present in the last common ancestor of cnidarians, or the earliest cnidarians had a medusa life stage, which was subsequently lost in the anthozoans. While we favour the earlier hypothesis, the latter is consistent with growing evidence that many of the earliest animals were more physically complex than previously hypothesized

Prognostic imaging biomarkers for diabetic kidney disease (iBEAt):study protocol

Background: Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim). Methods: iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes. Discussion: iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D. Trial registration: Clinicaltrials.gov (NCT03716401)