SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits.

Large-scale arrays of quantum-dot spin qubits in Si/SiGe quantum wells require large or tunable energy splittings of the valley states associated with degenerate conduction band minima. Existing proposals to deterministically enhance the valley splitting rely on sharp interfaces or modifications in the quantum well barriers that can be difficult to grow. Here, we propose and demonstrate a new heterostructure, the "Wiggle Well", whose key feature is Ge concentration oscillations inside the quantum well. Experimentally, we show that placing Ge in the quantum well does not significantly impact our ability to form and manipulate single-electron quantum dots. We further observe large and widely tunable valley splittings, from 54 to 239 µeV. Tight-binding calculations, and the tunability of the valley splitting, indicate that these results can mainly be attributed to random concentration fluctuations that are amplified by the presence of Ge alloy in the heterostructure, as opposed to a deterministic enhancement due to the concentration oscillations. Quantitative predictions for several other heterostructures point to the Wiggle Well as a robust method for reliably enhancing the valley splitting in future qubit devices.

Corrigendum: Identifying single electron charge sensor events using wavelet edge detection (2015Nanotechnology26215201).

The simulated noise used to benchmark wavelet edge detection in this work was described incorrectly. The correct description is given here, and new results based on noise that matches the original description are provided. The results support our original conclusion, which is that wavelet edge detection outperforms thresholding in the presence of white noise and 1/fnoise.

Autotuning of double dot devices in situ with machine learning.

The current practice of manually tuning quantum dots (QDs) for qubit operation is a relatively time-consuming procedure that is inherently impractical for scaling up and applications. In this work, we report on the in situ implementation of a recently proposed autotuning protocol that combines machine learning (ML) with an optimization routine to navigate the parameter space. In particular, we show that a ML algorithm trained using exclusively simulated data to quantitatively classify the state of a double-QD device can be used to replace human heuristics in the tuning of gate voltages in real devices. We demonstrate active feedback of a functional double-dot device operated at millikelvin temperatures and discuss success rates as a function of the initial conditions and the device performance. Modifications to the training network, fitness function, and optimizer are discussed as a path toward further improvement in the success rate when starting both near and far detuned from the target double-dot range.

Gene-gene and gene-environment interactions in lipodystrophy: Lessons learned from natural PPARγ mutants.

Monogenic lipodystrophies are a heterogeneous group of rare disorders characterized by a lack of adipose tissue (AT), all of which predispose patients to the development of insulin resistance and its related metabolic sequelae. The extent of AT loss ranges from partial, as in familial partial lipodystrophy (FPLD), to a total absence of metabolically active AT in congenital generalized lipodystrophy (CGL) and is generally associated with the severity of metabolic complications. Significant genetic, allelic, phenotypic, and clinical heterogeneity exists among the lipodystrophies. Patients with FPLD3 due to mutations in the PPARG gene, which encodes a key transcriptional regulator of adipocyte development and function, provide a particularly striking example of this heterogeneity. We will present several gene-gene and gene-environment factors and mechanisms that are critical for adequate PPARγ expression and activity in AT and discuss how these interactions potentially contribute to the observed spectrum of FPLD3 phenotypes. Comparable mechanisms may play a role in other types of lipodystrophies too, and their elucidation may further improve our molecular understanding of AT dysfunction.

Measurements of the Thermal Resistivity of InAlAs, InGaAs, and InAlAs/InGaAs Superlattices.

Thermal management efforts in nanoscale devices must consider both the thermal properties of the constituent materials and the interfaces connecting them. It is currently unclear whether alloy/alloy semiconductor superlattices such as InAlAs/InGaAs have lower thermal conductivities than their constituent alloys. We report measurements of the crossplane thermal resistivity of InAlAs/InGaAs superlattices at room temperature, showing that the superlattice resistivities are larger by a factor of 1.2-1.6 than that of the constituent bulk materials, depending on the strain state and composition. We show that the additional resistance present in these superlattices can be tuned by a factor of 2.5 by altering the lattice mismatch and thereby the phonon-mode mismatch at the interfaces, a principle that is commonly assumed for superlattices but has not been experimentally verified without adding new elements to the layers. We find that the additional resistance in superlattices does not increase significantly when the layer thickness is decreased from 4 to 2 nm. We also report measurements of 250-1000 nm thick films of undoped InGaAs and InAlAs lattice-matched to InP substrates, for there is no published thermal conductivity value for the latter, and we find it to be 2.24 ± 0.09 at 22 °C, which is ∼2.7 times smaller than the widely used estimates.

Farmers' Perceptions of Dairy Cattle Breeds, Breeding and Feeding Strategies: A Case of Smallholder Dairy Farmers in Western Kenya.

To understand farmers' preference and perceptions of breed attributes, breeding and feeding practices, 419 households in western Kenya were interviewed in a cross-sectional survey. Respondents scored their preference for cattle breeds, traits and breeding methods on a scale of 1 (most preferred) to 5 (least preferred). Preferences were compared using multinomial logistic regression models on weighted scores. The Ayrshire breed was most preferred followed by the Friesian. Using hardship tolerance as a reference trait, the Friesian was preferred 4.86 times more for high milk production and Ayrshire, Jersey and Guernsey breeds 4.61, 4.60 and 4.18 times (p < 0.01) more, respectively, for milk fat content. The Ayrshire was preferred 4.16 times more for its perceived low feed requirement and 1.22 times more (p < 0.01) for resistance to diseases. Friesian was the only breed preferred (3.18 times more) (p < 0.01) for high growth rate of calves. Artificial insemination (AI) was the breeding method of choice, but majority (>68%) of respondents used natural mating, because it was readily available and cheaper. The current study highlights the importance of taking into account farmers' objectives and the production environment when designing breed improvement programmes and recommends packaging of breeding together with feeding interventions.

Georeferenced soil provenancing with digital signatures.

The provenance or origin of a soil sample is of interest in soil forensics, archaeology, and biosecurity. In all of these fields, highly specialized and often expensive analysis is usually combined with expert interpretation to estimate sample origin. In this proof of concept study we apply rapid and non-destructive spectral analysis to the question of direct soil provenancing. This approach is based on one of the underlying tenets of soil science - that soil pedogenesis is spatially unique, and thus digital spectral signatures of soil can be related directly, rather than via individual soil properties, to a georeferenced location. We examine three different multivariate regression techniques to predict GPS coordinates in two nested datasets. With a minimum of data processing, we show that in most instances Eastings and Northings can be predicted to within 20% of the range of each within the dataset using the spectral signatures produced via portable x-ray fluorescence. We also generate 50 and 95% confidence intervals of prediction and express these as a range of GPS coordinates. This approach has promise for future application in soil and environmental provenancing.

Genetic syndromes of severe insulin resistance.

Insulin resistance underpins the link between obesity and most of its associated metabolic disorders including type 2 diabetes, fatty liver disease, dyslipidaemia and cardiovascular disease. Despite its importance and extensive scientific endeavour, its precise molecular pathogenesis remains unclear. Monogenic syndromes of extreme insulin resistance, whilst rare in themselves, can provide unique insights into the pathogenesis of human insulin resistance. Severe insulin resistance syndromes are broadly classified into three categories: lipodystrophies, primary insulin signalling defects or complex syndromes including severe insulin resistance. Genetically confirmed classification has facilitated the identification of robust diagnostic biochemical features accelerating accurate clinical diagnosis. Interestingly the biochemical features of lipodystrophies are far more closely aligned to what is seen in prevalent forms of insulin resistance than those of primary insulin signalling defects, suggesting that lipodystrophy could be a relevant model for common disease. This assertion is supported by genome-wide association data indicating that SNPs associated with fasting hyperinsulinemia and metabolic dyslipidaemia, are strongly associated with a subtle reduction in hip fat, suggesting that subtle forms of lipodystrophy are likely to be a significant contributor to prevalent insulin resistance.

A programmable two-qubit quantum processor in silicon.

Now that it is possible to achieve measurement and control fidelities for individual quantum bits (qubits) above the threshold for fault tolerance, attention is moving towards the difficult task of scaling up the number of physical qubits to the large numbers that are needed for fault-tolerant quantum computing. In this context, quantum-dot-based spin qubits could have substantial advantages over other types of qubit owing to their potential for all-electrical operation and ability to be integrated at high density onto an industrial platform. Initialization, readout and single- and two-qubit gates have been demonstrated in various quantum-dot-based qubit representations. However, as seen with small-scale demonstrations of quantum computers using other types of qubit, combining these elements leads to challenges related to qubit crosstalk, state leakage, calibration and control hardware. Here we overcome these challenges by using carefully designed control techniques to demonstrate a programmable two-qubit quantum processor in a silicon device that can perform the Deutsch-Josza algorithm and the Grover search algorithm-canonical examples of quantum algorithms that outperform their classical analogues. We characterize the entanglement in our processor by using quantum-state tomography of Bell states, measuring state fidelities of 85-89 per cent and concurrences of 73-82 per cent. These results pave the way for larger-scale quantum computers that use spins confined to quantum dots.

Characterization of a gate-defined double quantum dot in a Si/SiGe nanomembrane.

We report the fabrication and characterization of a gate-defined double quantum dot formed in a Si/SiGe nanomembrane. In the past, all gate-defined quantum dots in Si/SiGe heterostructures were formed on top of strain-graded virtual substrates. The strain grading process necessarily introduces misfit dislocations into a heterostructure, and these defects introduce lateral strain inhomogeneities, mosaic tilt, and threading dislocations. The use of a SiGe nanomembrane as the virtual substrate enables the strain relaxation to be entirely elastic, eliminating the need for misfit dislocations. However, in this approach the formation of the heterostructure is more complicated, involving two separate epitaxial growth procedures separated by a wet-transfer process that results in a buried non-epitaxial interface 625 nm from the quantum dot. We demonstrate that in spite of this buried interface in close proximity to the device, a double quantum dot can be formed that is controllable enough to enable tuning of the inter-dot tunnel coupling, the identification of spin states, and the measurement of a singlet-to-triplet transition as a function of an applied magnetic field.

Use of body linear measurements to estimate liveweight of crossbred dairy cattle in smallholder farms in Kenya.

Body linear measurements, and specifically heart girth (HG), have been shown to be useful predictors of cattle liveweight. To test the accuracy of body linear measurements for predicting liveweight, crossbred dairy cattle of different genotypes were measured and weighed. A total of 352 mature cows and 100 heifers were weighed using an electronic weighing scale and measurements of HG, body length, height at withers were taken using an ordinary measuring tape and body condition scored (BCS) using a five-point scale. The animals were grouped according to genotype and age. Genotype classification was undertaken from farmer recall and by visual appraisal as 40-60, 61-80 or 81-100 % exotic (non-indigenous). Age classification was simply as mature cows or heifers. Liveweight of the animals ranged from 102 to 433 kg. Liveweight was strongly correlated with HG (r = 0.84) and body condition scores (r = 0.70) and moderately correlated with body length (r = 0.64) and height at withers (0.61). Regressing LW on HG measurements gave statistically significant (P < 0.01) equations with R(2) ranging from of 0.53 to 0.78 and residual standard deviation ranging from 18.11 to 40.50 kg. The overall model developed (adjusted R(2) = 0.71) had a prediction error of 26 kg (or 11 % of the mean) and predicted LW of over 95 % of crossbred dairy cattle in the range of 100-450 kg, regardless of age and breed group. Including BCS in the model slightly improved the model fit but not the prediction error. It was concluded that the model can be useful in making general management decisions in smallholder farms.

Familial partial lipodystrophy linked to a novel peroxisome proliferator activator receptor -γ (PPARG) mutation, H449L: a comparison of people with this mutation and those with classic codon 482 Lamin A/C (LMNA) mutations.

AIMS: To describe the phenotype associated with a novel heterozygous missense PPARG mutation discovered in a Turkish family and to compare the fat distribution and metabolic characteristics of subjects with the peroxisome proliferator activator receptor -γ (PPARG) mutation with those of a cluster of patients with familial partial lipodystrophy with classic codon 482 Lamin A/C (LMNA) mutations. METHODS: The study involved four subjects with familial partial lipodystrophy who had a novel PPARG mutation (H449L) and six subjects with classic codon 482 LMNA mutations (R482W). RESULTS: Compared with subjects with LMNA R482W mutation, fat loss was generally less prominent in subjects with the PPARG H449L mutation. Partial fat loss was limited to the extremities, whilst truncal fat mass was preserved. The PPARG H449L mutation was associated with insulin resistance, hypertriglyceridaemia and non-alcoholic fatty liver disease in all affected subjects, but the severity was variable. Three out of four mutation carriers had overt diabetes or impaired glucose tolerance. Pioglitazone therapy in these three individuals resulted in a modest improvement in their metabolic control, and regular menstrual cycles in the two female subjects. CONCLUSIONS: We suggest that relatively modest fat loss in patients with PPARG mutations may render the recognition of the syndrome more difficult in routine clinical practice. The PPARG H449L mutation is associated with insulin resistance and metabolic complications, but their severity is variable among the affected subjects.

Second-Harmonic Coherent Driving of a Spin Qubit in a Si/SiGe Quantum Dot.

We demonstrate coherent driving of a single electron spin using second-harmonic excitation in a Si/SiGe quantum dot. Our estimates suggest that the anharmonic dot confining potential combined with a gradient in the transverse magnetic field dominates the second-harmonic response. As expected, the Rabi frequency depends quadratically on the driving amplitude, and the periodicity with respect to the phase of the drive is twice that of the fundamental harmonic. The maximum Rabi frequency observed for the second harmonic is just a factor of 2 lower than that achieved for the first harmonic when driving at the same power. Combined with the lower demands on microwave circuitry when operating at half the qubit frequency, these observations indicate that second-harmonic driving can be a useful technique for future quantum computation architectures.

Identifying single electron charge sensor events using wavelet edge detection.

The operation of solid-state qubits often relies on single-shot readout using a nanoelectronic charge sensor, and the detection of events in a noisy sensor signal is crucial for high fidelity readout of such qubits. The most common detection scheme, comparing the signal to a threshold value, is accurate at low noise levels but is not robust to low-frequency noise and signal drift. We describe an alternative method for identifying charge sensor events using wavelet edge detection. The technique is convenient to use and we show that, with realistic signals and a single tunable parameter, wavelet detection can outperform thresholding and is significantly more tolerant to 1/f and low-frequency noise.

Microwave-driven coherent operation of a semiconductor quantum dot charge qubit.

An intuitive realization of a qubit is an electron charge at two well-defined positions of a double quantum dot. This qubit is simple and has the potential for high-speed operation because of its strong coupling to electric fields. However, charge noise also couples strongly to this qubit, resulting in rapid dephasing at all but one special operating point called the 'sweet spot'. In previous studies d.c. voltage pulses have been used to manipulate semiconductor charge qubits but did not achieve high-fidelity control, because d.c. gating requires excursions away from the sweet spot. Here, by using resonant a.c. microwave driving we achieve fast (greater than gigahertz) and universal single qubit rotations of a semiconductor charge qubit. The Z-axis rotations of the qubit are well protected at the sweet spot, and we demonstrate the same protection for rotations about arbitrary axes in the X-Y plane of the qubit Bloch sphere. We characterize the qubit operation using two tomographic approaches: standard process tomography and gate set tomography. Both methods consistently yield process fidelities greater than 86% with respect to a universal set of unitary single-qubit operations.

Clinical and molecular characterization of a novel PLIN1 frameshift mutation identified in patients with familial partial lipodystrophy.

Perilipin 1 is a lipid droplet coat protein predominantly expressed in adipocytes, where it inhibits basal and facilitates stimulated lipolysis. Loss-of-function mutations in the PLIN1 gene were recently reported in patients with a novel subtype of familial partial lipodystrophy, designated as FPLD4. We now report the identification and characterization of a novel heterozygous frameshift mutation affecting the carboxy-terminus (439fs) of perilipin 1 in two unrelated families. The mutation cosegregated with a similar phenotype including partial lipodystrophy, severe insulin resistance and type 2 diabetes, extreme hypertriglyceridemia, and nonalcoholic fatty liver disease in both families. Poor metabolic control despite maximal medical therapy prompted two patients to undergo bariatric surgery, with remarkably beneficial consequences. Functional studies indicated that expression levels of the mutant protein were lower than wild-type protein, and in stably transfected preadipocytes the mutant protein was associated with smaller lipid droplets. Interestingly, unlike the previously reported 398 and 404 frameshift mutants, this variant binds and stabilizes ABHD5 expression but still fails to inhibit basal lipolysis as effectively as wild-type perilipin 1. Collectively, these findings highlight the physiological need for exquisite regulation of neutral lipid storage within adipocyte lipid droplets, as well as the possible metabolic benefits of bariatric surgery in this serious disease.

Two-axis control of a singlet-triplet qubit with an integrated micromagnet.

The qubit is the fundamental building block of a quantum computer. We fabricate a qubit in a silicon double-quantum dot with an integrated micromagnet in which the qubit basis states are the singlet state and the spin-zero triplet state of two electrons. Because of the micromagnet, the magnetic field difference ΔB between the two sides of the double dot is large enough to enable the achievement of coherent rotation of the qubit's Bloch vector around two different axes of the Bloch sphere. By measuring the decay of the quantum oscillations, the inhomogeneous spin coherence time T2* is determined. By measuring T2* at many different values of the exchange coupling J and at two different values of ΔB, we provide evidence that the micromagnet does not limit decoherence, with the dominant limits on T2* arising from charge noise and from coupling to nuclear spins.

Electrical control of a long-lived spin qubit in a Si/SiGe quantum dot.

Nanofabricated quantum bits permit large-scale integration but usually suffer from short coherence times due to interactions with their solid-state environment. The outstanding challenge is to engineer the environment so that it minimally affects the qubit, but still allows qubit control and scalability. Here, we demonstrate a long-lived single-electron spin qubit in a Si/SiGe quantum dot with all-electrical two-axis control. The spin is driven by resonant microwave electric fields in a transverse magnetic field gradient from a local micromagnet, and the spin state is read out in the single-shot mode. Electron spin resonance occurs at two closely spaced frequencies, which we attribute to two valley states. Thanks to the weak hyperfine coupling in silicon, a Ramsey decay timescale of 1 µs is observed, almost two orders of magnitude longer than the intrinsic timescales in GaAs quantum dots, whereas gate operation times are comparable to those reported in GaAs. The spin echo decay time is ~40 µs, both with one and four echo pulses, possibly limited by intervalley scattering. These advances strongly improve the prospects for quantum information processing based on quantum dots.

Quantum control and process tomography of a semiconductor quantum dot hybrid qubit.

The similarities between gated quantum dots and the transistors in modern microelectronics--in fabrication methods, physical structure and voltage scales for manipulation--have led to great interest in the development of quantum bits (qubits) in semiconductor quantum dots. Although quantum dot spin qubits have demonstrated long coherence times, their manipulation is often slower than desired for important future applications, such as factoring. Furthermore, scalability and manufacturability are enhanced when qubits are as simple as possible. Previous work has increased the speed of spin qubit rotations by making use of integrated micromagnets, dynamic pumping of nuclear spins or the addition of a third quantum dot. Here we demonstrate a qubit that is a hybrid of spin and charge. It is simple, requiring neither nuclear-state preparation nor micromagnets. Unlike previous double-dot qubits, the hybrid qubit enables fast rotations about two axes of the Bloch sphere. We demonstrate full control on the Bloch sphere with π-rotation times of less than 100 picoseconds in two orthogonal directions, which is more than an order of magnitude faster than any other double-dot qubit. The speed arises from the qubit's charge-like characteristics, and its spin-like features result in resistance to decoherence over a wide range of gate voltages. We achieve full process tomography in our electrically controlled semiconductor quantum dot qubit, extracting high fidelities of 85 per cent for X rotations (transitions between qubit states) and 94 per cent for Z rotations (phase accumulation between qubit states).