Low disorder and high valley splitting in silicon

The electrical characterisation of classical and quantum devices is a critical step in the development cycle of heterogeneous material stacks for semiconductor spin qubits. In the case of silicon, properties such as disorder and energy separation of conduction band valleys are commonly investigated individually upon modifications in selected parameters of the material stack. However, this reductionist approach fails to consider the interdependence between different structural and electronic properties at the danger of optimising one metric at the expense of the others. Here, we achieve a significant improvement in both disorder and valley splitting by taking a co-design approach to the material stack. We demonstrate isotopically-purified, strained quantum wells with high mobility of 3.14(8)$\times$10$^5$ cm$^2$/Vs and low percolation density of 6.9(1)$\times$10$^{10}$ cm$^{-2}$. These low disorder quantum wells support quantum dots with low charge noise of 0.9(3) $\mu$eV/Hz$^{1/2}$ and large mean valley splitting energy of 0.24(7) meV, measured in qubit devices. By striking the delicate balance between disorder, charge noise, and valley splitting, these findings provide a benchmark for silicon as a host semiconductor for quantum dot qubits. We foresee the application of these heterostructures in larger, high-performance quantum processors

Maltreated children use more grammatical negations

Many studies reveal a strong impact of childhood maltreatment on language development, mainly resulting in shorter utterances, less rich vocabulary, or a delay in grammatical complexity. However, different theories suggest the possibility for resilience – a positive adaptation to an otherwise adverse environment – in children who experienced childhood maltreatment. Here, we investigated different measures for language development in spontaneous speech, examining whether childhood maltreatment leads to a language deficit only or whether it can also result in differences in language use due to a possible adaptation to a toxic environment. We compared spontaneous speech during therapeutic peer-play sessions of 32 maltreated and 32 non-maltreated children from the same preschool and equivalent in gender, age (2 to 5 years), home neighborhood, ethnicity, and family income. Maltreatment status was reported by formal child protection reports, and corroborated by independent social service reports. We investigated general language sophistication (i.e., vocabulary, talkativeness, mean length of utterance), as well as grammatical development (i.e., use of plurals, tense, grammatical negations). We found that maltreated and non-maltreated children showed similar sophistication across all linguistic measures, except for the use of grammatical negations. Maltreated children used twice as many grammatical negations as non-maltreated children. The use of this highly complex grammatical structure shows an advanced linguistic skill, which shows that childhood maltreatment does not necessarily lead to a language deficit. The result might indicate the development of a negativity bias in the structure of spontaneous language due to an adaptation to their experiences

Article choice parameters in L2

This article concerns Ionin's (2003) Article Choice Parameter Hypothesis, which proposes a new semantic classification of languages. Article-based languages distribute articles on the basis of either a definiteness or a specificity parameter. Ionin's (2003) study shows that Russian and Korean (article-less) learners of L2 English (article-based) acquire articles fluctuating between a choice based on definiteness or on specificity. Since a choice based on specificity exists neither in L1 nor in L2, Ionin (2003) hypothesizes that Universal Grammar (UG) can play a role in this choice. The present article shows that even if both L1 and L2 are article-based languages, L2 learners fluctuate between a choice of articles based on definiteness or on specificity. Following Ionin, this could mean that such L2 learners fluctuate because they still have access to UG. The authors discuss this option and provide an alternative explanation for the fluctuation

The DREAMS Experiment Onboard the Schiaparelli Module of the ExoMars 2016 Mission: Design, Performances and Expected Results

The first of the two missions foreseen in the ExoMars program was successfully launched on 14th March 2016. It included the Trace Gas Orbiter and the Schiaparelli Entry descent and landing Demonstrator Module. Schiaparelli hosted the DREAMS instrument suite that was the only scientific payload designed to operate after the touchdown. DREAMS is a meteorological station with the capability of measuring the electric properties of the Martian atmosphere. It was a completely autonomous instrument, relying on its internal battery for the power supply. Even with low resources (mass, energy), DREAMS would be able to perform novel measurements on Mars (atmospheric electric field) and further our understanding of the Martian environment, including the dust cycle. DREAMS sensors were designed to operate in a very dusty environment, because the experiment was designed to operate on Mars during the dust storm season (October 2016 in Meridiani Planum). Unfortunately, the Schiaparelli module failed part of the descent and the landing and crashed into the surface of Mars. Nevertheless, several seconds before the crash, the module central computer switched the DREAMS instrument on, and sent back housekeeping data indicating that the DREAMS sensors were performing nominally. This article describes the instrument in terms of scientific goals, design, working principle and performances, as well as the results of calibration and field tests. The spare model is mature and available to fly in a future mission