Probing single electrons across 300-mm spin qubit wafers.

Building a fault-tolerant quantum computer will require vast numbers of physical qubits. For qubit technologies based on solid-state electronic devices1-3, integrating millions of qubits in a single processor will require device fabrication to reach a scale comparable to that of the modern complementary metal-oxide-semiconductor (CMOS) industry. Equally important, the scale of cryogenic device testing must keep pace to enable efficient device screening and to improve statistical metrics such as qubit yield and voltage variation. Spin qubits1,4,5 based on electrons in Si have shown impressive control fidelities6-9 but have historically been challenged by yield and process variation10-12. Here we present a testing process using a cryogenic 300-mm wafer prober13 to collect high-volume data on the performance of hundreds of industry-manufactured spin qubit devices at 1.6 K. This testing method provides fast feedback to enable optimization of the CMOS-compatible fabrication process, leading to high yield and low process variation. Using this system, we automate measurements of the operating point of spin qubits and investigate the transitions of single electrons across full wafers. We analyse the random variation in single-electron operating voltages and find that the optimized fabrication process leads to low levels of disorder at the 300-mm scale. Together, these results demonstrate the advances that can be achieved through the application of CMOS-industry techniques to the fabrication and measurement of spin qubit devices.

Engineering Spin-Orbit Interactions in Silicon Qubits at the Atomic-Scale.

Spin-orbit interactions arise whenever the bulk inversion symmetry and/or structural inversion symmetry of a crystal is broken providing a bridge between a qubit's spin and orbital degree of freedom. While strong interactions can facilitate fast qubit operations by all-electrical control, they also provide a mechanism to couple charge noise thereby limiting qubit lifetimes. Previously believed to be negligible in bulk silicon, recent silicon nano-electronic devices have shown larger than bulk spin-orbit coupling strengths from Dresselhaus and Rashba couplings. Here, it is shown that with precision placement of phosphorus atoms in silicon along the [110] direction (without inversion symmetry) or [111] direction (with inversion symmetry), a wide range of Dresselhaus and Rashba coupling strength can be achieved from zero to 1113 × 10-13eV-cm. It is shown that with precision placement of phosphorus atoms, the local symmetry (C2v, D2d, and D3d) can be changed to engineer spin-orbit interactions. Since spin-orbit interactions affect both qubit operation and lifetimes, understanding their impact is essential for quantum processor design.

Accessibility and Utilization of Telehealth Services During the COVID-19 Pandemic Among Medicare Beneficiaries by Diabetes Status.

Due to the influence types of telehealth services (i.e., phone and/or video) can have on patient care and outcomes, we sought to examine factors associated with the types of telehealth services offered and used among Medicare beneficiaries. We analyzed the Medicare Current Beneficiary Survey COVID-19 Public Use File (N = 1,403 and N = 2,218 for individuals with and without diabetes, respectively) and performed multinomial logit models to examine factors (e.g., sociodemographics, comorbidities, digital access/knowledge) associated with types of telehealth services offered and used among beneficiaries aged ≥65 years by diabetes status. Medicare beneficiaries seemed to prefer using telehealth via phone than video. Regardless of diabetes status, having not previously participated in video or voice calls or conferencing can be a barrier to telehealth being offered and used via video for beneficiaries. For older adults with diabetes, disparities in accessibility of telehealth via video by income and languages spoken other than English were observed. [Research in Gerontological Nursing, 16(3), 134-146.].

Factors Associated with Mental Health of Medicare Beneficiaries During the COVID-19 Pandemic.

OBJECTIVES: This study examined factors associated with the mental health of Medicare beneficiaries during the COVID-19 pandemic. METHODS: The Medicare Current Beneficiary Survey COVID-19 Supplement administered in the Fall of 2020 of beneficiaries aged ≥65 years was analyzed (n = 6,173). A survey-weighted logistic model, adjusted for socio-demographics and comorbidities, was performed to examine factors (e.g., accessibility of medical/daily needs, financial security, and social connectivity) associated with stress/anxiety. RESULTS: Of Medicare beneficiaries, 40.8% reported feeling more stressed/anxious during the pandemic. Factors that were associated with this increased stress/anxiety include the inability to get home supplies (95% CI [3.4%, 16.5%]) or a doctor's appointment (95% CI [1.7%, 20.7%]), feeling less financially secure (95% CI [23.1%, 33.2%]) or socially connected (95% CI [19.1%, 25.6%]), and being female (95% CI [7.2%, 12.2%]), when compared with their respective counterparts. Non-Hispanic blacks were less likely to report feeling more stressed/anxious than non-Hispanic whites (95% CI [-19.9%, -9.0%]). CONCLUSIONS: Our findings highlight that beneficiaries' mental health was adversely influenced by the pandemic, particularly in those who felt financially insecure and socially disconnected. CLINICAL IMPLICATIONS: It is warranted to screen at risk beneficiaries for stress/anxiety during Medicare wellness visits and advocate for programs to reduce those risk factors.

The Use of Exchange Coupled Atom Qubits as Atomic-Scale Magnetic Field Sensors.

Phosphorus atoms in silicon offer a rich quantum computing platform where both nuclear and electron spins can be used to store and process quantum information. While individual control of electron and nuclear spins has been demonstrated, the interplay between them during qubit operations has been largely unexplored. This study investigates the use of exchange-based operation between donor bound electron spins to probe the local magnetic fields experienced by the qubits with exquisite precision at the atomic scale. To achieve this, coherent exchange oscillations are performed between two electron spin qubits, where the left and right qubits are hosted by three and two phosphorus donors, respectively. The frequency spectrum of exchange oscillations shows quantized changes in the local magnetic fields at the qubit sites, corresponding to the different hyperfine coupling between the electron and each of the qubit-hosting nuclear spins. This ability to sense the hyperfine fields of individual nuclear spins using the exchange interaction constitutes a unique metrology technique, which reveals the exact crystallographic arrangements of the phosphorus atoms in the silicon crystal for each qubit. The detailed knowledge obtained of the local magnetic environment can then be used to engineer hyperfine fields in multi-donor qubits for high-fidelity two-qubit gates.

Ramped measurement technique for robust high-fidelity spin qubit readout.

State preparation and measurement of single-electron spin qubits typically rely on spin-to-charge conversion where a spin-dependent charge transition of the electron is detected by a coupled charge sensor. For high-fidelity, fast readout, this process requires that the qubit energy is much larger than the temperature of the system limiting the temperature range for measurements. Here, we demonstrate an initialization and measurement technique that involves voltage ramps rather than static voltages allowing us to achieve state-to-charge readout fidelities above 99% for qubit energies almost half that required by traditional methods. This previously unidentified measurement technique is highly relevant for achieving high-fidelity electron spin readout at higher temperature operation and offers a number of pragmatic benefits compared to traditional energy-selective readout such as real-time dynamic feedback and minimal alignment procedures.

Exploiting a Single-Crystal Environment to Minimize the Charge Noise on Qubits in Silicon.

Electron spins in silicon offer a competitive, scalable quantum-computing platform with excellent single-qubit properties. However, the two-qubit gate fidelities achieved so far have fallen short of the 99% threshold required for large-scale error-corrected quantum computing architectures. In the past few years, there has been a growing realization that the critical obstacle in meeting this threshold in semiconductor qubits is charge noise arising from the qubit environment. In this work, a notably low level of charge noise of S0  = 0.0088 ± 0.0004 µeV2 Hz-1 is demonstrated using atom qubits in crystalline silicon, achieved by separating the qubits from surfaces and interface states. The charge noise is measured using both a single electron transistor and an exchange-coupled qubit pair that collectively provide a consistent charge noise spectrum over four frequency decades, with the noise level S0 being an order of magnitude lower than previously reported. Low-frequency detuning noise, set by the total measurement time, is shown to be the dominant dephasing source of two-qubit exchange oscillations. With recent advances in fast (≈µs) single-shot readout, it is shown that by reducing the total measurement time to ≈1 s, 99.99% two-qubit S W A P gate fidelities can be achieved in single-crystal atom qubits in silicon.

Factors that predict complex reconstructions in facial skin cancer surgery.

There is a paucity of high-quality evidence and guidelines on the prediction of skin defect reconstruction, and the type of repair rests on the operating surgeon's experience and skill. Mismatches between planning and execution can have negative consequences on resources, staff, and patient counseling. To investigate the factors that predict complex reconstruction in facial skin cancer surgery, we performed a retrospective study collecting information on the several parameters that may affect the method of reconstruction. A total of 325 cases were included. Only the factors tumor size (Z = 2.54; P < .05) and predicted repair plan (Z = 2.73; P < .01) were found to be significant predictors of complex repairs. When broken down by site and size, only the nose, scalp, and temple demonstrated a significant correlation between tumor size and the need for complex repairs. Clinical judgment at the time of initial examination is by far the greatest predictor of complex repairs. This occurs even when clinicians have heterogeneous surgical skills, and most are not technically versed in complex repairs. Increasing tumor size was also found to be an independent risk factor albeit only at certain body sites such as the temple, scalp, and nose.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Spin read-out in atomic qubits in an all-epitaxial three-dimensional transistor.

The realization of the surface code for topological error correction is an essential step towards a universal quantum computer1-3. For single-atom qubits in silicon4-7, the need to control and read out qubits synchronously and in parallel requires the formation of a two-dimensional array of qubits with control electrodes patterned above and below this qubit layer. This vertical three-dimensional device architecture8 requires the ability to pattern dopants in multiple, vertically separated planes of the silicon crystal with nanometre precision interlayer alignment. Additionally, the dopants must not diffuse or segregate during the silicon encapsulation. Critical components of this architecture-such as nanowires9, single-atom transistors4 and single-electron transistors10-have been realized on one atomic plane by patterning phosphorus dopants in silicon using scanning tunnelling microscope hydrogen resist lithography11,12. Here, we extend this to three dimensions and demonstrate single-shot spin read-out with 97.9% measurement fidelity of a phosphorus dopant qubit within a vertically gated single-electron transistor with <5 nm interlayer alignment accuracy. Our strategy ensures the formation of a fully crystalline transistor using just two atomic species: phosphorus and silicon.

Navigating the Phenotype Frontier: The Monarch Initiative.

The principles of genetics apply across the entire tree of life. At the cellular level we share biological mechanisms with species from which we diverged millions, even billions of years ago. We can exploit this common ancestry to learn about health and disease, by analyzing DNA and protein sequences, but also through the observable outcomes of genetic differences, i.e. phenotypes. To solve challenging disease problems we need to unify the heterogeneous data that relates genomics to disease traits. Without a big-picture view of phenotypic data, many questions in genetics are difficult or impossible to answer. The Monarch Initiative (https://monarchinitiative.org) provides tools for genotype-phenotype analysis, genomic diagnostics, and precision medicine across broad areas of disease.

Targeting Tumors with Small Molecule Peptides.

Chemotherapeutic treatment of cancers is a challenging endeavor, hindered by poor selectivity towards tumorous tissues over healthy ones. Preferentially delivering a given drug to tumor sites necessitates the use of targeting elements, of which there are a wide range in development. In this Review, we highlight recent examples of peptide-based targeting ligands that have been exploited to selectively deliver a chemotherapeutic payload to specific tumor-associated sites such as the vasculature, lymphatics, or cell surface. The advantages and limitations of such approaches will be discussed with a view to potential future development. Additionally, we will also examine how peptide-based ligands can be used diagnostically in the detection and characterization of cancers through their incorporation into imaging agents.