Machine Learning-Assisted Precision Manufacturing of Atom Qubits in Silicon.

Donor-based qubits in silicon, manufactured using scanning tunneling microscope (STM) lithography, provide a promising route to realizing full-scale quantum computing architectures. This is due to the precision of donor placement, long coherence times, and scalability of the silicon material platform. The properties of multiatom quantum dot qubits, however, depend on the exact number and location of the donor atoms within the quantum dots.

A Stabilizer Framework for the Contextual Subspace Variational Quantum Eigensolver and the Noncontextual Projection Ansatz.

Quantum chemistry is a promising application for noisy intermediate-scale quantum (NISQ) devices. However, quantum computers have thus far not succeeded in providing solutions to problems of real scientific significance, with algorithmic advances being necessary to fully utilize even the modest NISQ machines available today. We discuss a method of ground state energy estimation predicated on a partitioning of the molecular Hamiltonian into two parts: one that is and can be solved classically, supplemented by a component that yields quantum corrections obtained via a Variational Quantum Eigensolver (VQE) routine.

Is vaccine confidence an unexpected victim of the COVID-19 pandemic?

Vaccines are among the safest and most effective primary prevention measures. Thanks to the synergistic global efforts of research institutions, pharmaceutical companies and national health services, COVID-19 vaccination campaigns were successfully rolled out less than a year after the start of the pandemic. While the unprecedented speed of development and approval of COVID-19 vaccines has been applauded as a public health success story, it also spurred considerable controversy and hesitancy even amongst individuals that did not previously hold anti-vaccination stances.

12.6 dB squeezed light at 1550 nm from a bow-tie cavity for long-term high duty cycle operation.

Squeezed states are an interesting class of quantum states that have numerous applications. This work presents the design, characterization, and operation of a bow-tie optical parametric amplifier (OPA) for squeezed vacuum generation. We report the high duty cycle operation and long-term stability of the system that makes it suitable for post-selection based continuous-variable quantum information protocols, cluster-state quantum computing, quantum metrology, and potentially gravitational wave detectors.

Postgraduate medical education quality metrics panels can be enhanced by including learner outcomes.

Postgraduate medical education (PME) quality assurance at Health Education England (HEE) currently relies upon survey data. As no one metric can reflect all aspects of training, and each has its limitations, additional metrics should be explored. At HEE (West Midlands), we explored the use of learner outcomes, speciality examination pass rates and Annual Review of Competence Progression (ARCP) outcomes, as quality metrics.

Multiparameter optimisation of a magneto-optical trap using deep learning.

Machine learning based on artificial neural networks has emerged as an efficient means to develop empirical models of complex systems. Cold atomic ensembles have become commonplace in laboratories around the world, however, many-body interactions give rise to complex dynamics that preclude precise analytic optimisation of the cooling and trapping process. Here, we implement a deep artificial neural network to optimise the magneto-optic cooling and trapping of neutral atomic ensembles.

A Comparison of the Bravyi-Kitaev and Jordan-Wigner Transformations for the Quantum Simulation of Quantum Chemistry.

The ability to perform classically intractable electronic structure calculations is often cited as one of the principal applications of quantum computing. A great deal of theoretical algorithmic development has been performed in support of this goal. Most techniques require a scheme for mapping electronic states and operations to states of and operations upon qubits.

High-performance Raman memory with spatio-temporal reversal.

A number of techniques exist to use an ensemble of atoms as a quantum memory for light. Many of these propose to use backward retrieval as a way to improve the storage and recall efficiency. We report on a demonstration of an off-resonant Raman memory that uses backward retrieval to achieve an efficiency of 65 ± 6% at a storage time of one pulse duration.

Structural and energetic evidence for highly peptide-specific tumor antigen targeting via allo-MHC restriction.

Immunotherapies targeting peptides presented by allogeneic MHC molecules offer the prospect of circumventing tolerance to key tumor-associated self-antigens. However, the degree of antigen specificity mediated by alloreactive T cells, and their ability to discriminate normal tissues from transformed cells presenting elevated antigen levels, is poorly understood. We examined allorecognition of an HLA-A2-restricted Hodgkin's lymphoma-associated antigen and were able to isolate functionally antigen-specific allo-HLA-A2-restricted T cells from multiple donors.

Retroviral transfer of a dominant TCR prevents surface expression of a large proportion of the endogenous TCR repertoire in human T cells.

The latent membrane protein-2 (LMP2) of Epstein-Barr virus is a potential target for T-cell receptor (TCR) gene therapy of Hodgkin lymphoma and nasopharyngeal carcinoma. Here, we modified a human leukocyte antigen-A2-restricted, LMP2-specific TCR to achieve efficient expression following retroviral TCR gene transfer. The unmodified TCR was poorly expressed in primary human T cells, suggesting that it competed inefficiently with endogenous TCR chains for cell surface expression.

WT1-targeted immunotherapy of leukaemia.

Since malignant cells are derived from normal cells, many tumour-associated antigens are also expressed in normal tissues. For examples, WT1 is expressed at elevated levels in most leukaemias, but it is also expressed at reduced levels in normal CD34+ haematopoietic stem cells and in progenitor cells of other tissues. Antigen expression in normal tissues is likely to trigger immunological tolerance and thus blunt T cell responses.

Use of the allogeneic TCR repertoire to enhance anti-tumor immunity.

It is well established that antigen-specific T lymphocytes can inhibit tumor growth in humans and in mice, leading to complete tumor elimination in some cases. However, in many cases T cell immunity is unable to successfully control tumor progression. Since tumors are derived from normal tissues, most antigens are shared with normal tissues, although expression levels are usually elevated in malignant cells.