Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction.

Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reservoir, in which reservoir noise is used as a resource to generate expressive, nonlinear signals that are efficiently learned with a single linear output layer. We address the need for quantum reservoir tuning with a novel and generally applicable approach to quantum circuit parameterization, in which tunable noise models are programmed to the quantum reservoir circuit to be fully controlled for effective optimization. Our systematic approach also involves reductions in quantum reservoir circuits in the number of qubits and entanglement scheme complexity. We show that with only a single noise model and small memory capacities, excellent simulation results were obtained on nonlinear benchmarks that include the Mackey-Glass system for 100 steps ahead in the challenging chaotic regime.

Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank.

Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank resource, a wide range of biochemistry markers were measured in all participants with an available biological sample. Here, we describe the approaches UK Biobank has taken to minimise error related to sample collection, processing, retrieval and assay measurement. Methods: During routine quality control checks, the laboratory team observed that some assay results were lower than expected for samples acquired during certain time periods. Analyses were undertaken to identify and correct for the unexpected dilution identified during sample processing, and for expected error caused by laboratory drift of assay results. Results: The vast majority (92%) of biochemistry serum assay results were assessed to be not materially affected by dilution, with an estimated difference in concentration of less than 1% (i.e. either lower or higher) than that expected if the sample were unaffected; 8.3% were estimated to be diluted by up to 10%; very few samples appeared to be diluted more than this. Biomarkers measured in urine (creatinine, microalbumin, sodium, potassium) and red blood cells (HbA1c) were not affected. In order to correct for laboratory variation over the assay period, all assay results were adjusted for date of assay, with the exception of those that had a high biological coefficient of variation or evident seasonal variability: vitamin D, lipoprotein (a), gamma glutamyltransferase, C-reactive protein and rheumatoid factor. Conclusions: Rigorous approaches related to sample collection, processing, retrieval, assay measurement and data analysis have been taken to mitigate the impact of both systematic and random variation in epidemiological analyses that use the biochemistry assay data in UK Biobank.

Pathways of family influence: alcohol use and disordered eating in daughters.

Models of addiction etiology and treatment emphasize the influence of family-of-origin experiences. Using two addiction-related coping behaviors (ARCBs) common among college women (i.e., problematic alcohol use, disordered eating), we examined whether ARCBs in parents related to matching ARCBs in college women offspring. We expected that matching parental ARCBs would relate more strongly to the ARCBs in offspring than more distal/general family factors. A total of 197 college women completed measures of family dynamics, parental difficulties with alcohol, family focus on appearance and weight, personal difficulties with alcohol use, and disordered eating. A significant indirect effect for family dysfunction on disordered eating and alcohol-related problems was found. That is, family relationship difficulties predicted parents' ARCBs, which predicted matching ARCBs in participants (e.g., parental alcohol problems predicted participant alcohol problems). Matched parental ARCBs were better predictors of participants' ARCBs than more general/distal family factors and non-matched ARCBs. Specifically, path analysis and testing of beta weights supported specificity of parental ARCBs for predicting matching offspring ARCBs. Implications of study findings for tailoring prevention efforts are discussed.

Quantum walks of correlated photon pairs in two-dimensional waveguide arrays.

We demonstrate quantum walks of correlated photons in a two-dimensional network of directly laser written waveguides coupled in a "swiss cross" arrangement. The correlated detection events show high-visibility quantum interference and unique composite behavior: strong correlation and independence of the quantum walkers, between and within the planes of the cross. Violations of a classically defined inequality, for photons injected in the same plane and in orthogonal planes, reveal nonclassical behavior in a nonplanar structure.

Two-photon quantum interference in integrated multi-mode interference devices.

Multi-mode interference (MMI) devices fabricated in silicon oxynitride (SiON) with a refractive index contrast of 2.4% provide a highly compact and stable platform for multi-photon non-classical interference. MMI devices can introduce which-path information for photons propagating in the multi-mode section which can result in degradation of this non-classical interference. We theoretically derive the visibility of quantum interference of two photons injected in a MMI device and predict near unity visibility for compact SiON devices. We complement the theoretical results by experimentally demonstrating visibilities of up to 97.7% in 2×2 MMI devices without the requirement of narrow-band photons.