Quantum magnetism in the rare-earth pyrosilicates

2021 Spring.Includes bibliographical references.In recent years, both physicists and non-physicists have shown immense interest in the burgeoning field of quantum computing and the possible applications a quantum computer could be used for [1]. However, current quantum computers suffer from issues of decoherence: where the quantum state used for computation is broken by external noise. A new possible avenue for quantum computation would be to use systems that are intrinsically protected from some level of noise, such as topologically protected states. Topological states are inherently protected from small perturbations due to their topological nature. However, to exploit this feature of topologically protected systems more experimental realizations are needed to better understand the underlying mechanisms. This has motivated a surge in interest of condensed matter systems with topologically protected states, such as the quantum spin liquid or fractional quantum Hall systems. A current focus in the subfield of quantum magnetism has focused on using the anisotropic exchange properties of the rare-earth (La - Lu) ions to find quantum spin liquid states, such as the Kitaev spin liquid that is predicted for systems exhibiting a honeycomb lattice. The Kitaev model is an exactly solvable model with a quantum spin liquid ground state, allowing for precise comparison between experiment and theory. Currently, no system has been rigorously proven to be a Kitaev spin liquid but developing our understanding of the underlying physical mechanisms in these systems may allow for the "engineering" of systems that are likely to be Kitaev spin liquids. The desire to understand the underlying mechanisms for quantum spin liquids and other quantum ground states led to the study of the three-honeycomb rare-earth pyrosilicate compounds discussed in this dissertation. The first compound, Yb2Si2O7, is a quantum dimer magnet system with the first evidence for a rare-earth based triplon Bose-Einstein condensate. Inelastic neutronscattering, specific heat, and ultrasound velocity measurements showed a characteristic (for triplon Bose-Einstein condensates) dome in the field-temperature phase diagram and provided evidence for predominantly isotropic exchange, something that is not typically expected for rare-earth systems. Following this work on Yb2Si2O7, our focused turned to two of the Er3+ rare-earth pyrosilicates. The first of these Er3+-based pyrosilicates measured was D-Er2Si2O7. Previous work on D-Er2Si2O7 discovered a highly anisotropic g-tensor, an antiferromagnetic ground state, and modeled some of the magnetic field induced transitions via Monte-Carlo simulations [2]. Our work followed up on this with AC susceptibility, powder inelastic neutron scattering, and powder neutron diffraction measurements to further investigate the ground state of this quantum magnet. Through this we discovered that the system enters an antiferromagnetic state with the spins almost aligned along the previously determined local Ising-axis [2]. The inelastic neutron scattering spectrum show a gapped excitation at zero field - consistent with Ising-like exchange. Transverse field AC susceptibility shows a change in the susceptibility at 2.65 T. These signatures indicate that D-Er2Si2O7 exhibits predominantly Ising-like exchange and that a transition can be induced by a field applied transverse to the Ising axis. This allows for the possibility of D-Er2Si2O7 bein g a new experimental realization of the Transverse Field Ising Model (TFIM). The TFIM is a simple, anisotropic exchange, theoretically tractable model exhibiting quantum criticality with few experimental examples, making new experimental examples of this model highly desired. These intriguing results on D-Er2Si2O7 and Yb2Si2O7 led to an interest in the polymorph formed at lower synthesis temperatures, C-Er2Si2O7, which happens to be isostructural to Yb2Si2O7. Measurements of the neutron diffraction, specific heat, and magnetization/susceptibility in this system allowed for us to determine that C-Er2Si2O7 magnetically orders at 2.3 K into an antiferromagnetic Néel state. While this is the expected ground state for an isotropically exchange coupled honeycomb system, C-Er2Si2O7 does not form a "perfect" honeycomb lattice and it is interesting that C-Er2Si2O7 magnetically orders while Yb2Si2O7 does not. Understanding the ground state for C-Er2Si2O7 will allow for bettering our understanding of Yb2Si2O7 and rare-earth quantum magnet ground states by comparing the properties of the two systems. Overall, the work on these three compounds required numerous experimental techniques, models, and theoretical understanding. It is my hope that the preliminary understanding for these three pyrosilicates will motivate future work within the rare-earth pyrosilicate family and provide a family of rare-earth quantum magnets that can be studied to improve our understanding of novel quantum states

Determining the presence of scour around bridge foundations using vehicle-induced vibrations

Bridge scour is the number one cause of failure in bridges located over waterways. Scour leads to rapid losses in foundation stiffness and can cause sudden collapse. Previous research on bridge health monitoring has used changes in natural frequency to identify damage in bridge beams. The possibility of using a similar approach to identifying scour is investigated in this paper. To assess if this approach is feasible, it is necessary to establish how scour affects the natural frequency of a bridge, and if it is possible to measure changes in frequency using the bridge dynamic response to a passing vehicle. To address these questions, a novel vehicle–bridge–soil interaction (VBSI) model was developed. By carrying out a modal study in this model, it is shown that for a wide range of possible soil states, there is a clear reduction in the natural frequency of the first mode of the bridge with scour. Moreover, it is shown that the response signals on the bridge from vehicular loading are sufficient to allow these changes in frequency to be detected

High-fidelity dimer excitations using quantum hardware

Many-body entangled quantum spin systems exhibit emergent phenomena such as topological quantum spin liquids with distinct excitation spectra accessed in inelastic neutron scattering (INS) experiments. Here we simulate the dynamics of a quantum spin dimer, the basic quantum unit of emergent many-body spin systems. While canonical Trotterization methods require deep circuits precluding long time-scale simulations, we demonstrate 'direct' Resource-Efficient Fast-forwarding (REFF) measurements with short-depth circuits that can be used to capture longer time dynamics on quantum hardware. The temporal evolution of the 2-spin correlation coefficients enabled the calculation of the dynamical structure factor $S(\mathbf{Q},\omega)$ - the key component of the neutron scattering cross-section. We simulate the triplet gap and the triplet splitting of the quantum dimer with sufficient fidelity to compare to experimental neutron data. Our results on current circuit hardware pave an important avenue to benchmark, or even predict, the outputs of the costly INS experiments.Comment: 24 pages, 3 tables, 16 figures, main text and supplementary material

Risk of hospital admission for patients with SARS-CoV-2 variant B.1.1.7: cohort analysis

Abstract: Objective: To evaluate the relation between diagnosis of covid-19 with SARS-CoV-2 variant B.1.1.7 (also known as variant of concern 202012/01) and the risk of hospital admission compared with diagnosis with wild-type SARS-CoV-2 variants. Design: Retrospective cohort analysis. Setting: Community based SARS-CoV-2 testing in England, individually linked with hospital admission data. Participants: 839 278 patients with laboratory confirmed covid-19, of whom 36 233 had been admitted to hospital within 14 days, tested between 23 November 2020 and 31 January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF), a proxy test for the B.1.1.7 variant. Patient data were stratified by age, sex, ethnicity, deprivation, region of residence, and date of positive test. Main outcome measures: Hospital admission between one and 14 days after the first positive SARS-CoV-2 test. Results: 27 710 (4.7%) of 592 409 patients with SGTF variants and 8523 (3.5%) of 246 869 patients without SGTF variants had been admitted to hospital within one to 14 days. The stratum adjusted hazard ratio of hospital admission was 1.52 (95% confidence interval 1.47 to 1.57) for patients with covid-19 infected with SGTF variants, compared with those infected with non-SGTF variants. The effect was modified by age (P<0.001), with hazard ratios of 0.93-1.21 in patients younger than 20 years with versus without SGTF variants, 1.29 in those aged 20-29, and 1.45-1.65 in those aged ≥30 years. The adjusted absolute risk of hospital admission within 14 days was 4.7% (95% confidence interval 4.6% to 4.7%) for patients with SGTF variants and 3.5% (3.4% to 3.5%) for those with non-SGTF variants. Conclusions: The results suggest that the risk of hospital admission is higher for people infected with the B.1.1.7 variant compared with wild-type SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults older than 30 years

Risk of hospital admission for patients with SARS-CoV-2 variant B.1.1.7: cohort analysis

Abstract: Objective: To evaluate the relation between diagnosis of covid-19 with SARS-CoV-2 variant B.1.1.7 (also known as variant of concern 202012/01) and the risk of hospital admission compared with diagnosis with wild-type SARS-CoV-2 variants. Design: Retrospective cohort analysis. Setting: Community based SARS-CoV-2 testing in England, individually linked with hospital admission data. Participants: 839 278 patients with laboratory confirmed covid-19, of whom 36 233 had been admitted to hospital within 14 days, tested between 23 November 2020 and 31 January 2021 and analysed at a laboratory with an available TaqPath assay that enables assessment of S-gene target failure (SGTF), a proxy test for the B.1.1.7 variant. Patient data were stratified by age, sex, ethnicity, deprivation, region of residence, and date of positive test. Main outcome measures: Hospital admission between one and 14 days after the first positive SARS-CoV-2 test. Results: 27 710 (4.7%) of 592 409 patients with SGTF variants and 8523 (3.5%) of 246 869 patients without SGTF variants had been admitted to hospital within one to 14 days. The stratum adjusted hazard ratio of hospital admission was 1.52 (95% confidence interval 1.47 to 1.57) for patients with covid-19 infected with SGTF variants, compared with those infected with non-SGTF variants. The effect was modified by age (P<0.001), with hazard ratios of 0.93-1.21 in patients younger than 20 years with versus without SGTF variants, 1.29 in those aged 20-29, and 1.45-1.65 in those aged ≥30 years. The adjusted absolute risk of hospital admission within 14 days was 4.7% (95% confidence interval 4.6% to 4.7%) for patients with SGTF variants and 3.5% (3.4% to 3.5%) for those with non-SGTF variants. Conclusions: The results suggest that the risk of hospital admission is higher for people infected with the B.1.1.7 variant compared with wild-type SARS-CoV-2, likely reflecting a more severe disease. The higher severity may be specific to adults older than 30 years

Comparative transmission of SARS-CoV-2 Omicron (B.1.1.529) and Delta (B.1.617.2) variants and the impact of vaccination: national cohort study, England

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) rapidly replaced Delta (B.1.617.2) to become dominant in England. Our study assessed differences in transmission between Omicron and Delta using two independent data sources and methods. Omicron and Delta cases were identified through genomic sequencing, genotyping and S-gene target failure in England from 5-11 December 2021. Secondary attack rates for named contacts were calculated in household and non-household settings using contact tracing data, while household clustering was identified using national surveillance data. Logistic regression models were applied to control for factors associated with transmission for both methods. For contact tracing data, higher secondary attack rates for Omicron vs. Delta were identified in households (15.0% vs. 10.8%) and non-households (8.2% vs. 3.7%). For both variants, in household settings, onward transmission was reduced from cases and named contacts who had three doses of vaccine compared to two, but this effect was less pronounced for Omicron (adjusted risk ratio, aRR 0.78 and 0.88) than Delta (aRR 0.62 and 0.68). In non-household settings, a similar reduction was observed only in contacts who had three doses vs. two doses for both Delta (aRR 0.51) and Omicron (aRR 0.76). For national surveillance data, the risk of household clustering, was increased 3.5-fold for Omicron compared to Delta (aRR 3.54 (3.29-3.81)). Our study identified increased risk of onward transmission of Omicron, consistent with its successful global displacement of Delta. We identified a reduced effectiveness of vaccination in lowering risk of transmission, a likely contributor for the rapid propagation of Omicron

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19