Pairing and Phase Coherence in High Temperature Superconductors

Mobile holes in an antiferromagnetic insulator form a slowly fluctuating array of quasi one-dimensional metallic stripes, which induce a spin gap or pseudogap in the intervening Mott-insulating regions. The mobile holes on an individual stripe acquire a spin gap via pair hopping between the stripe and its environment; i.e. via a magnetic analog of the usual superconducting proximity effect. This process is the analog of pairing in conventional superconductors. At non-vanishing stripe densities, Josephson coupling between stripes produces a dimensional crossover to a state with long-range superconducting phase coherence. In contrast to conventional superconductors, the superconducting state is characterised by a high density of (spin) pairs, but the phase stiffness, which is determined by the density and mobility of holes on the stripes, is very low.Comment: 4 pages. Proceedings of MMS-High Temperature Superconductivity, V (1997) To be published in Physica

Phonon and Magnetic Neutron Scattering at 41 Mev in YBa₂Cu₃O₇

We report inelastic neutron scattering measurements at excitation energies Latin small letter h with strokeω~41 meV in YBa2Cu3O7. We separate magnetic and phonon contributions to the scattering cross section by a detailed analysis of the momentum dependence of the scattered intensity. The previously reported broad peak around q=(π/a,π/a) in the normal state can be entirely accounted for by a phonon which primarily involves vibrations of the in-plane oxygen. Magnetic scattering centered around 41 meV and q=(π/a,π/a) appears in the superconducting state only. Theoretical implications of these findings are discussed

PetFMM--A dynamically load-balancing parallel fast multipole library

Fast algorithms for the computation of $N$-body problems can be broadly classified into mesh-based interpolation methods, and hierarchical or multiresolution methods. To this last class belongs the well-known fast multipole method (FMM), which offers O(N) complexity. This paper presents an extensible parallel library for $N$-body interactions utilizing the FMM algorithm, built on the framework of PETSc. A prominent feature of this library is that it is designed to be extensible, with a view to unifying efforts involving many algorithms based on the same principles as the FMM and enabling easy development of scientific application codes. The paper also details an exhaustive model for the computation of tree-based $N$-body algorithms in parallel, including both work estimates and communications estimates. With this model, we are able to implement a method to provide automatic, a priori load balancing of the parallel execution, achieving optimal distribution of the computational work among processors and minimal inter-processor communications. Using a client application that performs the calculation of velocity induced by $N$ vortex particles, ample verification and testing of the library was performed. Strong scaling results are presented with close to a million particles in up to 64 processors, including both speedup and parallel efficiency. The library is currently able to achieve over 85% parallel efficiency for 64 processors. The software library is open source under the PETSc license; this guarantees the maximum impact to the scientific community and encourages peer-based collaboration for the extensions and applications.Comment: 28 pages, 9 figure

A Generalizable Deep Learning System for Cardiac MRI

Cardiac MRI allows for a comprehensive assessment of myocardial structure, function, and tissue characteristics. Here we describe a foundational vision system for cardiac MRI, capable of representing the breadth of human cardiovascular disease and health. Our deep learning model is trained via self-supervised contrastive learning, by which visual concepts in cine-sequence cardiac MRI scans are learned from the raw text of the accompanying radiology reports. We train and evaluate our model on data from four large academic clinical institutions in the United States. We additionally showcase the performance of our models on the UK BioBank, and two additional publicly available external datasets. We explore emergent zero-shot capabilities of our system, and demonstrate remarkable performance across a range of tasks; including the problem of left ventricular ejection fraction regression, and the diagnosis of 35 different conditions such as cardiac amyloidosis and hypertrophic cardiomyopathy. We show that our deep learning system is capable of not only understanding the staggering complexity of human cardiovascular disease, but can be directed towards clinical problems of interest yielding impressive, clinical grade diagnostic accuracy with a fraction of the training data typically required for such tasks.Comment: 21 page main manuscript, 4 figures. Supplementary Appendix and code will be made available on publicatio

Complementary and alternative medicine for rheumatic diseases: a systematic review of randomized controlled trials

To summarize all good quality randomized controlled trials (RCTs) using complementary and alternative medicine (CAM) interventions in patients with rheumatic diseases.A systematic literature review guided by the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) was performed. We excluded non-English language articles and abstract-only publications. Due to the large number of RCTs identified, we only include "good quality" RCTs with Jadad score of five.We identified 60 good quality RCTs using CAM as intervention for patients with rheumatic diseases: acupuncture (9), Ayurvedic treatment (3), homeopathic treatment (3), electricity (2), natural products (31), megavitamin therapies (8), chiropractic or osteopathic manipulation (3), and energy healing therapy (1). The studies do not seem to suggest a particular type of CAM is effective for all types for rheumatic diseases. However, some CAM interventions appear to be more effective for certain types of rheumatic diseases. Acupuncture appears to be beneficial for osteoarthritis but not rheumatoid arthritis. For the other therapeutic modalities, the evidence base either contains too few trials or contains trials with contradictory findings which preclude any definitive summary. There were only minor adverse reactions observed for CAM interventions presented.We identified 60 good quality RCTs which were heterogenous in terms of interventions, disease, measures used to assess outcomes, and efficacy of CAM interventions. Evidence indicates that some CAM therapies may be useful for rheumatic diseases, such as acupuncture for osteoarthritis. Further research with larger sample size is required for more conclusive evidence regarding efficacy of CAM interventions