Scattering and Pairing in Cuprate Superconductors

The origin of the exceptionally strong superconductivity of cuprates remains a subject of debate after more than two decades of investigation. Here we follow a new lead: The onset temperature for superconductivity scales with the strength of the anomalous normal-state scattering that makes the resistivity linear in temperature. The same correlation between linear resistivity and Tc is found in organic superconductors, for which pairing is known to come from fluctuations of a nearby antiferromagnetic phase, and in pnictide superconductors, for which an antiferromagnetic scenario is also likely. In the cuprates, the question is whether the pseudogap phase plays the corresponding role, with its fluctuations responsible for pairing and scattering. We review recent studies that shed light on this phase - its boundary, its quantum critical point, and its broken symmetries. The emerging picture is that of a phase with spin-density-wave order and fluctuations, in broad analogy with organic, pnictide, and heavy-fermion superconductors.Comment: To appear in Volume 1 of the Annual Review of Condensed Matter Physic

Fermi-surface transformation across the pseudogap critical point of the cuprate superconductor La1.6−x_{1.6-x}Nd0.4_{0.4}Srx_{x}CuO4_4

The electrical resistivity $\rho$ and Hall coefficient R$_H$ of the tetragonal single-layer cuprate Nd-LSCO were measured in magnetic fields up to $H = 37.5$ T, large enough to access the normal state at $T \to 0$, for closely spaced dopings $p$ across the pseudogap critical point at $p^\star = 0.235$. Below $p^\star$, both coefficients exhibit an upturn at low temperature, which gets more pronounced with decreasing $p$. Taken together, these upturns show that the normal-state carrier density $n$ at $T = 0$ drops upon entering the pseudogap phase. Quantitatively, it goes from $n = 1 + p$ at $p = 0.24$ to $n = p$ at $p = 0.20$. By contrast, the mobility does not change appreciably, as revealed by the magneto-resistance. The transition has a width in doping and some internal structure, whereby R$_H$ responds more slowly than $\rho$ to the opening of the pseudogap. We attribute this difference to a Fermi surface that supports both hole-like and electron-like carriers in the interval $0.2 < p < p^\star$, with compensating contributions to R$_H$. Our data are in excellent agreement with recent high-field data on YBCO and LSCO. The quantitative consistency across three different cuprates shows that a drop in carrier density from $1 + p$ to $p$ is a universal signature of the pseudogap transition at $T=0$. We discuss the implication of these findings for the nature of the pseudogap phase.Comment: 11 pages, 12 figure

Two types of nematicity in the phase diagram of the cuprate superconductor YBa2_2Cu3_3Oy_y

Nematicity has emerged as a key feature of cuprate superconductors, but its link to other fundamental properties such as superconductivity, charge order and the pseudogap remains unclear. Here we use measurements of transport anisotropy in YBa$_2$Cu$_3$O$_y$ to distinguish two types of nematicity. The first is associated with short-range charge-density-wave modulations in a doping region near $p = 0.12$. It is detected in the Nernst coefficient, but not in the resistivity. The second type prevails at lower doping, where there are spin modulations but no charge modulations. In this case, the onset of in-plane anisotropy - detected in both the Nernst coefficient and the resistivity - follows a line in the temperature-doping phase diagram that tracks the pseudogap energy. We discuss two possible scenarios for the latter nematicity.Comment: 8 pages and 7 figures. Main text and supplementary material now combined into single articl

Hsp70 in mitochondrial biogenesis

The family of hsp70 (70 kilodalton heat shock protein) molecular chaperones plays an essential and diverse role in cellular physiology, Hsp70 proteins appear to elicit their effects by interacting with polypeptides that present domains which exhibit non-native conformations at distinct stages during their life in the cell. In this paper we review work pertaining to the functions of hsp70 proteins in chaperoning mitochondrial protein biogenesis. Hsp70 proteins function in protein synthesis, protein translocation across mitochondrial membranes, protein folding and finally the delivery of misfolded proteins to proteolytic enzymes in the mitochondrial matrix

Effects of exercise and environmental complexity on deficits in trace and contextual fear conditioning produced by neonatal alcohol exposure in rats

In rodents, voluntary exercise and environmental complexity increases hippocampal neurogenesis and reverses spatial learning and long-term potentiation deficits in animals prenatally exposed to alcohol. The present experiment extended these findings to neonatal alcohol exposure and to delay, trace, and contextual fear conditioning. Rats were administered either 5.25g/kg/day alcohol via gastric intubation or received sham-intubations (SI) between Postnatal Day (PD) 4 and 9 followed by either free access to a running wheel on PD 30-41 and housing in a complex environment on PD 42-72 (wheel-running plus environmental complexity; WREC) or conventional social housing (SHSH) from PD 30 to 72. Adult rats (PD 80 +/- 5) received 5 trials/day of a 10-s flashing-light conditioned stimulus (CS) paired with .8mA footshock either immediately (delay conditioning) or after a 10-s trace interval (trace conditioning) for 2 days. Neonatal alcohol exposure impaired context and trace conditioning, but not short-delay conditioning. The WREC intervention did not reverse these deficits, despite increasing context-related freezing in ethanol-exposed and SI animals. (c) 2012 Wiley Periodicals, Inc. Dev Psychobiol 55: 483-495, 201

Mind-Body Skills Groups for Adolescents with Depression in Primary Care: A Pilot Study

Objective: To determine acceptability and preliminary effectiveness of Mind-Body Skills Groups (MBSGs) as a treatment for depressed adolescents in primary care. Methods: A single arm clinical trial was conducted. A 10-week MBSG program was implemented in primary care. Participants completed self-report measures at baseline, post-intervention, and 3-months following the MBSGs. Measures included the Children’s Depression Inventory-2, Suicidal Ideation Questionnaire, Mindful Attention Awareness Scale, Self-Efficacy for Depressed Adolescents, rumination subscale of the Children’s Response Style Questionnaire, and a short acceptability questionnaire. Results: Participants included 43 adolescents. The total depression scores significantly improved following the MBSG intervention and continued to improve significantly from post-treatment to follow-up. Mindfulness, self-efficacy, rumination, and suicidal ideation all had significant improvement following the intervention. Acceptability of the program was strong, and attendance was excellent. Discussion: Preliminary evidence suggests that MBSGs are an acceptable treatment for primary care settings and lead to improved depression symptoms in adolescents.Sandra Eskenazi Mental Health Center and the Herbert Simon Family Foundation (070241-00002B

Anisotropy of the Seebeck Coefficient in the Cuprate Superconductor YBa2_{2}Cu3_{3}Oy_{y}: Fermi-Surface Reconstruction by Bidirectional Charge Order

The Seebeck coefficient $S$ of the cuprate YBa$_{2}$Cu$_{3}$O$_{y}$ was measured in magnetic fields large enough to suppress superconductivity, at hole dopings $p = 0.11$ and $p = 0.12$, for heat currents along the $a$ and $b$ directions of the orthorhombic crystal structure. For both directions, $S/T$ decreases and becomes negative at low temperature, a signature that the Fermi surface undergoes a reconstruction due to broken translational symmetry. Above a clear threshold field, a strong new feature appears in $S_{\rm b}$, for conduction along the $b$ axis only. We attribute this feature to the onset of 3D-coherent unidirectional charge-density-wave modulations seen by x-ray diffraction, also along the $b$ axis only. Because these modulations have a sharp onset temperature well below the temperature where $S/T$ starts to drop towards negative values, we infer that they are not the cause of Fermi-surface reconstruction. Instead, the reconstruction must be caused by the quasi-2D bidirectional modulations that develop at significantly higher temperature.Comment: 7 pages, 5 figure

Graph Neural Networks and Applied Linear Algebra

Sparse matrix computations are ubiquitous in scientific computing. With the recent interest in scientific machine learning, it is natural to ask how sparse matrix computations can leverage neural networks (NN). Unfortunately, multi-layer perceptron (MLP) neural networks are typically not natural for either graph or sparse matrix computations. The issue lies with the fact that MLPs require fixed-sized inputs while scientific applications generally generate sparse matrices with arbitrary dimensions and a wide range of nonzero patterns (or matrix graph vertex interconnections). While convolutional NNs could possibly address matrix graphs where all vertices have the same number of nearest neighbors, a more general approach is needed for arbitrary sparse matrices, e.g. arising from discretized partial differential equations on unstructured meshes. Graph neural networks (GNNs) are one approach suitable to sparse matrices. GNNs define aggregation functions (e.g., summations) that operate on variable size input data to produce data of a fixed output size so that MLPs can be applied. The goal of this paper is to provide an introduction to GNNs for a numerical linear algebra audience. Concrete examples are provided to illustrate how many common linear algebra tasks can be accomplished using GNNs. We focus on iterative methods that employ computational kernels such as matrix-vector products, interpolation, relaxation methods, and strength-of-connection measures. Our GNN examples include cases where parameters are determined a-priori as well as cases where parameters must be learned. The intent with this article is to help computational scientists understand how GNNs can be used to adapt machine learning concepts to computational tasks associated with sparse matrices. It is hoped that this understanding will stimulate data-driven extensions of classical sparse linear algebra tasks

Benchmarking quantum control methods on a 12-qubit system

In this letter, we present an experimental benchmark of operational control methods in quantum information processors extended up to 12 qubits. We implement universal control of this large Hilbert space using two complementary approaches and discuss their accuracy and scalability. Despite decoherence, we were able to reach a 12-coherence state (or 12-qubits pseudo-pure cat state), and decode it into an 11 qubit plus one qutrit labeled observable pseudo-pure state using liquid state nuclear magnetic resonance quantum information processors.Comment: 11 pages, 4 figures, to be published in PR