A hard x-ray, high-speed, high dynamic range scientific x-ray imager is described. The imager is based on the mixed-mode pixel array detector (MM-PAD) readout chip coupled to a 750 μm thick cadmium telluride (CdTe) sensor. The full imager is a 2 × 3 tiled array of MM-PAD sensor/readout chip hybrids. CdTe improves detection for high energy x-rays as compared to silicon sensors, enabling efficient x-ray imaging to extend to >100 keV . The detector is capable of 1 kHz imaging and in-pixel circuitry has been designed to allow for well depths of greater than 4 × 106 80 keV x-rays.

We discuss a new class of quantum phase transitions - deconfined Mott transition (DMT) - that describe a continuous transition between a Fermi liquid metal with a generic electronic Fermi surface and an electrical insulator without Fermi surfaces of emergent neutral excitations. We construct a unified U(2) gauge theory to describe a variety of metallic and insulating phases, which include Fermi liquids, fractionalized Fermi liquids (FL∗), conventional insulators, and quantum spin liquids, as well as the quantum phase transitions between them.

Spin-based memories are attractive for their non-volatility and high durability but provide modest resistance changes, whereas semiconductor logic transistors are capable of providing large resistance changes, but lack memory function with high durability. The recent availability of multiferroic materials provides an opportunity to directly couple the change in spin states of a magnetic memory to a charge change in a semiconductor transistor.

Selection rules are of vital importance in determining the basic optical properties of atoms, molecules and semiconductors. They provide general insights into the symmetry of the system and the nature of relevant electronic states. A two-dimensional electron gas in a magnetic field is a model system where optical transitions between Landau levels (LLs) are described by simple selection rules associated with the LL index N. Here we examine the inter-LL optical transitions of high-quality bilayer graphene by photocurrent spectroscopy measurement.

Niobium superconducting radio frequency (SRF) cavities enable the operation of modern superconducting accelerator facilities. These cavities do not approach the theoretical performance limits of Nb due to the deleterious effects of surface defects and chemical inhomogeneities such as Nb hydrides. Nitrogen doping is known to consistently increase the cavity performance and inhibit Nb hydride growth, but a comprehensive understanding of Nb hydride growth and suppression is not yet realized.

Determining the exact pairing symmetry of the superconducting order parameter in candidate unconventional superconductors remains an important challenge. Recently, a new method, based on phase sensitive quasiparticle interference measurements, was developed to identify gap sign changes in isotropic multiband systems. Here we extend this approach to the single-band and multiband nodal d-wave superconducting cases relevant, respectively, for the cuprates and likely for the infinite-layer nickelate superconductors.

There has been growing excitement over the possibility of employing artificial neural networks (ANNs) to gain new theoretical insight into the physics of quantum many-body problems. "Interpretability"remains a concern: can we understand the basis for the ANN's decision-making criteria in order to inform our theoretical understanding? "Interpretable"machine learning in quantum matter has to date been restricted to linear models, such as support vector machines, due to the greater difficulty of interpreting nonlinear ANNs.

We study the behavior of the Douglas–Rachford algorithm on the graph vertex-coloring problem. Given a graph and a number of colors, the goal is to find a coloring of the vertices so that all adjacent vertex pairs have different colors. In spite of the combinatorial nature of this problem, the Douglas–Rachford algorithm was recently shown to be a successful heuristic for solving a wide variety of graph coloring instances, when the problem was cast as a feasibility problem on binary indicator variables. In this work we consider a different formulation, based on semidefinite programming.

The ability to make controlled patterns of magnetic structures within a nonmagnetic background is essential for several types of existing and proposed technologies. Such patterns provide the foundation of magnetic memory and logic devices, allow the creation of artificial spin-ice lattices, and enable the study of magnon propagation. Here, a novel approach for magnetic patterning that allows repeated creation and erasure of arbitrary shapes of thin-film ferromagnetic structures is reported.

Posttraumatic osteoarthritis (PTOA) involves the mechanical and biological deterioration of articular cartilage that occurs following joint injury. PTOA is a growing problem in health care due to the lack of effective therapies combined with an aging population with high activity levels. Recently, acute mitochondrial dysfunction and altered cellular respiration have been associated with cartilage degeneration after injury.