Probing the structure of entanglement with entanglement moments

We introduce and define a set of functions on pure bipartite states called entanglement moments. Usual entanglement measures tell you if two systems are entangled, while entanglement moments tell you both if and how two systems are entangled. They are defined with respect to a measurement basis in one system (e.g., a measuring device), and output numbers describing how a system (e.g., a qubit) is entangled with that measurement basis. The moments utilize different distance measures on the Hilbert space of the measured system, and can be generalized to any N-dimensional Hilbert space. As an application, they can distinguish between projective and non-projective measurements. As a particular example, we take the Rabi model's eigenstates and calculate the entanglement moments as well as the full distribution of entanglement.Comment: 5 pages, 5 figure

Ground Systems Development Environment (GSDE) interface requirements and prototyping plan

This report describes the data collection and requirements analysis effort of the Ground System Development Environment (GSDE) Interface Requirements study. It identifies potential problems in the interfaces among applications and processors in the heterogeneous systems that comprises the GSDE. It describes possible strategies for addressing those problems. It also identifies areas for further research and prototyping to demonstrate the capabilities and feasibility of those strategies and defines a plan for building the necessary software prototypes

Nanoinformatics: a new area of research in nanomedicine

pre-printAbstract: Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and -omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings

Ground Systems Development Environment (GSDE) interface requirements analysis

A set of procedural and functional requirements are presented for the interface between software development environments and software integration and test systems used for space station ground systems software. The requirements focus on the need for centralized configuration management of software as it is transitioned from development to formal, target based testing. This concludes the GSDE Interface Requirements study. A summary is presented of findings concerning the interface itself, possible interface and prototyping directions for further study, and results of the investigation of the Cronus distributed applications environment

The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain

The abilities to form and abstract concepts is key to human intelligence, but such abilities remain lacking in state-of-the-art AI systems. There has been substantial research on conceptual abstraction in AI, particularly using idealized domains such as Raven's Progressive Matrices and Bongard problems, but even when AI systems succeed on such problems, the systems are rarely evaluated in depth to see if they have actually grasped the concepts they are meant to capture. In this paper we describe an in-depth evaluation benchmark for the Abstraction and Reasoning Corpus (ARC), a collection of few-shot abstraction and analogy problems developed by Chollet [2019]. In particular, we describe ConceptARC, a new, publicly available benchmark in the ARC domain that systematically assesses abstraction and generalization abilities on a number of basic spatial and semantic concepts. ConceptARC differs from the original ARC dataset in that it is specifically organized around "concept groups" -- sets of problems that focus on specific concepts and that are vary in complexity and level of abstraction. We report results on testing humans on this benchmark as well as three machine solvers: the top two programs from a 2021 ARC competition and OpenAI's GPT-4. Our results show that humans substantially outperform the machine solvers on this benchmark, showing abilities to abstract and generalize concepts that are not yet captured by AI systems. We believe that this benchmark will spur improvements in the development of AI systems for conceptual abstraction and in the effective evaluation of such systems

Author Correction: Fermiology and electron dynamics of trilayer nickelate La4Ni3O10.

The original version of this Article contained errors in Fig. 2, Fig. 3a-c and Supplementary Fig. 2. In Fig. 2g and Supplementary Fig. 2, the band structure plot calculated from density function theory (DFT) had a missing band of mainly z2 character that starts at about - 0.25 eV at the Y point and disperses downwards towards the Γ point. This band was inadvertently neglected when transferring the lines from the original band plot to the enhanced version for publication. Also in Fig. 2g, the points labelled M and Y were not exactly at (1/2 1/2 0) and (0 1/2 0), but rather (0.52 0.48 0) and (0 0.48 0) due to a bug in XCrysDen for low-symmetry structures that the authors failed to identify before publication. Thus, the bands presented were slightly off the true M-Y direction and additional splitting incorrectly appeared (in particular for the highly dispersive bands of x2-y2 character). The correct versions of Fig. 2g (cited as Fig. 1) and Supplementary Fig. 2 (cited as Fig. 2) are:which replaces the previous incorrect version, cited here as Fig. 3 and Fig. 4:Neither of these errors in Fig. 2g or Supplementary Fig. 2 affects either the discussion or any of the interpretations of the ARPES data provided in the paper. The authors discussed the multilayer band splitting along the Γ-M direction (δ band and α band as assigned in the paper), and ARPES did not see any split band. The authors did not discuss the further splitting that arises due to back folding along the M-Y direction.In Fig. 3a-c, the errors in the M and Y points in Fig. 2g cause subtle changes to the DFT dispersions. The correct version of Fig. 3a-c is cited here as Fig 5:which replaces the previous incorrect version (Fig. 6):However, the influence on the effective mass results of Fig. 3d is negligible.These errors have now been corrected in both the PDF and HTML versions of the Article. The authors acknowledge James Rondinelli and Danilo Puggioni from Northwestern University for calling our attention to these issues

Do Public School Police Departments Need Critical Response Teams?

Investigates the need for school district police department to have a critical response team of some sort in order to respond effectively to crisis