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Developing a theoretical framework for conducting electronic fluids qualitatively distinct from those described by Landau’s Fermi-liquid theory is of central importance to many outstanding problems in condensed matter physics. One such problem is that, above the transition temperature and near optimal doping, high-transition-temperature copper-oxide superconductors exhibit ‘strange metal’ behaviour that is inconsistent with being a traditional Landau Fermi liquid. Indeed, a microscopic theory of a strange-metal quantum phase could shed new light on the interesting low-temperature behaviour in the pseudogap regime and on the d -wave superconductor itself. Here we present a theory for a specific example of a strange metal—the ‘ d -wave metal’. Using variational wavefunctions, gauge theoretic arguments, and ultimately large-scale density matrix renormalization group calculations, we show that this remarkable quantum phase is the ground state of a reasonable microscopic Hamiltonian—the usual t–J model with electron kinetic energy t and two-spin exchange J supplemented with a frustrated electron ‘ring-exchange’ term, which we here examine extensively on the square lattice two-leg ladder. These findings constitute an explicit theoretical example of a genuine non-Fermi-liquid metal existing as the ground state of a realistic model. An explicit theoretical construction of a metallic non-Fermi liquid ground state opens a route to attack long-standing problems such as the ‘strange metal’ phase of high-temperature superconductors. The strangeness of metals When is a metal not a metal? The electronic fluids that define a conventional metal — as described by Fermi liquid theory — are commonplace and well understood. However, there are some seemingly metallic systems that do not lend themselves to such a theoretical description, for example the 'strange metal' state seen in high-temperature superconductors. We are now a step closer to understanding such exotic behaviours thanks to the development of a new theoretical model based on realistic physics, in which the ground state of the system is both metallic and quite distinct from a Fermi liquid.

This article considers a partly philosophical question: What are the ontological and epistemological reasons for using quantum-like models or theories (models and theories based on the mathematical formalism of quantum theory) vs. classical-like ones (based on the mathematics of classical physics), in considering human thinking and decision making? This question is only partly philosophical because it also concerns the scientific understanding of the phenomena considered by the theories that use mathematical models of either type, just as in physics itself, where this question also arises as a physical question. This is because this question is in effect: What are the physical reasons for using, even if not requiring, these types of theories in considering quantum phenomena, which these theories predict fully in accord with the experiment? This is clearly also a physical, rather than only philosophical, question and so is, accordingly, the question of whether one needs classical-like or quantum-like theories or both (just as in physics we use both classical and quantum theories) in considering human thinking in psychology and related fields, such as decision science. It comes as no surprise that many of these reasons are parallel to those that are responsible for the use of QM and QFT in the case of quantum phenomena. Still, the corresponding situations should be understood and justified in terms of the phenomena considered, phenomena defined by human thinking, because there are important differences between these phenomena and quantum phenomena, which this article aims to address. In order to do so, this article will first consider quantum phenomena and quantum theory, before turning to human thinking and decision making, in addressing which it will also discuss two recent quantum-like approaches to human thinking, that by M. G. D’Ariano and F. Faggin and that by A. Khrennikov. Both approaches are ontological in the sense of offering representations, different in character in each approach, of human thinking by the formalism of quantum theory. Whether such a representation, as opposed to only predicting the outcomes of relevant experiments, is possible either in quantum theory or in quantum-like theories of human thinking is one of the questions addressed in this article. The philosophical position adopted in it is that it may not be possible to make this assumption, which, however, is not the same as saying that it is impossible. I designate this view as the reality-without-realism, RWR, view and in considering strictly mental processes as the ideality-without-idealism, IWI, view, in the second case in part following, but also moving beyond, I. Kant’s philosophy.

The sign of six Interactions between microscopic particles are usually described as two-body interactions, although it has been shown that higher order multi-body interactions could give rise to novel quantum phases with intriguing properties. This paper demonstrates effective six-body interactions in a system of ultracold bosonic atoms in a three-dimensional optical lattice. The coherent multi-particle interactions observed here open a new window for simulations of effective field theories and may help to enable the realization of novel topologically ordered many-body quantum phases. Interactions between microscopic particles are usually described as two-body interactions, although it has been shown that higher-order multi-body interactions could give rise to new quantum phases with intriguing properties. Here, effective six-body interactions are demonstrated in a system of ultracold bosonic atoms in a three-dimensional optical lattice. Interactions lie at the heart of correlated many-body quantum phases 1 , 2 , 3 . Typically, the interactions between microscopic particles are described as two-body interactions. However, it has been shown that higher-order multi-body interactions could give rise to novel quantum phases with intriguing properties. So far, multi-body interactions have been observed as inelastic loss resonances in three- and four-body recombinations of atom–atom and atom–molecule collisions 4 , 5 , 6 . Here we demonstrate the presence of effective multi-body interactions 7 in a system of ultracold bosonic atoms in a three-dimensional optical lattice, emerging through virtual transitions of particles from the lowest energy band to higher energy bands. We observe such interactions up to the six-body case in time-resolved traces of quantum phase revivals 8 , 9 , 10 , 11 , using an atom interferometric technique that allows us to precisely measure the absolute energies of atom number states at a lattice site. In addition, we show that the spectral content of these time traces can reveal the atom number statistics at a lattice site, similar to foundational experiments in cavity quantum electrodynamics that yield the statistics of a cavity photon field 12 . Our precision measurement of multi-body interaction energies provides crucial input for the comparison of optical-lattice quantum simulators with many-body quantum theory.

The conventional theory of metals is in crisis. In the past 15 years, there has been an unexpected sprouting of metallic states in low-dimensional systems, directly contradicting conventional wisdom. For example, bosons are thought to exist in one of two ground states: condensed in a superconductor or localized in an insulator. However, several experiments on thin metal-alloy films have observed that a metallic phase disrupts the direct transition between the superconductor and the insulator. We analyze the experiments on the insulator-superconductor transition and argue that the intervening metallic phase is bosonic. All relevant theoretical proposals for the Bose metal are discussed, particularly the recent idea that the metallic phase is glassy. The implications for the putative vortex-glass state in the copper oxide superconductors are examined.

Determining the nature of the electronic phases that compete with superconductivity in high-transition-temperature (high- T c ) superconductors is one of the deepest problems in condensed matter physics. One candidate is the ‘stripe’ phase 1 , 2 , 3 , in which the charge carriers (holes) condense into rivers of charge that separate regions of antiferromagnetism. A related but lesser known system is the ‘spin ladder’, which consists of two coupled chains of magnetic ions forming an array of rungs. A doped ladder can be thought of as a high- T c material with lower dimensionality, and has been predicted to exhibit both superconductivity 4 , 5 , 6 and an insulating ‘hole crystal’ 4 , 7 , 8 phase in which the carriers are localized through many-body interactions. The competition between the two resembles that believed to operate between stripes and superconductivity in high- T c materials 9 . Here we report the existence of a hole crystal in the doped spin ladder of Sr 14 Cu 24 O 41 using a resonant X-ray scattering technique 10 . This phase exists without a detectable distortion in the structural lattice, indicating that it arises from many-body electronic effects. Our measurements confirm theoretical predictions 4 , 7 , 8 , and support the picture that proximity to charge ordered states is a general property of superconductivity in copper oxides.

Background Following recent advances in bioimaging, high-resolution 3D models of biological structures are now generated rapidly and at low-cost. To use this data to address evolutionary and ecological questions, an array of tools has been developed to conduct shape analysis and quantify topographic complexity. Here we focus particularly on shape techniques applied to irregular-shaped objects lacking clear homologous landmarks, and propose a new ‘alpha-shapes’ method for quantifying 3D shape complexity. Methods We apply alpha-shapes to quantify shape complexity in the mammalian baculum as an example of a morphologically disparate structure. Micro- computed-tomography (μCT) scans of bacula were conducted. Bacula were binarised and converted into point clouds. Following application of a scaling factor to account for absolute size differences, a suite of alpha-shapes was fitted per specimen. An alpha shape is formed from a subcomplex of the Delaunay triangulation of a given set of points, and ranges in refinement from a very coarse mesh (approximating convex hulls) to a very fine fit. ‘Optimal’ alpha was defined as the refinement necessary in order for alpha-shape volume to equal CT voxel volume, and was taken as a metric of overall ‘complexity’. Results Our results show that alpha-shapes can be used to quantify interspecific variation in shape ‘complexity’ within biological structures of disparate geometry. The ‘stepped’ nature of alpha curves is informative with regards to the contribution of specific morphological features to overall ‘complexity’. Alpha-shapes agrees with other measures of complexity (dissection index, Dirichlet normal energy) in identifying ursid bacula as having low shape complexity. However, alpha-shapes estimates mustelid bacula as being most complex, contrasting with other shape metrics. 3D fractal dimension is identified as an inappropriate metric of complexity when applied to bacula. Conclusions Alpha-shapes is used to calculate ‘optimal’ alpha refinement as a proxy for shape ‘complexity’ without identifying landmarks. The implementation of alpha-shapes is straightforward, and is automated to process large datasets quickly. We interpret alpha-shapes as being particularly sensitive to concavities in surface topology, potentially distinguishing it from other shape complexity metrics. Beyond genital shape, the alpha-shapes technique holds considerable promise for new applications across evolutionary, ecological and palaeoecological disciplines.

Background Hundreds of herbarium collections have accumulated a valuable heritage and knowledge of plants over several centuries. Recent initiatives started ambitious preservation plans to digitize this information and make it available to botanists and the general public through web portals. However, thousands of sheets are still unidentified at the species level while numerous sheets should be reviewed and updated following more recent taxonomic knowledge. These annotations and revisions require an unrealistic amount of work for botanists to carry out in a reasonable time. Computer vision and machine learning approaches applied to herbarium sheets are promising but are still not well studied compared to automated species identification from leaf scans or pictures of plants in the field. Results In this work, we propose to study and evaluate the accuracy with which herbarium images can be potentially exploited for species identification with deep learning technology. In addition, we propose to study if the combination of herbarium sheets with photos of plants in the field is relevant in terms of accuracy, and finally, we explore if herbarium images from one region that has one specific flora can be used to do transfer learning to another region with other species; for example, on a region under-represented in terms of collected data. Conclusions This is, to our knowledge, the first study that uses deep learning to analyze a big dataset with thousands of species from herbaria. Results show the potential of Deep Learning on herbarium species identification, particularly by training and testing across different datasets from different herbaria. This could potentially lead to the creation of a semi, or even fully automated system to help taxonomists and experts with their annotation, classification, and revision works.

Background Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis. Results We empirically compare new and known methods for generating a summary tree. Some new methods are motivated by mathematical constructions such as tree metrics, while the rest employ tree concepts which work well in practice. These use more of the posterior than existing methods, which discard information not directly mapped to the chosen topology. Using results from a large number of simulations we assess the quality of a summary tree, measuring (a) how well it explains the sequence data under the model and (b) how close it is to the “truth”, i.e to the tree used to generate the sequences. Conclusions Our simulations indicate that no single method is “best”. Methods producing good divergence time estimates have poor branch lengths and lower model fit, and vice versa. Using the results presented here, a user can choose the appropriate method based on the purpose of the summary tree.

Autonomous multi-agent systems use different modes of communication to support their autonomy and ease of interaction. In order to enable modelling and reasoning about such systems, we need frameworks that combine many forms of communication. R-CHECK is a modelling, simulation, and verification environment supporting the development of multi-agent systems, providing attributed channelled broadcast and multicast communication. Another common communication mode is point-to-point, wherein agents communicate with each other directly. Capturing point-to-point through R-CHECK ’s multicast and broadcast is possible, but cumbersome and prone to interference. Here, we extend R-CHECK (and its underlying formal calculus ReCiPe ) with bidirectional attributed point-to-point communication, which can be established based on identity or properties of participants. Moreover, we provide a compositional semantics that clearly describes how different modes of interaction co-exist without interference. We also support model-checking of point-to-point interactions by extending linear temporal logic with observation descriptors related to the participants in this communication mode. We argue that these extensions simplify the design, and demonstrate their benefits by means of an illustrative case study.