Nuances of knowing: Brain potentials reveal implicit effects of domain knowledge on word processing in the absence of sentence-level knowledge

In previous work investigating the relationship between domain knowledge (of the fictional world of Harry Potter) and sentence comprehension, domain knowledge had a greater impact on electrical brain potentials to words which completed sentences about fictional "facts" participants reported they did not know compared to facts they did. This suggests that individuals use domain knowledge continuously to activate relevant/related concepts as they process sentences, even with only partial knowledge. As that study relied on subjective reports, it may have resulted in response bias related to an individual's overall domain knowledge. In the present study, we therefore asked participants with varying degrees of domain knowledge to complete sentences describing fictional "facts" as an objective measure of sentence-level knowledge. We then recorded EEG as the same individuals (re-)read the same sentences, including their appropriate final words, and sorted these according to their objective knowledge scores. Replicating and extending Troyer et al., domain knowledge immediately facilitated access to meaning for unknown words; greater domain knowledge was associated with reduced N400 amplitudes for unknown words. These findings constitute novel evidence for graded preactivation of conceptual knowledge (e.g., at the level of semantic features and/or relations) in the absence of lexical prediction. Knowledge also influenced post-N400 memory/integration processes for these same unknown words; greater domain knowledge was associated with enhanced late positive components (LPCs), suggesting that deeper encoding during language processing may be engendered when knowledgeable individuals encounter an apparent gap in their knowledge.

Investigating the Extent to which Distributional Semantic Models Capture a Broad Range of Semantic Relations

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract-concrete continuum (19 sets of ratings). We found that, overall, the DSMs are best at capturing overall semantic similarity and also can capture verb-noun thematic role relations and noun-noun event-based relations that play important roles in sentence comprehension. Interestingly, Skip-gram and CBOW performed the best in terms of capturing similarity, whereas GloVe dominated the thematic role and event-based relations. We discuss the theoretical and practical implications of our results, make recommendations for users of these models, and demonstrate significant differences in model performance on event-based relations.

Patterns of hemispheric asymmetry provide evidence dissociating the semantic and syntactic P600

To understand how neural networks in the left (LH) and right (RH) cerebral hemispheres contribute to different aspects of language comprehension, in two experiments we measured event-related potentials (ERPs) as right-handed participants read sentences, some of which contained morphosyntactic and thematic role violations. Replicating prior work (Kuperberg et al., 2006), in Experiment 1 thematic role violations elicited both an N400 and a (semantic) P600 effect. Morphosyntactic violations elicited effects that differed as a function of participants' familial sinistrality (the presence [FS+] or absence [FS-] of a left-handed biological relative): FS+ participants showed a (syntactic) P600 effect whereas FS- participants showed a biphasic N400 and P600 response. To assess whether this difference reflects different underlying patterns of lateralization, in Experiment 2 target words were presented using visual half-field (VF) presentation. Indeed, for morphosyntactic violations, the FS- group elicited an asymmetric pattern, showing a P600 effect only with LH-biased presentation and an N400 effect in both VFs (cf. Lee and Federmeier, 2015). In contrast, FS+ participants showed a bilateral (N400-only) response pattern. This provides further evidence of FS-based differences in hemispheric contributions to syntactic processing. Strikingly, we found that, when lateralized, thematic role violations did not elicit a P600 effect, suggesting that this effect requires contributions from both hemispheres. The different response patterns for morphosyntactic and thematic role animacy violations across FS and VF also point to a processing difference in the comprehension mechanisms underlying the semantic and syntactic P600, which had heretofore been assumed to be variants of the same component.

Evaluation of synthetic and experimental training data in supervised machine learning applied to charge-state detection of quantum dots

Automated tuning of gate-defined quantum dots is a requirement for large-scale semiconductor-based qubit initialisation. An essential step of these tuning procedures is charge-state detection based on charge stability diagrams. Using supervised machine learning to perform this task requires a large dataset for models to train on. In order to avoid hand labelling experimental data, synthetic data has been explored as an alternative. While providing a significant increase in the size of the training dataset compared to using experimental data, using synthetic data means that classifiers are trained on data sourced from a different distribution than the experimental data that is part of the tuning process. Here we evaluate the prediction accuracy of a range of machine learning models trained on simulated and experimental data, and their ability to generalise to experimental charge stability diagrams in two-dimensional electron gas and nanowire devices. We find that classifiers perform best on either purely experimental or a combination of synthetic and experimental training data, and that adding common experimental noise signatures to the synthetic data does not dramatically improve the classification accuracy. These results suggest that experimental training data as well as realistic quantum dot simulations and noise models are essential in charge-state detection using supervised machine learning.

Thematic and other semantic relations central to abstract (and concrete) concepts

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations. We discuss theories of, and experimental work on, abstract concepts through the lens of the importance of thematic and other semantic relations. We then tie these findings to the sentence processing literature in which such meaningful relations within sentential contexts are often experimentally manipulated. In this literature, some specific classes/types of abstract words have been studied, although not comprehensively, and with limited connection to the literature on knowledge underlying abstract concepts reviewed herein. We conclude by arguing that the ways in which humans understand relatively more abstract concepts, in particular, can be informed by the careful study of words presented not in isolation, but rather in situational and linguistic contexts, and as a function of individual differences in knowledge, goals, and beliefs.

To catch a Snitch: Brain potentials reveal variability in the functional organization of (fictional) world knowledge during reading

We harnessed the temporal sensitivity of event-related brain potentials (ERPs) alongside individual differences in Harry Potter (HP) knowledge to investigate the extent to which the availability and timing of information relevant for real-time written word processing are influenced by variation in domain knowledge. We manipulated meaningful (category, event) relationships between sentence fragments about HP stories and their sentence final words. During word-by-word reading, N400 amplitudes to (a) linguistically supported and (b) unsupported but meaningfully related, but not to (c) unsupported, unrelated sentence endings varied with HP domain knowledge. Single-trial analyses revealed that only the N400s to linguistically supported (but not to either type of unsupported) sentence-final words varied as a function of whether individuals knew (or could remember) the correct (supported) ending for each HP "fact." We conclude that the quick availability of information relevant for word understanding in sentences is a function of individuals' knowledge of both specific facts and the domain to which the facts belong. During written sentence processing, as domain knowledge increases, it is clearly evident that individuals can make use of the relevant knowledge systematically organized around themes, events, and categories in that domain, to the extent they have it.

Lumos!: Electrophysiological tracking of (wizarding) world knowledge use during reading

In Troyer and Kutas (2018), individual differences in knowledge of the world of Harry Potter (HP) rapidly modulated individuals' average electrical brain potentials to contextually supported words in sentence endings. Using advances in single-trial electroencephalogram analysis, we examined whether this relationship is strictly a result of domain knowledge mediating the proportion of facts each participant knew; we find it is not. Participants read sentences ending in a contextually supported word, reporting online whether they had known each fact. Participants' reports correlated with HP domain knowledge and reliably modulated event-related brain potentials to sentence-final words within 250 ms. Critically, domain knowledge had a dissociable influence in the same time window for endings that participants reported not having known and/or were less likely to be known/remembered across participants. We hypothesize that knowledge impacts written word processing primarily by affecting the neural processes of (implicit) retrieval from long-term memory (LTM): Greater knowledge eases otherwise difficult retrieval processes. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Harry Potter and the Chamber of What?: The impact of what individuals know on word processing during reading

During reading, effects of contextual support indexed by N400-a brain potential sensitive to semantic activation/retrieval-amplitude are presumably mediated by comprehenders' world knowledge. Moreover, variability in knowledge may influence the contents, timing, and mechanisms of what is brought to mind during real-time sentence processing. Since it is infeasible to assess the entirety of each individual's knowledge, we investigated a limited domain-the narrative world of Harry Potter (HP). We recorded event-related brain potentials while participants read sentences ending in words more/less contextually supported. For sentences about HP, but not about general topics, contextual N400 effects were graded according to individual participants' HP knowledge. Our results not only confirm that context affects semantic processing by ~250 ms or earlier, on average, but empirically demonstrate what has until now been assumed-that N400 context effects are a function of each individual's knowledge, which here is highly correlated with their reading experience.

Maternal Socioeconomic Status Influences the Range of Expectations During Language Comprehension in Adulthood

In infancy, maternal socioeconomic status (SES) is associated with real-time language processing skills, but whether or not (and if so, how) this relationship carries into adulthood is unknown. We explored the effects of maternal SES in college-aged adults on eye-tracked, spoken sentence comprehension tasks using the visual world paradigm. When sentences ended in highly plausible, expected target nouns (Exp. 1), higher SES was associated with a greater likelihood of considering alternative endings related to the action of the sentence. Moreover, for unexpected sentence endings (Exp. 2), individuals from higher SES backgrounds were sensitive to whether the ending was action-related (plausible) or unrelated (implausible), showing a benefit for plausible endings. Individuals from lower SES backgrounds did not show this advantage. This suggests maternal SES can influence the dynamics of sentence processing even in adulthood, with consequences for processing unexpected content. These findings highlight the importance of early lexical experience for adult language skills.

Robust Type-II Weyl Semimetal Phase in Transition Metal Diphosphides XP_{2} (X=Mo, W)

The recently discovered type-II Weyl points appear at the boundary between electron and hole pockets. Type-II Weyl semimetals that host such points are predicted to exhibit a new type of chiral anomaly and possess thermodynamic properties very different from their type-I counterparts. In this Letter, we describe the prediction of a type-II Weyl semimetal phase in the transition metal diphosphides MoP_{2} and WP_{2}. These materials are characterized by relatively simple band structures with four pairs of type-II Weyl points. Neighboring Weyl points have the same chirality, which makes the predicted topological phase robust with respect to small perturbations of the crystalline lattice. In addition, this peculiar arrangement of the Weyl points results in long topological Fermi arcs, thus making them readily accessible in angle-resolved photoemission spectroscopy.

Elaboration over a Discourse Facilitates Retrieval in Sentence Processing

Language comprehension requires access to stored knowledge and the ability to combine knowledge in new, meaningful ways. Previous work has shown that processing linguistically more complex expressions (‘Texas cattle rancher’ vs. ‘rancher’) leads to slow-downs in reading during initial processing, possibly reflecting effort in combining information. Conversely, when this information must subsequently be retrieved (as in filler-gap constructions), processing is facilitated for more complex expressions, possibly because more semantic cues are available during retrieval. To follow up on this hypothesis, we tested whether information distributed across a short discourse can similarly provide effective cues for retrieval. Participants read texts introducing two referents (e.g., two senators), one of whom was described in greater detail than the other (e.g., ‘The Democrat had voted for one of the senators, and the Republican had voted for the other, a man from Ohio who was running for president’). The final sentence (e.g., ‘The senator who the {Republican/Democrat}had voted for…’) contained a relative clause picking out either the Many-Cue referent (with ‘Republican’) or the One-Cue referent (with ‘Democrat’). We predicted facilitated retrieval (faster reading times) for the Many-Cue condition at the verb region (‘had voted for’), where readers could understand that ‘The senator’ is the object of the verb. As predicted, this pattern was observed at the retrieval region and continued throughout the rest of the sentence. Participants also completed the Author/Magazine Recognition Tests (ART/MRT; Stanovich and West, 1989), providing a proxy for world knowledge. Since higher ART/MRT scores may index (a) greater experience accessing relevant knowledge and/or (b) richer/more highly structured representations in semantic memory, we predicted it would be positively associated with effects of elaboration on retrieval. We did not observe the predicted interaction between ART/MRT scores and Cue condition at the retrieval region, though ART/MRT interacted with Cue condition in other locations in the sentence. In sum, we found that providing more elaborative information over the course of a text can facilitate retrieval for referents, consistent with a framework in which referential elaboration over a discourse and not just local linguistic information directly impacts information retrieval during sentence processing.

Action verbs are processed differently in metaphorical and literal sentences depending on the semantic match of visual primes

Language comprehension requires rapid and flexible access to information stored in long-term memory, likely influenced by activation of rich world knowledge and by brain systems that support the processing of sensorimotor content. We hypothesized that while literal language about biological motion might rely on neurocognitive representations of biological motion specific to the details of the actions described, metaphors rely on more generic representations of motion. In a priming and self-paced reading paradigm, participants saw video clips or images of (a) an intact point-light walker or (b) a scrambled control and read sentences containing literal or metaphoric uses of biological motion verbs either closely or distantly related to the depicted action (walking). We predicted that reading times for literal and metaphorical sentences would show differential sensitivity to the match between the verb and the visual prime. In Experiment 1, we observed interactions between the prime type (walker or scrambled video) and the verb type (close or distant match) for both literal and metaphorical sentences, but with strikingly different patterns. We found no difference in the verb region of literal sentences for Close-Match verbs after walker or scrambled motion primes, but Distant-Match verbs were read more quickly following walker primes. For metaphorical sentences, the results were roughly reversed, with Distant-Match verbs being read more slowly following a walker compared to scrambled motion. In Experiment 2, we observed a similar pattern following still image primes, though critical interactions emerged later in the sentence. We interpret these findings as evidence for shared recruitment of cognitive and neural mechanisms for processing visual and verbal biological motion information. Metaphoric language using biological motion verbs may recruit neurocognitive mechanisms similar to those used in processing literal language but be represented in a less-specific way.

Pre-processing in sentence comprehension: Sensitivity to likely upcoming meaning and structure

For more than a decade, views of sentence comprehension have been shifting toward wider acceptance of a role for linguistic pre-processing-that is, anticipation, expectancy, (neural) pre-activation, or prediction-of upcoming semantic content and syntactic structure. In this survey, we begin by examining the implications of each of these "brands" of predictive comprehension, including the issue of potential costs and consequences to not encountering highly constrained sentence input. We then describe a number of studies (many using online methodologies) that provide results consistent with prospective sensitivity to various grains and levels of semantic and syntactic information, acknowledging that such pre-processing is likely to occur in other linguistic and extralinguistic domains, as well. This review of anticipatory findings also includes some discussion on the relationship of priming to prediction. We conclude with a brief examination of some possible limits to prediction, and with a suggestion for future work to probe whether and how various strands of prediction may integrate during real-time comprehension.

Nonlocal quantum fluctuations and fermionic superfluidity in the imbalanced attractive Hubbard model

We study fermionic superfluidity in strongly anisotropic optical lattices with attractive interactions utilizing the cluster dynamical mean-field theory method, and focusing in particular on the role of nonlocal quantum fluctuations. We show that nonlocal quantum fluctuations impact the BCS superfluid transition dramatically. Moreover, we show that exotic superfluid states with a delicate order parameter structure, such as the Fulde-Ferrell-Larkin-Ovchinnikov phase driven by spin population imbalance, can emerge even in the presence of such strong fluctuations.

Critical temperature of interacting Bose gases in periodic potentials

The superfluid transition of a repulsive Bose gas in the presence of a sinusoidal potential which represents a simple-cubic optical lattice is investigated using quantum Monte Carlo simulations. At the average filling of one particle per well the critical temperature has a nonmonotonic dependence on the interaction strength, with an initial sharp increase and a rapid suppression at strong interactions in the vicinity of the Mott transition. In an optical lattice the positive shift of the transition is strongly enhanced compared to the homogenous gas. By varying the lattice filling we find a crossover from a regime where the optical lattice has the dominant effect to a regime where interactions dominate and the presence of the lattice potential becomes almost irrelevant.

Ferromagnetism of a repulsive atomic Fermi gas in an optical lattice: a quantum Monte Carlo study

Using continuous-space quantum Monte Carlo methods, we investigate the zero-temperature ferromagnetic behavior of a two-component repulsive Fermi gas under the influence of periodic potentials that describe the effect of a simple-cubic optical lattice. Simulations are performed with balanced and with imbalanced components, including the case of a single impurity immersed in a polarized Fermi sea (repulsive polaron). For an intermediate density below half filling, we locate the transitions between the paramagnetic, and the partially and fully ferromagnetic phases. As the intensity of the optical lattice increases, the ferromagnetic instability takes place at weaker interactions, indicating a possible route to observe ferromagnetism in experiments performed with ultracold atoms. We compare our findings with previous predictions based on the standard computational method used in material science, namely density functional theory, and with results based on tight-binding models.

Bosonic superfluid-insulator transition in continuous space

We investigate the zero-temperature phase diagram of interacting Bose gases in the presence of a simple cubic optical lattice, going beyond the regime where the mapping to the single-band Bose-Hubbard model is reliable. Our computational approach is a new hybrid quantum Monte Carlo method which combines algorithms used to simulate homogeneous quantum fluids in continuous space with those used for discrete lattice models of strongly correlated systems. We determine the critical interaction strength and optical lattice intensity where the superfluid-to-insulator transition takes place, considering also the regime of shallow optical lattices and strong interatomic interactions. The implications of our findings for the supersolid state of matter are discussed.

Itinerant ferromagnetism of a repulsive atomic Fermi gas: a quantum monte carlo study

We investigate the phase diagram of a two-component repulsive Fermi gas at T=0 by means of quantum Monte Carlo simulations. Both purely repulsive and resonant attractive model potentials are considered in order to analyze the limits of the universal regime where the details of interatomic forces can be neglected. The equation of state of both balanced and unbalanced systems is calculated as a function of the interaction strength and the critical density for the onset of ferromagnetism is determined. The energy of the strongly polarized gas is calculated and parametrized in terms of the physical properties of repulsive polarons, which are relevant for the stability of the fully ferromagnetic state. Finally, we analyze the phase diagram in the interaction-polarization plane under the assumption that only phases with homogeneous magnetization can be produced.

Quantitative determination of temperature in the approach to magnetic order of ultracold fermions in an optical lattice

We perform a quantitative simulation of the repulsive Fermi-Hubbard model using an ultracold gas trapped in an optical lattice. The entropy of the system is determined by comparing accurate measurements of the equilibrium double occupancy with theoretical calculations over a wide range of parameters. We demonstrate the applicability of both high-temperature series and dynamical mean-field theory to obtain quantitative agreement with the experimental data. The reliability of the entropy determination is confirmed by a comprehensive analysis of all systematic errors. In the center of the Mott insulating cloud we obtain an entropy per atom as low as 0.77k(B) which is about twice as large as the entropy at the Néel transition. The corresponding temperature depends on the atom number and for small fillings reaches values on the order of the tunneling energy.

Supersolid phase with cold polar molecules on a triangular lattice

We study a system of heteronuclear molecules on a triangular lattice and analyze the potential of this system for the experimental realization of a supersolid phase. The ground state phase diagram contains superfluid, solid, and supersolid phases. At finite temperatures and strong interactions there is an additional emulsion region, in contrast with similar models with short-range interactions. We derive the maximal critical temperature T{c} and the corresponding entropy S/N=0.04(1) for supersolidity and find feasible experimental conditions for its realization.

Absence of a direct superfluid to mott insulator transition in disordered bose systems

We prove the absence of a direct quantum phase transition between a superfluid and a Mott insulator in a bosonic system with generic, bounded disorder. We also prove the compressibility of the system on the superfluid-insulator critical line and in its neighborhood. These conclusions follow from a general theorem of inclusions, which states that for any transition in a disordered system, one can always find rare regions of the competing phase on either side of the transition line. Quantum Monte Carlo simulations for the disordered Bose-Hubbard model show an even stronger result, important for the nature of the Mott insulator to Bose glass phase transition: the critical disorder bound Delta(c) corresponding to the onset of disorder-induced superfluidity, satisfies the relation Delta(c)>Eg/2, with Eg/2 the half-width of the Mott gap in the pure system.

Discerning incompressible and compressible phases of cold atoms in optical lattices

Experiments with cold atoms trapped in optical lattices offer the potential to realize a variety of novel phases but suffer from severe spatial inhomogeneity that can obscure signatures of new phases of matter and phase boundaries. We use a high temperature series expansion to show that compressibility in the core of a trapped Fermi-Hubbard system is related to measurements of changes in double occupancy. This core compressibility filters out edge effects, offering a direct probe of compressibility independent of inhomogeneity. A comparison with experiments is made.

Virtual EEG: A Software-Based Electroencephalogram Designed for Undergraduate Neuroscience-Related Courses

A current topic in neuroscience addresses the link between brain activity and visual awareness. The electroencephalogram (EEG), which uses non-invasive high temporal resolution scalp recordings to measure brain activity, is a common tool used to probe this question. EEG recordings, however, are difficult to implement in the curriculum of laboratory-based courses. Thus, undergraduate students often lack experience with EEG experiments. We report here an EEG program (Virtual EEG) that can be used in undergraduate courses to analyze averaged EEG data, termed Event Related Potentials (ERPs). The program was designed so that students can generate hypothesis-driven studies that address how the brain encodes categories of visual stimuli. The Virtual EEG is a large database of EEG recordings consisting of 32 channels taken from real human subjects who were shown 256 pictures of visual stimuli. The program provides a number of possible ways to group the stimuli. After selecting the appropriate stimuli, the program constructs graphs of the ERPs. The channels can be selected for statistical analysis. Because the program uses real data, students are encouraged to interpret their results in light of previously published work. Thus, students have the opportunity to discover something new about how the brain processes visual information. This article also includes a tutorial and summarizes the results of an assessment survey. Finally, we include information regarding the companion Virtual EEG website. The Virtual EEG has been used successfully for the past six years at Indiana University with over a thousand undergraduate students in a research methods course, and the assessment results illustrate its strengths and limitations.

Binding of a 3He impurity to a screw dislocation in solid 4He

Using first-principles simulations for the probability density of finding a 3He atom in the vicinity of the screw dislocation in solid 4He, we determine the binding energy to the dislocation nucleus E(B)=0.8+/-0.1 K and the density of localized states at larger distances. The specific heat due to 3He features a peak similar to the one observed in recent experiments, and our model can also account for the observed increase in shear modulus at low temperature. We further discuss the role of 3He in the picture of superfluid defects.

Expansion of a quantum gas released from an optical lattice

We analyze the interference pattern produced by ultracold atoms released from an optical lattice, commonly interpreted as the momentum distributions of the trapped quantum gas. We show that for finite times of flight the resulting density distribution can, however, be significantly altered, similar to a near-field diffraction regime in optics. We illustrate our findings with a simple model and realistic quantum Monte Carlo simulations for bosonic atoms and compare the latter to experiments.

Local stress and superfluid properties of solid 4He

We provide a semiquantitative tool, derived from first-principles simulations, for answering the question of whether certain types of defects in solid 4He support mass superflow. Although ideal crystals of 4He are not supersolid, the gap for vacancy creation closes when applying a moderate stress. While a homogeneous system becomes unstable at this point, the stressed core of crystalline defects (dislocations and grain boundaries) can turn superfluid.

Deconfined criticality: generic first-order transition in the SU(2) symmetry case

Monte Carlo simulations of the SU(2)-symmetric deconfined critical point action reveal strong violations of scale invariance for the deconfinement transition. We find compelling evidence that the generic runaway renormalization flow of the gauge coupling is to a weak first-order transition, similar to the case of U(1) x U(1) symmetry. Our results imply that recent numeric studies of the Nèel antiferromagnet to valence bond solid quantum phase transition in SU(2)-symmetric models were not accurate enough in determining the nature of the transition.

Luttinger liquid in the core of a screw dislocation in helium-4

On the basis of first-principles Monte Carlo simulations we find that the screw dislocation along the hexagonal axis of an hcp 4He crystal features a superfluid (at T-->0) core. This is the first example of a regular quasi-one-dimensional supersolid--the phase featuring both translational and superfluid orders, and one of the cleanest cases of a Luttinger-liquid system. In contrast, the same type of screw dislocation in solid H2 is insulating.

Superfluidity of grain boundaries in solid 4He

By large-scale quantum Monte Carlo simulations we show that grain boundaries in 4He crystals are generically superfluid at low temperature, with a transition temperature of the order of approximately 0.5 K at the melting pressure; nonsuperfluid grain boundaries are found only for special orientations of the grains. We also find that close vicinity to the melting line is not a necessary condition for superfluid grain boundaries, and a grain boundary in direct contact with the superfluid liquid at the melting curve is found to be mechanically stable and the grain-boundary superfluidity observed by Sasaki et al. [Science 313, 1098 (2006)10.1126/science.1130879] is not just a crack filled with superfluid.

Fate of vacancy-induced supersolidity in 4He

The supersolid state of matter, exhibiting nondissipative flow in solids, has been elusive for 35 years. The recent discovery of a nonclassical moment of inertia in solid 4He by Kim and Chan provided the first experimental evidence, although the interpretation in terms of supersolidity of the ideal crystal phase remains a subject to debate. Using quantum Monte Carlo methods we investigate the long-standing question of vacancy-induced superflow and find that vacancies in a 4He crystal phase separate instead of forming a supersolid. On the other hand, nonequilibrium vacancies relaxing on defects of polycrystalline samples could provide an explanation for the experimental observations.

Two-step restoration of SU(2) symmetry in a frustrated ring-exchange magnet

We demonstrate the existence of a spin-nematic, moment-free phase in a quantum four-spin ring-exchange model on the square lattice. This unusual quantum state is created by the interplay of frustration and quantum fluctuations that lead to a partial restoration of SU(2) symmetry when going from a four-sublattice orthogonal biaxial Néel order to this exotic uniaxial magnet. A further increase of frustration drives a transition to a fully gapped SU(2) symmetric valence bond crystal.

Néel temperature of quasi-low-dimensional Heisenberg antiferromagnets

The Néel temperature T(N) of quasi-one- and quasi-two-dimensional antiferromagnetic Heisenberg models on a cubic lattice is calculated by Monte Carlo simulations as a function of interchain (interlayer) to intrachain (intralayer) coupling J(')/J down to J(')/J approximately = 10(-3). We find that T(N) obeys a modified random-phase approximationlike relation for small J(')/J with an effective universal renormalized coordination number, independent of the size of the spin. Empirical formulas describing T(N) for a wide range of J(') and useful for the analysis of experimental measurements are presented.

Performance limitations of flat-histogram methods

We determine the optimal scaling of local-update flat-histogram methods with system size by using a perfect flat-histogram scheme based upon the exact density of states of 2D Ising models. The typical tunneling time needed to sample the entire bandwidth does not scale with the number of spins N as the minimal N2 of an unbiased random walk in energy space. While the scaling is power law for the ferromagnetic and fully frustrated Ising model, for the +/-J nearest-neighbor spin glass the distribution of tunneling times is governed by a fat-tailed Fréchet extremal value distribution that obeys exponential scaling. Furthermore, the shape parameters of these distributions indicate that statistical sample means become ill defined already for moderate system sizes within these complex energy landscapes.

Broken time-reversal symmetry in strongly correlated ladder structures

We provide, for the first time, in a doped strongly correlated system (two-leg ladder), a controlled theoretical demonstration of the existence of a state in which long-range ordered orbital currents are arranged in a staggered pattern, coexisting with a charge density wave. The method used is the highly accurate density-matrix renormalization group technique. This brings us closer to recent proposals that this order is realized in the enigmatic pseudogap phase of the cuprate high temperature superconductors.

Mott domains of bosons confined on optical lattices

In the absence of a confining potential, the boson-Hubbard model exhibits a superfluid to Mott insulator quantum phase transition at commensurate fillings and strong coupling. We use quantum Monte Carlo simulations to study the ground state of the one-dimensional bosonic Hubbard model in a trap. Some, but not all, aspects of the Mott insulating phase persist. Mott behavior occurs for a continuous range of incommensurate fillings, very different from the unconfined case, and the establishment of the Mott phase does not proceed via a traditional quantum phase transition. These results have important implications for interpreting experiments on ultracold atoms on optical lattices.

Phase diagram and dynamics of the projected SO(5) symmetric model of high- T(c) superconductivity

We present numerical studies of a quantum "projected" SO(5) model which aims at a unifying description of antiferromagnetism and superconductivity in the high- T(c) cuprates, while properly taking into account the Mott insulating gap. Our numerical results, obtained by the quantum Monte Carlo technique of stochastic series expansion, show that this model can give a realistic description of the global phase diagram of the high- T(c) superconductors and accounts for many of their physical properties. Moreover, we address the question of asymptotic restoring of the SO(5) symmetry at the critical point.

Topologically protected quantum bits using Josephson junction arrays

All physical implementations of quantum bits (or qubits, the logical elements in a putative quantum computer) must overcome conflicting requirements: the qubits should be manipulable through external signals, while remaining isolated from their environment. Proposals based on quantum optics emphasize optimal isolation, while those following the solid-state route exploit the variability and scalability of nanoscale fabrication techniques. Recently, various designs using superconducting structures have been successfully tested for quantum coherent operation, however, the ultimate goal of reaching coherent evolution over thousands of elementary operations remains a formidable task. Protecting qubits from decoherence by exploiting topological stability is a qualitatively new proposal that holds promise for long decoherence times, but its physical implementation has remained unclear. Here we show how strongly correlated systems developing an isolated twofold degenerate quantum dimer liquid ground state can be used in the construction of topologically stable qubits; we discuss their implementation using Josephson junction arrays. Although the complexity of their architecture challenges the technology base available today, such topological qubits greatly benefit from their built-in fault-tolerance.

Accessing the dynamics of large many-particle systems using the stochastic series expansion

The stochastic series expansion (SSE) method is a quantum Monte Carlo (QMC) technique working directly in the imaginary time continuum and thus avoiding "Trotter discretization" errors. Using a nonlocal "operator-loop update," it allows one to treat large quantum mechanical systems of many thousand sites. In this paper we first give a comprehensive review on SSE and present benchmark calculations of SSE scaling behavior with system size and inverse temperature, and compare it to the loop algorithm, whose scaling is known to be one of the best of all QMC methods. Finally we introduce an efficient algorithm to measure Green's functions and thus dynamical properties within SSE.

Spin orthogonality catastrophe in two-dimensional antiferromagnets and superconductors

We compute the spectral function of a spin S hole injected into a two-dimensional antiferromagnet or superconductor in the vicinity of a magnetic quantum critical point. We show that, near Van Hove singularities, the problem maps onto that of a static vacancy carrying excess spin S. The hole creation operator is characterized by a new boundary anomalous dimension and a vanishing quasiparticle residue at the critical point. We discuss possible relevance to photoemission spectra of cuprate superconductors near the antinodal points.

Li2VO(Si,Ge)O4, a prototype of a two-dimensional frustrated quantum heisenberg antiferromagnet

NMR and magnetization measurements in Li2VOSiO4 and Li2VOGeO4 are reported. The analysis of the susceptibility shows that both compounds are two-dimensional S = 1/2 Heisenberg antiferromagnets on a square lattice with a sizable frustration induced by the competition between the superexchange couplings J1 along the sides of the square and J2 along the diagonal. Li2VOSiO4 undergoes a low-temperature phase transition to a collinear order, as theoretically predicted for J2/J1>0.5. Just above the magnetic transition the degeneracy between the two collinear ground states is lifted by the onset of a structural distortion.

Unilateral pallidotomy for Parkinson's disease: results after more than 1 year

OBJECTIVE

To examine follow up results of unilateral ventral medial pallidotomy in 22 patients with advanced Parkinson's disease more than 1 year after the operation in comparison with their results (previously reported) at 3 months.

METHODS

Twenty patients who had undergone unilateral pallidotomy were assessed with the core assessment programme for intracerebral transplantation (CAPIT) protocol preoperatively, at 3 months postoperatively, and again after a median postoperative follow up of 14 months. Two further patients had only one evaluation 3 months postoperatively.

RESULTS

The reduction of contralateral dyskinesias (median 67%) at 3 months was slightly attenuated after 1 year to 55% (both p<0.001 compared with baseline). A less pronounced effect on ipsilateral and axial dyskinesias decreased from 39% to 33% (p<0.005 and p<0.01), and from 50% to 12.5% (p<0.001 and p<0.01), respectively. However, there was no significant change between the 3 month and the follow up assessment. The modest improvement of the contralateral unified Parkinson's disease rating scale (UPDRS) motor score in the "off" state remained improved compared with preoperative levels, but less significantly (26%, p<0.001, and 18%, p<0.01). The activities of daily living (ADL) subscore of the UPDRS in the off state remained improved with median changes of 23% and 22% at follow up (both p<0. 005). There was no significant improvement of "on" state or ipsilateral off state motor scores. Median modified Hoehn and Yahr scores in off and on state were unchanged, as was the time spent off. Speech in off had significantly deteriorated by 1 year after the operation.

CONCLUSIONS

The beneficial effects of unilateral pallidotomy persist for at least 12 months and, dyskinesias are most responsive to this procedure.