Imaging magnetic polarons in the doped Fermi-Hubbard model

Polarons are among the most fundamental quasiparticles emerging in interacting many-body systems, forming already at the level of a single mobile dopant. In the context of the two-dimensional Fermi-Hubbard model, such polarons are predicted to form around charged dopants in an antiferromagnetic background in the low doping regime close to the Mott insulating state. Macroscopic transport and spectroscopy measurements related to high $T_{c}$ materials have yielded strong evidence for the existence of such quasiparticles in these systems. Here we report the first microscopic observation of magnetic polarons in a doped Fermi-Hubbard system, harnessing the full single-site spin and density resolution of our ultracold-atom quantum simulator. We reveal the dressing of mobile doublons by a local reduction and even sign reversal of magnetic correlations, originating from the competition between kinetic and magnetic energy in the system. The experimentally observed polaron signatures are found to be consistent with an effective string model at finite temperature. We demonstrate that delocalization of the doublon is a necessary condition for polaron formation by contrasting this mobile setting to a scenario where the doublon is pinned to a lattice site. Our work paves the way towards probing interactions between polarons, which may lead to stripe formation, as well as microscopically exploring the fate of polarons in the pseudogap and bad metal phase

Mid-Infrared interferometry of dust around massive evolved stars

We report long-baseline interferometric measurements of circumstellar dust around massive evolved stars with the MIDI instrument on the Very Large Telescope Interferometer and provide spectrally dispersed visibilities in the 8-13 micron wavelength band. We also present diffraction-limited observations at 10.7 micron on the Keck Telescope with baselines up to 8.7 m which explore larger scale structure. We have resolved the dust shells around the late type WC stars WR 106 and WR 95, and the enigmatic NaSt1 (formerly WR 122), suspected to have recently evolved from a Luminous Blue Variable (LBV) stage. For AG Car, the protoypical LBV in our sample, we marginally resolve structure close to the star, distinct from the well-studied detached nebula. The dust shells around the two WC stars show fairly constant size in the 8-13 micron MIDI band, with gaussian half-widths of ~ 25 to 40 mas. The compact dust we detect around NaSt1 and AG Car favors recent or ongoing dust formation. Using the measured visibilities, we build spherically symmetric radiative transfer models of the WC dust shells which enable detailed comparison with existing SED-based models. Our results indicate that the inner radii of the shells are within a few tens of AU from the stars. In addition, our models favor grain size distributions with large (~ 1 micron) dust grains. This proximity of the inner dust to the hot central star emphasizes the difficulty faced by current theories in forming dust in the hostile environment around WR stars. Although we detect no direct evidence for binarity for these objects, dust production in a colliding-wind interface in a binary system is a feasible mechanism in WR systems under these conditions.Comment: 21 pages, 4 tables, 13 figures. Accepted for publication in the Astrophysical Journa

Direct observation of incommensurate magnetism in Hubbard chains

The interplay between magnetism and doping is at the origin of exotic strongly correlated electronic phases and can lead to novel forms of magnetic ordering. One example is the emergence of incommensurate spin-density waves with a wave vector that does not match the reciprocal lattice. In one dimension this effect is a hallmark of Luttinger liquid theory, which also describes the low energy physics of the Hubbard model. Here we use a quantum simulator based on ultracold fermions in an optical lattice to directly observe such incommensurate spin correlations in doped and spin-imbalanced Hubbard chains using fully spin and density resolved quantum gas microscopy. Doping is found to induce a linear change of the spin-density wave vector in excellent agreement with Luttinger theory predictions. For non-zero polarization we observe a decrease of the wave vector with magnetization as expected from the Heisenberg model in a magnetic field. We trace the microscopic origin of these incommensurate correlations to holes, doublons and excess spins which act as delocalized domain walls for the antiferromagnetic order. Finally, when inducing interchain coupling we observe fundamentally different spin correlations around doublons indicating the formation of a magnetic polaron

Molecular estimation of neurodegeneration pseudotime in older brains.

The temporal molecular changes that lead to disease onset and progression in Alzheimer\u27s disease (AD) are still unknown. Here we develop a temporal model for these unobserved molecular changes with a manifold learning method applied to RNA-Seq data collected from human postmortem brain samples collected within the ROS/MAP and Mayo Clinic RNA-Seq studies. We define an ordering across samples based on their similarity in gene expression and use this ordering to estimate the molecular disease stage-or disease pseudotime-for each sample. Disease pseudotime is strongly concordant with the burden of tau (Braak score, P = 1.0 × 10-5), Aβ (CERAD score, P = 1.8 × 10-5), and cognitive diagnosis (P = 3.5 × 10-7) of late-onset (LO) AD. Early stage disease pseudotime samples are enriched for controls and show changes in basic cellular functions. Late stage disease pseudotime samples are enriched for late stage AD cases and show changes in neuroinflammation and amyloid pathologic processes. We also identify a set of late stage pseudotime samples that are controls and show changes in genes enriched for protein trafficking, splicing, regulation of apoptosis, and prevention of amyloid cleavage pathways. In summary, we present a method for ordering patients along a trajectory of LOAD disease progression from brain transcriptomic data

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology

Macroeconomic Fluctuations, Inequality, and Human Development

This paper examines the two-way relationship between inequality and economic fluctuations, and the implications for human development. For years, the dominant paradigm in macroeconomics, which assumed that income distribution did not matter, at least for macroeconomic behavior, ignored inequality--both its role in causing crises and the effect of fluctuations in general, and crises in particular, on inequality. But the most recent financial crisis has shown the errors in this thinking, and these views are finally beginning to be questioned. Economists who had looked at the average equity of a homeowner--ignoring the distribution--felt comfortable that the economy could easily withstand a large fall in housing prices. When such a fall occurred, however, it had disastrous effects, because a large fraction of homeowners owed more on their homes than the value of the home, leading to waves of foreclosure and economic stress. Policy-makers and economists alike have begun to take note: inequality can contribute to volatility and the creation of crises, and volatility can contribute to inequality. Here, we explore the variety of channels through which inequality affects fluctuations and fluctuations affect inequality, and explore how some of the changes in our economy may have contributed to increased inequality and volatility both directly and indirectly. After describing the two-way relationship, the paper discusses hysteresis--the fact that the consequences of an economic downturn can be long-lived. Then, it examines how policy can either mitigate or exacerbate the inequality consequences of economic downturns, and shows how well-intentioned policies can sometimes be counterproductive. Finally, it links these issues to human development, especially in developing countries