Degenerate distributions in complex Langevin dynamics: one-dimensional QCD at finite chemical potential

We demonstrate analytically that complex Langevin dynamics can solve the sign problem in one-dimensional QCD in the thermodynamic limit. In particular, it is shown that the contributions from the complex and highly oscillating spectral density of the Dirac operator to the chiral condensate are taken into account correctly. We find an infinite number of classical fixed points of the Langevin flow in the thermodynamic limit. The correct solution originates from a continuum of degenerate distributions in the complexified space.Comment: 20 pages, several eps figures, minor comments added, to appear in JHE

The sign problem across the QCD phase transition

The average phase factor of the QCD fermion determinant signals the strength of the QCD sign problem. We compute the average phase factor as a function of temperature and baryon chemical potential using a two-flavor NJL model. This allows us to study the strength of the sign problem at and above the chiral transition. It is discussed how the $U_A(1)$ anomaly affects the sign problem. Finally, we study the interplay between the sign problem and the endpoint of the chiral transition.Comment: 9 pages and 9 fig

Developments in lattice quantum chromodynamics for matter at high temperature and density

A brief overview of the QCD phase diagram at nonzero temperature and density is provided. It is explained why standard lattice QCD techniques are not immediately applicable for its determination, due to the sign problem. We then discuss a selection of recent lattice approaches that attempt to evade the sign problem and classify them according to the underlying principle: constrained simulations (density of states, histograms), holomorphicity (complex Langevin, Lefschetz thimbles), partial summations (clusters, subsets, bags) and change in integration order (strong coupling, dual formulations)

Learning Moore Machines from Input-Output Traces

The problem of learning automata from example traces (but no equivalence or membership queries) is fundamental in automata learning theory and practice. In this paper we study this problem for finite state machines with inputs and outputs, and in particular for Moore machines. We develop three algorithms for solving this problem: (1) the PTAP algorithm, which transforms a set of input-output traces into an incomplete Moore machine and then completes the machine with self-loops; (2) the PRPNI algorithm, which uses the well-known RPNI algorithm for automata learning to learn a product of automata encoding a Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore machine using PTAP extended with state merging. We prove that MooreMI has the fundamental identification in the limit property. We also compare the algorithms experimentally in terms of the size of the learned machine and several notions of accuracy, introduced in this paper. Finally, we compare with OSTIA, an algorithm that learns a more general class of transducers, and find that OSTIA generally does not learn a Moore machine, even when fed with a characteristic sample

Conductivity and quasinormal modes in holographic theories

We show that in field theories with a holographic dual the retarded Green's function of a conserved current can be represented as a convergent sum over the quasinormal modes. We find that the zero-frequency conductivity is related to the sum over quasinormal modes and their high-frequency asymptotics via a sum rule. We derive the asymptotics of the quasinormal mode frequencies and their residues using the phase-integral (WKB) approach and provide analytic insight into the existing numerical observations concerning the asymptotic behavior of the spectral densities.Comment: 24 pages, 3 figure

In vivo validation of the electronic depth control probes.

In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model

Bayesian modeling of recombination events in bacterial populations

Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of strains in a data set increases. Results: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites. Conclusion: A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/ mnf//mate/jc/software/brat.html

Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke.

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation

Disposition of Federally Owned Surpluses

PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions

Wake up, wake up! It's me! It's my life! patient narratives on person-centeredness in the integrated care context: a qualitative study

Person-centered care emphasizes a holistic, humanistic approach that puts patients first, at the center of medical care. Person-centeredness is also considered a core element of integrated care. Yet typologies of integrated care mainly describe how patients fit within integrated services, rather than how services fit into the patient's world. Patient-centeredness has been commonly defined through physician's behaviors aimed at delivering patient-centered care. Yet, it is unclear how 'person-centeredness' is realized in integrated care through the patient voice. We aimed to explore patient narratives of person-centeredness in the integrated care context