The Kondo lattice model with correlated conduction electrons

We investigate a Kondo lattice model with correlated conduction electrons. Within dynamical mean-field theory the model maps onto an impurity model where the host has to be determined self-consistently. This impurity model can be derived from an Anderson-Hubbard model both by equating the low-energy excitations of the impurity and by a canonical transformation. On the level of dynamical mean-field theory this establishes the connection of the two lattice models. The impurity model is studied numerically by an extension of the non-crossing approximation to a two-orbital impurity. We find that with decreasing temperature the conduction electrons first form quasiparticles unaffected by the presence of the lattice of localized spins. Then, reducing the temperature further, the particle-hole symmetric model turns into an insulator. The quasiparticle peak in the one-particle spectral density splits and a gap opens. The size of the gap increases when the correlations of the conduction electrons become stronger. These findings are similar to the behavior of the Anderson-Hubbard model within dynamical mean-field theory and are obtained with much less numerical effort.Comment: 7 pages RevTeX with 3 ps figures, accepted by PR

Enhanced Local Moment Formation in a Chiral Luttinger Liquid

We derive here a stability condition for a local moment in the presence of an interacting sea of conduction electrons. The conduction electrons are modeled as a Luttinger liquid in which chirality and spin are coupled. We show that an Anderson-U defect in such an interacting system can be transformed onto a nearly-Fermi liquid problem. We find that correlations among the conduction electrons stabilize the local moment phase. A Schrieffer-Wolff transformation is then performed which results in an anisotropic exchange interaction indicative of the Kondo effect in a Luttinger liquid. The ground-state properties of this model are then equivalent to those of the Kondo model in a Luttinger liquid.Comment: 11 pages, no figure

Generalized Heisenberg algebras and k-generalized Fibonacci numbers

It is shown how some of the recent results of de Souza et al. [1] can be generalized to describe Hamiltonians whose eigenvalues are given as k-generalized Fibonacci numbers. Here k is an arbitrary integer and the cases considered by de Souza et al. corespond to k=2.Comment: 8 page

Periodic Anderson model with correlated conduction electrons

We investigate a periodic Anderson model with interacting conduction electrons which are described by a Hubbard-type interaction of strength U_c. Within dynamical mean-field theory the total Hamiltonian is mapped onto an impurity model, which is solved by an extended non-crossing approximation. We consider the particle-hole symmetric case at half-filling. Similar to the case U_c=0, the low-energy behavior of the conduction electrons at high temperatures is essentially unaffected by the f-electrons and for small U_c a quasiparticle peak corresponding to the Hubbard model evolves first. These quasiparticles screen the f-moments when the temperature is reduced further, and the system turns into an insulator with a tiny gap and flat bands. The formation of the quasiparticle peak is impeded by increasing either U_c or the c-f hybridization. Nevertheless almost dispersionless bands emerge at low temperature with an increased gap, even in the case of initially insulating host electrons. The size of the gap in the one-particle spectral density at low temperatures provides an estimate for the low-energy scale and increases as U_c increases.Comment: 11 pages RevTeX with 13 ps figures, accepted by PR

Local Moments in an Interacting Environment

We discuss how local moment physics is modified by the presence of interactions in the conduction sea. Interactions in the conduction sea are shown to open up new symmetry channels for the exchange of spin with the localized moment. We illustrate this conclusion in the strong-coupling limit by carrying out a Schrieffer Wolff transformation for a local moment in an interacting electron sea, and show that these corrections become very severe in the approach to a Mott transition. As an example, we show how the Zhang Rice reduction of a two-band model is modified by these new effects.Comment: Latex file with two postscript figures. Revised version, with more fully detailed calculation

The boson-fermion model with on-site Coulomb repulsion between fermions

The boson-fermion model, describing a mixture of itinerant electrons hybridizing with tightly bound electron pairs represented as hard-core bosons, is here generalized with the inclusion of a term describing on-site Coulomb repulsion between fermions with opposite spins. Within the general framework of the Dynamical Mean-Field Theory, it is shown that around the symmetric limit of the model this interaction strongly competes with the local boson-fermion exchange mechanism, smoothly driving the system from a pseudogap phase with poor conducting properties to a metallic regime characterized by a substantial reduction of the fermionic density. On the other hand, if one starts from correlated fermions described in terms of the one-band Hubbard model, the introduction in the half-filled insulating phase of a coupling with hard-core bosons leads to the disappearance of the correlation gap, with a consequent smooth crossover to a metallic state.Comment: 7 pages, 6 included figures, to appear in Phys. Rev.

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

Magnetic impurities coupled to quantum antiferromagnets in one dimension

Magnetic impurities coupled antiferromagnetically to a one-dimensional Heisenberg model are studied by numerical diagonalization of chains of finite clusters. By calculating the binding energy and the correlation function, it is shown that a local singlet develops around each impurity. This holds true for systems with a single impurity, with two impurities, and for impurities forming a lattice. The local character of the singlet is found to be little affected by the presence of other impurity spins. A small effective interaction is found between a pair of impurity spins, which oscillates depending on impurity distances. For impurity lattices, the energy spectrum shows a gap which is found to be much smaller than the binding energy per impurity if the coupling constants are small. For larger coupling constants, it increases to the same order of magnitude as the binding energy, indicating that a local singlet is broken to create excited states. Impurity lattices with ferromagnetic couplings are also studied and their connection to the Haldane problem is discussed.Comment: 25 pages, plain TeX, 17 figures available on request, to be publised in Phys. Rev.

Indications of Spin-Charge Separation at Short Distance and Stripe Formation in the Extended t-J Model on Ladders and Planes

The recently discussed tendency of holes to generate nontrivial spin environments in the extended two-dimensional t-J model (G. Martins, R. Eder, and E. Dagotto, Phys. Rev. B{\bf 60}, R3716 (1999)) is here investigated using computational techniques applied to ladders with several number of legs. This tendency is studied also with the help of analytic spin-polaron approaches directly in two dimensions. Our main result is that the presence of robust antiferromagnetic correlations between spins located at both sides of a hole either along the x or y axis, observed before numerically on square clusters, is also found using ladders, as well as applying techniques based on a string-basis expansion. This so-called "across-the-hole" nontrivial structure exists even in the two-leg spin-gapped ladder system, and leads to an effective reduction in dimensionality and spin-charge separation at short-distances, with a concomitant drastic reduction in the quasiparticle (QP) weight Z. In general, it appears that holes tend to induce one-dimensional-like spin arrangements to improve their mobility. Using ladders it is also shown that the very small J/t$\sim$0.1 regime of the standard t-J model may be more realistic than anticipated in previous investigations, since such regime shares several properties with those found in the extended model at realistic couplings. Another goal of the present article is to provide additional information on the recently discussed tendencies to stripe formation and spin incommensurability reported for the extended t-J model.Comment: 14 pages, 21 figures, LateX, submited to Phys. Rev.

Identification of functional rare variants in genome-wide association studies using stability selection based on random collapsing

Genome-wide association studies are a powerful approach used to identify common variants for complex disease. However, the traditional genome-wide association methods may not be optimal when they are applied to rare variants because of the rare variants’ low frequencies and weak signals. To alleviate the difficulty, investigators have proposed many methods that collapse rare variants. In this paper, we propose a novel ranking method, which we call stability selection based on random collapsing, to rank the candidate rare variants. We use the simulated mini-exome data sets of unrelated individuals from Genetic Analysis Workshop 17 for the analysis. The numerical results suggest that the selection based on a random collapsing method is promising for identifying functional rare variants in genome-wide association studies. Further research to examine the error control property of the proposed method is underway