Canonical representation for electrons and its application to the Hubbard model

A new representation for electrons is introduced, in which the electron operators are written in terms of a spinless fermion and the Pauli operators. This representation is canonical, invertible and constraint-free. Importantly, it simplifies the Hubbard interaction. On a bipartite lattice, the Hubbard model is reduced to a form in which the exchange interaction emerges simply by decoupling the Pauli subsystem from the spinless fermion bath. This exchange correctly reproduces the large $U$ superexchange. Also derived, for $U=\pm\infty$, is the Hamiltonian to study Nagaoka ferromagnetism. In this representation, the infinite-$U$ Hubbard problem becomes elegant and easier to handle. Interestingly, the ferromagnetism in Hubbard model is found to be related to the gauge invariance of the spinless fermions. Generalization of this representation for the multicomponent fermions, a new representation for bosons, the notion of a `soft-core' fermion, and some interesting unitary transformations are introduced and discussed in the appendices.Comment: 10+ pages, 3 Figure

Zero Temperature Insulator-Metal Transition in Doped Manganites

We study the transition at T=0 from a ferromagnetic insulating to a ferromagnetic metallic phase in manganites as a function of hole doping using an effective low-energy model Hamiltonian proposed by us recently. The model incorporates the quantum nature of the dynamic Jahn-Teller(JT) phonons strongly coupled to orbitally degenerate electrons as well as strong Coulomb correlation effects and leads naturally to the coexistence of localized (JT polaronic) and band-like electronic states. We study the insulator-metal transition as a function of doping as well as of the correlation strength U and JT gain in energy E_{JT}, and find, for realistic values of parameters, a ground state phase diagram in agreement with experiments. We also discuss how several other features of manganites as well as differences in behaviour among manganites can be understood in terms of our model.Comment: To be published in Europhysics Letter

Effect of Ni-doping on magnetism and superconductivity in Eu0.5K0.5Fe2As2

The effect of Ni-doping on the magnetism and superconductivity in Eu0.5K0.5Fe2As2 has been studied through a systematic investigation of magnetic and superconducting properties of Eu0.5K0.5(Fe1-xNix)2As2 (x = 0, 0.03, 0.05, 0.08 and 0.12) compounds by means of dc and ac magnetic susceptibilities, electrical resistivity and specific heat measurements. Eu0.5K0.5Fe2As2 is known to exhibit superconductivity with superconducting transition temperature Tc as high as 33 K. The Ni-doping leads to a rapid decrease in Tc; Tc is reduced to 23 K with 3% Ni-doping, and 8% Ni-doping suppresses the superconductivity to below 1.8 K. In 3% Ni-doped sample Eu0.5K0.5(Fe0.97Ni0.03)2As2 superconductivity coexists with short range ordering of Eu2+ magnetic moments at Tm ~ 6 K. The suppression of superconductivity with Ni-doping is accompanied with the emergence of a long range antiferromagnetic ordering with TN = 8.5 K and 7 K for Eu0.5K0.5(Fe0.92Ni0.08)2As2 and Eu0.5K0.5(Fe0.88Ni0.12)2As2, respectively. The temperature and field dependent magnetic measurements for x = 0.08 and 0.12 samples reflect the possibility of a helical magnetic ordering of Eu2 moments. We suspect that the helimagnetism of Eu spins could be responsible for the destruction of superconductivity as has been observed in Co-doped EuFe2As2. The most striking feature seen in the resistivity data for x = 0.08 is the reappearance of the anomaly presumably due to spin density wave transition at around 60 K. This could be attributed to the compensation of holes (K-doping at Eu-site) by the electrons (Ni-doping at Fe site). The anomaly associated with spin density wave further shifts to 200 K for x = 0.12 for which the electron doping has almost compensated the holes in the system.Comment: 9 pages, 10 figure

Thermo-magnetic history effects in the vortex state of YNi_2B_2C superconductor

The nature of five-quadrant magnetic isotherms for is different from that for in a single crystal of YNi2B2C, pointing towards an anisotropic behaviour of the flux line lattice (FLL). For, a well defined peak effect (PE) and second magnetization peak (SMP) can be observed and the loop is open prior to the PE. However, for, the loop is closed and one can observe only the PE. We have investigated the history dependence of magnetization hysteresis data for by recording minor hysteresis loops. The observed history dependence in across different anomalous regions are rationalized on the basis of su-perheating/supercooling of the vortex matter across the first-order-like phase transition and possible additional effects due to annealing of the disordered vortex bundles to the underlying equilibrium state.Comment: 4 pages, 4 figure

A conformational analysis of walker motif A [GXXXXGKT (S)] in nucleotide-binding and other proteins

The sequence GXXXXGKT/S, popularly known as Walker motif A, is widely believed to be the site for binding nucleotides in many proteins. Examination of the crystal structures in the Protein Data Bank showed that about half of the examples having these sequences do not bind or use nucleotides. Data analyses showed 92 different Walker sequences of the variable quartet (XXXX). Ramachandran angles in this segment revealed conformational similarity in the group of 45 proteins, known to bind or utilize nucleotides. The conformations of this segment in other proteins differ widely and it is not known whether they play any role in their functions. A flip of a peptide unit at different locations, with little change in the backbone conformation was noted in nine pairs of these proteins having same Walker sequence. An examination of the immediate neighborhood of the Walker sequence indicates that this region is preceded by a β -strand and followed by an α-helix, resulting in the motif β–W–α, an invariant feature amongst nucleotide-binding proteins

Inference in Probabilistic Logic Programs with Continuous Random Variables

Probabilistic Logic Programming (PLP), exemplified by Sato and Kameya's PRISM, Poole's ICL, Raedt et al's ProbLog and Vennekens et al's LPAD, is aimed at combining statistical and logical knowledge representation and inference. A key characteristic of PLP frameworks is that they are conservative extensions to non-probabilistic logic programs which have been widely used for knowledge representation. PLP frameworks extend traditional logic programming semantics to a distribution semantics, where the semantics of a probabilistic logic program is given in terms of a distribution over possible models of the program. However, the inference techniques used in these works rely on enumerating sets of explanations for a query answer. Consequently, these languages permit very limited use of random variables with continuous distributions. In this paper, we present a symbolic inference procedure that uses constraints and represents sets of explanations without enumeration. This permits us to reason over PLPs with Gaussian or Gamma-distributed random variables (in addition to discrete-valued random variables) and linear equality constraints over reals. We develop the inference procedure in the context of PRISM; however the procedure's core ideas can be easily applied to other PLP languages as well. An interesting aspect of our inference procedure is that PRISM's query evaluation process becomes a special case in the absence of any continuous random variables in the program. The symbolic inference procedure enables us to reason over complex probabilistic models such as Kalman filters and a large subclass of Hybrid Bayesian networks that were hitherto not possible in PLP frameworks. (To appear in Theory and Practice of Logic Programming).Comment: 12 pages. arXiv admin note: substantial text overlap with arXiv:1203.428

Modeling and Analysis of Interactions in Virtual Enterprises

Advances in computer networking technology and open system standards are making the creation and management of virtual enterprises feasible. A virtual enterprise is a temporary consortium of autonomous, diverse, and possibly geographically dispersed organizations that pool their resources to meet short-term objectives and exploit fastchanging market trends. For a virtual enterprise to succeed, its business processes must be automated, and its startup costs must be minimized. In this paper we describe a formal framework for modeling and reasoning about interactions in a virtual enterprise. Such a framework will form the basis for tools that provide automated support for creation and operation of virtual enterprises. 1