Hyperbolic Deformation on Quantum Lattice Hamiltonians

A group of non-uniform quantum lattice Hamiltonians in one dimension is introduced, which is related to the hyperbolic $1 + 1$-dimensional space. The Hamiltonians contain only nearest neighbor interactions whose strength is proportional to $\cosh j \lambda$, where $j$ is the lattice index and where $\lambda \ge 0$ is a deformation parameter. In the limit $\lambda \to 0$ the Hamiltonians become uniform. Spacial translation of the deformed Hamiltonians is induced by the corner Hamiltonians. As a simple example, we investigate the ground state of the deformed $S = 1/2$ Heisenberg spin chain by use of the density matrix renormalization group (DMRG) method. It is shown that the ground state is dimerized when $\lambda$ is finite. Spin correlation function show exponential decay, and the boundary effect decreases with increasing $\lambda$.Comment: 5 pages, 4 figure

Path integral Monte Carlo simulations of silicates

We investigate the thermal expansion of crystalline SiO$_2$ in the $\beta$-- cristobalite and the $\beta$-quartz structure with path integral Monte Carlo (PIMC) techniques. This simulation method allows to treat low-temperature quantum effects properly. At temperatures below the Debye temperature, thermal properties obtained with PIMC agree better with experimental results than those obtained with classical Monte Carlo methods.Comment: 27 pages, 10 figures, Phys. Rev. B (in press

Product Wave Function Renormalization Group: construction from the matrix product point of view

We present a construction of a matrix product state (MPS) that approximates the largest-eigenvalue eigenvector of a transfer matrix T, for the purpose of rapidly performing the infinite system density matrix renormalization group (DMRG) method applied to two-dimensional classical lattice models. We use the fact that the largest-eigenvalue eigenvector of T can be approximated by a state vector created from the upper or lower half of a finite size cluster. Decomposition of the obtained state vector into the MPS gives a way of extending the MPS, at the system size increment process in the infinite system DMRG algorithm. As a result, we successfully give the physical interpretation of the product wave function renormalization group (PWFRG) method, and obtain its appropriate initial condition.Comment: 8 pages, 8 figure

The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein–organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein–organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein–organelle membership from quantitative MS experiments. Biological significance Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein–organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein–organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein–organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]

The Word Problem for Omega-Terms over the Trotter-Weil Hierarchy

For two given $\omega$-terms $\alpha$ and $\beta$, the word problem for $\omega$-terms over a variety $\boldsymbol{\mathrm{V}}$ asks whether $\alpha=\beta$ in all monoids in $\boldsymbol{\mathrm{V}}$. We show that the word problem for $\omega$-terms over each level of the Trotter-Weil Hierarchy is decidable. More precisely, for every fixed variety in the Trotter-Weil Hierarchy, our approach yields an algorithm in nondeterministic logarithmic space (NL). In addition, we provide deterministic polynomial time algorithms which are more efficient than straightforward translations of the NL-algorithms. As an application of our results, we show that separability by the so-called corners of the Trotter-Weil Hierarchy is witnessed by $\omega$-terms (this property is also known as $\omega$-reducibility). In particular, the separation problem for the corners of the Trotter-Weil Hierarchy is decidable

A 23 GHz Survey of GRB Error Boxes

The Haystack 37-meter telescope was used in a pilot project in May 1995 to observe GRB error boxes at 23~GHz. Seven BATSE error boxes and two IPN arcs were scanned by driving the beam of the telescope rapidly across their area. For the BATSE error boxes, the radio observations took place two to eighteen days after the BATSE detection, and several boxes were observed more than once. Total power data were recorded continuously as the telescope was driven at a rate of 0.2~degrees/second, yielding Nyquist sampling of the beam with an integration time of 50~milliseconds, corresponding to a theoretical rms sensitivity of 0.5~Jy. Under conditions of good weather, this sensitivity was achieved. In a preliminary analysis of the data we detect only two sources, 3C273 and 0552+398, both catalogued sources that are known to be variable at 23~GHz. Neither had a flux density that was unusally high or low at the time of our observations.Comment: 5 pages, 1 postscript figure. To appear in Proceedings of the Third Huntsville Symposium on Gamma-Ray Bursts (eds. C. Kouveliotou, M. S. Briggs, and G. J. Fishman

Cost-effectiveness analysis of maternal immunisation against group B Streptococcus (GBS) disease: A modelling study

Background There is a considerable global burden of invasive group B streptococcal (GBS) disease. Vaccines are being developed for use in pregnant women to offer protection to neonates. Objective To estimate the potential impact and cost-effectiveness of maternal immunisation against neonatal and maternal invasive GBS disease in the UK. Methods We developed a decision-tree model encompassing GBS-related events in infants and mothers, following a birth cohort with a time horizon equivalent to average life expectancy (81 years). We parameterised the model using contemporary data from disease surveillance and outcomes in GBS survivors. Costs were taken from NHS sources and research studies. Maternal immunisation in combination with risk-based intrapartum antibiotic prophylaxis (IAP) was compared to the current standard practice of risk-based IAP alone from an NHS and Personal Social Services (health-provider) perspective. We estimated the cases averted and cost per QALY gained through vaccination. One-way sensitivity analysis, scenario analysis and probabilistic sensitivity analysis were performed. Results An effective maternal immunisation programme could substantially reduce the burden of GBS disease. The deterministic analysis estimated the threshold cost-effective price for a GBS vaccine to be £54 per dose at £20,000/QALY (£71 per dose at £30,000/QALY). Results were most sensitive to assumptions on disease incidence, sequelae rate and vaccine efficacy. Probabilistic analysis showed 90.66% of iterations fell under the £30,000 threshold at a vaccine price of £55. Inclusion of modest prevention of stillbirths and/or, preterm births, carer health impacts, maternal GBS deaths and 1.5% discounting improved cost-effectiveness compared to the base case. Lowering vaccine strain coverage made the vaccine less cost-effective. A key limitation is that the properties of the final GBS vaccine are unknown. Conclusions Maternal GBS immunisation is expected to be cost-effective, even at a relatively high vaccine price

Doped two orbital chains with strong Hund's rule couplings - ferromagnetism, spin gap, singlet and triplet pairings

Different models for doping of two-orbital chains with mobile $S=1/2$ fermions and strong, ferromagnetic (FM) Hund's rule couplings stabilizing the S=1 spins are investigated by density matrix renormalization group (DMRG) methods. The competition between antiferromagnetic (AF) and FM order leads to a rich phase diagram with a narrow FM region for weak AF couplings and strongly enhanced triplet pairing correlations. Without a level difference between the orbitals, the spin gap persists upon doping, whereas gapless spin excitations are generated by interactions among itinerant polarons in the presence of a level difference. In the charge sector we find dominant singlet pairing correlations without a level difference, whereas upon the inclusion of a Coulomb repulsion between the orbitals or with a level difference, charge density wave (CDW) correlations decay slowest. The string correlation functions remain finite upon doping for all models.Comment: 9pages, 9figure

Corner Transfer Matrix Renormalization Group Method

We propose a new fast numerical renormalization group method,the corner transfer matrix renormalization group (CTMRG) method, which is based on a unified scheme of Baxter's corner transfer matrix method and White's density matrix renormalization groupmethod. The key point is that a product of four corner transfer matrices gives the densitymatrix. We formulate the CTMRG method as a renormalization of 2D classical models.Comment: 8 pages, LaTeX and 4 figures. Revised version is converted to a latex file and added an example of a computatio