Exact and Scaling Form of the Bipartite Fidelity of the Infinite XXZ Chain

We find an exact expression for the bipartite fidelity f=|'|^2, where |vac> is the vacuum eigenstate of an infinite-size antiferromagnetic XXZ chain and |vac>' is the vacuum eigenstate of an infinite-size XXZ chain which is split in two. We consider the quantity -ln(f) which has been put forward as a measure of quantum entanglement, and show that the large correlation length xi behaviour is consistent with a general conjecture -ln(f) ~ c/8 ln(xi), where c is the central charge of the UV conformal field theory (with c=1 for the XXZ chain). This behaviour is a natural extension of the existing conformal field theory prediction of -ln(f) ~ c/8 ln(L) for a length L bipartite system with 0<< L <<xi.Comment: 6 page

Bi-partite entanglement entropy in integrable models with backscattering

In this paper we generalise the main result of a recent work by J. L. Cardy and the present authors concerning the bi-partite entanglement entropy between a connected region and its complement. There the expression of the leading order correction to saturation in the large distance regime was obtained for integrable quantum field theories possessing diagonal scattering matrices. It was observed to depend only on the mass spectrum of the model and not on the specific structure of the diagonal scattering matrix. Here we extend that result to integrable models with backscattering (i.e. with non-diagonal scattering matrices). We use again the replica method, which connects the entanglement entropy to partition functions on Riemann surfaces with two branch points. Our main conclusion is that the mentioned infrared correction takes exactly the same form for theories with and without backscattering. In order to give further support to this result, we provide a detailed analysis in the sine-Gordon model in the coupling regime in which no bound states (breathers) occur. As a consequence, we obtain the leading correction to the sine-Gordon partition function on a Riemann surface in the large distance regime. Observations are made concerning the limit of large number of sheets.Comment: 22 pages, 2 figure

Alkali-Alumina Sorbents for Regenerable SO_2 Removal in Fluidized-Coal Combustion

Sodium and sodium-lithium oxides supported on porous alumina have been investigated as regenerable SO_2 sorbents for fluidized coal combustion. In adsorption the oxides are converted to sulfates. In regeneration, carried out by reduction with CO, the sulfates are converted back to oxides while sulfur is removed in elemental form (S_2), SO_2 and COS. The transient composition of sorbent and gaseous products was measured in a thermogravimetric analyzer and a packed-bed microreactor in order to delineate the basic chemistry of regeneration and determine conditions that maximize the yield of elemental sulfur

Mapping quantum Hall edge states in graphene by scanning tunneling microscopy

Quantum Hall edge states are the paradigmatic example of the bulk-boundary correspondence. They are prone to intricate reconstructions calling for their detailed investigation at high spatial resolution. Here, we map quantum Hall edge states of monolayer graphene at a magnetic field of 7 T with scanning tunneling microscopy. The graphene sample features a gate-tunable lateral interface between areas of different filling factor. We compare the results with detailed tight-binding calculations quantitatively accounting for the perturbation by the tip-induced quantum dot. We find that the edge state pattern is mapped with little perturbation by adequate choice of gate voltage. We observe extended compressible regions, the antinodal structure of edge states and their meandering along the lateral interface.Comment: 23 pages, 23 figure

Derivation of Matrix Product Ansatz for the Heisenberg Chain from Algebraic Bethe Ansatz

We derive a matrix product representation of the Bethe ansatz state for the XXX and XXZ spin-1/2 Heisenberg chains using the algebraic Bethe ansatz. In this representation, the components of the Bethe eigenstates are expressed as traces of products of matrices which act on ${\bar {\mathscr H}}$, the tensor product of auxiliary spaces. By changing the basis in ${\bar {\mathscr H}}$, we derive explicit finite-dimensional representations for the matrices. These matrices are the same as those appearing in the recently proposed matrix product ansatz by Alcaraz and Lazo [Alcaraz F C and Lazo M J 2006 {\it J. Phys. A: Math. Gen.} \textbf{39} 11335.] apart from normalization factors. We also discuss the close relation between the matrix product representation of the Bethe eigenstates and the six-vertex model with domain wall boundary conditions [Korepin V E 1982 {\it Commun. Math. Phys.}, \textbf{86} 391.] and show that the change of basis corresponds to a mapping from the six-vertex model to the five-vertex model.Comment: 24 pages; minor typos are correcte

Hyperuniversality of Fully Anisotropic Three-Dimensional Ising Model

For the fully anisotropic simple-cubic Ising lattice, the critical finite-size scaling amplitudes of both the spin-spin and energy-energy inverse correlation lengths and the singular part of the reduced free-energy density are calculated by the transfer-matrix method and a finite-size scaling for cyclic L x L x oo clusters with L=3 and 4. Analysis of the data obtained shows that the ratios and the directional geometric means of above amplitudes are universal.Comment: RevTeX 3.0, 24 pages, 2 figures upon request, accepted for publication in Phys. Rev.

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201

Decomposition of automotive manufacturing machines through a mechanism taxonomy within a product lifecycle management framework

The automotive sector as with other manufacturing industries is under continual pressure from the consumer to deliver greater levels of product customisation at a higher quality and at reduced costs. Maintaining market position is therefore increasingly determined by a company's ability to innovate design changes quickly and produce greater numbers of product variants on leaner production lines with shorter times to market. In response manufacturers are attempting to accommodate product customisation and change through the use of reconfigurable production machines. Besides the need for flexibility, production facilities represent a significant investment for automotive manufacturers which is increasingly critical to commercial success; consequently the need to reduce costs through the reuse of assembly and manufacturing hardware on new product programs is becoming crucial. The aim of this research is to enable production machines to be more easily and cost effectively built and subsequently reconfigurable through the adoption of a component-based approach to their implementation utilising virtual manufacturing tools such as Product Lifecycle Management (PLM). It is suggested that through the decomposition of manufacturing machines into standardised mechanisms and their associated data structures a revised business model can be defined. The mechanisms are classified and deployed as part of a consistent integrated data structure that encompasses product, process and plant information. An objective is to properly integrate manufacturing data with more established Product Data Management (PDM) processes. The main areas of research reported in this article are, (1) development of a method for identifying and mapping data producers, consumers and flow, (2) development of standardised data structures for the management of manufacturing data within a PLM tool, (3) development of a taxonomy for the decomposition of manufacturing and assembly lines into a library of standard physical, logical and structural mechanisms and their associated interfaces. An automotive OEM case study is presented to illustrate the classification and management of production mechanisms focusing on an engine assembly line

The Primordial Inflation Polarization Explorer (PIPER)

The Primordial Inflation Polarization Explorer (PIPER) is a balloon-borne cosmic microwave background (CMB) polarimeter designed to search for evidence of inflation by measuring the large-angular scale CMB polarization signal. BICEP2 recently reported a detection of B-mode power corresponding to the tensor-to-scalar ratio r = 0.2 on ~2 degree scales. If the BICEP2 signal is caused by inflationary gravitational waves (IGWs), then there should be a corresponding increase in B-mode power on angular scales larger than 18 degrees. PIPER is currently the only suborbital instrument capable of fully testing and extending the BICEP2 results by measuring the B-mode power spectrum on angular scales $\theta$ = ~0.6 deg to 90 deg, covering both the reionization bump and recombination peak, with sensitivity to measure the tensor-to-scalar ratio down to r = 0.007, and four frequency bands to distinguish foregrounds. PIPER will accomplish this by mapping 85% of the sky in four frequency bands (200, 270, 350, 600 GHz) over a series of 8 conventional balloon flights from the northern and southern hemispheres. The instrument has background-limited sensitivity provided by fully cryogenic (1.5 K) optics focusing the sky signal onto four 32x40-pixel arrays of time-domain multiplexed Transition-Edge Sensor (TES) bolometers held at 140 mK. Polarization sensitivity and systematic control are provided by front-end Variable-delay Polarization Modulators (VPMs), which rapidly modulate only the polarized sky signal at 3 Hz and allow PIPER to instantaneously measure the full Stokes vector (I, Q, U, V) for each pointing. We describe the PIPER instrument and progress towards its first flight.Comment: 11 pages, 7 figures. To be published in Proceedings of SPIE Volume 9153. Presented at SPIE Astronomical Telescopes + Instrumentation 2014, conference 915