Gaussian quantum Monte Carlo methods for fermions

We introduce a new class of quantum Monte Carlo methods, based on a Gaussian quantum operator representation of fermionic states. The methods enable first-principles dynamical or equilibrium calculations in many-body Fermi systems, and, combined with the existing Gaussian representation for bosons, provide a unified method of simulating Bose-Fermi systems. As an application, we calculate finite-temperature properties of the two dimensional Hubbard model.Comment: 4 pages, 3 figures, Revised version has expanded discussion, simplified mathematical presentation, and application to 2D Hubbard mode

Improving the efficiency of remanufacture through enhanced pre-processing inspection–a comprehensive study of over 2000 engines at Caterpillar remanufacturing, U.K.

Remanufacture, an industrial process to return used product to an “as-new” condition, is a key strategy in environmentally conscious manufacturing and waste management. However strategies to improve the efficiency of the process are hampered by a lack of remanufacturing-specific knowledge and tools. This paper presents the results of quantitative research, conducted in a Caterpillar Remanufacturing UK facility, to establish the relationship between pre-processing inspection levels and the subsequent remanufacturing process time for returned used products known as cores. It concludes that for components (i.e. cores) having either complex geometry (such as internal ports), a large number of sub-components or that are constructed from, or comprising of, multiple materials the remanufacturing process is shortened by increased inspection prior to processing. However, these benefits are currently limited by the amount of information that can be gained from the inspection methods used. The paper describes the practical use of these factors in a decision-making methodology for inspection and in a refined cost assessment tool

What Are Lightness Illusions and Why Do We See Them?

Lightness illusions are fundamental to human perception, and yet why we see them is still the focus of much research. Here we address the question by modelling not human physiology or perception directly as is typically the case but our natural visual world and the need for robust behaviour. Artificial neural networks were trained to predict the reflectance of surfaces in a synthetic ecology consisting of 3-D “dead-leaves” scenes under non-uniform illumination. The networks learned to solve this task accurately and robustly given only ambiguous sense data. In addition—and as a direct consequence of their experience—the networks also made systematic “errors” in their behaviour commensurate with human illusions, which includes brightness contrast and assimilation—although assimilation (specifically White's illusion) only emerged when the virtual ecology included 3-D, as opposed to 2-D scenes. Subtle variations in these illusions, also found in human perception, were observed, such as the asymmetry of brightness contrast. These data suggest that “illusions” arise in humans because (i) natural stimuli are ambiguous, and (ii) this ambiguity is resolved empirically by encoding the statistical relationship between images and scenes in past visual experience. Since resolving stimulus ambiguity is a challenge faced by all visual systems, a corollary of these findings is that human illusions must be experienced by all visual animals regardless of their particular neural machinery. The data also provide a more formal definition of illusion: the condition in which the true source of a stimulus differs from what is its most likely (and thus perceived) source. As such, illusions are not fundamentally different from non-illusory percepts, all being direct manifestations of the statistical relationship between images and scenes

Quantum chaos in a Bose-Hubbard dimer with modulated tunnelling

In the large-$N$, classical limit, the Bose-Hubbard dimer undergoes a transition to chaos when its tunnelling rate is modulated in time. We use exact and approximate numerical simulations to determine the features of the dynamically evolving state that are correlated with the presence of chaos in the classical limit. We propose the statistical distance between initially similar number distributions as a reliable measure to distinguish regular from chaotic behaviour in the quantum dynamics. Besides being experimentally accessible, number distributions can be efficiently reconstructed numerically from binned phase-space trajectories in a truncated Wigner approximation. Although the evolving Wigner function becomes very irregular in the chaotic regions, the truncated Wigner method is nevertheless able to capture accurately the beyond mean-field dynamics.Comment: 10 pages, 10 figure

Saddle-point scrambling without thermalisation

Out-of-time-order correlators (OTOCs) have proven to be a useful tool for studying thermalisation in quantum systems. In particular, the exponential growth of OTOCS, or scrambling, is sometimes taken as an indicator of chaos in quantum systems, despite the fact that saddle points in integrable systems can also drive rapid growth in OTOCs. By analysing the Dicke model and a driven Bose-Hubbard dimer, we demonstrate that the OTOC growth driven by chaos can, nonetheless, be distinguished from that driven by saddle points through the long-term behaviour. Besides quantitative differences in the long-term average, the saddle point gives rise to large oscillations not observed in the chaotic case. The differences are also highlighted by entanglement entropy, which in the chaotic driven dimer matches a Page curve prediction. These results illustrate additional markers that can be used to distinguish chaotic behaviour in quantum systems, beyond the initial exponential growth in OTOCs.Comment: 7 pages, 5 figure

Gaussian phase-space representations for fermions

We introduce a positive phase-space representation for fermions, using the most general possible multi-mode Gaussian operator basis. The representation generalizes previous bosonic quantum phase-space methods to Fermi systems. We derive equivalences between quantum and stochastic moments, as well as operator correspondences that map quantum operator evolution onto stochastic processes in phase space. The representation thus enables first-principles quantum dynamical or equilibrium calculations in many-body Fermi systems. Potential applications are to strongly interacting and correlated Fermi gases, including coherent behaviour in open systems and nanostructures described by master equations. Examples of an ideal gas and the Hubbard model are given, as well as a generic open system, in order to illustrate these ideas.Comment: More references and examples. Much less mathematical materia

Monte Carlo techniques for real-time quantum dynamics

The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the "weight", and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The method is applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed.Comment: 28 pages, submitted to J. Comp. Phy

Rapid identification of some Leptospira isolates from cattle by random amplified polymorphic DNA fingerprinting

We compared random amplified polymorphic DNA (RAPD) fingerprinting with cross-absorption agglutination and restriction enzyme analysis for typing bovine leptospires. Using RAPD fingerprinting, we examined a number of Leptospira serovars, namely, hardjo genotypes bovis and prajitno, pomona, balcanica, tarassovi, swajizak, kremastos, australis, and zanoni, which are likely to be isolated from Australian cattle. Each serovar and genotype had a unique RAPD profile. Of 26 field isolates of Leptospira, 23 were identified as hardjo genotype bovis subtype A, 2 were identified as zanoni, and 1 was identified as pomona by RAPD fingerprinting, and their types were confirmed by cross-absorption agglutination and restriction enzyme analysis

Quantum many-body simulations using Gaussian phase-space representations

Phase-space representations are of increasing importance as a viable and successful means to study exponentially complex quantum many-body systems from first principles. This review traces the background of these methods, starting from the early work of Wigner, Glauber and Sudarshan. We focus on modern phase-space approaches using non-classical phase-space representations. These lead to the Gaussian representation, which unifies bosonic and fermionic phase-space. Examples treated include quantum solitons in optical fibers, colliding Bose-Einstein condensates, and strongly correlated fermions on lattices.Comment: Short Review (10 pages); Corrected typo in eq (14); Added a few more reference