Elementary Quantum Mechanics in a Space-time Lattice

Studies of quantum fields and gravity suggest the existence of a minimal length, such as Planck length \cite{Floratos,Kempf}. It is natural to ask how the existence of a minimal length may modify the results in elementary quantum mechanics (QM) problems familiar to us \cite{Gasiorowicz}. In this paper we address a simple problem from elementary non-relativistic quantum mechanics, called "particle in a box", where the usual continuum (1+1)-space-time is supplanted by a space-time lattice. Our lattice consists of a grid of $\lambda_0 \times \tau_0$ rectangles, where $\lambda_0$, the lattice parameter, is a fundamental length (say Planck length) and, we take $\tau_0$ to be equal to $\lambda_0/c$. The corresponding Schrodinger equation becomes a difference equation, the solution of which yields the $q$-eigenfunctions and $q$-eigenvalues of the energy operator as a function of $\lambda_0$. The $q$-eigenfunctions form an orthonormal set and both $q$-eigenfunctions and $q$-eigenvalues reduce to continuum solutions as $\lambda_0 \rightarrow 0 .$ The corrections to eigenvalues because of the assumed lattice is shown to be $O(\lambda_0^2).$ We then compute the uncertainties in position and momentum, $\Delta x, \Delta p$ for the box problem and study the consequent modification of Heisenberg uncertainty relation due to the assumption of space-time lattice, in contrast to modifications suggested by other investigations such as \cite{Floratos}

Anisotropic magnetoresistance in a 2DEG in a quasi-random magnetic field

We present magnetotransport results for a 2D electron gas (2DEG) subject to the quasi-random magnetic field produced by randomly positioned sub-micron Co dots deposited onto the surface of a GaAs/AlGaAs heterostructure. We observe strong local and non-local anisotropic magnetoresistance for external magnetic fields in the plane of the 2DEG. Monte-Carlo calculations confirm that this is due to the changing topology of the quasi-random magnetic field in which electrons are guided predominantly along contours of zero magnetic field.Comment: 4 pages, 6 figures, submitted to Phys. Rev.

Ballistic electron motion in a random magnetic field

Using a new scheme of the derivation of the non-linear $\sigma$-model we consider the electron motion in a random magnetic field (RMF) in two dimensions. The derivation is based on writing quasiclassical equations and representing their solutions in terms of a functional integral over supermatrices $Q$ with the constraint $Q^2=1$. Contrary to the standard scheme, neither singling out slow modes nor saddle-point approximation are used. The $\sigma$-model obtained is applicable at the length scale down to the electron wavelength. We show that this model differs from the model with a random potential (RP).However, after averaging over fluctuations in the Lyapunov region the standard $\sigma$-model is obtained leading to the conventional localization behavior.Comment: 10 pages, no figures, to be submitted in PRB v2: Section IV is remove

Archaeology and Desertification in the Wadi Faynan: the Fourth (1999) Season of the Wadi Faynan Landscape Survey

Reproduced with permission of the publisher. © 2000 Council for British Research in the Levant. Details of the publication are available at: http://www.cbrl.org.uk/Publications/publications_default.shtmThis report describes the fourth season of fieldwork by an interdisciplinary team of archaeologists and geographers working together to reconstruct the landscape history of the Wadi Faynan in southern Jordan. The particular focus of the project is the long-term history of inter-relationships between landscape and people, as a contribution to the study of processes of desertification and environmental degradation. The 1999 fieldwork contributed significantly towards the five Objectives defined for the final two field seasons of the project in 1999 and 2000: to map the archaeology outside the ancient field systems flooring the wadi that have formed the principal focus of the archaeological survey in the previous seasons; to use ethnoarchaeological studies both to reconstruct modern and recent land use and also to yield archaeological signatures of land use to inform the analysis of the survey data; to complete the survey of ancient field systems and refine understanding of when and how they functioned; to complete the programme of geomorphological and palaeoecological fieldwork, and in particular to refine the chronology of climatic change and human impacts; and to complete the recording and classification of finds

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Acoustic cell washing and raman spectroscopy technologies To address cell therapy bioprocess challenges

Many organizations are confronting the challenges of economically ensuring the manufacture of safe and efficacious cell therapy products. These processes often depend on devices and methods that were developed for only related applications, such as blood cell processing or scientific research. Thus, we are in a window of opportunity to tailor innovative technologies to address the emerging specialized needs of cell therapy manufacturing. The most frequent unit operation is to wash cells between process stages, such as from DMSO containing cryopreservation medium to culture expansion medium. In particular for relatively small-scale autologous cell therapy processing, cell washing is imperfectly performed by closed system blood cell centrifuges or filters. We previously developed an acoustic cell separation device, widely used for over 15 years in CHO cell perfusion cultures. This technology acts as a non-fouling filter for months of operation, by using the forces generated in ultrasonic standing wave fields. These forces separate cells from medium based on differences in density and compressibility. Greater than 99.9% cell washing with 95% washed cell recovery efficiencies have been provided by our device. We also have recently enhanced the acoustic technology to perfuse 100 million cell/mL cultures, maintaining \u3e99% cell separation efficiencies. This provides an alternative high performance closed manufacturing system, to perfuse, concentrate and wash cells, with no physical filter barrier or mechanical moving parts. While many clinical trials have had few adverse events, the great promise of cellular therapies comes with grave risks, such as from potentially oncogenic pluripotent cells present in embryonic stem cell derived populations. There is an urgent need for process analytical technologies to non-invasively monitor mammalian cell populations and improve the reliability of manufactured cell products. This includes to monitor both the expected differentiation as well as to detect unexpected cells in the process. Recently, technological advances have led to an explosive growth in the capabilities of Raman spectroscopy, increasing the potential for novel applications. We are developing the use of this spectroscopic technique to track cell development, by measuring macromolecular changes in cell samples from cultures where stem cells are differentiated towards insulin-producing cells for the treatment of diabetes. Raman spectroscopy has great potential to provide continuous on-line assessment of cell quality during the manufacture of cell-derived therapeutic cells

A Fuzzy Spatio-Temporal-based Approach for Activity Recognition

International audienceOver the last decade, there has been a significant deployment of systems dedicated to surveillance. These systems make use of real-time sensors that generate continuous streams of data. Despite their success in many cases, the increased number of sensors leads to a cognitive overload for the operator in charge of their analysis. However, the context and the application requires an ability to react in real-time. The research presented in this paper introduces a spatio-temporal-based approach the objective of which is to provide a qualitative interpretation of the behavior of an entity (e.g., a human or vehicle). The process is formally supported by a fuzzy logic-based approach, and designed in order to be as generic as possible

Semiclassical theory of transport in a random magnetic field

We study the semiclassical kinetics of 2D fermions in a smoothly varying magnetic field $B({\bf r})$. The nature of the transport depends crucially on both the strength $B_0$ of the random component of $B({\bf r})$ and its mean value $\bar{B}$. For $\bar{B}=0$, the governing parameter is $\alpha=d/R_0$, where $d$ is the correlation length of disorder and $R_0$ is the Larmor radius in the field $B_0$. While for $\alpha\ll 1$ the Drude theory applies, at $\alpha\gg 1$ most particles drift adiabatically along closed contours and are localized in the adiabatic approximation. The conductivity is then determined by a special class of trajectories, the "snake states", which percolate by scattering at the saddle points of $B({\bf r})$ where the adiabaticity of their motion breaks down. The external field also suppresses the diffusion by creating a percolation network of drifting cyclotron orbits. This kind of percolation is due only to a weak violation of the adiabaticity of the cyclotron rotation, yielding an exponential drop of the conductivity at large $\bar{B}$. In the regime $\alpha\gg 1$ the crossover between the snake-state percolation and the percolation of the drift orbits with increasing $\bar{B}$ has the character of a phase transition (localization of snake states) smeared exponentially weakly by non-adiabatic effects. The ac conductivity also reflects the dynamical properties of particles moving on the fractal percolation network. In particular, it has a sharp kink at zero frequency and falls off exponentially at higher frequencies. We also discuss the nature of the quantum magnetooscillations. Detailed numerical studies confirm the analytical findings. The shape of the magnetoresistivity at $\alpha\sim 1$ is in good agreement with experimental data in the FQHE regime near $\nu=1/2$.Comment: 22 pages REVTEX, 14 figure