Loss Of Locality Research Articles

Fermi model of a quantum black hole

We propose a quantum model of the Schwarzschild black hole as a quantum mechanics of a system of fermionic degrees of freedom. The system has a constant density of states and a Fermi energy that is inversely proportional to the size of the system. Assuming the equivalence principle, we show that the degeneracy pressure of the Fermi degrees of freedom is able to withstand the collapse of gravity if the radius of the system is given precisely by the horizon radius of the Schwarzschild black hole. In our model, the fermionic degrees of freedom at each energy level can be entangled in certain different ways, giving rise to a multitude of degenerate ground states of the system. The counting of these microstates reproduces precisely the Bekenstein-Hawking entropy. This simple Fermi model is universal and works also for the Reissner-Nordström charged black hole as well as black holes with a cosmological constant. From the properties of the Fermi variables, we propose that quantum gravity is characterized by a principle of where there can be no more than V/lP3 quantum states in any volume V. It implies a loss of spatial locality below the Planck length and suggests that any singularity predicted by general relativity is resolved and replaced by a quantum space in quantum gravity. In our model, a black hole spacetime is equipped with a uniform distribution of energy levels. This is another reason why black holes can be considered a simple harmonic oscillator of quantum gravity. Published by the American Physical Society 2024

A Lagrangian/semi-Lagrangian coupling approach for accelerated meshfree modelling of extreme deformation problems

In the reproducing kernel particle method (RKPM), the approximation is achieved through construction of shape functions in the physical domain and the interaction of neighbouring nodes. When modelling large deformation problems, Lagrangian and semi-Lagrangian formulations have been proposed, where the RK functions are evaluated in the reference initial coordinates and in the current configuration, respectively. The Lagrangian RKPM breaks down when the mapping between current and reference configuration is not one-to-one and the deformation gradient is not invertible, such as in modelling high velocity impact and penetration processes. On the other hand, the semi-Lagrangian RKPM formulation with RK functions evaluated in the current configuration eliminates the requirement on the deformation mapping but results in a high computational cost. In order to retain the advantages of both formulations, a blending-based spatial coupling scheme is proposed to allow transition from the Lagrangian to the semi-Lagrangian RKPM meshfree formulation. Spatial consistency and temporal stability of the proposed coupling approach are analysed. The analysis results show that the critical time step of the coupled formulation is larger than the worst case between the pure Lagrangian and pure semi-Lagrangian RK cases. Moreover, an algorithm to update three-dimensional semi-Lagrangian kernel supports and smoothing cells is introduced to enhance the solution accuracy of the semi-Lagrangian portion of the proposed coupling scheme. The proposed update algorithm avoids the numerical issues of either insufficient support coverage or loss of locality associated with the conventional pure semi-Lagrangian formulation under large deformations. The performance of the proposed Lagrangian/semi-Lagrangian coupling approach is verified through a suite of benchmark problems, including extreme deformation problems.

Curved Momentum Space, Locality, and Generalized Space-Time

We establish the correspondence between two apparently unrelated but in fact complementary approaches of a relativistic deformed kinematics: the geometric properties of momentum space and the loss of absolute locality in canonical space-time, which can be restored with the introduction of a generalized space-time. This correspondence is made explicit for the case of κ-Poincaré kinematics and compared with its properties in the Hopf algebra framework.

Convolution dictionary learning for visible-infrared image fusion via local processing

Abstract Although convolutional sparse coding overcomes the limitations of block-based sparse representation in the process of convolutional dictionary learning, it relies too much on the Alternating Direction Method of Multipliers(ADMM) formula in the Fourier domain. This leads to a loss of locality, impacting the quality of the fused image which tends to have a fuzzy texture. To solve this problem, we use a local processing convolution dictionary-learning method to obtain a dictionary and apply the obtained dictionary to the fusion of visible-infrared images. The proposed method not only solves the problem of global convolutional sparse coding, but also overcomes the blurry fusion image defect. Experimental results show that the proposed method is superior to the comparison methods in subjective and objective evaluation. Compared with deep learning fusion methods, our fusion framework achieves an average improvement of 5.18%, 5.02%, and 4.77% in the objective evaluation QAB/F, Qe and Qp, respectively.

A Unified Framework for Clustering Constrained Data Without Locality Property

In this paper, we consider a class of constrained clustering problems of points in $$\mathbb {R}^{d}$$, where d could be rather high. A common feature of these problems is that their optimal clusterings no longer have the locality property (due to the additional constraints), which is a key property required by many algorithms for their unconstrained counterparts. To overcome the difficulty caused by the loss of locality, we present in this paper a unified framework, called Peeling-and-Enclosing, to iteratively solve two variants of the constrained clustering problems, constrained k-means clustering (k-CMeans) and constrained k-median clustering (k-CMedian). Our framework generalizes Kumar et al.’s (J ACM 57(2):5, 2010) elegant k-means clustering approach from unconstrained data to constrained data, and is based on two standalone geometric techniques, called Simplex Lemma and Weaker Simplex Lemma, for k-CMeans and k-CMedian, respectively. The simplex lemma (or weaker simplex lemma) enables us to efficiently approximate the mean (or median) point of an unknown set of points by searching a small-size grid, independent of the dimensionality of the space, in a simplex (or the surrounding region of a simplex), and thus can be used to handle high dimensional data. If k and $$\frac{1}{\epsilon }$$ are fixed numbers, our framework generates, in nearly linear time (i.e., $$O(n(\log n)^{k+1}d)$$), $$O((\log n)^{k})$$k-tuple candidates for the k mean or median points, and one of them induces a $$(1+\epsilon )$$-approximation for k-CMeans or k-CMedian, where n is the number of points. Combining this unified framework with a problem-specific selection algorithm (which determines the best k-tuple candidate), we obtain a $$(1+\epsilon )$$-approximation for each of the constrained clustering problems. Our framework improves considerably the best known results for these problems. We expect that our technique will be applicable to other variants of k-means and k-median clustering problems without locality.

Sustainable Construction in Kurdish Vernacular Architecture

The Kurdistan region is currently undergoing rapid change and development in many ways. The economy is growing, and the population is increasing. Adopting a modern lifestyle is influencing individuals and social behavior. These factors are collectively affecting the architectural styles and construction techniques of the buildings. Abandoning the vernacular architecture has led to a loss of locality. This research outlines the characteristics and elements of Kurdish vernacular architecture in Erbil city and the villages in mountainous area; it then analyses them in terms of sustainability. A descriptive method is adopted to identify the sustainable aspects of traditional building techniques and designs. Finally, the paper concludes that with developed construction regulations, some of the designs and construction methods of traditional architecture, with the right management, can be adopted in modern buildings.

SteeringWheel: A Locality-Preserving Magnification Interface for Low Vision Web Browsing.

Low-vision users struggle to browse the web with screen magnifiers. Firstly, magnifiers occlude significant portions of the webpage, thereby making it cumbersome to get the webpage overview and quickly locate the desired content. Further, magnification causes loss of spatial locality and visual cues that commonly define semantic relationships in the page; reconstructing semantic relationships exclusively from narrow views dramatically increases the cognitive burden on the users. Secondly, low-vision users have widely varying needs requiring a range of interface customizations for different page sections; dynamic customization in extant magnifiers is disruptive to users' browsing. We present SteeringWheel, a magnification interface that leverages content semantics to preserve local context. In combination with a physical dial, supporting simple rotate and press gestures, users can quickly navigate different webpage sections, easily locate desired content, get a quick overview, and seamlessly customize the interface. A user study with 15 low-vision participants showed that their web-browsing efficiency improved by at least 20 percent with SteeringWheel compared to extant screen magnifiers.

Specific Features of Energy Dispersive X-Ray Electron Probe Microanalysis in the Low Vacuum Mode

Experimental data on the generation and detection of characteristic X-radiation of elements in electron probe microanalysis of dielectric samples in the low vacuum mode without the deposition of conducting coatings are discussed. The main advantage of the considered method of analysis is the stability of the intensity ratio between diagnostic analyte lines in the wide range of currents of the electron probe and gas phase pressure in the chamber in the range 60–130 Pa, sufficient for obtaining undistorted images of the surface of dielectrics. The stability of the intensity ratio ensures obtaining correct data of the quantitative analysis of nonconducting samples without the deposition of conducting coatings. The main features of low-vacuum microanalysis for the range of gas phase pressures used are discussed, which can create additional difficulties in the study. Among such features is a possibility of the manifestation of reflexes of gas-phase elements, significant underestimation of the relative emission intensity from lighter elements in the composition of the studied samples, loss of scanning locality in the analysis of small sites on the sample surface. An example of the correct quantitative elemental analysis of a dielectric surface without the deposition of an electroconductive coating for a number of aluminosilicates is presented.

Loss of locality in gravitational correlators with a large number of insertions

We review lessons from the AdS/CFT correspondence that indicate that the emergence of locality in quantum gravity is contingent upon considering observables with a small number of insertions. Correlation functions, where the number of insertions scales with a power of the central charge of the CFT, are sensitive to nonlocal effects in the bulk theory, which arise from a combination of the effects of the bulk Gauss law and a breakdown of perturbation theory. To examine whether a similar effect occurs in flat space, we consider the scattering of massless particles in the bosonic string and the superstring in the limit, where the number of external particles, n, becomes very large. We use estimates of the volume of the Weil-Petersson moduli space of punctured Riemann surfaces to argue that string amplitudes grow factorially in this limit. We verify this factorial behavior through an extensive numerical analysis of string amplitudes at large n. Our numerical calculations rely on the observation that, in the large n limit, the string scattering amplitude localizes on the Gross-Mende saddle points, even though individual particle energies are small. This factorial growth implies the breakdown of string perturbation theory for $n\ensuremath{\sim}{(\frac{{M}_{\mathrm{pl}}}{E})}^{d\ensuremath{-}2}$ in $d$ dimensions, where $E$ is the typical individual particle energy. We explore the implications of this breakdown for the black hole information paradox. We show that the loss of locality suggested by this breakdown is precisely sufficient to resolve the cloning and strong subadditivity paradoxes.

Evolved Sustainable Building Engineering in Vernacular Architecture of Kurdistan

Vernacular Architecture in Kurdistan is a widely understudied subject. Whilst rapid development is taking place across the Kurdistan region of Iraq, the lack of a clear knowledge of local building traditions has led to the loss of locality and engineering adaptability of newly developed buildings. Advances in mass development in the Kurdistan region need to have clear signs of Kurdish cultural heritage alongside lasting and sustainable solutions. The study of mountain villages of rural Kurdistan will provide valuable information about sustainable building practices as well as cultural values in regional settlements. This in turn will be useful in finding more adoptable green choices in the region and identifying the characteristics of the evolved building engineering of these indigenous settlements. This paper will first describes the characteristics of the evolved engineering and sustainable adoptions of Kurdish historical building traditions through selected site visits to Kurdish vernacular settlements and then analyses the building customs of rural communities of Kurdistan for possible adoption in contemporary developments.

Tesseract

Double-paging is an often-cited, if unsubstantiated, problem in multi-level scheduling of memory between virtual machines (VMs) and the hypervisor. This problem occurs when both a virtualized guest and the hypervisor overcommit their respective physical address-spaces. When the guest pages out memory previously swapped out by the hypervisor, it initiates an expensive sequence of steps causing the contents to be read in from the hypervisor swapfile only to be written out again, significantly lengthening the time to complete the guest I/O request. As a result, performance rapidly drops. We present Tesseract, a system that directly and transparently addresses the double-paging problem. Tesseract tracks when guest and hypervisor I/O operations are redundant and modifies these I/Os to create indirections to existing disk blocks containing the page contents. Although our focus is on reconciling I/Os between the guest disks and hypervisor swap, our technique is general and can reconcile, or deduplicate, I/Os for guest pages read or written by the VM. Deduplication of disk blocks for file contents accessed in a common manner is well-understood. One challenge that our approach faces is that the locality of guest I/Os (reflecting the guest's notion of disk layout) often differs from that of the blocks in the hypervisor swap. This loss of locality through indirection results in significant performance loss on subsequent guest reads. We propose two alternatives to recovering this lost locality, each based on the idea of asynchronously reorganizing the indirected blocks in persistent storage. We evaluate our system and show that it can significantly reduce the costs of double-paging. We focus our experiments on a synthetic benchmark designed to highlight its effects. In our experiments we observe Tesseract can improve our benchmark's throughput by as much as 200% when using traditional disks and by as much as 30% when using SSD. At the same time worst case application responsiveness can be improved by a factor of 5.

Locality and the relativity principle beyond special relativity

Locality of interactions is an essential ingredient of Special Relativity. Recently, a new framework under the name of relative locality [G. Amelino-Camelia, L. Freidel, J. Kowalski-Glikman, and L. Smolin, arXiv:1101.0931.] has been proposed as a way to consider Planckian modifications of the relativistic dynamics of particles. We note in this paper that the loss of absolute locality is a general feature of theories beyond Special Relativity with an implementation of a relativity principle. We give an explicit construction of such an implementation and compare it both with the previously mentioned framework of relative locality and the so-called Doubly Special Relativity theories.

Smoothed aggregation multigrid solvers for high-order discontinuous Galerkin methods for elliptic problems

We develop a smoothed aggregation-based algebraic multigrid solver for high-order discontinuous Galerkin discretizations of the Poisson problem. Algebraic multigrid is a popular and effective method for solving the sparse linear systems that arise from discretizing partial differential equations. However, high-order discontinuous Galerkin discretizations have proved challenging for algebraic multigrid. The increasing condition number of the matrix and loss of locality in the matrix stencil as p increases, in addition to the effect of weakly enforced Dirichlet boundary conditions all contribute to the challenging algebraic setting. We propose a smoothed aggregation approach that addresses these difficulties. In particular, the approach effectively coarsens degrees-of-freedom centered at the same spatial location as well as degrees-of-freedom at the domain boundary. Moreover, the character of the near null-space, particularly at the domain boundary, is captured by interpolation. One classic prolongation smoothing step of weighted-Jacobi is also shown to be ineffective at high-order, and a more robust energy-minimization approach is used, along with block relaxation that more directly utilizes the block diagonal structure of the discontinuous Galerkin discretization. Finally, we conclude by examining numerical results in support our proposed method.

Chiral anomalies and rooted staggered fermions

A popular approximation in lattice gauge theory is an extrapolation in the number of fermion species away from the four fold degeneracy natural with the staggered fermion formulation. I show that the procedure mutilates the expected continuum holomorphic behavior in the quark masses. This is due to a chiral symmetry group that is of a higher rank than desired. The conventional resolution proposes canceling the unphysical singularities with a plethora of extra states appearing at finite lattice spacing. This unproven conjecture requires an explicit loss of unitarity and locality. Even if correct, the approach implies large cutoff effects in the low-energy flavor-neutral sector.

Socialization practices of Moroccan families after migration

This article compares the pre-migration and post-migration socialization practices of Moroccan families in The Netherlands. Our main theoretical interest is in continuity and change in the reconstruction of socialization practices in new contexts and how the nature of this reconstruction can be understood. The article addresses social organization in general, the social organization of the family, values and goals related to upbringing and practices of upbringing. The findings indicate a changed power balance in the family, a diminishing distance between parents and children, and a more egalitarian style of parenting. These changes are interpreted against the idea of the ‘loss of locality’ and the reproduction of old practices in new contexts in which cultural differences do not count ‘as such’but become the input for a complex process in which both local and more global developments, both resistance to change and attempts to adapt constantly interact.

Maximizing data locality in distributed systems

The effectiveness of a distributed system hinges on the manner in which tasks and data are assigned to the underlying system resources. Moreover, today's large-scale distributed systems must accommodate heterogeneity in both the offered load and in the makeup of the available storage and compute capacity. The ideal resource assignment must balance the utilization of the underlying system against the loss of locality incurred when individual tasks or data objects are fragmented among several servers. In this paper we describe this locality-maximizing placement problem and show that an optimal solution is NP-hard. We then describe a polynomial-time algorithm that generates a placement within an additive constant of two from optimal.

CacheFlow: Cache Optimizations for Data Driven Multithreading

Data-Driven Multithreading is a non-blocking multithreading model of execution that provides effective latency tolerance by allowing the computation processor do useful work, while a long latency event is in progress. With the Data-Driven Multithreading model, a thread is scheduled for execution only if all of its inputs have been produced and placed in the processor's local memory. Data-driven sequencing leads to irregular memory access patterns that could affect negatively cache performance. Nevertheless, it enables the implementation of short-term optimal cache management policies. This paper presents the implementation of CacheFlow, an optimized cache management policy which eliminates the side effects due to the loss of locality caused by the data-driven sequencing, and reduces further cache misses. CacheFlow employs thread-based prefetching to preload data blocks of threads deemed executable. Simulation results, for nine scientific applications, on a 32-node Data-Driven Multithreaded machine show an average speedup improvement from 19.8 to 22.6. Two techniques to further improve the performance of CacheFlow, conflict avoidance and thread reordering, are proposed and tested. Simulation experiments have shown a speedup improvement of 24% and 32%, respectively. The average speedup for all applications on a 32-node machine with both optimizations is 26.1.

Towards general and exact distributed invalidation

This paper develops and proves an exact distributed invalidation algorithm for programs with general array accesses, arbitrary parallelisation and migratory writes. We present an efficient constructive algorithm that globally combines locally gathered information to insert coherence calls in such a manner to eliminate invalidation traffic without loss of locality and places the minimal number of coherence calls. Experimental results across a range of benchmarks show that it outperforms hardware based sequential and release consistency approaches and decreases application execution time by up to 12%. This is due to eliminating over 99% of the invalidation traffic in all benchmarks. This dramatic reduction in invalidation traffic reduces the total amount of network traffic by up to 28% and the number of network words transmitted by up to 19%.

Wait-free cache-affinity thread scheduling

Cache utilisation is often very poor in multithreaded applications, due to the loss of data access locality incurred by frequent context switching. This problem is compounded on shared memory multiprocessors when dynamic load balancing is introduced, as thread migration disrupts cache content. Batching, a technique for reducing the negative impact of fine grain multithreading on cache performance is introduced to mitigate this problem. Moreover, the related issue of contention for shared data within a thread scheduler for shared memory multiprocessors is considered. In this regard wait-free techniques are applied in lieu of conventional lock-based methods for accessing internal scheduler structures, alleviating to some extent serialisation and hence the degree of contention. Prototype schedulers which make use of the above ideas are described, and finally experimental results which illustrate the observed improvements are presented.

T2

As computational power and storage capacity increase, processing and analyzing large volumes of data play an increasingly important part in many domains of scientific research. Typical examples of large scientific datasets include long running simulations of time-dependent phenomena that periodically generate snapshots of their state (e.g. hydrodynamics and chemical transport simulation for estimating pollution impact on water bodies [4, 6, 20], magnetohydrodynamics simulation of planetary magnetospheres [32], simulation of a flame sweeping through a volume [28], airplane wake simulations [21]), archives of raw and processed remote sensing data (e.g. AVHRR [25], Thematic Mapper [17], MODIS [22]), and archives of medical images (e.g. confocal light microscopy, CT imaging, MRI, sonography). These datasets are usually multi-dimensional. The data dimensions can be spatial coordinates, time, or experimental conditions such as temperature, velocity or magnetic field. The importance of such datasets has been recognized by several database research groups and vendors, and several systems have been developed for managing and/or visualizing them [2, 7, 14, 19, 26, 27, 29, 31]. These systems, however, focus on lineage management, retrieval and visualization of multi-dimensional datasets. They provide little or no support for analyzing or processing these datasets -- the assumption is that this is too application-specific to warrant common support. As a result, applications that process these datasets are usually decoupled from data storage and management, resulting in inefficiency due to copying and loss of locality. Furthermore, every application developer has to implement complex support for managing and scheduling the processing. Over the past three years, we have been working with several scientific research groups to understand the processing requirements for such applications [1, 5, 6, 10, 18, 23, 24, 28]. Our study of a large set of applications indicates that the processing for such datasets is often highly stylized and shares several important characteristics. Usually, both the input dataset as well as the result being computed have underlying multi-dimensional grids, and queries into the dataset are in the form of ranges within each dimension of the grid. The basic processing step usually consists of transforming individual input items, mapping the transformed items to the output grid and computing output items by aggregating, in some way, all the transformed input items mapped to the corresponding grid point. For example, remote-sensing earth images are often generated by performing atmospheric correction on several days worth of raw telemetry data, mapping all the data to a latitude-longitude grid and selecting those measurements that provide the clearest view. In this paper, we present T2, a customizable parallel database that integrates storage, retrieval and processing of multi-dimensional datasets. T2 provides support for many operations including index generation, data retrieval, memory management, scheduling of processing across a parallel machine and user interaction. It achieves its primary advantage from the ability to seamlessly integrate data retrieval and processing for a wide variety of applications and from the ability to maintain and process multiple datasets with different underlying grids. Most other systems for multi-dimensional data have focused on uniformly distributed datasets, such as images, maps, and dense multi-dimensional arrays. Many real datasets, however, are non-uniform or unstructured. For example, satellite data is a two dimensional strip that is embedded in a three dimensional space; water contamination studies use unstructured meshes to selectively simulate regions and so on. T2 can handle both uniform and non-uniform datasets. T2 has been developed as a set of modular services. Since its structure mirrors that of a wide variety of applications, T2 is easy to customize for different types of processing. To build a version of T2 customized for a particular application, a user has to provide functions to pre-process the input data, map input data to elements in the output data, and aggregate multiple input data items that map to the same output element. T2 presents a uniform interface to the end users (the clients of the database system). Users specify the dataset(s) of interest, a region of interest within the dataset(s), and the desired format and resolution of the output. In addition, they select the mapping and aggregation functions to be used. T2 analyzes the user request, builds a suitable plan to retrieve and process the datasets, executes the plan and presents the results in the desired format. In Section 2 we first present several motivating applications and illustrate their common structure. Section 3 then presents an overview of T2, including its distinguishing features and a running example. Section 4 describes each database service in some detail. An example of how to customize several of the database services for a particular application is given in Section 5. T2 is a system in evolution. We conclude in Section 6 with a description of the current status of both the T2 design and the implementation of various applications with T2.