The Geometry of Speed Limiting Resources in Physical Models of Computation

We study the maximum speed of quantum computation and how it is affected by limitations on physical resources. We show how the resulting concepts generalize to a broader class of physical models of computation within dynamical systems and introduce a specific algebraic structure representing these speed limits. We derive a family of quantum speed limit results in resource-constrained quantum systems with pure states and a finite dimensional state space, by using a geometric method based on right invariant action functionals on SU(N). We show that when the action functional is bi-invariant, the minimum time for implementing any quantum gate using a potentially time-dependent Hamiltonian is equal to the minimum time when using a constant Hamiltonian, thus constant Hamiltonians are time optimal for these constraints. We give an explicit formula for the time in these cases, in terms of the resource constraint. We show how our method produces a rich family of speed limit results, of which the generalized Margolus–Levitin theorem and the Mandelstam–Tamm inequality are special cases. We discuss the broader context of geometric approaches to speed limits in physical computation, including the way geometric approaches to quantum speed limits are a model for physical speed limits to computation arising from a limited resource

Evolution and Modern Approaches for Thermal Analysis of Electrical Machines

In this paper, the authors present an extended survey on the evolution and the modern approaches in the thermal analysis of electrical machines. The improvements and the new techniques proposed in the last decade are analyzed in depth and compared in order to highlight the qualities and defects of each. In particular, thermal analysis based on lumped-parameter thermal network, finite-element analysis, and computational fluid dynamics are considered in this paper. In addition, an overview of the problems linked to the thermal parameter determination and computation is proposed and discussed. Taking into account the aims of this paper, a detailed list of books and papers is reported in the references to help researchers interested in these topics

The role of graphics super-workstations in a supercomputing environment

A new class of very powerful workstations has recently become available which integrate near supercomputer computational performance with very powerful and high quality graphics capability. These graphics super-workstations are expected to play an increasingly important role in providing an enhanced environment for supercomputer users. Their potential uses include: off-loading the supercomputer (by serving as stand-alone processors, by post-processing of the output of supercomputer calculations, and by distributed or shared processing), scientific visualization (understanding of results, communication of results), and by real time interaction with the supercomputer (to steer an iterative computation, to abort a bad run, or to explore and develop new algorithms)

Fast Universal Quantum Computation with Railroad-switch Local Hamiltonians

We present two universal models of quantum computation with a time-independent, frustration-free Hamiltonian. The first construction uses 3-local (qubit) projectors, and the second one requires only 2-local qubit-qutrit projectors. We build on Feynman's Hamiltonian computer idea and use a railroad-switch type clock register. The resources required to simulate a quantum circuit with L gates in this model are O(L) small-dimensional quantum systems (qubits or qutrits), a time-independent Hamiltonian composed of O(L) local, constant norm, projector terms, the possibility to prepare computational basis product states, a running time O(L log^2 L), and the possibility to measure a few qubits in the computational basis. Our models also give a simplified proof of the universality of 3-local Adiabatic Quantum Computation.Comment: Added references to work by de Falco et al., and realized that Feynman's '85 paper already contained the idea of a switch in i

Computational fluid dynamics at NASA Ames and the numerical aerodynamic simulation program

Computers are playing an increasingly important role in the field of aerodynamics such as that they now serve as a major complement to wind tunnels in aerospace research and development. Factors pacing advances in computational aerodynamics are identified, including the amount of computational power required to take the next major step in the discipline. The four main areas of computational aerodynamics research at NASA Ames Research Center which are directed toward extending the state of the art are identified and discussed. Example results obtained from approximate forms of the governing equations are presented and discussed, both in the context of levels of computer power required and the degree to which they either further the frontiers of research or apply to programs of practical importance. Finally, the Numerical Aerodynamic Simulation Program--with its 1988 target of achieving a sustained computational rate of 1 billion floating-point operations per second--is discussed in terms of its goals, status, and its projected effect on the future of computational aerodynamics

Fast Escape from Quantum Mazes in Integrated Photonics

Escaping from a complex maze, by exploring different paths with several decision-making branches in order to reach the exit, has always been a very challenging and fascinating task. Wave field and quantum objects may explore a complex structure in parallel by interference effects, but without necessarily leading to more efficient transport. Here, inspired by recent observations in biological energy transport phenomena, we demonstrate how a quantum walker can efficiently reach the output of a maze by partially suppressing the presence of interference. In particular, we show theoretically an unprecedented improvement in transport efficiency for increasing maze size with respect to purely quantum and classical approaches. In addition, we investigate experimentally these hybrid transport phenomena, by mapping the maze problem in an integrated waveguide array, probed by coherent light, hence successfully testing our theoretical results. These achievements may lead towards future bio-inspired photonics technologies for more efficient transport and computation.Comment: 13 pages, 10 figure

Load management strategy for Particle-In-Cell simulations in high energy particle acceleration

In the wake of the intense effort made for the experimental CILEX project, numerical simulation cam- paigns have been carried out in order to finalize the design of the facility and to identify optimal laser and plasma parameters. These simulations bring, of course, important insight into the fundamental physics at play. As a by-product, they also characterize the quality of our theoretical and numerical models. In this paper, we compare the results given by different codes and point out algorithmic lim- itations both in terms of physical accuracy and computational performances. These limitations are illu- strated in the context of electron laser wakefield acceleration (LWFA). The main limitation we identify in state-of-the-art Particle-In-Cell (PIC) codes is computational load imbalance. We propose an innovative algorithm to deal with this specific issue as well as milestones towards a modern, accurate high-per- formance PIC code for high energy particle acceleration

Parallel Algorithm and Dynamic Exponent for Diffusion-limited Aggregation

A parallel algorithm for ``diffusion-limited aggregation'' (DLA) is described and analyzed from the perspective of computational complexity. The dynamic exponent z of the algorithm is defined with respect to the probabilistic parallel random-access machine (PRAM) model of parallel computation according to $T \sim L^{z}$, where L is the cluster size, T is the running time, and the algorithm uses a number of processors polynomial in L\@. It is argued that z=D-D_2/2, where D is the fractal dimension and D_2 is the second generalized dimension. Simulations of DLA are carried out to measure D_2 and to test scaling assumptions employed in the complexity analysis of the parallel algorithm. It is plausible that the parallel algorithm attains the minimum possible value of the dynamic exponent in which case z characterizes the intrinsic history dependence of DLA.Comment: 24 pages Revtex and 2 figures. A major improvement to the algorithm and smaller dynamic exponent in this versio

Invasion and adaptive evolution for individual-based spatially structured populations

The interplay between space and evolution is an important issue in population dynamics, that is in particular crucial in the emergence of polymorphism and spatial patterns. Recently, biological studies suggest that invasion and evolution are closely related. Here we model the interplay between space and evolution starting with an individual-based approach and show the important role of parameter scalings on clustering and invasion. We consider a stochastic discrete model with birth, death, competition, mutation and spatial diffusion, where all the parameters may depend both on the position and on the trait of individuals. The spatial motion is driven by a reflected diffusion in a bounded domain. The interaction is modelled as a trait competition between individuals within a given spatial interaction range. First, we give an algorithmic construction of the process. Next, we obtain large population approximations, as weak solutions of nonlinear reaction-diffusion equations with Neumann's boundary conditions. As the spatial interaction range is fixed, the nonlinearity is nonlocal. Then, we make the interaction range decrease to zero and prove the convergence to spatially localized nonlinear reaction-diffusion equations, with Neumann's boundary conditions. Finally, simulations based on the microscopic individual-based model are given, illustrating the strong effects of the spatial interaction range on the emergence of spatial and phenotypic diversity (clustering and polymorphism) and on the interplay between invasion and evolution. The simulations focus on the qualitative differences between local and nonlocal interactions