2,116 research outputs found
Learning from Data with Heterogeneous Noise using SGD
We consider learning from data of variable quality that may be obtained from
different heterogeneous sources. Addressing learning from heterogeneous data in
its full generality is a challenging problem. In this paper, we adopt instead a
model in which data is observed through heterogeneous noise, where the noise
level reflects the quality of the data source. We study how to use stochastic
gradient algorithms to learn in this model. Our study is motivated by two
concrete examples where this problem arises naturally: learning with local
differential privacy based on data from multiple sources with different privacy
requirements, and learning from data with labels of variable quality.
The main contribution of this paper is to identify how heterogeneous noise
impacts performance. We show that given two datasets with heterogeneous noise,
the order in which to use them in standard SGD depends on the learning rate. We
propose a method for changing the learning rate as a function of the
heterogeneity, and prove new regret bounds for our method in two cases of
interest. Experiments on real data show that our method performs better than
using a single learning rate and using only the less noisy of the two datasets
when the noise level is low to moderate
Living Liquid Crystals
Collective motion of self-propelled organisms or synthetic particles often
termed active fluid has attracted enormous attention in broad scientific
community because of it fundamentally non-equilibrium nature. Energy input and
interactions among the moving units and the medium lead to complex dynamics.
Here we introduce a new class of active matter, living liquid crystals (LLCs)
that combine living swimming bacteria with a lyotropic liquid crystal. The
physical properties of LLCs can be controlled by the amount of oxygen available
to bacteria, by concentration of ingredients, or by temperature. Our studies
reveal a wealth of new intriguing dynamic phenomena, caused by the coupling
between the activity-triggered flow and long-range orientational order of the
medium. Among these are (a) non-linear trajectories of bacterial motion guided
by non-uniform director, (b) local melting of the liquid crystal caused by the
bacteria-produced shear flows, (c) activity-triggered transition from a
non-flowing uniform state into a flowing one-dimensional periodic pattern and
its evolution into a turbulent array of topological defects, (d)
birefringence-enabled visualization of microflow generated by the
nanometers-thick bacterial flagella. Unlike their isotropic counterpart, the
LLCs show collective dynamic effects at very low volume fraction of bacteria,
on the order of 0.2%. Our work suggests an unorthodox design concept to control
and manipulate the dynamic behavior of soft active matter and opens the door
for potential biosensing and biomedical applications.Comment: 32 pages, 8 figures, Supporting Information include
GASPRNG: GPU accelerated scalable parallel random number generator library
AbstractGraphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution on NVIDIA graphics processing units (GPUs) along with a programming interface to support various usage models for pseudorandom numbers and computational science applications executing on the CPU, GPU, or both. This paper describes the implementation approach used to produce high performance and also describes how to use the programming interface. The programming interface allows a user to be able to use GASPRNG the same way as SPRNG on traditional serial or parallel computers as well as to develop tightly coupled programs executing primarily on the GPU. We also describe how to install GASPRNG and use it. To help illustrate linking with GASPRNG, various demonstration codes are included for the different usage models. GASPRNG on a single GPU shows up to 280x speedup over SPRNG on a single CPU core and is able to scale for larger systems in the same manner as SPRNG. Because GASPRNG generates identical streams of pseudorandom numbers as SPRNG, users can be confident about the quality of GASPRNG for scalable computational science applications.Program summaryProgram title: GASPRNGCatalogue identifier: AEOI_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOI_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: UTK license.No. of lines in distributed program, including test data, etc.: 167900No. of bytes in distributed program, including test data, etc.: 1422058Distribution format: tar.gzProgramming language: C and CUDA.Computer: Any PC or workstation with NVIDIA GPU (Tested on Fermi GTX480, Tesla C1060, Tesla M2070).Operating system: Linux with CUDA version 4.0 or later. Should also run on MacOS, Windows, or UNIX.Has the code been vectorized or parallelized?: Yes. Parallelized using MPI directives.RAM: 512 MB∼ 732 MB (main memory on host CPU, depending on the data type of random numbers.) / 512 MB (GPU global memory)Classification: 4.13, 6.5.Nature of problem:Many computational science applications are able to consume large numbers of random numbers. For example, Monte Carlo simulations are able to consume limitless random numbers for the computation as long as resources for the computing are supported. Moreover, parallel computational science applications require independent streams of random numbers to attain statistically significant results. The SPRNG library provides this capability, but at a significant computational cost. The GASPRNG library presented here accelerates the generators of independent streams of random numbers using graphical processing units (GPUs).Solution method:Multiple copies of random number generators in GPUs allow a computational science application to consume large numbers of random numbers from independent, parallel streams. GASPRNG is a random number generators library to allow a computational science application to employ multiple copies of random number generators to boost performance. Users can interface GASPRNG with software code executing on microprocessors and/or GPUs.Running time:The tests provided take a few minutes to run
Modeling pulsar time noise with long term power law decay modulated by short term oscillations of the magnetic fields of neutron stars
We model the evolution of the magnetic fields of neutron stars as consisting
of a long term power-law decay modulated by short term small amplitude
oscillations. Our model predictions on the timing noise of neutron
stars agree well with the observed statistical properties and correlations of
normal radio pulsars. Fitting the model predictions to the observed data, we
found that their initial parameter implies their initial surface magnetic
dipole magnetic field strength ~ 5E14 G at ~0.4 year old and that the
oscillations have amplitude between E-8 to E-5 and period on the order of
years. For individual pulsars our model can effectively reduce their timing
residuals, thus offering the potential of more sensitive detections of
gravitational waves with pulsar timing arrays. Finally our model can also
re-produce their observed correlation and oscillations of the second derivative
of spin frequency, as well as the "slow glitch" phenomenon.Comment: 10 pages, 6 figures, submitted to IJMPD, invited talk in the 3rd
Galileo-XuGuangqi Meeting}, Beijing, China, 12-16 October 201
Landau-Zener-St\"uckelberg Spectroscopy of a Superconducting Flux Qubit
We proposed a new method to measure the energy spectrum of a superconducting
flux qubit. Different from the conventional frequency spectroscopy, a short
triangle pulse is used to drive the qubit through the anticrossing and
generates Landau-Zener-St\"uckelberg interference patterns, from which the
information of the energy spectrum can be extracted. Without installing
microwave lines one can simplify the experimental setup and reduce the unwanted
effects of noise. Moreover, the method can be applied to other quantum systems,
opening the possibility of calibrating and manipulating qubits with linear
pulses.Comment: 7 pages, 5 figure
Dilaton Black Holes in de Sitter or Anti-de Sitter Universe
Poletti and Wiltshire have shown that, with the exception of a pure
cosmological constant, the solution of a dilaton black hole in the background
of de Sitter or anti-de Sitter universe, does not exist in the presence of one
Liouville-type dilaton potential. Here with the combination of three
Liouville-type dilaton potentials, we obtain the dilaton black hole solutions
in the background of de Sitter or anti-de Sitter universe.Comment: 13 pages,to appear in Phys. Rev.
Cooperating or Fighting with Decoherence in the Optimal Control of Quantum Dynamics
This paper explores the use of laboratory closed-loop learning control to
either fight or cooperate with decoherence in the optimal manipulation of
quantum dynamics. Simulations of the processes are performed in a Lindblad
formulation on multilevel quantum systems strongly interacting with the
environment without spontaneous emission. When seeking a high control yield it
is possible to find fields that successfully fight with decoherence while
attaining a good quality yield. When seeking modest control yields, fields can
be found which are optimally shaped to cooperate with decoherence and thereby
drive the dynamics more efficiently. In the latter regime when the control
field and the decoherence strength are both weak, a theoretical foundation is
established to describe how they cooperate with each other. In general, the
results indicate that the population transfer objectives can be effectively met
by appropriately either fighting or cooperating with decoherence
Observation-assisted optimal control of quantum dynamics
This paper explores the utility of instantaneous and continuous observations
in the optimal control of quantum dynamics. Simulations of the processes are
performed on several multilevel quantum systems with the goal of population
transfer. Optimal control fields are shown to be capable of cooperating or
fighting with observations to achieve a good yield, and the nature of the
observations may be optimized to more effectively control the quantum dynamics.
Quantum observations also can break dynamical symmetries to increase the
controllability of a quantum system. The quantum Zeno and anti-Zeno effects
induced by observations are the key operating principles in these processes.
The results indicate that quantum observations can be effective tools in the
control of quantum dynamics
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