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 $\ddot\nu$ 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