12,844 research outputs found
Wiring Nanoscale Biosensors with Piezoelectric Nanomechanical Resonators
Nanoscale integrated circuits and sensors will require methods for unobtrusive interconnection with the macroscopic world to fully realize their potential. We report on a nanoelectromechanical system that may present a solution to the wiring problem by enabling information from multisite sensors to be multiplexed onto a single output line. The basis for this method is a mechanical Fourier transform mediated by piezoelectrically coupled nanoscale resonators. Our technique allows sensitive, linear, and real-time measurement of electrical potentials from conceivably any voltage-sensitive device. With this method, we demonstrate the direct transduction of neuronal action potentials from an extracellular microelectrode. This approach to wiring nanoscale devices could lead to minimally invasive implantable sensors with thousands of channels for in vivo neuronal recording, medical diagnostics, and electrochemical sensing
Tensor Computation: A New Framework for High-Dimensional Problems in EDA
Many critical EDA problems suffer from the curse of dimensionality, i.e. the
very fast-scaling computational burden produced by large number of parameters
and/or unknown variables. This phenomenon may be caused by multiple spatial or
temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit
simulation), nonlinearity of devices and circuits, large number of design or
optimization parameters (e.g. full-chip routing/placement and circuit sizing),
or extensive process variations (e.g. variability/reliability analysis and
design for manufacturability). The computational challenges generated by such
high dimensional problems are generally hard to handle efficiently with
traditional EDA core algorithms that are based on matrix and vector
computation. This paper presents "tensor computation" as an alternative general
framework for the development of efficient EDA algorithms and tools. A tensor
is a high-dimensional generalization of a matrix and a vector, and is a natural
choice for both storing and solving efficiently high-dimensional EDA problems.
This paper gives a basic tutorial on tensors, demonstrates some recent examples
of EDA applications (e.g., nonlinear circuit modeling and high-dimensional
uncertainty quantification), and suggests further open EDA problems where the
use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and
System
Colored noise in oscillators. Phase-amplitude analysis and a method to avoid the Ito-Stratonovich dilemma
We investigate the effect of time-correlated noise on the phase fluctuations
of nonlinear oscillators. The analysis is based on a methodology that
transforms a system subject to colored noise, modeled as an Ornstein-Uhlenbeck
process, into an equivalent system subject to white Gaussian noise. A
description in terms of phase and amplitude deviation is given for the
transformed system. Using stochastic averaging technique, the equations are
reduced to a phase model that can be analyzed to characterize phase noise. We
find that phase noise is a drift-diffusion process, with a noise-induced
frequency shift related to the variance and to the correlation time of colored
noise. The proposed approach improves the accuracy of previous phase reduced
models
Direct and Inverse Computational Methods for Electromagnetic Scattering in Biological Diagnostics
Scattering theory has had a major roll in twentieth century mathematical
physics. Mathematical modeling and algorithms of direct,- and inverse
electromagnetic scattering formulation due to biological tissues are
investigated. The algorithms are used for a model based illustration technique
within the microwave range. A number of methods is given to solve the inverse
electromagnetic scattering problem in which the nonlinear and ill-posed nature
of the problem are acknowledged.Comment: 61 pages, 5 figure
An Efficient Integrated Circuit Simulator And Time Domain Adjoint Sensitivity Analysis
In this paper, we revisit time-domain adjoint sensitivity with a circuit theoretic approach and an efficient solution is clearly stated in terms of device level. Key is the linearization of the energy storage elements (e.g., capacitance and inductance) and nonlinear memoryless elements (e.g., MOS, BJT DC characteristics) at each time step. Due to the finite precision of computation, numerical errors that accumulate across timesteps can arise in nonlinear elements
Floquet theory for temporal correlations and spectra in time-periodic open quantum systems: Application to squeezed parametric oscillation beyond the rotating-wave approximation
Open quantum systems can display periodic dynamics at the classical level
either due to external periodic modulations or to self-pulsing phenomena
typically following a Hopf bifurcation. In both cases, the quantum fluctuations
around classical solutions do not reach a quantum-statistical stationary state,
which prevents adopting the simple and reliable methods used for stationary
quantum systems. Here we put forward a general and efficient method to compute
two-time correlations and corresponding spectral densities of time-periodic
open quantum systems within the usual linearized (Gaussian) approximation for
their dynamics. Using Floquet theory we show how the quantum Langevin equations
for the fluctuations can be efficiently integrated by partitioning the time
domain into one-period duration intervals, and relating the properties of each
period to the first one. Spectral densities, like squeezing spectra, are
computed similarly, now in a two-dimensional temporal domain that is treated as
a chessboard with one-period x one-period cells. This technique avoids
cumulative numerical errors as well as efficiently saves computational time. As
an illustration of the method, we analyze the quantum fluctuations of a damped
parametrically-driven oscillator (degenerate parametric oscillator) below
threshold and far away from rotating-wave approximation conditions, which is a
relevant scenario for modern low-frequency quantum oscillators. Our method
reveals that the squeezing properties of such devices are quite robust against
the amplitude of the modulation or the low quality of the oscillator, although
optimal squeezing can appear for parameters that are far from the ones
predicted within the rotating-wave approximation.Comment: Comments and constructive criticism are welcom
Rapid flipping of parametric phase states
Since the invention of the solid-state transistor, the overwhelming majority
of computers followed the von Neumann architecture that strictly separates
logic operations and memory. Today, there is a revived interest in alternative
computation models accompanied by the necessity to develop corresponding
hardware architectures. The Ising machine, for example, is a variant of the
celebrated Hopfield network based on the Ising model. It can be realized with
artifcial spins such as the `parametron' that arises in driven nonlinear
resonators. The parametron encodes binary information in the phase state of its
oscillation. It enables, in principle, logic operations without energy transfer
and the corresponding speed limitations. In this work, we experimentally
demonstrate flipping of parametron phase states on a timescale of an
oscillation period, much faster than the ringdown time \tau that is often
(erroneously) deemed a fundamental limit for resonator operations. Our work
establishes a new paradigm for resonator-based logic architectures.Comment: 6 pages, 3 figure
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