California Institute of Technology

About: California Institute of Technology is a education organization based out in Pasadena, California, United States. It is known for research contribution in the topics: Galaxy & Redshift. The organization has 57649 authors who have published 146691 publications receiving 8620287 citations. The organization is also known as: Caltech & Cal Tech.

A microfabricated fluorescence-activated cell sorter

Abstract: We have demonstrated a disposable microfabricated fluorescence-activated cell sorter (µFACS) for sorting various biological entities Compared with conventional FACS machines, the µFACS provides higher sensitivity, no cross-contamination, and lower cost We have used µFACS chips to obtain substantial enrichment of micron-sized fluorescent bead populations of differing colors Furthermore, we have separated Escherichia coli cells expressing green fluorescent protein from a background of nonfluorescent E coli cells and shown that the bacteria are viable after extraction from the sorting device These sorters can function as stand-alone devices or as components of an integrated microanalytical chip

Pattern recognition computation using action potential timing for stimulus representation

Abstract: A computational model is described in which the sizes of variables are represented by the explicit times at which action potentials occur, rather than by the more usual 'firing rate' of neurons. The comparison of patterns over sets of analogue variables is done by a network using different delays for different information paths. This mode of computation explains how one scheme of neuroarchitecture can be used for very different sensory modalities and seemingly different computations. The oscillations and anatomy of the mammalian olfactory systems have a simple interpretation in terms of this representation, and relate to processing in the auditory system. Single-electrode recording would not detect such neural computing. Recognition 'units' in this style respond more like radial basis function units than elementary sigmoid units.

Encoding a qubit in an oscillator

Abstract: Quantum error-correcting codes are constructed that embed a finite-dimensional code space in the infinite-dimensional Hilbert space of a system described by continuous quantum variables. These codes exploit the noncommutative geometry of phase space to protect against errors that shift the values of the canonical variables q and p. In the setting of quantum optics, fault-tolerant universal quantum computation can be executed on the protected code subspace using linear optical operations, squeezing, homodyne detection, and photon counting; however, nonlinear mode coupling is required for the preparation of the encoded states. Finite-dimensional versions of these codes can be constructed that protect encoded quantum information against shifts in the amplitude or phase of a d-state system. Continuous-variable codes can be invoked to establish lower bounds on the quantum capacity of Gaussian quantum channels.

Neuroeconomics: How Neuroscience Can Inform Economics

Abstract: We review recent developments in neuroeconomics and their implications for economics. The paper consists of six sections. Following the Introduction, the second section enumerates the different research methods that neuroscientists use evaluates their strengths and limitations for analyzing economic phenomena. The third section provides a review of basic findings in neuroscience that we deemed especially relevant to economics, and proposes a two-dimensional dichotomization of neural processes between automatic and controlled processes on the one hand, and cognitive and affective processes on the other. Section four reviews general implications of neuroscience for economics. Research in neuroscience, for example, raises questions about the usefulness of many economic constructs, such as 'time preference' and 'risk preference'. It also suggests that, contrary to the assumption that humans are likely to possess domain-specific intelligence - to be brilliant when it comes to problems that the brain is well evolved for performing and flat-footed for problems that lie outside of the brains existing specialized functions. Section 5 provides more detailed discussions of four specific applications: intertemporal choice, decision making under risk and uncertainty, game theory, and labor-market discrimination. Section 6 concludes by proposing a distinction between two general approaches in applying neuroscience to economics which we term 'incremental' and 'radical'. The former draws on neuroscience findings to refine existing economic models, while the latter poses more basic challenges to the standard economic understanding of human behavior.