Engineering Entanglement,Conceptualizing Quantum Information

Proposed by Einstein, Podolsky, and Rosen (EPR) in 1935, the entangled state has played a central part in exploring the foundation of quantum mechanics. At the end of the twentieth century, however, some physicists and mathematicians set aside the epistemological debates associated with EPR and turned it from a philosophical puzzle into practical resources for information processing. This paper examines the origin of what is known as quantum information. Scientists had considered making quantum computers and employing entanglement in communications for a long time. But the real breakthrough only occurred in the 1980s when they shifted focus from general-purpose systems such as Turing machines to algorithms and protocols that solved particular problems, including quantum factorization, quantum search, superdense code, and teleportation. Key to their development was two groups of mathematical manipulations and deformations of entanglement—quantum parallelism and ‘feedback EPR’—that served as conceptual templates. The early success of quantum parallelism and feedback EPR was owed to the idealized formalism of entanglement researchers had prepared for philosophical discussions. Yet, such idealization is difficult to hold when the physical implementation of quantum information processors is at stake. A major challenge for today's quantum information scientists and engineers is thus to move from Einstein et al.'s well-defined scenarios into realistic models.     

Tubes,randomness, and Brownian motions: or,how engineers learned to start worrying about electronic noise

In this paper, we examine the pioneering research on electronic noise—the current fluctuations in electronic circuit devices due to their intrinsic physical characteristics rather than their defects—in Germany and the U.S. during the 1910s–1920s. Such research was not just another demonstration of the general randomness of the physical world Einstein’s work on Brownian motion had revealed. In contrast, we stress the importance of a particular engineering context to electronic noise studies: the motivation to design and improve high-gain thermionic-tube amplifiers for radio and wired communications. Engineering scientists’ endeavors to understand electronic noise started in 1918, when Walter Schottky at Siemens formulated a theory of “shot noise,” current fluctuations owing to the random emissions of discrete electrons in a tube. Schottky’s theory was revised and experimentally tested at Siemens, General Electric, and AT&T during the 1920s, leading to the discoveries of several other types of noise and an increasing interest in the thermal fluctuations in electronic circuits. In 1925–1928, J.B. Johnson and Harry Nyquist at Bell Labs developed a theory of thermal noise for any electrical resistor at a non-zero temperature. Although these studies were initiated to chart the fundamental performance limit of electronic technology, they ended up assisting the empirical determination of individual electronic components’ characteristics.     

Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex

Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 microm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 microm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.