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Networks of Quantum Sensors
Published in Jonathan P. Dowling, Schrödinger’s Web, 2020
When imaging distant astronomical objects with a telescope, there are two important metrics of goodness for the telescope – the amount of light it gathers and the resolution of the distant image. You want the image to be bright and all the small features in it easy to see. You can improve both of these features of the telescope by making the diameter of the receiving dish bigger. It is obvious that a bigger telescope gathers more light, but it is less obvious that it also improves the image quality. This latter property is called the angular resolution of the telescope.9 The rule that – the bigger the telescope, the better – also applies to cameras. You don’t see the professional wedding photographer taking photos with his mobile phone – instead, he lugs around a huge camera with a big lens on the front. That big lens pulls in more light and improves the resolution of the photo. Each telescope in the Very Large Array is about the size of a house. To improve your image quality, you could try to make a single telescope the size of a football field. However, the current radio telescopes, which make up the array, are almost at the point where they would collapse under their weight. The largest, single, radio telescope in the world is the great Arecibo Radio Observatory, which has a total area of about 20 football fields. The builders solved the weight problem by nestling the giant telescope into a huge sinkhole crater in Puerto Rico.10 That thing is a wonder of engineering and the end of the line for making telescopes bigger and bigger. Fortunately, there is an end-run around this rule. Instead of making a single large telescope – you phase-lock together a whole bunch of smaller telescopes into one single virtual telescope whose effective diameter is equal to the diameter of the array. The Socorro array has a layout shown in Figure 7.5.
Distributed Sensor Arrays
Published in Prabhakar S. Naidu, Distributed Sensor Arrays Localization, 2017
In many applications, it is not possible to achieve an ordered distribution of sensors, particularly when we have a very large number of sensors over a large area. But the location of sensors is precisely known. A recent example of such a large array is the largest radio telescope in the world, consisting of 25,000 small antennas distributed over Western Europe (aperture ≈ 1000 km). Sometimes, the constraints of space, for example in biomedical applications, demand sensors to be distributed over available space. In a distributed array of the previously mentioned type, all sensors are wired (or alternatively connected wirelessly) to a central processing unit where most of the signal processing tasks are carried out. Sensors, however, perform signal conditioning, A/D conversion, and so on. Each sensor is also able to communicate with the central processor. The location of all sensors is known, but the location of the transmitter and the emitted signal waveform are unknown. Wired sensor arrays of this type are usually small, with a limited number of sensors strategically placed surrounding a target of interest. Sometimes it becomes necessary to keep the target away from the sensor array for safety or security reasons. Location estimation is based on ToA information at each sensor. ToA estimation requires the transmitter to send out a known waveform at a fixed time instant. The time of arrival at each sensor is measured relative to the instant of transmission. The clocks of all sensors and the clock at transmitter must be synchronized to get correct ToA estimates. In addition, the transmitter must be a friendly one so that it may be programmed to transmit a waveform at a preprogrammed time instant. When this is not possible (e.g., with an enemy transmitter), we can use TDoA at all pairs of sensors whose clocks are synchronized. One advantage of using of ToA or TDoA for localization is that it is not necessary to maintain λ/2 spacing between sensors as in a regular array. Nor is it necessary to calibrate sensors.
T
Published in Splinter Robert, Illustrated Encyclopedia of Applied and Engineering Physics, 2017
[astrophysics/astronomy, general, nuclear, optics] Device used to increase the resolution with respect to a distant phenomenon or object. Telescopes use a broad range of the electromagnetic spectrum, from ultraviolet to the microwave. Telescopes operating in the visible spectrum provide a means to visually enlarge an object at a great distance. Telescopes operating in other parts of the electromagnetic spectrum require signal and image-processing techniques to reveal specific characteristics of the phenomenon under observation, such as a star or galaxy. Radio telescopes are used in astronomy in order to observe in the radio-frequency and microwave bands by means of an array of dish antennas. Radio telescopes often need to rely on interference properties to provide location-specific information. The first use of an optical telescope was described by the scientists and spectacle makers from Germany/the Netherlands, Hans Lippershey (1570–1619; also known as Johannes Lipperhey) and Zacharias Janssen (1580–1640) in 1608, with contributions from Jacobus Metius (1571–1624; also known as Jacobus Adriaanszoon). Galileo Galilei (1564–1642) built his own telescope in 1609 based on the Dutch inspiration. A brief list of notable researchers in astronomy are Nicolaus Copernicus (1473–1543), Tycho Brahe (1546–1601; Tyge Ottesen Brahe, scientist from Denmark), and Edwin Powell Hubble (1889–1953). Telescopes can rely on reflective imaging or refraction imaging. Optical telescopes use both reflection and refraction, often in combination, where the reflection aspect provides a larger opening angle and provides smaller constraints on the material properties. Long wavelength telescopes primarily rely on reflection-based focusing (also seeHubble telescopeandradio-telescope) (see Figure T.16).
A hybrid solution to parallel calculation of augmented join trees of scalar fields in any dimension
Published in Computer-Aided Design and Applications, 2018
Paul Rosen, Junyi Tu, Les A. Piegl
In radio astronomy, scalar fields are one of the primary data sources used to validate hypotheses. Radio telescopes capture 3D maps of the radio signals in the sky. Two dimensions of these maps are spatial positions in the sky. The third dimension is different radio frequencies. Unfortunately for astronomers, the radio signals collected are very low power and have a high signal to noise ratio. The problem was described best by one radio astronomer, “a cell phone on the moon would be a brightest signal in the sky”.