Performance of charge-injection-device infrared detector arrays at low and moderate backgrounds

Three 2 x 64 element charge injection device infrared detector arrays were tested at low and moderate background to evaluate their usefulness for space based astronomical observations. Testing was conducted both in the laboratory and in ground based telescope observations. The devices showed an average readout noise level below 200 equivalent electrons, a peak responsivity of 4 A/W, and a noise equivalent power of 3x10 sq root of W/Hz. Array well capacity was measured to be significantly smaller than predicted. The measured sensitivity, which compares well with that of nonintegrating discrete extrinsic silicon photoconductors, shows these arrays to be useful for certain astronomical observations. However, the measured readout efficiency and frequency response represent serious limitations in low background applications

Detector arrays for low-background space infrared astronomy

The status of development and characterization tests of integrated infrared detector array technology for astronomy applications is described. The devices under development include intrinsic, extrinsic silicon, and extrinsic germanium detectors, with hybrid silicon multiplexers. Laboratory test results and successful astronomy imagery have established the usefulness of integrated arrays in low-background astronomy applications

On the suitability of suffix arrays for lempel-ziv data compression

Lossless compression algorithms of the Lempel-Ziv (LZ) family are widely used nowadays. Regarding time and memory requirements, LZ encoding is much more demanding than decoding. In order to speed up the encoding process, efficient data structures, like suffix trees, have been used. In this paper, we explore the use of suffix arrays to hold the dictionary of the LZ encoder, and propose an algorithm to search over it. We show that the resulting encoder attains roughly the same compression ratios as those based on suffix trees. However, the amount of memory required by the suffix array is fixed, and much lower than the variable amount of memory used by encoders based on suffix trees (which depends on the text to encode). We conclude that suffix arrays, when compared to suffix trees in terms of the trade-off among time, memory, and compression ratio, may be preferable in scenarios (e.g., embedded systems) where memory is at a premium and high speed is not critical

Efficient LZ78 factorization of grammar compressed text

We present an efficient algorithm for computing the LZ78 factorization of a text, where the text is represented as a straight line program (SLP), which is a context free grammar in the Chomsky normal form that generates a single string. Given an SLP of size $n$ representing a text $S$ of length $N$, our algorithm computes the LZ78 factorization of $T$ in $O(n\sqrt{N}+m\log N)$ time and $O(n\sqrt{N}+m)$ space, where $m$ is the number of resulting LZ78 factors. We also show how to improve the algorithm so that the $n\sqrt{N}$ term in the time and space complexities becomes either $nL$, where $L$ is the length of the longest LZ78 factor, or $(N - \alpha)$ where $\alpha \geq 0$ is a quantity which depends on the amount of redundancy that the SLP captures with respect to substrings of $S$ of a certain length. Since $m = O(N/\log_\sigma N)$ where $\sigma$ is the alphabet size, the latter is asymptotically at least as fast as a linear time algorithm which runs on the uncompressed string when $\sigma$ is constant, and can be more efficient when the text is compressible, i.e. when $m$ and $n$ are small.Comment: SPIRE 201

Dictionary Matching with One Gap

The dictionary matching with gaps problem is to preprocess a dictionary $D$ of $d$ gapped patterns $P_1,\ldots,P_d$ over alphabet $\Sigma$, where each gapped pattern $P_i$ is a sequence of subpatterns separated by bounded sequences of don't cares. Then, given a query text $T$ of length $n$ over alphabet $\Sigma$, the goal is to output all locations in $T$ in which a pattern $P_i\in D$, $1\leq i\leq d$, ends. There is a renewed current interest in the gapped matching problem stemming from cyber security. In this paper we solve the problem where all patterns in the dictionary have one gap with at least $\alpha$ and at most $\beta$ don't cares, where $\alpha$ and $\beta$ are given parameters. Specifically, we show that the dictionary matching with a single gap problem can be solved in either $O(d\log d + |D|)$ time and $O(d\log^{\varepsilon} d + |D|)$ space, and query time $O(n(\beta -\alpha )\log\log d \log ^2 \min \{ d, \log |D| \} + occ)$, where $occ$ is the number of patterns found, or preprocessing time and space: $O(d^2 + |D|)$, and query time $O(n(\beta -\alpha ) + occ)$, where $occ$ is the number of patterns found. As far as we know, this is the best solution for this setting of the problem, where many overlaps may exist in the dictionary.Comment: A preliminary version was published at CPM 201

Suffix Tree of Alignment: An Efficient Index for Similar Data

We consider an index data structure for similar strings. The generalized suffix tree can be a solution for this. The generalized suffix tree of two strings $A$ and $B$ is a compacted trie representing all suffixes in $A$ and $B$. It has $|A|+|B|$ leaves and can be constructed in $O(|A|+|B|)$ time. However, if the two strings are similar, the generalized suffix tree is not efficient because it does not exploit the similarity which is usually represented as an alignment of $A$ and $B$. In this paper we propose a space/time-efficient suffix tree of alignment which wisely exploits the similarity in an alignment. Our suffix tree for an alignment of $A$ and $B$ has $|A| + l_d + l_1$ leaves where $l_d$ is the sum of the lengths of all parts of $B$ different from $A$ and $l_1$ is the sum of the lengths of some common parts of $A$ and $B$. We did not compromise the pattern search to reduce the space. Our suffix tree can be searched for a pattern $P$ in $O(|P|+occ)$ time where $occ$ is the number of occurrences of $P$ in $A$ and $B$. We also present an efficient algorithm to construct the suffix tree of alignment. When the suffix tree is constructed from scratch, the algorithm requires $O(|A| + l_d + l_1 + l_2)$ time where $l_2$ is the sum of the lengths of other common substrings of $A$ and $B$. When the suffix tree of $A$ is already given, it requires $O(l_d + l_1 + l_2)$ time.Comment: 12 page

The Infrared Array Camera (IRAC) for the Spitzer Space Telescope

The Infrared Array Camera (IRAC) is one of three focal plane instruments in the Spitzer Space Telescope. IRAC is a four-channel camera that obtains simultaneous broad-band images at 3.6, 4.5, 5.8, and 8.0 microns. Two nearly adjacent 5.2x5.2 arcmin fields of view in the focal plane are viewed by the four channels in pairs (3.6 and 5.8 microns; 4.5 and 8 microns). All four detector arrays in the camera are 256x256 pixels in size, with the two shorter wavelength channels using InSb and the two longer wavelength channels using Si:As IBC detectors. IRAC is a powerful survey instrument because of its high sensitivity, large field of view, and four-color imaging. This paper summarizes the in-flight scientific, technical, and operational performance of IRAC.Comment: 7 pages, 3 figures. Accepted for publication in the ApJS. A higher resolution version is at http://cfa-www.harvard.edu/irac/publication

Space Systems: Emerging Technologies and Operations

SPACE SYSTEMS: EMERGING TECHNOLOGIES AND OPERATIONS is our seventh textbook in a series covering the world of UASs / CUAS/ UUVs. Other textbooks in our series are Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA\u27s Advanced Air Assets, 1st edition. Our previous six titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols et al., 2021) (Nichols R. K. et al., 2020) (Nichols R. et al., 2020) (Nichols R. et al., 2019) (Nichols R. K., 2018) Our seventh title takes on a new purview of Space. Let\u27s think of Space as divided into four regions. These are Planets, solar systems, the great dark void (which fall into the purview of astronomers and astrophysics), and the Dreamer Region. The earth, from a measurement standpoint, is the baseline of Space. It is the purview of geographers, engineers, scientists, politicians, and romantics. Flying high above the earth are Satellites. Military and commercial organizations govern their purview. The lowest altitude at which air resistance is low enough to permit a single complete, unpowered orbit is approximately 80 miles (125 km) above the earth\u27s surface. Normal Low Earth Orbit (LEO) satellite launches range between 99 miles (160 km) to 155 miles (250 km). Satellites in higher orbits experience less drag and can remain in Space longer in service. Geosynchronous orbit is around 22,000 miles (35,000 km). However, orbits can be even higher. UASs (Drones) have a maximum altitude of about 33,000 ft (10 km) because rotating rotors become physically limiting. (Nichols R. et al., 2019) Recreational drones fly at or below 400 ft in controlled airspace (Class B, C, D, E) and are permitted with prior authorization by using a LAANC or DroneZone. Recreational drones are permitted to fly at or below 400 ft in Class G (uncontrolled) airspace. (FAA, 2022) However, between 400 ft and 33,000 ft is in the purview of DREAMERS. In the DREAMERS region, Space has its most interesting technological emergence. We see emerging technologies and operations that may have profound effects on humanity. This is the mission our book addresses. We look at the Dreamer Region from three perspectives:1) a Military view where intelligence, jamming, spoofing, advanced materials, and hypersonics are in play; 2) the Operational Dreamer Region; whichincludes Space-based platform vulnerabilities, trash, disaster recovery management, A.I., manufacturing, and extended reality; and 3) the Humanitarian Use of Space technologies; which includes precision agriculture wildlife tracking, fire risk zone identification, and improving the global food supply and cattle management. Here’s our book’s breakdown: SECTION 1 C4ISR and Emerging Space Technologies. C4ISR stands for Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance. Four chapters address the military: Current State of Space Operations; Satellite Killers and Hypersonic Drones; Space Electronic Warfare, Jamming, Spoofing, and ECD; and the challenges of Manufacturing in Space. SECTION 2: Space Challenges and Operations covers in five chapters a wide purview of challenges that result from operations in Space, such as Exploration of Key Infrastructure Vulnerabilities from Space-Based Platforms; Trash Collection and Tracking in Space; Leveraging Space for Disaster Risk Reduction and Management; Bio-threats to Agriculture and Solutions From Space; and rounding out the lineup is a chapter on Modelling, Simulation, and Extended Reality. SECTION 3: Humanitarian Use of Space Technologies is our DREAMERS section. It introduces effective use of Drones and Precision Agriculture; and Civilian Use of Space for Environmental, Wildlife Tracking, and Fire Risk Zone Identification. SECTION 3 is our Hope for Humanity and Positive Global Change. Just think if the technologies we discuss, when put into responsible hands, could increase food production by 1-2%. How many more millions of families could have food on their tables? State-of-the-Art research by a team of fifteen SMEs is incorporated into our book. We trust you will enjoy reading it as much as we have in its writing. There is hope for the future.https://newprairiepress.org/ebooks/1047/thumbnail.jp