Related papers: Second Order Operators in the NASA Astrophysics Da…
Stators, which may be intuitively defined as "half states, half operators" are mathematical objects which act on two Hilbert spaces and utilize entanglement to create remote operations and exchange information between two physical systems.…
With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…
The NASA Astrophysics Data System (ADS), a critical research service for the astrophysics community, strives to provide the most accessible and inclusive environment for the discovery and exploration of the astronomical literature. Part of…
Scientific discovery and engineering design are currently limited by the time and cost of physical experiments, selected mostly through trial-and-error and intuition that require deep domain expertise. Numerical simulations present an…
Fourier neural operators (FNOs) are a recently introduced neural network architecture for learning solution operators of partial differential equations (PDEs), which have been shown to perform significantly better than comparable deep…
In many massively parallel data management platforms, programs are represented as small imperative pieces of code connected in a data flow. This popular abstraction makes it hard to apply algebraic reordering techniques employed by…
One of the major challenges in Dynamic Spectrum Access (DSA) systems is to guarantee a required level of Quality of Service (QoS) to secondary users of the spectrum. In this paper, we propose efficient algorithms for deriving optimal…
The Sloan Digital Sky Survey science database is approaching 2TB. While the vast majority of queries normally execute in seconds or minutes, this interactive execution time can be disproportionately increased by a small fraction of queries…
Stochastic partial differential equations (SPDEs) are significant tools for modeling dynamics in many areas including atmospheric sciences and physics. Neural Operators, generations of neural networks with capability of learning maps…
We are used to thinking of an operator acting once, twice, and so on. However, an operator acting integer times can be consistently analytic continued to an operator acting complex times. Applications: (s,r) diagrams and an extension of…
A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high-dimensional input space of the training samples into a low-dimensional space with the topology relations preserved. This makes SOMs…
Accurate measurements of statistical properties, such as the star formation rate and the lifetime of young stellar objects (YSOs) in different stages, is essential for constraining star formation theories. However, it is a difficult task to…
Software-intensive Systems-of-Systems (SoS) refer to an arrangement of managerially and operationally independent systems(i.e., constituent systems), which work collaboratively towards the achievement of global missions. Because some SoS…
The emergence of Agile Earth Observation Satellites (AEOSs) has marked a significant turning point in the field of Earth Observation (EO), offering enhanced flexibility in data acquisition. Concurrently, advancements in onboard satellite…
Foreign Object Debris (FOD) detection has attracted increased attention in the area of machine learning and computer vision. However, a robust and publicly available image dataset for FOD has not been initialized. To this end, this paper…
Structure information is ubiquitous in natural scene images and it plays an important role in scene representation. In this paper, third order structure statistics (TOSS) and fourth order structure statistics (FOSS) are exploited to encode…
On-orbit performance of the Solar Optical Telescope (SOT) aboard Hinode is described with some attentions on its unpredicted aspects. In general, SOT revealed an excellent performance and has been providing outstanding data. Some unexpected…
We define two classes of functions, called regular (respectively, first-order) list functions, which manipulate objects such as lists, lists of lists, pairs of lists, lists of pairs of lists, etc. The definition is in the style of regular…
We explore how astronomers take observational data from telescopes, process them into usable scientific data products, curate them for later use, and reuse data for further inquiry. Astronomers have invested heavily in knowledge…
Due to the increasing complexity and heterogeneity of contemporary Command, Control, Communications, Computers, & Intelligence systems at all levels within military organizations, the adoption of the Service Oriented Architectures (SOA)…