More clearly see the profundities you seek
We can partner with you to enhance your ability to more clearly observe the profound astrophysical phenomena you study.
Any modality / data type
We have the experience to work with any data source used in modern astronomy. At any scale.
Next-generation deep space multi-spectral
We are well equipped to work with data from the JWST and/or alternative multispectral imaging platforms.
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Land-based telescopy
Peer even deeper into the cosmos than previously possible;
De-noise or error-correct images
Conventional deep learning techniques can be used to correct single images including de-noising, de-artifacting, registering, etc.
Represent and identify anomalies
Once an image similarity model is learned, a set of images can be mapped into a representation space and unusual images can be identified.
Enhance resolution
Multiple-exposure hyper-spectral images can be composited to generate single ultra-resolution hyper-spectral images.
Enhanced radio- and custom-sensing
Enhancement of noisy signals deconvolution, denoising, enhancing,
We can handle deconvolution, denoising, enhancing, and other signal improvement operations of noisy signals and signal mixtures.
Representation learning and applications
Representation learning can provide a foundation whereby anomalies can be detected, e.g. rare and/or novel astrophysical events.
Advanced mathematical toolkit
We have the modern mathematical and statistical tools to help you better observe the nature of the Universe and its astrophysical phenomena
Modelling and design
We can support advanced system design with in silico modelling of optical phenomena such as to estimate improvements in image resolution and noise by changes in imaging system design
Resolution and de-noising
Advanced algorithms for enhancing resolution and reducing noise could permit higher-resolution measurements of the structure of cosmic-scale webs of galaxies and dark matter.
Improved anomaly detection
By detecting anomalies in large observational datasets, we can search for rare events of either scientific interest or engineering concern.
Understanding complex signals
Emerging dimensionality reduction methods can improve our understanding of the structure of high-complexity signal data as well as provide estimates of confidence in inferred signal structure.
Rapid prototyping
Our prototyping tool set permits us to move from problem to prototype solution far more rapidly than when working with alternative technologies.
Schedule a chat >>Accelerated implementations
Our implementation approach is highly amenable to translation into GPU- and FPGA-optimized processing including in distributed forms.
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There are profound truths to be known
Astronomy meaningfully serves the human project by giving us access to sacred truths of the nature of our Universe