Radio Astronomy for Programmers
Rusty R. Hall | Sun 24 Jan 11:40 a.m.–12:25 p.m.
Presented by
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Mars Buttfield-Addison
@TheMartianLife
https://themartianlife.com
Mars Buttfield-Addison (née Geldard) is a Software Engineer and Data Scientist, currently working towards a PhD in Computer Engineering with the University of Tasmania and CSIRO Data61--investigating the use of machine learning to assist large-scale radio telescope installations in reliably tracking objects in orbit. Before that, she completed successive degrees in ICT in which she conducted research across domains as diverse as serious games, information behaviours, public health and complex social media analysis.
But that wasn't enough to channel her passion for technology: Mars is also a frequent volunteer and speaker at industry events worldwide; a teaching and research assistant at UTAS; a freelance developer and author of educational materials (including Practical AI with Swift for O'Reilly Media, and related books still in the works); a conference organiser (/dev/world and EveryWorld), industry council member (AUC and prev. ACS) and community advocate in the field of Swift and Apple platform development, just to name a few.
She spends any remaining time she has helping to build the world of Game of Thrones in Minecraft as part of the WesterosCraft project, supporting whatever antics her game developer husband is up to, tweeting about Star Trek at @TheMartianLife, or in the wilderness.
Mars Buttfield-Addison
@TheMartianLife
https://themartianlife.com
Abstract
Space is cool, right? Of course it is! But ask any programmer you know how much they know about the technical implementations of how humans observe or operate in space? They'll likely be unable to tell you much. Because this is a domain entrenched in hardware and communications technologies we developers don't have to interact with often, if at all; to many, domain-specific hardware in a science like astronomy may as well be magic. But the same can be true for the other side; many of the highly technical personnel working in the space sciences--from astrophysicists to communications engineers--often know software practices only as far as it is required to construct scripts or maintain single libraries to run a pipeline whose parameters or requirements sometimes won't change for decades. Herein lies an interdisciplinary domain ripe for collaboration or specialisation.
This talk is a high-speed crash course in the some of the key data formats, units and terminology used in the domain of radio astronomy--particularly the kind of near-Earth observation that has become so critical to our mitigation of the ever-impending space debris crisis--for those from a software background. But there will be no circuit diagrams here; let's approach the topic with less maths and more drawings and mad gesturing, and to tell the great story of space observation that led us to this point and its impact on practices (particularly software practices) still in use today.
From the technical and socio-political determinants of core components like units of measurement and the conflicting standards for their conversion, to the slightly incorrect application of open source paradigms and the prevalence of sole maintainers. From the original FORTRAN, QBASIC and C libraries that still underlie the majority of this domain, to the costs of opting for one of the modern Python alternatives. And with a special focus on the particularities of Australia's own radio telescopy capabilities and publicly available resources.
In this tale of off-by-one errors and spherical trigonometry there is fun and humour to be found, as well as tools and lessons you can use to start delving into hard space science problems from your own computer: such as tracking satellite passes, interpreting analog-first telescope imagery, measuring the efficacy of different space surveillance systems, and more! All you need is some Python (or your own favourite language)!
Space is cool, right? Of course it is! But ask any programmer you know how much they know about the technical implementations of how humans observe or operate in space? They'll likely be unable to tell you much. Because this is a domain entrenched in hardware and communications technologies we developers don't have to interact with often, if at all; to many, domain-specific hardware in a science like astronomy may as well be magic. But the same can be true for the other side; many of the highly technical personnel working in the space sciences--from astrophysicists to communications engineers--often know software practices only as far as it is required to construct scripts or maintain single libraries to run a pipeline whose parameters or requirements sometimes won't change for decades. Herein lies an interdisciplinary domain ripe for collaboration or specialisation. This talk is a high-speed crash course in the some of the key data formats, units and terminology used in the domain of radio astronomy--particularly the kind of near-Earth observation that has become so critical to our mitigation of the ever-impending space debris crisis--for those from a software background. But there will be no circuit diagrams here; let's approach the topic with less maths and more drawings and mad gesturing, and to tell the great story of space observation that led us to this point and its impact on practices (particularly software practices) still in use today. From the technical and socio-political determinants of core components like units of measurement and the conflicting standards for their conversion, to the slightly incorrect application of open source paradigms and the prevalence of sole maintainers. From the original FORTRAN, QBASIC and C libraries that still underlie the majority of this domain, to the costs of opting for one of the modern Python alternatives. And with a special focus on the particularities of Australia's own radio telescopy capabilities and publicly available resources. In this tale of off-by-one errors and spherical trigonometry there is fun and humour to be found, as well as tools and lessons you can use to start delving into hard space science problems from your own computer: such as tracking satellite passes, interpreting analog-first telescope imagery, measuring the efficacy of different space surveillance systems, and more! All you need is some Python (or your own favourite language)!