I'd like to understand if there is a way to contribute to space missions like these, or space research in general, as a "civilian" software developer. Is there perhaps a community of space enthusiasts working on domain-specific open source tools? What are some unsolved problems in this field?
Great question, and I suggest you take a look at SatNOGS! It's a community driven satellite ground station project, where you can offer your own antenna and make use of the antennas of others. At my work we host 4 groundstations and regularly make use of those offered. A large open-source project like this can always use more contributors.
Hello! I work at a space start up called Loft Orbital, we've open sourced all our core astrodynamics and satellite simulation tooling.
Here's a link to the GitHub repo, https://github.com/open-space-collective.
It's used by a few start ups and I'm hoping to spread the word a bit more once I get some time to clean some things up. Astrodynamics sorely lacks a great open source ecosystem. Poliastro was great but is now unmaintained.
There's Orekit (which is fantastic) but it's in Java which makes it difficult to scale across languages or stacks.
Nyx Space is excellent, and it's focused on deep space applications.
Contributing to any of these tools would be a great way to improve the open source community in astrodynamics!
I was involved in this industry about decade, when relations with Russia was warmed after end of cold war, so could share some experience.
In any case, you must understand, even on warmest times, space technologies considered as semi-weapons, so if you cannot achieve military clearance, you will have access only to some niches.
If niches are not scary for you, excellent, there are plenty opportunities.
First, in many countries exist large niche of high altitude air research, for which constantly need small cheap rockets and balloons, and all of these need reliable organizations, who will do regular starts and than find all things returned from near space.
So, what I mean - great deal of space work is just find and gather all parts fallen from missions.
Sure, all that things mean, better to make reliable control system, and reliable return system, than to literally looking for needle at haystack sized about hundred kilometers. But unfortunately, even best real rockets have failure rate ~0.4..0.7% (amateurs usually considered good to achieve 10..20% fr), so for every 100 starts, could have 1 failure for professional approach, or 10..20 for amateur, and will work on field.
Problems near infinite, because even amateur rockets are not cheap, and in many cases civilian equipment are not working (yes, civilian GPS are just turning off or hanging if achieve military bounds for altitude or speed, so need to make your own navigation) and all additional weight subtract from profit, and any failure also could be fatal for economy, so there constantly appear new brave people and on other side, appear disappointed, who leave to more calm industries.
But as others pointed out, there are a lot of civil space companies needing embedded systems programmers to work on space subsystems and (generally student lead) open source CubeSat tech. You'd likely need an actual job to work on solving novel hardware-specific problems like autonomous navigation, docking, landing, robotics, advanced Space Domain Awareness etc
Seconding GMAT. It's a distant third in the space in terms of adoption (behind FreeFlyer which is itself (anecdotally) far behind STK) but as a GN&C contractor I've used GMAT over FF and STK for a few jobs.
Particularly when it comes to code generation it has, IMO, a big advantage over FF and especially over STK. It's relatively lightweight, at least in my experience it's much faster to spawn and destroy instances than FreeFlyer, and it's pretty simple to write code to leverage GMAT to do interesting things.
Two things I've used GMAT for that would have taken longer in FF or STK are generating thousands of randomized ephemerides with keplerian parameters distributed in a set range, and automating a Monte Carlo-esque analysis focusing on error magnitude permutations by generating GMAT code from templates and collating into a single script file.
Not to mention it's free; STK and FF are very much not.
I'm on a first name basis with a chunk of the GMAT development team, though it's been a minute and I don't know how they're faring given recent political changes - they were out of Goddard which was having issues even before this January.
I don't know how often they accept code from the public, but I know they appreciate bug reports.
Anyways I guess I just wanted to go on about GMAT a little. It's a really cool tool and it's awesome that it's free. I wish it had more industry adoption.
Well, there's plenty of civilian space companies these days! It's largely embedded-oriented (code that controls launch vehicles and satellites) from what I've seen, but the opportunities are there.
I contributed to one company(intuitive machines) by buying their stock a few weeks back, they are public - ticker is LUNR. They have a moon mission going on as this is written and plan to touch down on the moon 3/6/25 and drill for water(look for IM-2 mission). Last year they were the first private company to send a lander to moon and made headlines due to the missions success. So for me its profitable and I get to contribute to interesting science.
There's always some small nonprofit, research, university, ham radio and similar themed 'cubesat' projects that need embedded software engineering. I'd suggest to start familiarizing yourself with common cubesat platforms, then see what the embedded hardware looks like and what you think you could do with it.
Surely you understand that if you have two systems that depend on millions of variables, and you compare 1 single variable, you cant assign the outcomes being different to that one variable?
I mean, maybe you don't understand really basic critical thinking, maybe my bar is too high here?
Step 1 - Pause the ad. Click on the settings icon and select "Statistics for nerds"
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I don't find this very convincing.
The causal effect could also be the other way around: people whose mental health or well-being was better for other reasons (less stressed, wealthier) had more free time or resources to think about and plan healthier dietary choices and the budget to afford better food options.
