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Is the telescope design available anywhere for hobbyists to build? I can't seem to find anything in the article or in a separate search. I'd be interested in perhaps putting one of these together to do radio astronomy with my kids.


edit: It looks like NASA is back selling Radio JOVE kits again. So this might be your only turnkey choice. It uses 2x large wire dipoles for 20.1 MHz for receiving Jupiter/Io radio bursts which you just view in a spectrogram on a computers (includes SDR receiver): https://radiojove.gsfc.nasa.gov/kits/

I think the SETI "Horn of Plenty" design is a pretty good way to get started with kids. The antenna itself uses metalized foam board with copper (or even aluminum tape) to make a pyramidal horn. Making the waveguide out of folded aluminum siding is a bit more kid dangerous (tin snips cutting sheet metal). And the actual antenna is a monopole feed placed in the waveguide. You'll still probably need an cheap ebay low noise amplifier, less cheap hydrogen line bandpass filter, a SDR receiver with a couple MHz instantaneous bandwidth and a computer. Cheap RTL-SDR usb receivers aren't great at 1420 MHz but they do work if you have a good filter. You'll have to decide on the receiver based on the processing toolchain you chose and it's requirements. Examples using GNU Radio https://github.com/ccera-astro or https://wvurail.org/dspira-lessons/

The "science" output of this isn't very exciting to kids as it's just a spectrum plot for a point in the sky at the time showing how fast towards or away from us some of the hydrogen is going. But if you do it over many full sidereal days at different elevations and record the elevation w/time then you can make a nice looking "image" of the sky showing something useful.

If your kids are older and ambitious take a look at the STARE2 project for detecting fast radio bursts which does actual honest to goodness publishable (https://www.nature.com/articles/s41586-020-2872-x) radio astronomy with a meter scale horn+receiver setup. https://www.caltech.edu/about/news/magnificent-burst-within-... https://arxiv.org/abs/2001.05077 The secret sauce of STARE2 is math heavy calibration though.


I couldn't find the link that they mentioned too. Maybe they forgot to actually put it?

Search on “diy radio telescope”, that gave me lots of projects and videos

> “This isn’t just a new value of the Hubble constant,” the collaboration notes, “it’s a community-built framework that brings decades of independent distance measurements together, transparently and accessibly.”

Don't love that I can't read sentences like this without wondering if an LLM was involved.


Yeah it's sort of an LLM smell but honestly the models learned that pattern because it's common in the training data. People write that way because it sounds like they're revealing something profound.


LLM inference does not just regurgitate the training corpus; RLHF is almost certainly to blame for this. There’s probably some Google n-gram graph to prove it.


Nobody seriously doubts the "tension" anymore. The analysis is good.

The question is are there systemic errors. Chief among them is whether our ability to infer the distance to objects billions of light years away is truly as good as we think it is.


According to the article “This work effectively rules out explanations of the Hubble tension that rely on a single overlooked error in local distance measurements". So any systemic errors would need to affect multiple measurement types.


Definitely a good first step if their research holds up. Given the huge implications thou, it is unlikely to sway opinions much.

Extraordinary claims require extraordinary evidence


We don't just use one single method to infer distances. TA is about that there are multiple methods, and that the framework is open for new ones. What is more likely at fault is the underlying model of how the cosmos developed, which is highly likely to be incomplete or misguided.


Actually is quite the opposite. If the difference in expansion between the early and late universe is real than the reigning cosmological model lambda-CDM will at least have to be revised, or be replaced with a model that made that prediction (there are several of them)


I was referring to that model :-)


That stuck out at me too, along with the em-dashes above.


I have been doing a one-line-a-day journal for the past two years. If I ever feel like writing more I have a separate section for that, but I only ever tell myself to write the one line. It's the first time I have been able to consistently write in a journal for a very long time before I started. My entries are not nearly as "composed" as the examples here, though, just tiny highlights of what happened during the day.


I once made one photo out of my window every day for a year. "Project 266 days", I called it. That year (2016) had a few very foggy days, so all I was able to shot on those days was white. :D

I guess writing a short journal everyday is a bit similar like this. Just forcing yourself into a routine of some sort. Just to get one thing surely checked off per day.


> every day for a year. "Project 266 days", I called it

Okay, I have to ask an obvious question.


Typo. Not using AI yet to write my comments, so things can go wrong like this. :D


Is the point of journalling for you to have memories to look back on or to help you process what happened during the day or another reason? (I've never tried it so I'm trying to understand the purpose.)


Probably the biggest purpose for me is to have something to look back on. The last time I consistently journaled before this was during the time when I dated, got engaged to, and married my wife. Granted, that was more than a line journal, but it has been really nice for us to go back and read it together all this time later. With the line journal it is more of a prompt to help me remember that time period than a detailed description. But also I guess there is an autobiographical aspect to it that appeals to me--maybe someday I'll use it to help write an actual autobiography. And if not I also like to think of it as something to leave for my kids or grandkids to read when I'm gone.


Right. All it takes is for one to work out, if you have several suitable options. If some of the options are only vaguely suitable, or it comes to light through the process that some of them are not suitable at all, then it takes more than just one working out. That's what I was thinking while reading this.


If you're referring to Cubit, they license the ACIS kernel under the hood.


They’re (possibly) referring to “Scalable Geometric Modeler” (SGM)

https://github.com/sandialabs/sgm

Originally open-source, but since taken back in-house. As I understand, which should not be construed as an accurate accounting, Sandia wants to flesh out the basics further before (potentially) open-sourcing it again.


I was referring to Cubit. Phooey on the fact that it's ACIS.


I notice that your application asks about willingness to relocate. Are you able to do fully remote for the right candidate?


Thanks for your interest. Currently we require relocation. We're "hybrid" so some occasional work from home may be allowed, but not fully remote.


> So much of writing is managing your own emotions. The virtue of “pseudowriting” is that it helps you preserve hope for as long as possible—hope that what you will eventually put in place of those square brackets will be good. Hope keeps you coming back: it is more pleasant and low-stakes to pseudowrite than to fix actual language into the draft; and it is less daunting to return to a document where it feels like all that’s left is for you to fill in some blanks. Do that enough times and you will, in fact, end up with something you can read top to bottom.

This describes how I write a new chunk of research code, often. I'll type along until I get to something like "oh, I'll need to calculate the foo of the widget here," and I'll just put a non-existent function call calculateFoo(widget) there until later, when I'll come back and fill it in. I feel like it keeps it manageable; I'm choosing the level of abstraction that I'm drafting code at, and I come in and fill in the details later. I hadn't connected this idea to the journal articles that I am working on; I typically feel somewhat guilty when I add a FIXME in my LaTex document, but with this framing I see now that that is probably the better way to do it than aiming for a finished paragraph from the get-go. The square brackets and placeholders also seem much nicer that the FIXME I was using. Glad to have seen this at a timely moment for me!


I didn't have time to get through the whole article today, but I did spend some time with my kids playing the Wikipedia first link game, which we enjoyed. We kept trying to find one that didn't end in Philosophy, and my youngest son said we should try Brick. Sure enough, it ended in a loop consisting of Existence and Reality.


My brother just finished building an automatic pipe organ for his Mechanical Engineering senior project. Or maybe you'd call it a street organ since it has no keyboard. It has midi input on some arduino-like device, 3d printed pipes, a hand crank pump to fill the bellows, and a bunch of shift registers, relays, and solenoids (on breadboards at this point) to open the valves for the pipes. It turned out really nice, and was a hit at the project showcase. I was involved in helping him figure out the electronics and the code, though I think he threw out the code I wrote in favor of using ChatGPT. All in all, it's not a technically difficult thing to make, though I have the benefit of his hindsight at this point. Maybe I'll get him to write it up at some point.


I'm the kind of guy who decently likes maps, and I pay attention to where I'm going and also to the map before, during, and after using a GPS (Google maps). I do benefit from Google maps in learning my way around a place. It depends on how you use it. So if people use LLMs to code without trying to learn from it and just copy and paste, then yeah, they're not going to learn the skills themselves. But if they are paying attention to the answers they are getting from the LLMs, adjusting things themselves, etc. then they should be able to learn from that as well as they can from online code snippets, modulus the (however occasional) bad examples from the LLM.


> I do benefit from Google maps in learning my way around a place.

Tangent: I once got into a discussion with a friend who was surprised I had the map (on a car dashboard display) locked to North-is-up instead of relative to the car's direction of travel.

I agreed that it's less-convenient for relative turn decisions, but rationalized that setting as making it easier to learn the route's correspondence to the map, and where it passed relative to other landmarks beyond visual sight. (The issue of knowing whether the upcoming turn was left-or-right was addressed by the audio guidance portion.)


It's neat to hear that I'm not the only one who does this. It makes a night-and-day difference for me.

When the map is locked north, I'm always aware of my location within the larger area, even when driving somewhere completely new.

Without it, I could never develop any associations between what I'm seeing outside the windshield and a geospatial location unless I was already familiar with the area.


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