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[Julia in space in lead?!] beta2. I added to Wikidata already with "Preferred rank", but then I get an error here so I moved to "Normal rank" (disables the error). |
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| latest_release_version = {{wikidata|property|edit|reference|Q28974961 |P548=Q2804309|P348}}
| latest_release_date = {{nowrap|{{start date and age|{{wikidata|qualifier| Q28974961 |P348|P577}}|df=y}}}}<br /> and 1.10.9<ref>{{Cite web |title=GitHub - JuliaLang/julia at v1.10.9 |url=https://github.com/JuliaLang/julia/tree/v1.10.9 |access-date=2025-03-10 |website=GitHub |language=en}}</ref> ([[long-term support|LTS]]) / {{nowrap|{{start date and age|2025|03|10|df=y}}}}
| latest preview version = 1.12.0-
| latest_preview_date = {{start date and age|2025|04|
| typing = [[Dynamic programming language|Dynamic]],<ref name="Engheim">{{Cite web|last=Engheim|first=Erik|date=2017-11-17|title=Dynamically Typed Languages Are Not What You Think|url=https://erik-engheim.medium.com/dynamically-typed-languages-are-not-what-you-think-ac8d1392b803|access-date=2021-01-27|website=Medium|language=en|archive-date=5 March 2021|archive-url=https://web.archive.org/web/20210305194133/https://erik-engheim.medium.com/dynamically-typed-languages-are-not-what-you-think-ac8d1392b803|url-status=live}}</ref> [[type inference|inferred]], [[optional typing|optional]], [[nominal type system|nominative]], [[parametric polymorphism|parametric]], [[strong and weak typing|strong]]<ref name="Engheim" />
| implementations =
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* [[Lisp (programming language)|Lisp]]<ref name="announcement"/><ref name="JuliaCon2016">{{Cite web |url=https://juliacon.org/2016 |title=JuliaCon 2016 |publisher=JuliaCon |quote="He has co-designed the programming language Scheme, which has greatly influenced the design of Julia" |access-date=6 December 2016 |archive-date=4 March 2017 |archive-url=https://web.archive.org/web/20170304010606/http://juliacon.org/2016/ |url-status=live }}</ref>
* [[Lua (programming language)|Lua]]<ref name="Introduction">{{Cite web|url=https://docs.julialang.org/en/v1/|title=<!--Chapter: Introduction under --> Home · The Julia Language|website=docs.julialang.org|language=en|access-date=2018-08-15|archive-date=11 January 2021|archive-url=https://web.archive.org/web/20210111031656/https://docs.julialang.org/en/v1/|url-status=live}}</ref>
* [[Wolfram Language|Mathematica]]<ref>{{Cite web |url=https://fatiherikli.github.io/programming-language-network/#language:Julia |title=Programming Language Network |publisher=GitHub |access-date=6 December 2016 |archive-date=20 December 2020 |archive-url=https://web.archive.org/web/20201220131729/http://fatiherikli.github.io/programming-language-network/#language:Julia }}</ref><ref>{{Cite
* [[MATLAB]]<ref name="announcement"/>
* [[Perl]]<ref name="Introduction"/>
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Julia is supported by programmer tools like IDEs (see below) and by notebooks like Pluto.jl, Jupyter, and since 2025 Google Colab officially supports Julia natively.
<!--
Julia works on the [[Raspberry Pi]] computer, and is e.g. supported in [[Raspbian]].<ref>{{cite web |url=https://julialang.org/blog/2017/05/raspberry-pi-julia |title=Julia available in Raspbian on the Raspberry Pi |quote=Julia works on all the Pi variants, we recommend using the Pi 3.}}</ref>▼
▲<!- For now also commented out (see Talk, and above shorter text):
Julia's [[Visual Studio Code]] extension provides a fully-featured [[integrated development environment]] with "built-in dynamic autocompletion, inline results, plot pane, integrated REPL, variable view, code navigation, and many other advanced language features"<ref>{{Cite news |title=Julia in Visual Studio Code |url=https://code.visualstudio.com/docs/languages/julia}}</ref> e.g. debugging is possible, [[lint (software)|linting]], and [[profiling (computer programming)|profiling]].<ref>{{Cite web|last=Holy|first=Tim|title=GitHub - timholy/ProfileView.jl: Visualization of Julia profiling data.|website=[[GitHub]]|date=2019-09-13|url=https://github.com/timholy/ProfileView.jl|access-date=2019-09-22|archive-date=31 January 2020|archive-url=https://web.archive.org/web/20200131231452/https://github.com/timholy/ProfileView.jl|url-status=live}}</ref><ref>{{Cite web|last=Gregg|first=Brendan|title=GitHub - brendangregg/FlameGraph: Stack trace visualizer.|website=[[GitHub]]|date=2019-09-20|url=https://github.com/brendangregg/FlameGraph|access-date=2019-09-22|archive-date=26 September 2019|archive-url=https://web.archive.org/web/20190926230048/https://github.com/brendangregg/FlameGraph|url-status=live}}</ref><ref>{{Cite web|url=https://julialang.org/blog/2019/03/debuggers|title=A Julia interpreter and debugger|website=julialang.org|access-date=2019-04-10}}</ref><ref>{{Cite web|url=https://timholy.github.io/Rebugger.jl/dev/|title=Home · Rebugger.jl|website=timholy.github.io|access-date=2019-04-10|archive-date=31 March 2019|archive-url=https://web.archive.org/web/20190331171846/https://timholy.github.io/Rebugger.jl/dev/|url-status=live}}</ref>
->▼
Some state-of-the-art software has already been written in Julia, because it's considered easier to do then in the other popular languages. Some of it can also be used from other languages like Python or R. Julia was designed to be unusually easy to work with other languages, i.e. to benefit from code already written in other languages, to "reuse" their code.
▲-->
▲Julia
-->▼
==History==
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<!-- I think this is now outdated: Some users may want to postpone upgrading to 1.11 (e.g. those calling Julia from R), because of known temporary package incompatibility.
-->
Much smaller binary executables are possible with <code>juliac</code> which is available in the upcoming Julia 1.12 (now in beta2).
===JuliaCon===
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* Automatic generation of code for different argument types
* Extensible conversions and promotions for numeric and other types
Multiple dispatch (also termed [[multimethod]]s in Lisp) is a [[generalization]] of [[single dispatch]]{{snd}} the [[polymorphism (computer science)|polymorphic mechanism]] used in common [[object-oriented programming]] (OOP) languages, such as [[Python (programming language)|Python]], [[C++]], [[Java (programming language)|Java]], [[JavaScript]], and [[Smalltalk]]{{snd}} that uses [[inheritance (object-oriented programming)|inheritance]]. In Julia, all concrete types are [[subtyping|subtypes]] of abstract types, directly or indirectly subtypes of the <code>Any</code> type, which is the top of the type hierarchy. Concrete types can not themselves be subtyped the way they can in other languages; composition is used instead (see also [[inheritance (object-oriented programming)#Inheritance vs subtyping|inheritance vs subtyping]]).
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Julia has tier 1 [[macOS]] support, for 64-bit [[Apple Silicon]] Macs, natively (previously such [[Apple M1]]-based Macs were only supported by ''running in [[Rosetta 2]] emulation''<ref name="Apple Silicon">{{Cite web |date=2022-05-25 |title=Julia v1.7.3 has been released |url=https://discourse.julialang.org/t/julia-v1-7-3-has-been-released/81683 |access-date=2022-05-26 |website=JuliaLang |language=en |archive-date=26 May 2022 |archive-url=https://web.archive.org/web/20220526015606/https://discourse.julialang.org/t/julia-v1-7-3-has-been-released/81683 |url-status=live }}</ref><ref>{{Cite web|title=Darwin/ARM64 tracking issue · Issue #36617 · JuliaLang/julia|url=https://github.com/JuliaLang/julia/issues/36617|access-date=2020-12-08|website=GitHub|language=en|archive-date=11 November 2020|archive-url=https://web.archive.org/web/20201111014801/https://github.com/JuliaLang/julia/issues/36617|url-status=live}}</ref>), and also fully supports Intel-based Macs. [[Windows 10|Windows on ARM]] has no official support yet. Julia has "initial support of OpenBSD in julia." but more is coming to make it actually work: https://github.com/JuliaLang/julia/issues/53632 -->
Julia has four support tiers.<ref>{{Cite web|url=https://julialang.org/downloads/#support-tiers|title=Julia Downloads|website=julialang.org|access-date=2019-05-17|archive-date=26 January 2021|archive-url=https://web.archive.org/web/20210126095723/https://julialang.org/downloads/#support-tiers|url-status=live}}</ref> All [[IA-32]] processors completely implementing the [[P6 (microarchitecture)|i686]] subarchitecture are supported and all 64-bit [[x86-64]] (aka [[amd64]]), i.e. all less than about a decade old are supported. 64-bit [[Armv8]] (and later; i.e. [[AArch64]]) processors are supported on first tier (for macOS); otherwise second tier on Linux, and ARMv7 (AArch32) on third tier<!-- , and ARMv6 were known to work with some caveats in Julia 1.0.x -->.<ref>{{Cite web |title=julia/arm.md |date=2021-10-07 |url=https://github.com/JuliaLang/julia/blob/master/doc/src/devdocs/build/arm.md |publisher=The Julia Language |quote=A list of known issues for ARM is available. |access-date=2022-05-15 |archive-date=15 May 2022 |archive-url=https://web.archive.org/web/20220515202910/https://github.com/JuliaLang/julia/blob/master/doc/src/devdocs/build/arm.md |url-status=live }}</ref> Hundreds of packages are [[general-purpose computing on graphics processing units|GPU-accelerated]]:<ref>{{Cite web |title=JuliaGPU |url=https://juliagpu.org/ |access-date=2022-11-16 |website=juliagpu.org |quote=Almost 300 packages rely directly or indirectly on Julia's GPU capabilities. |archive-date=23 May 2020 |archive-url=https://web.archive.org/web/20200523103259/https://juliagpu.org/ |url-status=live }}</ref> Nvidia GPUs have support with ''[[CUDA]].jl'' (tier 1 on 64-bit Linux and tier 2 on 64-bit Windows, the package implementing [[Parallel Thread Execution|PTX]], for compute capability 3.5 (Kepler) or higher; both require CUDA 11+, older package versions work down to CUDA 9). There are also additionally packages supporting other accelerators, such as Google's [[tensor processing unit|TPU]]s,<ref>{{Cite web|title=Julia on TPUs|date=2019-11-26|url=https://github.com/JuliaTPU/XLA.jl|publisher=JuliaTPU|access-date=2019-11-29|archive-date=30 April 2019|archive-url=https://web.archive.org/web/20190430044159/https://github.com/JuliaTPU/XLA.jl|url-status=live}}</ref> and some Intel (integrated) GPUs, through ''[[oneAPI (compute acceleration)|oneAPI.jl]]'',<ref>{{Cite web|title=Introducing: oneAPI.jl ⋅ JuliaGPU|url=https://juliagpu.org/post/2020-11-05-oneapi_0.1/|access-date=2021-09-06|website=juliagpu.org}}</ref> and AMD's GPUs have support with e.g. [[OpenCL]]; and experimental support for the AMD [[ROCm]] stack.<ref>{{Cite web|url=https://juliagpu.org/rocm/|title=AMD ROCm · JuliaGPU|website=juliagpu.org|access-date=2020-04-20|archive-date=13 June 2020|archive-url=https://web.archive.org/web/20200613154944/https://juliagpu.org/rocm/|url-status=live}}</ref>
<!--
Julia has been built on the following ARMv8 devices:
On some platforms, Julia may need to be compiled from source code (e.g., the original [[Raspberry Pi]]), with specific build options, which has been done and unofficial pre-built binaries (and build instructions) are available.<ref>{{Cite web|title=Build Julia for RaspberryPi Zero|url=https://gist.github.com/terasakisatoshi/3f8a55391b1fc22a5db4a43da8d92c98|access-date=2020-08-14|website=Gist|language=en|archive-date=1 December 2020|archive-url=https://web.archive.org/web/20201201075252/https://gist.github.com/terasakisatoshi/3f8a55391b1fc22a5db4a43da8d92c98|url-status=live}}</ref><ref>{{Cite web|title=JuliaBerry: Julia on the Raspberry Pi|url=https://juliaberry.github.io/|access-date=2020-08-14|website=juliaberry.github.io|archive-date=8 July 2020|archive-url=https://web.archive.org/web/20200708065730/https://juliaberry.github.io/|url-status=live}}</ref> Julia has been built <!--on the following ARMv8 devices:▼
* [https://www.nvidia.com/object/embedded-systems-dev-kits-modules.html nVidia Jetson TX1 & TX2];
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* [https://softiron.com/products/overdrive-3000/ Overdrive 3000];
* [https://www.cavium.com/ThunderX_ARM_Processors.html Cavium ThunderX]-->
for several ARM platforms, from small Raspberry Pis to the world's fastest (at one point, until recently) supercomputer [[Fugaku (supercomputer)|Fugaku]]'s ARM-based [[Fujitsu A64FX|A64FX]].<ref>{{Cite web |last=Giordano |first=Mosè |title=Julia on Fugaku (2022-07-23) |website=[[GitHub]] |date=2022-09-29 |url=https://github.com/giordano/julia-on-fugaku |access-date=2022-11-08 |archive-date=8 November 2022 |archive-url=https://web.archive.org/web/20221108120723/https://github.com/giordano/julia-on-fugaku |url-status=live }}</ref> [[Power Architecture|<!--- meaning [[POWER8]], but shown as: -->PowerPC]] [[little endian|LE]] (64-bit) has tier 3 support, meaning it "may or may not build", and its tier will lower to 4 for 1.12, i.e. then no longer builds/works.<ref>{{Cite web |date=2025-02-18 |title=PowerPC will be demoted to Tier 4 in Julia 1.12 and later |url=https://discourse.julialang.org/t/powerpc-will-be-demoted-to-tier-4-in-julia-1-12-and-later/122923/4 |access-date=2025-02-23 |website=Julia Programming Language |language=en}}</ref>
<!--
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"[[Nightly build]]s are available for ARMv7-A. [..] Note that OpenBLAS only supports ARMv7. For older ARM variants, using the reference BLAS may be the simplest thing to do. [..] Note: These [Raspberry Pi] chips use ARMv6, which is not well supported at the moment. However it is possible to get a working Julia build. [e.g., supported] [[Tegra#Tegra P1|nVidia Jetson TX2]] [with] CUDA functionality"<ref>{{Cite web|publisher=JuliaLang |url=https://github.com/JuliaLang/julia/blob/v0.6.2/README.arm.md |title=julia/README.arm.md at v0.5.2 · JuliaLang/julia · GitHub |website=Github.com |access-date=2017-05-31}}</ref>
▲-->
Julia has official (tier 2) support for 64-bit ARMv8 meaning e.g. newer 64-bit (ARMv8-A) [[Raspberry Pi]] computers work with Julia (e.g. the Pi Compute Module 4 has been used in space running Julia code).<ref name="space_GPS" /> For many Pis, especially older 32-bit ones, it helps to cross-compile the user's Julia code for them. The older 32-bit ARMv7 Pis worked in older Julia versions (still do, but for latest Julia version(s), note its tier 4: "Julia built at some point in the past, but is known not to build currently."). The original [[Raspberry Pi]] 1 has no official support (since it uses [[ARMv6]] which has newer had a support tier; though some cut-down Julia <!-- i.e. missing OpenBLAS, that has a replacement --> has been known to run on that Pi).<ref>{{Cite web |url=https://github.com/JuliaLang/julia/issues/10488
|title=Cross-compiling for ARMv6
|quote=I believe #10917 should fix this. The CPU used there <code>arm1176jzf-s</code>. Please reopen if it does not.
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|title=ARM build failing during bootstrap on Raspberry Pi 2
|quote=I can confirm (FINALLY) that it works on the Raspberry Pi 2 [..] I guess we can announce alpha support for arm in 0.4 as well. |access-date=16 May 2015}}</ref>
Pico versions of the Pi are known to no work (since using the M-profile Arm, not running under Linux; not yet supported). Julia is now supported in [[Raspbian]]<ref>{{Cite web |url=https://julialang.org/blog/2017/05/raspberry-pi-julia |title=Julia available in Raspbian on the Raspberry Pi |quote=Julia works on all the Pi variants, we recommend using the Pi 3. |access-date=6 June 2017 |archive-date=4 May 2017 |archive-url=https://web.archive.org/web/20170504162102/https://julialang.org/blog/2017/05/raspberry-pi-julia |url-status=live }}</ref> while support is better for newer Pis, e.g., those with Armv7 or newer; the Julia support is promoted by the [[Raspberry Pi Foundation]].<ref>{{Cite web |url=https://www.raspberrypi.org/blog/julia-language-raspberry-pi/ |title=Julia language for Raspberry Pi |work=[[Raspberry Pi Foundation]] |date=12 May 2017 |access-date=6 June 2017 |archive-date=2 June 2017 |archive-url=https://web.archive.org/web/20170602144753/https://www.raspberrypi.org/blog/julia-language-raspberry-pi/ |url-status=live }}</ref>
▲On some platforms, Julia may need to be compiled from source code (e.g., the original [[Raspberry Pi]]), with specific build options, which has been done and unofficial pre-built binaries (and build instructions) are available.<ref>{{Cite web|title=Build Julia for RaspberryPi Zero|url=https://gist.github.com/terasakisatoshi/3f8a55391b1fc22a5db4a43da8d92c98|access-date=2020-08-14|website=Gist|language=en|archive-date=1 December 2020|archive-url=https://web.archive.org/web/20201201075252/https://gist.github.com/terasakisatoshi/3f8a55391b1fc22a5db4a43da8d92c98|url-status=live}}</ref><ref>{{Cite web|title=JuliaBerry: Julia on the Raspberry Pi|url=https://juliaberry.github.io/|access-date=2020-08-14|website=juliaberry.github.io|archive-date=8 July 2020|archive-url=https://web.archive.org/web/20200708065730/https://juliaberry.github.io/|url-status=live}}</ref>
▲Julia is now supported in [[Raspbian]]<ref>{{Cite web |url=https://julialang.org/blog/2017/05/raspberry-pi-julia |title=Julia available in Raspbian on the Raspberry Pi |quote=Julia works on all the Pi variants, we recommend using the Pi 3. |access-date=6 June 2017 |archive-date=4 May 2017 |archive-url=https://web.archive.org/web/20170504162102/https://julialang.org/blog/2017/05/raspberry-pi-julia |url-status=live }}</ref> while support is better for newer Pis, e.g., those with Armv7 or newer; the Julia support is promoted by the [[Raspberry Pi Foundation]].<ref>{{Cite web |url=https://www.raspberrypi.org/blog/julia-language-raspberry-pi/ |title=Julia language for Raspberry Pi |work=[[Raspberry Pi Foundation]] |date=12 May 2017 |access-date=6 June 2017 |archive-date=2 June 2017 |archive-url=https://web.archive.org/web/20170602144753/https://www.raspberrypi.org/blog/julia-language-raspberry-pi/ |url-status=live }}</ref> Julia has also been built for 64-bit [[RISC-V]],<ref>{{Cite web |title=Release v1.12-0a92fecc12 · maleadt/julia |url=https://github.com/maleadt/julia/releases/tag/v1.12-0a92fecc12 |access-date=2024-10-12 |website=GitHub |language=en}}</ref><ref>{{Cite web |title=julia/doc/src/devdocs/build/riscv.md at master · alexfanqi/julia |url=https://github.com/alexfanqi/julia/blob/master/doc/src/devdocs/build/riscv.md |access-date=2024-10-09 |website=GitHub |language=en}}</ref> that has some supporting code in core Julia.
Julia has also been built for 64-bit [[RISC-V]] (has tier 3 support),<ref>{{Cite web |title=Release v1.12-0a92fecc12 · maleadt/julia |url=https://github.com/maleadt/julia/releases/tag/v1.12-0a92fecc12 |access-date=2024-10-12 |website=GitHub |language=en}}</ref><ref>{{Cite web |title=julia/doc/src/devdocs/build/riscv.md at master · alexfanqi/julia |url=https://github.com/alexfanqi/julia/blob/master/doc/src/devdocs/build/riscv.md |access-date=2024-10-09 |website=GitHub |language=en}}</ref> i.e. has some supporting code in core Julia.
While Julia requires an [[operating system]] by default, and has no official support to run without, or on [[embedded system]] platforms such as [[Arduino]], Julia code has still been run on it, with some limitations, i.e. on a baremetal 16 [[Hertz#Computers|MHz]] [[8-bit computing|8-bit]] ([[ATmega328P]]) [[AVR microcontrollers|AVR-microcontroller]] Arduino with 2 KB RAM (plus 32 KB of flash memory).<ref>{{Cite web |title=Running Julia baremetal on an Arduino |url=https://seelengrab.github.io/articles/Running%20Julia%20baremetal%20on%20an%20Arduino/ |access-date=2022-05-24 |website=seelengrab.github.io |archive-date=24 May 2022 |archive-url=https://web.archive.org/web/20220524075548/https://seelengrab.github.io/articles/Running%20Julia%20baremetal%20on%20an%20Arduino/ |url-status=live }}</ref><ref>{{Cite web |last=Sukera |title=AVRDevices.jl |website=[[GitHub]] |date=2023-07-31 |url=https://github.com/Seelengrab/AVRDevices.jl |access-date=2023-08-05 |archive-date=5 August 2023 |archive-url=https://web.archive.org/web/20230805203930/https://github.com/Seelengrab/AVRDevices.jl |url-status=live }}</ref>
==Adoption==
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* NASA and the [[Jet Propulsion Laboratory]] use Julia to model spacecraft separation dynamics,<ref>{{Cite web |title=Modeling Spacecraft Separation Dynamics in Julia - Jonathan Diegelman | website=[[YouTube]] | date=9 March 2021 |url=https://www.youtube.com/watch?v=tQpqsmwlfY0 |language=en |access-date=2021-09-06 |archive-date=6 September 2021 |archive-url=https://web.archive.org/web/20210906221540/https://www.youtube.com/watch?v=tQpqsmwlfY0 |url-status=live }}</ref><ref>{{Cite web |title=Circuitscape/Circuitscape.jl |date=2020-02-25 |url=https://github.com/Circuitscape/Circuitscape.jl |publisher=Circuitscape |access-date=2020-05-26 |archive-date=30 July 2020 |archive-url=https://web.archive.org/web/20200730074511/https://github.com/Circuitscape/Circuitscape.jl |url-status=live }}</ref><ref>{{Cite web |title=Conservation through Coding: 5 Questions with Viral Shah {{!}} Science Mission Directorate |url=https://science.nasa.gov/earth-science/applied-sciences/making-space-for-earth/5-questions-with-viral-shah |access-date=2020-05-26 |website=science.nasa.gov |archive-date=25 May 2020 |archive-url=https://web.archive.org/web/20200525212814/https://science.nasa.gov/earth-science/applied-sciences/making-space-for-earth/5-questions-with-viral-shah |url-status=dead }}</ref> analyze [[TRAPPIST]] [[exoplanet]] datasets,<ref>{{Cite web |title=Julia in the Wild - Julia Data Science |url=https://juliadatascience.io/julia_wild |access-date=2022-09-12 |website=juliadatascience.io |archive-date=12 September 2022 |archive-url=https://web.archive.org/web/20220912202632/https://juliadatascience.io/julia_wild |url-status=live }}</ref><ref>{{Cite web |title=Seven Rocky TRAPPIST-1 Planets May Be Made of Similar Stuff |url=https://exoplanets.nasa.gov/news/1669/seven-rocky-trappist-1-planets-may-be-made-of-similar-stuff/ |access-date=2022-10-06 |website=Exoplanet Exploration: Planets Beyond our Solar System |date=21 January 2021 |archive-date=6 October 2022 |archive-url=https://web.archive.org/web/20221006193612/https://exoplanets.nasa.gov/news/1669/seven-rocky-trappist-1-planets-may-be-made-of-similar-stuff/ |url-status=live }}</ref> and analyze [[cosmic microwave background]] data from the [[Big Bang]]<ref>{{Cite web |title=Julia in Astronomy & Astrophysics Research {{!}} Eric B. Ford {{!}} JuliaCon 2022 | website=[[YouTube]] | date=25 July 2022 |url=https://www.youtube.com/watch?v=vj1uzilanQI |language=en |access-date=2022-10-06 |archive-date=6 October 2022 |archive-url=https://web.archive.org/web/20221006193235/https://www.youtube.com/watch?v=vj1uzilanQI |url-status=live }}</ref>
* The Brazilian [[National Institute for Space Research|INPE]], for space missions and [[satellite]] simulations<ref>{{Cite web |title=JuliaSpace/SatelliteToolbox.jl |date=2020-05-20 |url=https://github.com/JuliaSpace/SatelliteToolbox.jl |publisher=JuliaSpace |access-date=2020-05-26 |archive-date=16 June 2021 |archive-url=https://web.archive.org/web/20210616105212/https://github.com/JuliaSpace/SatelliteToolbox.jl |url-status=live }}</ref>
* Julia has also flown in space, on a small <!-- [[cubsat]] --> satellite,<ref name="space_GPS">{{Cite web |date=2024-12-13 |title=Julia and the GPS payload onboard Waratah Seed-1 satellite |url=https://discourse.julialang.org/t/julia-and-the-gps-payload-onboard-waratah-seed-1-satellite/123795 |access-date=2025-02-04 |website=Julia Programming Language |quote=We flew our GPS receiver payload, Harry v3 on Waratah Seed-1 6U cubesat [..] <!-- Julia running in space! --> Julia can also run on Raspberry Pi CM4, the processor I used on our GPS payload computer. <!-- [..] In space, we also capture IF data for us to do postprocessing in ground. --> |language=en}}</ref> used for a GPS module.<!-- https://www.reddit.com/r/Julia/comments/17vrk5r/what_are_the_most_fascinating_projects_you_have/ --> And Julia has also been used to design satellites constallations.<ref>{{Cite AV media |url=https://www.youtube.com/watch?v=2AfCljss-Lk |title=Designing satellites constellations with Julia {{!}} Clement de Givry {{!}} JuliaCon 2024 |date=2024-10-01 |last=The Julia Programming Language |access-date=2025-02-04 |via=YouTube}}</ref>
* [[Embedded system|Embedded]] hardware to plan and execute flight of autonomous U.S. [[Air Force Research Laboratory]] [[VTOL]] [[unmanned aircraft system|drones]]<ref>{{Cite web |last=Hobbs |first=Kerianne |date=December 2022 |title=Year of Autonomy in Alaskan Glaciers, Flight, Earth Orbit, Cislunar Space and Mars |url=https://digitaleditions.walsworth.com/publication/?m=7270&i=769555&p=48 |publisher=Aerospace America Year in Review |page=48 |quote=The flight test team was able to demonstrate … a vertical takeoff and landing vehicle with both electric and conventional fuel propulsion systems onboard. The [[unmanned aircraft system|[uncrewed aerial system]]] was able to plan and execute these missions autonomously using onboard hardware. It was the first time the Julia programming language was flown on the embedded hardware - algorithms were precompiled ahead of time. <!-- Too much detail to also include this in footnote?: The algorithms used to perform the various missions involved feedback control, mixed-integer linear programming and optimal control. --> |access-date=26 January 2023 |archive-date=19 June 2024 |archive-url=https://web.archive.org/web/20240619193142/https://digitaleditions.walsworth.com/publication/?m=7270&i=769555&p=48 |url-status=live }}</ref>
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