https://community.wolfram.com RSS Feed for Wolfram Community showing any discussions tagged with Astronomy sorted by active. https://community.wolfram.com/groups/-/m/t/3716438 ![Painting a Kerr black hole: a backward null-geodesic ray tracer with a real astrophotograph][1] *"Hook image: a viewport screenshot from inside an interactive Wolfram viewer, looking at a 360-degree black-hole panorama generated by OpenAI's gpt-image-2. This is AI art -- striking, but not derived from general relativity. The rest of the notebook builds the same scene from physics, in pure Wolfram Language. See Section 11 for the viewer itself."* &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=PaintingaKerrblackhole.jpg&userId=20103 [2]: https://www.wolframcloud.com/obj/1cc09d34-423c-4144-9e2c-c256740295ad Marco Thiel 2026-05-15T09:49:06Z https://community.wolfram.com/groups/-/m/t/3716185 ![Aliens? Or weather balloons? You decide!][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=AliensOrWeatherBalloonsYouDecide.jpg&userId=20103 [2]: https://www.wolframcloud.com/obj/a9f85d83-9d1a-47dc-92bc-bf3cfa1232c4 Arnoud Buzing 2026-05-15T00:20:07Z https://community.wolfram.com/groups/-/m/t/3636637 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/2eb2cb4e-4a63-4a59-a5e4-d983775859c3 Donald Airey 2026-02-08T20:17:36Z https://community.wolfram.com/groups/-/m/t/3715214 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/f3cc5b88-f290-4e68-ac29-2d450c373fd1 Diego Zviovich 2026-05-12T23:08:24Z https://community.wolfram.com/groups/-/m/t/3714827 ![Google Earth Engine (GEE) client paclet][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=10966GoogleEarthEngine%28GEE%29clientpaclet.jpg&userId=20103 [2]: https://www.wolframcloud.com/obj/2a2947bc-b39e-494c-9309-173af5069ad5 Diego Zviovich 2026-05-12T01:32:46Z https://community.wolfram.com/groups/-/m/t/3714638 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/69a3596e-883a-4663-b088-21e5944d9a48 Zihni Kaan Baykara 2026-05-11T15:31:12Z https://community.wolfram.com/groups/-/m/t/3712435 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/d265c46a-003e-4024-80bd-f4e249f39a50 Mohammad Bahrami 2026-05-05T19:57:28Z https://community.wolfram.com/groups/-/m/t/3706203 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/1ad1af94-9785-4367-b665-21c66f5a4045 Lim Lee 2026-04-27T04:06:18Z https://community.wolfram.com/groups/-/m/t/3711592 This formula is more accurate at predicting SNe Ia comoving distances than FLRW and since it's analytical, it will execute upwards of 10,000 faster and give you machine precision. $D_C(z) = \frac{t_o\left(2V_0 - A t_o\right) z}{2 + z}$ ![enter image description here][1] That's it. That's all there is to it. Here's how it compares to FLRW: ![enter image description here][2] Red is the analytical formula, blue is FLRW. Using the full covariance matrix of the Pantheon+ SH0ES project, the reduced $\chi^2$ of 1.68 for the analytical formula is significantly better than 2.49 for the numerical FLRW solution. This is an outrageous claim, so it should be easy to debunk. The full paper is here: [Acceleration Law Article][3] and the notebook is here: [Acceleration Law Notebook][4]. I'd appreciate your feedback, positive or negative. [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2026-05-04204344.png&userId=20103 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=HubbleDiagram.png&userId=3608757 [3]: https://www.wolframcloud.com/obj/de2ae88c-5ea9-4334-8b9c-3edbbac38fa5 [4]: https://www.wolframcloud.com/obj/ed737c03-5baf-49f4-90e3-83b91b245c2a Donald Airey 2026-05-04T19:36:36Z https://community.wolfram.com/groups/-/m/t/3675919 **Intro** A fundamental question keeps coming up for me: If biological evolution operates in astronomically large spaces, why is search computationally tractable at all? Even a modest protein corresponds to a combinatorial space that is effectively impossible to exhaustively explore. Yet evolution does not behave like an unconstrained random search. So what makes the space navigable? **Essay** In 1859, two different perspectives on complexity emerged. Bernhard Riemann revealed deep structural order underlying the distribution of prime numbers. Charles Darwin introduced a dynamical process of variation and selection. Modern biology has successfully developed Darwin’s framework. However, something is often left implicit: the assumption that the search space is already structured in a way that makes local exploration effective. From a purely combinatorial perspective, this is problematic. Under simple assumptions (independent variation, no bias), expected search time grows exponentially with the amount of required information. In that regime, evolution would be computationally intractable. But real systems do not operate in that regime. Instead, they appear to evolve within a highly structured, constrained subspace, where: functional states are not isolated viable configurations form connected regions local mutations can traverse meaningful paths This suggests that evolution can be framed as a constrained search problem, rather than a purely stochastic process. Evolution is not merely a process acting within a space — it is a process shaped by the structure of the space it can access. This shifts the central question: What determines that accessible space? **A Minimal Computational Model** To make this concrete, consider a simple toy model. We define: a sequence space a mutation operator a constraint that restricts transitions **Basic setup** L = 20; randomSeq[] := RandomInteger[{0, 1}, L]; mutate[s_] := ReplacePart[s, RandomInteger[{1, L}] -> 1 - #] & @ s; **Fitness function** fitness[s_] := Boole[Total[s] > 12]; **Constraint energy** energy[s_] := Total[ Map[If[# === {1, 1}, 0, 1] &, Partition[s, 2, 1]] ]; **Dynamics: constrained vs unconstrained** stepConstrained[s_] := Module[{s2 = mutate[s]}, If[constraint[s, s2], s2, s] ]; stepRandom[s_] := mutate[s]; **Search experiment** findFunctional[step_, max_] := Module[ {s = randomSeq[], t = 0}, While[t < max && !TrueQ[fitness[s] == 1], s = step[s]; t++; ]; t ]; trialsConstrained = Table[ findFunctional[stepConstrained, 1000], {50} ]; trialsRandom = Table[ findFunctional[stepRandom, 1000], {50} ]; **Visualization** Histogram[ {trialsRandom, trialsConstrained}, ChartLegends -> {"Random", "Constrained"}, PlotTheme -> "Scientific", Frame -> True ] **Interpretation** In many runs, the constrained dynamics reaches functional states faster — not because the system is explicitly guided toward a target, but because the structure of the space itself has changed. Even in this minimal model, a key effect emerges: Pure random mutation behaves like unstructured search Even a simple constraint dramatically reshapes accessibility The constraint does not “guide” the system toward solutions. Instead, it reshapes the space such that functional paths become possible in the first place. **Open Questions** This raises several structural questions: - How can we formally define a constraint operator in general systems? - Can constraint-induced subspaces be measured or classified? - How does connectivity emerge in high-dimensional spaces under constraints? - Do constrained systems exhibit characteristic spectral signatures (e.g., non-random eigenvalue statistics)? **Closing Thought** The difference between intractable search and effective evolution may not lie in time or randomness — but in the geometry of the accessible space itself. Maurice Crutzen 2026-04-07T09:31:01Z https://community.wolfram.com/groups/-/m/t/3710432 ![Computational geometry modeling of the neolithic circular ditch in Vinoř, Prague][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=ComputationalgeometrymodelingoftheneolithiccircularditchinVino%C5%99,Prague2.jpg&userId=20103 [2]: https://www.wolframcloud.com/obj/97db78e9-ef10-4f2f-8506-9a77b82eff35 Jessica Alfonsi 2026-05-01T15:59:22Z https://community.wolfram.com/groups/-/m/t/3706027 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/9823b1a8-b2fd-491e-83d0-5ee54badd179 Marco Thiel 2026-04-26T19:39:43Z https://community.wolfram.com/groups/-/m/t/3707090 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/6473f01c-b05e-47e9-b7e6-eb1be887dd10 Marco Thiel 2026-04-28T14:30:05Z https://community.wolfram.com/groups/-/m/t/3701280 ![Exploring NASA SkyView: live imagery, dark-nebula analysis, & catalogue-driven sky-survey downloader][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=ExploringNASASkyViewliveimagery.png&userId=20103 [2]: https://www.wolframcloud.com/obj/928898a9-67eb-4590-bdf7-0113b2c76db4 Marco Thiel 2026-04-22T22:27:38Z https://community.wolfram.com/groups/-/m/t/3686348 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/e1aa2b28-96b1-4104-8347-1e38ecdf5e0d Brian Beckman 2026-04-14T16:21:26Z https://community.wolfram.com/groups/-/m/t/3673962 ![View of the Moon from Artemis II][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=ArtemisIIFlyBy_final.gif&userId=20103 [2]: https://www.wolframcloud.com/obj/54c0ec26-f350-4965-a1bc-bd7b5e34dbf5 Jeffrey Bryant 2026-04-03T19:51:12Z https://community.wolfram.com/groups/-/m/t/3680003 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/193a32aa-8598-4eb0-a601-ef448032e058 Alexander Zhidenko 2026-04-09T10:35:12Z https://community.wolfram.com/groups/-/m/t/3672762 ![Artemis II trajectory: crewed lunar flyby to launch on April 1, 2026][1] &[Wolfram Notebook][2] [ORIGINAL GIF]: https://community.wolfram.com//c/portal/getImageAttachment?filename=10956ArtemisIItrajectorycrewedlunarflybytolaunchonApril1,2026.gif&userId=20103 [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=4398testing2-optimize.gif&userId=20103 [2]: https://www.wolframcloud.com/obj/1f4c613a-e72e-487b-9b5a-c75613d8a099 Jeffrey Bryant 2026-03-31T21:27:57Z https://community.wolfram.com/groups/-/m/t/3672541 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/7c20d0a3-0451-4f2c-95b5-d4014f395ab4 Rudnei Ramos 2026-03-31T17:01:30Z https://community.wolfram.com/groups/-/m/t/3671922 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/53dcf037-fe9d-4e60-a6b9-aaf92a854da6 Brian Beckman 2026-03-30T15:51:29Z