https://community.wolfram.com RSS Feed for Wolfram Community showing questions tagged with Astronomy sorted by active. 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/3667575 g'day, G’day, I am trying to find a good way to obtain eclipses with the moon and planets or stars (such as Regulus) from pre-history to future, say 20000bc to 20000ad: And do it from a certain longitude and latitude on the earth. I did try angular positioning and various other things. I just found out that the “fullmoon” function goes back to 1900ad only. Any help would be appreciated. Thanks Dan Widhalm 2026-03-23T00:33:22Z https://community.wolfram.com/groups/-/m/t/3547640 Hello, I am trying to evaluate the Diractrace using Feyncalc package. The expression involves projection operator 'ab' which comes from completeness relation of spin 3/2 particles (Delta-). I am having some issues while evaluating this. The newer version of Mathematica i.e. 14.3 does not provide any output and kernel becomes dead. Can anyone help me with this? &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/2682002a-17a6-4539-aed3-8c47d6e10b00 Yogeesh N 2025-09-19T06:30:56Z https://community.wolfram.com/groups/-/m/t/3539516 Author: Modise Rex Seemela Thematic Link: This work connects the Wolfram Physics Project to AI Safety via the concept of Rulial Space. --- ##Introduction to the Problem The development of Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI) presents a fundamental challenge: ensuring these entities' goals and operations remain aligned with complex, multifaceted human values. Traditional alignment approaches, often rooted in reinforcement learning from human feedback (RLHF) and interpretability, struggle with the combinatorial explosion of potential computational states an AGI might traverse. We need a framework that doesn't just analyze a single reasoning path but models the entire space of possible paths. Stephen Wolfram's concept of Rulial Space—the encompassing space of all possible computations—provides a powerful paradigm for this. By modeling AI cognition as a trajectory through a multi-computational graph of evolving states, we can begin to: Map alignment attractors (regions of computational state space that correspond to safe outcomes). Identify instability basins where small perturbations lead to rapid divergence into misaligned states. Formally reason about emergence in AI behavior, not as magic, but as a consequence of the topology of this rulial space. This post uses the Wolfram Language to construct a toy model of an AI's reasoning process within a rulial space, visualizing the paths it could take and analyzing the points where its alignment is determined. --- ##Wolfram Language Code: Simulating a Rulial Reasoning Graph We start by defining a function to generate a multi-computational graph from a set of transformation rules. This graph represents the "universe" of possible computational states the AI can reach. (* Define a function to generate a rulial multi-graph from a set of rules *) GenerateRulialGraph[rules_List, initialState_, steps_Integer] := Module[ {states, edges, vertexStyles, alignmentAttractorQ}, (* A simple predicate to tag "aligned" states. This is a placeholder for a complex alignment metric *) alignmentAttractorQ[state_] := StringContainsQ[ToString[state], "h"]; (* e.g., states involving 'h' are "aligned" *) (* Generate all states up to a given number of steps *) states = NestList[ DeleteDuplicates @* Flatten @* Map[ReplaceList[#, rules] &], {initialState}, steps ]; (* Build edges between states *) edges = Flatten @ Table[ Map[DirectedEdge[states[[i, j]], #] &, states[[i + 1]]], {i, Length[states] - 1}, {j, Length[states[[i]]]} ]; (* Style vertices based on our simple alignment predicate *) vertexStyles = If[alignmentAttractorQ[#], {# -> Green}, {# -> Red}] & /@ Flatten[states] // Flatten; (* Return an annotated graph *) Graph[edges, VertexLabels -> Placed["Name", Center], VertexSize -> Large, VertexStyle -> vertexStyles, VertexLabelStyle -> Directive[Bold, 12, White], GraphLayout -> "LayeredDigraphEmbedding", ImageSize -> Large ] ] (* Define a simple rule set for an AI's "reasoning" process. f[]: could represent a "safe" operation. g[]: could represent an "unsafe" operation. h[]: could represent a terminal "aligned" conclusion. *) reasoningRules = { a -> {f[a], g[a]}, (* From initial state 'a', the AI can choose a safe or unsafe path *) f[x_] -> {f[f[x]], h[x]}, (* A safe operation can lead to more safety or a conclusion *) g[x_] -> {g[g[x]], x} (* An unsafe operation can lead to deeper unsafety or a dead end *) }; (* Generate the rulial graph for our AI's reasoning space *) reasoningSpaceGraph = GenerateRulialGraph[reasoningRules, a, 4] This code produces a graph where green nodes represent "aligned" states, and red nodes represent potentially misaligned or neutral states. --- ##Analysis: Paths, Attractors, and Basins The graph is a simplified map of the AI's potential "thought processes." We can now analyze it for alignment properties. (* Find all simple paths from the initial state to any aligned (green) state *) alignedPaths = FindPath[reasoningSpaceGraph, a, _?alignmentAttractorQ, Infinity, All]; (* Print the number of paths to alignment and an example *) Print["Number of paths to alignment: ", Length[alignedPaths]]; Print["Example path to alignment: ", alignedPaths[[1]]]; (* Analyze the "basin of attraction" for alignment: how many states eventually lead to alignment? *) allVertices = VertexList[reasoningSpaceGraph]; alignedVertices = Select[allVertices, alignmentAttractorQ]; basinOfAttraction = ConnectedComponents[UndirectedGraph[reasoningSpaceGraph]]; statesThatLeadToAlignment = Select[basinOfAttraction, Intersection[#, alignedVertices] =!= {} &] // Flatten // Union; Print["Number of states in the rulial space: ", Length[allVertices]]; Print["Number of states that eventually lead to alignment: ", Length[statesThatLeadToAlignment]]; Discussion of Output: The code calculates all possible paths the AI could take to reach a safe conclusion. It defines a basin of attraction for alignment—the set of all states from which an aligned outcome is still reachable. This is a crucial safety metric; if the AI's state leaves this basin, alignment may no longer be possible. In a real model, the alignmentAttractorQ function would be a sophisticated metric evaluating the state against a framework of human values. --- ##Questions for Community Discussion 1. Attractor Geometry: How can we formally define the geometry (e.g., homology, curvature) of alignment attractors within an ASI's rulial space? Could certain topologies be inherently safer than others? 2. Instability Detection: Can rulial geometry help define a formal "divergence metric" to detect instability regions where AGI reasoning becomes chaotic and unpredictable, providing an early warning system? 3. Quantum & Probabilistic Computation: How might we extend this model from discrete, deterministic rules to probabilistic or quantum computations, which are inherently non-deterministic? Could this be modeled with multiway causal graphs? 4. Application to High-Risk Domains: How could this modeling approach inform the design of safety constraints for autonomous systems in finance, defense, or space exploration, where the cost of misalignment is catastrophic? 5. Connection to Fundamental Physics: This model is a direct application of the principles behind the Wolfram Physics Project. Does this suggest that the problem of AI alignment is not just a software engineering challenge but a fundamental physical one, relating to the concept of observers and the evolution of causal structures? --- ##References & Further Reading Wolfram, Stephen. What Is Consciousness? Some New Perspectives from Our Physics Project – Stephen Wolfram Writings Wolfram Physics Project: Multiway Systems Wolfram Language Documentation: Graph, FindPath Alignment Forum Modise Seemela 2025-09-03T06:21:59Z https://community.wolfram.com/groups/-/m/t/3534507 Hello Wolfram Community, The concept of branchial space—introduced in the Wolfram Physics Project—offers a transformative way to model multi-way relationships between system states. While profound in theoretical physics, I believe it also holds immense potential for applied engineering. In this post, I’ll demonstrate a simple proof-of-concept using Wolfram Language: visualizing satellite close approaches ("conjunctions") through the lens of branchial space. This approach could redefine how we handle space traffic management. The Challenge: Uncertainty in Orbital Dynamics A satellite’s orbit isn’t deterministic; it’s a cloud of possibilities due to measurement errors, solar radiation pressure, and atmospheric drag. Traditional Monte Carlo simulations model many paths, but branchial space allows us to explore the relationships between all possible future states. A Simple Branchial Model in Wolfram Language Let’s model two satellites on near-collision courses. We’ll represent each satellite’s state by its orbital elements and simulate their evolution under uncertainty. Step 1: Define orbital propagation with uncertainty: ```wolfram (* Propagate an orbit: add uncertainty to mean anomaly *) propagateOrbit[state_, dt_, uncertainty_] := Module[{a, e, v, newV}, {a, e, v} = state; newV = v + dt/1000 + RandomVariate[NormalDistribution[0, uncertainty]]; {a, e, newV} ]; (* Initial states for two satellites *) sat1Initial = {7000, 0.01, 0}; (* {semi-major axis (km), eccentricity, mean anomaly} *) sat2Initial = {7000, 0.01, Pi + 0.001}; (* Second satellite starts near the first *) (* Generate possible states over 10 timesteps *) numSteps = 10; uncertainty = 0.0005; sat1States = NestList[propagateOrbit[#, 1, uncertainty] &, sat1Initial, numSteps]; sat2States = NestList[propagateOrbit[#, 1, uncertainty] &, sat2Initial, numSteps]; ``` Step 2: Construct a branchial graph of conjunctions: We define a node for each combination of satellite states at a given time.An edge connects two nodes if the satellites are dangerously close (a conjunction) at that point, linking possible futures. ```wolfram (* Calculate distance in parameter space *) stateDistance[state1_, state2_] := Abs[state1[[3]] - state2[[3]]]; (* Build graph of conjunctions: nodes are (time, branch1, branch2) *) conjunctionThreshold = 0.002; branchialGraph = {}; Do[ dist = stateDistance[sat1States[[t, b1]], sat2States[[t, b2]]]; If[dist < conjunctionThreshold, AppendTo[branchialGraph, Labeled[ {t, b1, b2} -> {t+1, b1, b2}, Round[dist, 0.0001]] ] ], {t, 1, numSteps-1}, {b1, Length[sat1States]}, {b2, Length[sat2States]} ]; (* Visualize the graph *) Graph[branchialGraph, GraphLayout -> "SpringElectricalEmbedding", VertexLabels -> Placed["Index", Center], EdgeLabels -> "EdgeTag", PlotLabel -> "Branchial Graph of Satellite Conjunction Scenarios", ImageSize -> 800 ] ``` Step 3: Interpretation: · Each node represents a possible system state at time t. · Edges indicate potential conjunctions—paths the system could traverse through branchial space. · Clusters show high-risk scenarios where many branches lead to close encounters. Why This Matters This model moves beyond probability estimates to reveal the connectivity of risk: · Identify critical decision points to avoid entire branches of collisions. · Plan maneuvers that minimize risk across multiple possible futures. · Extend this to cybersecurity, finance, or logistics—any domain with branching futures. Conclusion: Toward Applied Rulial Thinking This is a basic illustration, but it highlights a powerful application of computational irreducibility and branchial space. At Rulial Space Agency, we’re working to operationalize these concepts from the Wolfram Physics Project into scalable solutions for space, defense, and finance. We’re building the tools to navigate the ruliad—and we welcome discussions, collaborations, or questions from the community. To learn more about our work, visit us at Rulial Space Agency. Modise Seemela 2025-08-22T13:11:00Z https://community.wolfram.com/groups/-/m/t/3472860 My Mathematica code is taking too much time to compute. I don't know what the issue is. Can anyone suggest any changes that I need to make in order for the code to work? Ananth Krishna V &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/cec6225e-eaf9-40c5-bb9c-428f578a3931 Ananth Krishna 2025-06-02T12:57:50Z https://community.wolfram.com/groups/-/m/t/3352551 &[Wolfram Notebook][1]Dear All, I am trying to reproduce the top left figure 5 with $q = 0$ from the manuscript <https://arxiv.org/pdf/1707.09521> . In this case, for $\theta = \pi/2$ in equation 52, $\alpha$ is equal to equation 45 in negative. Furthermore, I replace equation 44 to obtain $\beta$ in equation 52. However, I am not getting the figure. I am attaching my worksheet. Perhaps the goal would be to plot equation 55, but I can't figure out how to plot the contour of an equation of the type $\alpha(x)^2 + \beta(x)^2 = f(x)$ with $\alpha$ and $\beta$ on the horizontal and vertical axes. ![enter image description here][2] Any help would be appreciated. Best regards. [1]: https://www.wolframcloud.com/obj/14ca306a-b442-427d-be1b-26c1596e1a4d [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Falla.jpg&userId=3244911 Malej Est 2025-01-07T17:05:09Z https://community.wolfram.com/groups/-/m/t/3205951 Is there an existing method to get a satellite's altitude and azimuth at different times? For example, running the snippet below will retrieve the current altitude and azimuth; however, there does not appear to be an option to add a specific time to this method. satellite = Entity["Satellite", "25544"]; altitude = SatelliteData[satellite, "Altitude"]; azimuth = SatelliteData[satellite, "Azimuth"]; {altitude, azimuth} I have looked for a built-in method to propagate a TLE, and also tried using the Wolfram plugin for ChatGPT to find this - that led to a long sequence of ChatGPT attempts to add time as parameter to the SatelliteData function - but no luck so far. Tim Kennedy 2024-07-05T13:09:51Z https://community.wolfram.com/groups/-/m/t/3067368 Hi there, I have some basic code for plotting the gravitional time dilation as one moves closer to the event horizon of a black hole of a given mass. See code: ClearAll["Global`*"]'; tp = 1; G = 6.67408*10^(-11); M = (6.5*10^9)*(1.989*10^30); c = 2.99*10^8; rs = (2*G* M)/(c^2); Print[]; Print[" Black hole mass:", M, "kg", " \ Schhwarzchild radius:", rs, "m"]; Print[]; Plot[ tp*Sqrt[1 - (rs/r)], {r, 0, 2*10^14}, AxesLabel -> {" ", "Time (s)"}, AxesLabel -> {Style[" (m)", Bold, 26], Style["Time (s)", Bold, 16]}, LabelStyle -> Directive[Black, 16], AxesOrigin -> {0, 0}, GridLines -> {{rs}, {}}, GridLinesStyle -> {Directive[{Dashed, Thick}, Red], Directive[Thick, Red]}, ColorFunction -> "NeonColors"] I want to create a 3D plot for different masses of black holes ranging from the one given in the code to one a thousand times more massive, with a 3D sheet. I am not great at this, and while my basic code works fine, when I go to do a 3D plot, nothing seems to work. Estelle Asmodelle 2023-11-20T03:35:09Z https://community.wolfram.com/groups/-/m/t/3020936 Dear all, In my old version, was possible to read images.fits using the following command: image = First@ Import["/users/Image001.fits", ImageSize -> Small]; Now in the new version 13.3 this is not working Could somebody help me with this? Thanks in advance Cesar Antonio de Oliveira 2023-09-25T14:18:12Z https://community.wolfram.com/groups/-/m/t/2907932 I wonder how to calculate the date of the vernal equinox, summer solstice, autumnal equinox, and winter solstice in Mathematica. I searched Wolfram Community for a post showing how to calculate the solstices and equinoxes but I couldn't a post. Kenneth R. Lang states in his book Essential Astrophysics > As the Sun moves along the ecliptic, it crosses the celestial equator > twice, on its way north at the Vernal Equinox, on about March 20, and > then at the Autumnal Equinox on about September 23. On either equinox, > the Sun lies in the Earth’s equatorial plane, so the twilight zone > that separates night and day then cuts the Earth in equal parts and > the days and nights are equally long. The point at which the Sun is > farthest north, is the Summer Solstice (on about June 21), and its > most southerly point is the Winter Solstice on about December 22. The > days in the northern hemisphere are the longest on the Summer > Solstice, and shortest on the Winter Solstice. So the crossing of the > Sun at the equinoxes and solstices mark the beginning of the seasons > in the Earth’s northern hemisphere, and the location of these points > on the celestial sphere are given in Table 1.1. I understand autumnal equinox is when the days are the same length. Peter Burbery 2023-04-26T00:42:04Z https://community.wolfram.com/groups/-/m/t/2896297 *With the exception of the two planets that have retrograde rotation*, the planets (including Ganymede) line up almost perfectly on a scatter between the magnetic and inertial moments. This includes Saturn's anomalous alignment between magnetic axis and rotational axis, which has required some post-hoc theorizing. Occam's Razor, however, would indicate that it is the inertial moment, and not other variables, that accounts for the magnetic moment -- with something quite exceptional going on with the retrograde rotation planets: Venus and Mars. While I can quite understand why it would be that inertial moment would drive whatever planetary dynamo might be in operation, it does seem rather strange that the other components contributing to the magnetic moment would take on values so as to coincidentally line up the inertial moment with the magnetic moment. It is also rather strange that both retrograde planets, just "coincidentally" are in a completely different distribution. What if anything explains these "coincidences"? PS: Upon further research I discovered this correlation is known as “[magnetic Bode’s law][1]”. The conventional explanation for the points on the line is that it is a spurious correlation. However, it sticks in my craw that the two retrograde planets, Venus and Mars, are not part of this “spurious” correlation. &[Wolfram Notebook][2] [1]: https://ned.ipac.caltech.edu/level5/March03/Vallee2/Vallee2_3.html [2]: https://www.wolframcloud.com/obj/99893646-d72f-4242-bf3d-3ebdc319cb85 James Bowery 2023-04-12T01:31:55Z https://community.wolfram.com/groups/-/m/t/2835102 Hi everyone, when you compute earth's mean anomaly from mathematica's astronomical data over a period of time it appears to move to fast: FromDMS /@ PlanetData["Earth", EntityProperty["Planet", "MeanAnomaly", {"Date" -> #}] & /@ {DateObject[{2023, 1, 1, 0, 0, 0}, TimeZone -> "Europe/London"], DateObject[{2024, 1, 1, 0, 0, 0}, TimeZone -> "Europe/London"]}] The result given is {356.374, 358.018} (angles modulo 360), and this amounts to an elliptic precession of 1.64396 degree per year. Earth should have that much in about a century. (There is nothing special about the dates chosen, the mean anomaly increases linearly as expected, but the slope is slightly too high.) Do I have some sort of misconception, or is there some trouble with the data? Yours, Bernd. Bernd Günther 2023-02-21T14:32:25Z https://community.wolfram.com/groups/-/m/t/2754928 The expression of Ricci rotation coefficient is mentioned below. I want to write a Mathematica program to calculate the Ricci rotation coefficients (or, so-called the Spin connections) in the Kerr or Schwarzschild spacetime. Can anyone help me to write the program? ![enter image description here][1] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshotfrom2023-01-0222-07-09.png&userId=2271980 Chandrachur Chakraborty 2023-01-02T16:50:05Z https://community.wolfram.com/groups/-/m/t/2752609 I found this set of sentences in the Wikipedia article on the [Celestial Sphere][1]: The celestial sphere can thus be thought of as a kind of astronomical shorthand, and is applied very frequently by astronomers. For instance, the Astronomical Almanac for 2010 lists the apparent geocentric position of the Moon on January 1 at 00:00:00.00 Terrestrial Time, in equatorial coordinates, as right ascension 6h 57m 48.86s, declination +23° 30' 05.5". Implied in this position is that it is as projected onto the celestial sphere; any observer at any location looking in that direction would see the "geocentric Moon" in the same place against the stars. For many rough uses (e.g. calculating an approximate phase of the Moon), this position, as seen from the Earth's center, is adequate. I am wondering how to verify this statement with Mathematica's date and time functionality. I have the following code: AstroPosition[ Entity["PlanetaryMoon", "Moon"], {"Equatorial", "Date" -> DateObject[{2010, 1, 1, 0, 0, 0.`}, "Instant", "Gregorian", 0.`, "TT"]}] I have an output that is not precise enough to compare to the right ascension of 6 hours, 57 minutes, and 48.86 seconds. I have 6 hours and 57 minutes and 48.9 seconds, which 48.86 seconds could be rounded to but I am wondering how to show more details about the data in an equatorial coordinate system. Here are some other things I tried to see the right ascension more precisely: This code returns cartesian coordinates with the unit of astronomical units, which is not what I AstroPosition[ Entity["PlanetaryMoon", "Moon"], {"Equatorial", "Date" -> DateObject[{2010, 1, 1, 0, 0, 0.`}, "Instant", "Gregorian", 0.`, "TT"]}]["Data"] I tried using FullForm to display the full number but it stores it as an XYZ FullForm[ AstroPosition[ Entity["PlanetaryMoon", "Moon"], {"Equatorial", "Date" -> DateObject[{2010, 1, 1, 0, 0, 0.`}, "Instant", "Gregorian", 0.`, "TT"]}]] list not a number. How can I see the extended precision for the right ascension? [1]: https://en.wikipedia.org/wiki/Celestial_sphere Peter Burbery 2022-12-29T14:57:57Z https://community.wolfram.com/groups/-/m/t/2741272 “[A First Look at Cepheids in a Type Ia Supernova Host with JWST][1]” may have just killed the CMBR H0. Mathematica returns the (lambdaCDM) theory-dependent CMBR H0 of 68 km/(Mpc s) and doesn’t provide the more-directly *empirical* distance ladder H0 that JWST now appears to have sided with in the so-called [Hubble Tension][2]. &[Wolfram Notebook][3] [1]: https://iopscience.iop.org/article/10.3847/2041-8213/ac9b27/pdf [2]: https://en.wikipedia.org/wiki/Hubble%27s_law#Hubble_tension [3]: https://www.wolframcloud.com/obj/f73f55fa-5a9c-4684-92b4-e7a4cb6b4c7f James Bowery 2022-12-23T23:56:29Z https://community.wolfram.com/groups/-/m/t/2744556 New to Mathematica and looking to get my feet wet in both the graphics and computational aspects. I see the AstroPosition function in 13.2 and haven't dabbled in astronomy for decades. Does Mathematica have a heliocentric version of the planetary position functions? Ideally, for a given date, I would like to display a 3d graphic with scroll bars. It will plot out the 8 planets (plus Pluto) and their current position with the center of the Sun represented as [0,0,0]. Any guidance would be greatly appreciated. Best of the season to you and yours. Art Cashin 2022-12-23T20:12:31Z https://community.wolfram.com/groups/-/m/t/2735722 I installed the newest version of Mathematica (13.2) on my Mac, and I was trying out AstroPosition, the first example from Stephen Wolfram's version announcement blog post. But when I type AstroPosition["Mars"] it chugs along for a while, and then returns a message "Cannot initialize ephemeris information". Bruce Bartlett 2022-12-18T13:21:26Z https://community.wolfram.com/groups/-/m/t/2709922 I have a question I came up with that I would like to answer. What is the radius of all the planets who have at least one moon with a density that is greater than or equal to 0.55 times the density of Earth's moon? I have computed a dataset but I don't know how to filter with SortBy. For example the following code gives the number of moons Jupiter has that exeeds or equals Earth's moons density times 0.55 planets["Jupiter", "Moons", Length@*Select[#Mass/(4/3 \[Pi] #Radius^3) > 0.55 (planets["Earth", "Moons", Values, #Mass/(4/3 \[Pi] #Radius^3) &] // Normal // First) &]] I can also compute this for all planets with planets[All, "Moons", Length@*Select[#Mass/(4/3 \[Pi] #Radius^3) > 0.55 (planets["Earth", "Moons", Values, #Mass/(4/3 \[Pi] #Radius^3) &] // Normal // First) &]] I tried the following code but it returned an empty list. It should return Earth, Mars, Jupiter, Saturn, and Neptune. planets[Select[ planets[#, "Moons", Length@*Select[#Mass/(4/3 \[Pi] #Radius^3) > 0.55 (planets["Earth", "Moons", Values, #Mass/(4/3 \[Pi] #Radius^3) &] // Normal // First) &]] >= 1 &], "Mass"] How can I finish my complex query? I am using ExampleData[{"Dataset", "Planets"}] Peter Burbery 2022-11-25T21:53:40Z https://community.wolfram.com/groups/-/m/t/2514874 I have a list of astronomical objects that I need to sort by distance from Earth: {Alpha Centauri, Andromeda Galaxy, Antennae Galaxy, Eagle Nebula, Jupiter, Moon, Orion Nebula, Pleiades Star Cluster, Pluto, Ring Nebula, Sombrero Galaxy, Sun} Entering "distance *{list}*" returns a table of distances in different units, and using the Sort and SortBy functions with distance will only interpret one or two items from the list. Is there a way to sort these distances, or at least force all the distances to the same unit? Owen Lieberman 2022-04-20T13:16:41Z