Box4D – 4D physics demo using Rust and wgpu

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This is a little physics toy I've been working on off and on for a while. I originally planned on making a more fully featured game of some sort (I suppose I still may some day), but it turns out that writing interesting graphics and physics algorithms is more compelling than the hard work of polishing an actual product. Who knew? While there are plenty of good guides for 2D and 3D graphics and physics, there's not much out there for 4D. In hopes of alleviating that, the code here is arranged such that the commits are more or less a step-by-step guide, with comments for the interesting or tricky parts. While I don't think I came close to the simplicity or clarity of Box2D Lite, I hope it can serve as a useful example to anyone interested in 4D rendering and physics.

Visit product View on Hacker NewsDec 23, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, code · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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