
Security News
Deno Goes the Way of the Dinosaur
Cloudflare is acquiring Deno’s team, which will provide another year of bug fixes and security updates before ending support for the runtime.
Aetheris Motion is a high-performance, physics-native animation framework for React. It utilizes a zero-reconciliation architecture designed to minimize the overhead associated with React's virtual DOM and render cycles. By leveraging a centralized requestAnimationFrame ticker and a stable Runge-Kutta (RK4) integrator, Aetheris achieves consistent 60fps+ motion even in high-density environments.
Traditional animation libraries often rely on state interpolation which triggers React re-renders for every frame. Aetheris bypasses this by updating DOM attributes directly via a specialized batching system. This physics-first approach ensures that motion properties such as mass, tension, and friction result in natural, organic movement that remains numerically stable across varying hardware capabilities.
Install via your preferred package manager:
npm install aetheris
# or
pnpm add aetheris
# or
yarn add aetheris
The following example demonstrates a basic implementation using the a.div proxy component. All motion is handled outside of the React render loop.
import React from "react";
import { MotionProvider, a } from "aetheris";
export default function App() {
return (
<MotionProvider>
<a.div
style={{
width: 200,
height: 200,
background: "#0070f3",
}}
/>
</MotionProvider>
);
}
The following table defines the core physics properties used by the Aetheris solver:
| Property | Type | Default | Description |
|---|---|---|---|
| mass | number | 1.0 | The inertia of the object. Higher values result in slower acceleration and deceleration. |
| tension | number | 170.0 | The stiffness of the spring. Higher values increase the natural frequency and snap. |
| friction | number | 26.0 | The damping coefficient. Higher values reduce overshoot and settle the object faster. |
| velocity | number | 0.0 | The initial velocity applied to the spring-solver. |
Full API documentation and advanced usage guides are available in the official repository.
This project is licensed under the MIT License.
See CONTRIBUTING.md for architectural mandates (zero-reconciliation) and testing requirements.
Aetheris operates on several foundational principles:
requestAnimationFrame loop that drives all motion subscribers, ensuring frame-perfect synchronization across the entire UI.will-change and hardware-accelerated transforms to ensure motion remains off-loaded to the GPU where possible.For architectural inquiries or implementation support, please refer to the documentation in the docs directory or open a technical issue.
© 2026 Aetheris Framework. MIT License.
aetheris/
├── src/
│ ├── core/ # The Engine: Ticker, Batcher, Physics Solver, MotionValue
│ ├── hooks/ # Reactive hooks (useAnimationFrame, useAetherisProps)
│ ├── text/ # Text-based animations (Scramble, Physics Split)
│ ├── backgrounds/ # GPU-accelerated field & mesh backgrounds
│ ├── hover/ # Reactive mouse-tracking effects
│ ├── scroll/ # Momentum-based scroll triggers
│ ├── buttons/ # Tactile & Particle-based interaction
│ ├── cards/ # 3D Depth & Parallax systems
│ └── cursor/ # Physics-based custom cursor followers
├── dist/ # Optimized production bundles (ESM/CJS)
└── examples/
└── playground/ # Interactive showcase & real-time prop editor
FAQs
A physics-native, high-performance motion framework for React.
We found that aetheris demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

Security News
Cloudflare is acquiring Deno’s team, which will provide another year of bug fixes and security updates before ending support for the runtime.

Security News
Anthropic’s free OSS Scanner uses Mythos and other Claude models to find open source vulnerabilities and send maintainers reports with proposed fixes.

Security News
On Front Lines’ Early Adopters: CISO podcast, Andrew Becherer shares lessons from Datadog, weighs the long-term costs of AI-built tools, and explains how founders can actually gain a CISO’s trust.