PhysSandbox
Classical MechanicsWaves & SoundElectricity & MagnetismOptics & LightGravity & OrbitsLabs
🌙Astronomy & The Sky🌡️Thermodynamics🌍Biophysics, Fluids & Geoscience📐Math Visualization🔧Engineering🧪Chemistry

More from Classical Mechanics

Other simulators in this category — or see all 85.

View category →
NewUniversity / research

Poincaré Section (Double Pendulum)

(θ₁, ω₁) when sin θ₂ crosses 0 with ω₂>0; RK4, chaotic return map.

Launch Simulator
NewSchool

Catenary Cable

Uniform chain between level anchors: y ∝ cosh(x/a); sag, arc length, tension directions.

Launch Simulator
NewSchool

Magnus Effect (Ball)

Same v₀ and θ with vs without spin: toy a = (kωv_y, −g − kωv_x); range comparison.

Launch Simulator
NewSchool

Fluid Surface (Accel / Spin)

Linear tank: tan α = a/g; rotating bucket: paraboloid sketch vs rpm.

Launch Simulator
NewUniversity / research

Water Hammer (1D)

Linearized P,V waves; valve closes; Joukowsky ΔP ≈ ρaV hint.

Launch Simulator
NewSchool

Foucault Pendulum (Sketch)

Ω_eff = Ω_E sin|λ| with time scale; top view rotating swing line.

Launch Simulator
PhysSandbox

Interactive physics, chemistry, and engineering simulators for students, teachers, and curious minds.

Physics

  • Classical Mechanics
  • Waves & Sound
  • Electricity & Magnetism

Science

  • Optics & Light
  • Gravity & Orbits
  • Astronomy & The Sky

More

  • Thermodynamics
  • Biophysics, Fluids & Geoscience
  • Math Visualization
  • Engineering
  • Chemistry

© 2026 PhysSandbox. Free interactive science simulators.

PrivacyTermsContact
Home/Classical Mechanics/Particle Life

Particle Life

Particle Life explores a simplified model of emergent collective behavior based on pairwise forces. It simulates a population of particles moving on a two-dimensional toroidal surface, where each particle is assigned one of six types. The core physics is governed by a custom force matrix that defines an attractive or repulsive interaction strength between every pair of types. This creates a synthetic, non-conservative force field where particles experience a net force calculated by summing contributions from all nearby particles according to their type-pair value. The simulation integrates Newton's second law of motion (F=ma) to update particle velocities and positions, while incorporating a velocity damping term to approximate viscous drag and prevent energy divergence. Key simplifications include the absence of explicit potentials (like Lennard-Jones), the use of a distance cutoff for forces, and the toroidal boundary conditions which eliminate edges. By interacting with the presets—which yield clusters, linear 'worms', or gaseous foams—students learn how complex, lifelike structures can emerge from simple local rules. This connects to principles in statistical mechanics, self-organization, and agent-based modeling, illustrating how macroscopic order arises from microscopic interactions without centralized control.

Who it's for: Undergraduate students in physics, computer science, or complex systems exploring emergent phenomena and agent-based modeling, as well as educators teaching Newtonian mechanics and numerical integration.

Key terms

  • Newton's Second Law
  • Pairwise Forces
  • Toroidal Boundary Conditions
  • Emergent Behavior
  • Numerical Integration
  • Self-Organization
  • Agent-Based Model
  • Viscous Damping

Interaction

62 px
1.05
0.88

Six species, toroidal world, O(N²) demo. Change preset or gain and watch clusters, filaments, or churn.

Measured values

Particles280
Types6

How it works

A cousin of reaction–diffusion visually: structure from nothing but short-range attraction and repulsion between labels.

Frequently asked questions

Are the forces in this simulation conservative, like gravity or spring forces?
No. The forces are defined by an arbitrary matrix and are not derived from a potential energy function. This means energy is not conserved; it can be injected or dissipated by the force rules and the damping term. This is a deliberate simplification to explore a wider range of dynamical behaviors, unlike real-world closed physical systems.
Why does the simulation use a torus (wrapping edges) instead of a box with walls?
Toroidal boundaries eliminate edge effects, ensuring all particles have identical environmental conditions. This is common in computational physics to model bulk properties of infinite systems or to study intrinsic dynamics without boundary reflections, which can simplify the analysis of emergent patterns.
What real-world systems does this abstract model relate to?
While highly stylized, it shares conceptual links with models of flocking birds, cell sorting in biology, and phase separation in materials. It demonstrates how simple attraction/repulsion rules between different 'species' can lead to sorting, clustering, and pattern formation seen in complex systems.
How does the damping term affect the physics?
The damping term acts as a velocity-dependent drag force, analogous to moving through a viscous fluid. It continuously removes kinetic energy, preventing the system from heating up indefinitely due to the non-conservative forces. This allows the system to settle into stable, dynamic structures rather than becoming a chaotic gas.
Can I create any pattern I want by adjusting the force matrix?
Not arbitrarily. The matrix defines local interactions, but the global pattern that emerges is a nonlinear, collective outcome. Small changes can lead to qualitatively different structures (like shifting from clusters to filaments), demonstrating sensitivity and the challenge of inverse design in complex systems.