Differentiable Physics: A Position Piece
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Abstract (arXiv)
Differentiable physics provides a new approach for modeling and understanding the physical systems by pairing the new technology of differentiable programming with classical numerical methods for physical simulation. We survey the rapidly growing literature of differentiable physics techniques and highlight methods for parameter estimation, learning representations, solving differential equations, and developing what we call scientific foundation models using data and inductive priors. We argue that differentiable physics offers a new paradigm for modeling physical phenomena by combining classical analytic solutions with numerical methodology using the bridge of differentiable programming.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 57 of its 123 references that are in the map. First posted on arXiv 14 Sep 2021.
Builds on
57 of 123 references.
References · 57
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38 more
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50 most cited of 57 All 57 (JSON)
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Citing papers per year: 2022: 2; 2023: 1; 2024: 6; 2025: 1; 2026: 2.
12 papers.
- 2024Scaling physics-informed hard constraints with mixture-of-expertscited by 24
- 2022Differentiable physics-enabled closure modeling for Burgers' turbulencecited by 7
- 2024What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learningcited by 5
- 2023Open Source Infrastructure for Differentiable Density Functional Theorycited by 1
- 2024Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equationscited by 1
- 2022Differentiable Physics-based Greenhouse Simulationcited by 0
- 2024Open-Source Fermionic Neural Networks with Ionic Charge Initializationcited by 0
- 2024Open source Differentiable ODE Solving Infrastructurecited by 0
- 2024Finding the Underlying Viscoelastic Constitutive Equation via Universal Differential Equations and Differentiable Physicscited by 0
- 2025Learning second-order TVD flux limiters using differentiable solverscited by 0
- 2026Integrating Mechanistic and Data-Driven Models for Neurological Disorders through Differentiable Programmingcited by 0
- 2026Wall Shear Stress Reconstruction from Concentration: Differentiable Physics and Physics-Informed Neural Networkscited by 0
- 2026Wall Shear Stress Reconstruction from Concentration: Differentiable Physics and Physics-Informed Neural Networks4 Jun 2026
- 2026Integrating Mechanistic and Data-Driven Models for Neurological Disorders through Differentiable Programming4 Jun 2026
- 2025Learning second-order TVD flux limiters using differentiable solvers11 Mar 2025
- 2024Finding the Underlying Viscoelastic Constitutive Equation via Universal Differential Equations and Differentiable Physics31 Dec 2024
- 2024Open source Differentiable ODE Solving Infrastructure29 Nov 2024
- 2024What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning22 Nov 2024
- 2024Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equations1 Nov 2024
- 2024Scaling physics-informed hard constraints with mixture-of-experts20 Feb 2024
- 2024Open-Source Fermionic Neural Networks with Ionic Charge Initialization16 Jan 2024
- 2023Open Source Infrastructure for Differentiable Density Functional Theory27 Sep 2023
- 2022Differentiable Physics-based Greenhouse Simulation21 Nov 2022
- 2022Differentiable physics-enabled closure modeling for Burgers' turbulence23 Sep 2022