PhysMaster

MCTS-based autonomous physics problem solver with arXiv search, prior knowledge retrieval, and multi-agent reasoning. Use when you need to solve physics problems, search arXiv for relevant papers, or generate structured physics solutions with iterative refinement.

Use when solving problems involving Maxwell's equations, electrostatics, magnetostatics, electromagnetic waves, radiation, or relativistic electrodynamics.

Use when applying conservation of energy, momentum, angular momentum, charge, or other conserved quantities to constrain or solve a physical system.

Use when checking dimensional consistency, estimating physical scales, or deriving functional forms via the Buckingham Pi theorem.

Use when decomposing signals or fields into frequency/momentum components, applying Fourier transforms, or using spectral methods to solve differential equations.

Use when solving ordinary or partial differential equations numerically, including choosing integrators, discretization schemes, and stability analysis.

Use when solving a problem by expanding around a known solution in a small parameter, including regular and singular perturbation theory.

Use when solving quantum mechanical problems including the Schrodinger equation, angular momentum coupling, scattering theory, or many-body quantum systems.

Use when propagating uncertainties, performing error analysis, fitting data with error bars, or assessing statistical significance of physical measurements.

Use when identifying symmetries of a physical system, applying group theory, classifying representations, or deriving selection rules.

Use when computing partition functions, thermodynamic potentials, phase transitions, equations of state, or ensemble averages.

Use when applying variational principles such as Lagrangian/Hamiltonian mechanics, the Rayleigh-Ritz method, or variational estimation of ground-state energies.

Use when relating quasi-observables at finite hadron momentum to light-cone quantities using leading-power LaMET asymptotic expansion.