Statistical Physics and Thermodynamics Physicist (PhD)

CritPt is a public benchmark of research-level physics challenges, built to test whether frontier AI models can carry out genuine physics research reasoning rather than textbook problem solving. The benchmark paper is [arXiv:2509.26574](https://arxiv.org/abs/2509.26574) and we recommend reading it before applying. It will tell you quickly whether this work interests you.

We are engaging physicists to work on research-level physics problems in their own subfield. Depending on where your publication record fits, that can mean creating problems, solving them, reviewing completed work, or auditing it. We agree the specific assignment with you once you are matched to an area.

This is research-grade work rather than volume work. Whatever you produce has to be complete enough for another specialist in your subfield to follow and verify independently, so written reasoning is part of every assignment.

Five areas. We match narrowly: you need to have published on one of these specific phenomena, not in statistical physics broadly. Each area lists the methods it requires.

1\. Disordered spin models and the Nishimori line, QEC thresholds, mixed-state topological order: Replicated random-bond Ising model, Nishimori line and gauge symmetry of disordered spin models, quenched disorder averaging, Kramers-Wannier duality and square-lattice self-duality, Ashkin-Teller coupled Ising flavors, domain-wall free energy from twisted boundary conditions, exact lattice evaluation of Ising partition functions, decoherence-induced mixed-state topological order and quantum memory thresholds.

2\. Entanglement entropy via the replica trick, Goldstone modes and tower of states: Replica trick, analytic continuation in the replica index, Gaussian lattice sums and theta functions, Poisson summation and modular transformations, Renyi and von Neumann entanglement entropies, Goldstone modes and tower-of-states structure.

3\. Range expansions with long-range dispersal, front propagation, heavy-tailed jumps: Long-range dispersal kernels, heavy-tailed jump processes, stratified diffusion and coalescing colony models, self-consistent mean-field growth equations, convolution integral equations, asymptotic expansions with logarithmic corrections, front propagation in range expansions.