2548 papers
Mathematical physics sits at the fascinating intersection where abstract equations meet the fundamental laws of our universe. This field uses rigorous mathematical tools to model everything from the behavior of subatomic particles to the curvature of spacetime, turning complex theories into testable predictions. It is the language through which physicists describe reality, bridging the gap between pure mathematics and physical observation.
On Gist.Science, we process every new preprint published in this category on arXiv to make these dense studies accessible to everyone. Whether you are a specialist or a curious reader, you will find both plain-language overviews and detailed technical summaries for each paper. Below are the latest mathematical physics papers from arXiv, curated to help you explore the cutting edge of theoretical science.
This paper presents a novel construction of static, geometrically local Hamiltonians with provably volume-law entangled ground states and infinite-temperature eigenstate properties across their entire spectrum, achieved by adapting the Feynman-Kitaev clock with periodic boundary conditions and combining it with exactly solvable Floquet circuits that satisfy the eigenstate thermalization hypothesis.
This paper constructs the first explicit nontrivial example of a quantum integrable hierarchy from a cohomological field theory with fermionic fields by deriving a closed, modular expression for the Gromov-Witten theory of elliptic curves using intersection numbers of double ramification cycles and specific vanishing results for Hodge classes.
This paper presents a complete group-theoretical derivation of Nielsen's quantum complexity for unitaries in oscillator group representations by explicitly solving geodesic equations under right-invariant metrics and expressing the resulting complexity in terms of solutions to a transcendental equation.
This paper demonstrates that a formal deformation quantisation of degree-2 differential graded symplectic manifolds generates the complete classical kinematics and dynamics of NS-NS supergravity and double field theory, providing a unified algebraic framework that extends the tensor hierarchy, incorporates the dilaton via a graded Moyal–Weyl star product, and facilitates the construction of the DFT action.
This paper presents a machine-verified construction in Lean 4 of non-Gaussian functional integrals for finite bosonic modes using the Henstock–Kurzweil gauge integral and Chernoff product approximations, proving the finiteness and smoothness of these integrals without relying on Wick rotation or perturbative series, and demonstrating their applicability to diverse fields such as quantum mechanics, finance, and neuroscience.
This paper establishes a time-frequency framework for lattice GKP codes using modulation spaces and vector-valued Zak transforms to represent logical information via Gabor analysis, thereby proving isometric encoding, constructing stable normalizable approximants, and enabling robust syndrome recovery.
This paper introduces a phenomenological framework for fully-heavy tetraquark spectroscopy using a colour-Casimir adjacency matrix approach, which corrects the mass ordering flaws of previous Laplacian-based models and predicts an all-bottom ground state at 18.7–18.9 GeV while highlighting the necessity of long-range molecular dynamics to explain the under-binding of the state.
This paper establishes a probabilistic representation of particle numbers in locally interacting bosonic quasi-free states as an infinite sum of independent geometrically distributed variables, thereby deriving exponential tail bounds, limit theorems, and a detailed description of quantum depletion statistics in Bose-Einstein condensates.
This paper unifies Costello's extension of the AKSZ construction to non-topological theories and the presymplectic approach into a single general algebraic framework involving constrained DGCAs and degenerate presymplectic structures, which is then used to derive first-principles formulations for the Chalmers-Siegel model and self-dual higher-spin gauge theories.
This paper proposes conditioning denoising diffusion models on short windows of past observations to enable efficient, accurate data assimilation and direct observation prediction without the need for expensive retraining, demonstrating that this approach achieves minimal posterior error comparable to fully-cycled systems.