4462 papers
Hep-Th, or high-energy theoretical physics, explores the fundamental building blocks of our universe and the forces that govern them. Researchers in this field use complex mathematics to understand everything from subatomic particles to the behavior of black holes, often pushing the boundaries of what we know about space and time.
At Gist.Science, we monitor the arXiv repository to ensure you stay ahead of the curve in this rapidly evolving discipline. For every new preprint uploaded to arXiv under this category, our team generates both accessible plain-language overviews and detailed technical summaries, making cutting-edge research understandable regardless of your background.
Below are the latest papers in high-energy theoretical physics, curated to help you navigate the most significant recent discoveries.
This paper develops a novel framework for constructing quantum many-body scar states in bipartite systems with perfectly correlated Hamiltonians, demonstrating that initializing such systems in a purification of a generic equilibrium state leads to universal finite-time revivals, a phenomenon analytically and numerically validated using the double-scaled SYK model.
This paper introduces the "Log-Kernel" neural network architecture that enforces local conformal symmetry to realize Virasoro and super-Virasoro algebras, analytically deriving the algebra from neural statistics and numerically validating the emergence of the expected central charge and scaling dimensions.
This paper demonstrates that the two-dimensional nonlinear sigma model possesses a generic complex conformal field theory fixed point in the complex coupling plane, which is numerically confirmed in non-Hermitian Heisenberg spin chains and can be realized through engineered dissipation to prepare long-range entangled states.
This paper proposes a Lorentz-symmetry-breaking Euler-Heisenberg pseudo-electrodynamics model in 1+2 dimensions by integrating out fermions and adding a Chern-Simons term, demonstrating that birefringence in a planar medium arises exclusively under a uniform electric background field.
This paper investigates the impact of a circularly polarized laser field on top quark decay within the type-I two Higgs doublet model, demonstrating that specific laser parameters can significantly enhance the branching ratio of the channel to 0.97, thereby surpassing the standard decay and offering a promising strategy for detecting charged Higgs bosons.
This paper extends the Koopman-von Neumann-Sudarshan Hilbert space formulation to relativistic QCD, demonstrating that the covariant Wigner operator is fundamentally a quantum probability amplitude projected onto phase space, thereby offering a unified framework that clarifies the origin of nonclassical features like negativity and establishes a transparent foundation for parton distribution functions.
This paper presents a static, spherically symmetric black hole solution embedded in a Plummer dark matter halo and a Letelier cloud of strings, systematically analyzing its geometric properties, shadow, deflection angle, scalar perturbations, and thermodynamics to demonstrate that the string-cloud tension parameter drives leading-order modifications to all observables while the dark matter halo density provides only subdominant corrections.
This paper utilizes a new symplectic structure formula in open string field theory to demonstrate that the energy of a D-brane with constant electric flux, calculated via a generalized Ellwood invariant, is consistent with the result derived from the Dirac-Born-Infeld action.
This paper employs machine-learning-style optimization, featuring a novel singular-value-based optimizer and uncertainty estimation, to numerically explore the landscape of two-dimensional conformal field theories with central charges between 1 and 8/7, identifying candidate spectra in a previously uncharted region and suggesting a tighter constraint on the spectral gap near .
The paper introduces Sven, a computationally efficient natural gradient optimization algorithm that utilizes a truncated singular value decomposition of the loss Jacobian to simultaneously satisfy individual data point residuals, offering faster convergence and lower final loss than standard first-order methods on regression tasks while scaling linearly with the number of retained singular directions rather than quadratically with the number of parameters.