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Theoretical physicist Robbert Dijkgraaf explores how physicists are striving for the long-sought unification of quantum mechanics and general relativity, with string theory being a leading contender.
Explore integer-valued Gromov-Witten type invariants in symplectic geometry, focusing on genus zero cases for symplectic manifolds. Learn about recent developments and their applications in mathematical research.
Advocating for interpretable machine learning models in high-stakes decisions, highlighting their reliability and transparency compared to black box models with potentially misleading explanations.
Explore interpretable machine learning with a focus on decision trees, information theory, and analytical bounds. Gain insights into modern approaches and practical applications.
Explore interpretable machine learning with Cynthia Rudin, covering classification, natural language processing, and decision trees. Gain insights into model complexity and information theory applications.
Explore neutrino quantum kinetics in neutron star mergers, focusing on flavor transformation, radiation transport, and their impact on heavy element formation and kilonova observations.
Explore quantum entanglement's role in resolving spacetime puzzles, focusing on black holes and their connections to various physics fields. Four researchers present fascinating insights.
Explore ultralight dark matter theories, their exotic phenomena, and experimental tests across cosmic scales. Delve into composite models and their observables, connecting to early dark energy and the Hubble tension.
Explore singularity formation in reduced fluid equation models, focusing on electron magnetohydrodynamics and its connection to Euler equations. Gain insights into nonlinear dynamics and finite-time singularities.
Exploration of categorical local Langlands correspondence, discussing recent progress, proofs, and implications for number theory and algebraic geometry.
Explore the intersection of pure mathematics and machine learning through the lens of combinatorial invariance, featuring insights on neural networks and their application to mathematical conjectures.
Explore a unified framework for proving mixing bounds in Markov chains, connecting Spectral Independence and Stochastic Localization techniques through the concept of localization schemes.
Explore random matrix models, focusing on the Gaussian Unitary Ensemble and its applications to gravity, holography, and quantum physics. Discover new insights into discrete spectra and non-perturbative information.
Explore crystalline cohomology and the de Rham-Witt complex in algebraic geometry, with insights on alternative constructions and applications in positive characteristic fields.
Explore gauge theory scattering amplitudes as chiral algebra correlators, connecting to celestial holography and deriving expressions for form factors using innovative mathematical approaches.
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