Zobrazeno 1 - 10
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pro vyhledávání: '"Rigas P"'
Autor:
Rigas, Pete
We study the emptiness formation probability, along with various representations for nonlocal correlation functions, of the 20-vertex model. In doing so, we leverage previous arguments for representations of nonlocal correlation functions for the 6-v
Externí odkaz:
http://arxiv.org/abs/2409.05309
Autor:
Rigas, Spyros, Papachristou, Michalis, Papadopoulos, Theofilos, Anagnostopoulos, Fotios, Alexandridis, Georgios
Physics-Informed Neural Networks (PINNs) have emerged as a robust framework for solving Partial Differential Equations (PDEs) by approximating their solutions via neural networks and imposing physics-based constraints on the loss function. Traditiona
Externí odkaz:
http://arxiv.org/abs/2407.17611
In this note, we examine voting on four major blockchain DAOs: Aave, Compound, Lido and Uniswap. Using data directly collected from the Ethereum blockchain, we examine voter activity. We find that in most votes, the "minimal quorum," i.e., the smalle
Externí odkaz:
http://arxiv.org/abs/2407.10945
Autor:
Rigas, Pete
We initiate a novel application of the quantum-inverse scattering method for the 20-vertex model, building upon seminal work from Faddeev and Takhtajan on the study of Hamiltonian systems, with applications to crossing probabilities, 3D Poisson struc
Externí odkaz:
http://arxiv.org/abs/2407.11066
Autor:
Rigas, Pete
We extend computations for the scaling limit of the prudent walk on the square lattice, due to Beffara, Friedli, and Velenik in 2010, to obtain the scaling limit of the prudent walk on the triangular lattice. In comparison to computing the probabilit
Externí odkaz:
http://arxiv.org/abs/2312.16236
Autor:
Rigas, Pete
We analyze optimal, and approximately optimal, quantum strategies for a variety of non-local XOR games. Building upon previous arguments due to Ostrev in 2016, which characterized approximately optimal, and optimal, strategies that players Alice and
Externí odkaz:
http://arxiv.org/abs/2311.12887
Many engineering applications rely on the evaluation of expensive, non-linear high-dimensional functions. In this paper, we propose the RONAALP algorithm (Reduced Order Nonlinear Approximation with Active Learning Procedure) to incrementally learn a
Externí odkaz:
http://arxiv.org/abs/2311.10550
Autor:
Rigas, Pete
We study open boundary conditions for the $D^{(2)}_3$ spin chain, which shares connections with the six-vertex model, under staggering, and also to the antiferromagnetic Potts model. By formulating a suitable transfer matrix, we obtain an integrable,
Externí odkaz:
http://arxiv.org/abs/2310.18499
Autor:
Rigas, Pete
We compute the action-angle variables for a Hamiltonian flow of the inhomogeneous six-vertex model, from a formulation introduced in a 2022 work due to Keating, Reshetikhin, and Sridhar, hence confirming a conjecture of the authors as to whether the
Externí odkaz:
http://arxiv.org/abs/2310.15181
The Koopman operator presents an attractive approach to achieve global linearization of nonlinear systems, making it a valuable method for simplifying the understanding of complex dynamics. While data-driven methodologies have exhibited promise in ap
Externí odkaz:
http://arxiv.org/abs/2310.10745