Triad second renormalization group
نویسندگان
چکیده
A bstract We propose a second renormalization group (SRG) in the triad representation of tensor networks. The SRG method improves two parts group, which are decomposition intermediate tensors and preparation isometries, taking influence environment into account. Every fundamental including is given as rank-3 tensor, computational cost proposed algorithm scales with $$ \mathcal{O} O ( χ 5 ) employing randomized SVD where bond dimension tensors. test this classical Ising model on dimensional square lattice, find that numerical results obtained good accuracy for fixed time.
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ژورنال
عنوان ژورنال: Journal of High Energy Physics
سال: 2022
ISSN: ['1127-2236', '1126-6708', '1029-8479']
DOI: https://doi.org/10.1007/jhep04(2022)121