Exploring the nexus of many-body theories through neural network techniques: the tangent model
In this paper, we present a physically informed neural network (NN) representation of the effective interactions associated with coupled-cluster downfolding models to describe chemical systems and processes. The NN representation not only allows us to evaluate the effective interactions efficiently...
Saved in:
| Main Authors: | Senwei Liang, Karol Kowalski, Chao Yang, Nicholas P Bauman |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
|
| Series: | Machine Learning: Science and Technology |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-2153/add78c |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Asymptotic approximations of complex order tangent, Tangent-Bernoulli and Tangent-Genocchi polynomials
by: Cristina B. Corcino, et al.
Published: (2024-12-01) -
Tangent cones, starshape and convexity
by: J. M. Borwein
Published: (1978-01-01) -
Effective many-body interactions in reduced-dimensionality spaces through neural network models
by: Senwei Liang, et al.
Published: (2024-12-01) -
Approximations of Apostol-Tangent Polynomials of Complex Order with Parameters a, b, and c
by: Cristina B. Corcino, et al.
Published: (2024-12-01) -
Decreasing property of ratio of two logarithmic expressions involving tangent function
by: Feng Qi, et al.
Published: (2025-12-01)