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20242026
most citedConformal Fields from Neural Networks

9 citations · 13 across the 7 of their papers we have counts for

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hep-th2026

Spinning Conformal Correlators from Neural Networks

Manas Dogra, James Halverson, Joydeep Naskar

We construct spinning conformal fields from neural networks and the embedding formalism, computing their two-, three- and four-point functions in examples, building on scalar confo…

hep-th2026

On a mixed-state extension of the holographic signal inequality

Joydeep Naskar

A novel inequality involving the residual entropy and genuine multi-entropy was proposed in \cite{Balasubramanian:2025hxg} for tripartite holographic pure states, using which it wa…

hep-th20251 cited

Tripartite Correlation Signal from Multipartite Entanglement of Purification

Ning Bao, Keiichiro Furuya, Joydeep Naskar

We propose a signal for genuine tripartite entanglement in finite-dimensional quantum systems and for holographic systems. We prove that is non-…

hep-th20252 cited

On the completeness of contraction map proof method for holographic entropy inequalities

Ning Bao, Keiichiro Furuya, Joydeep Naskar

The contraction map proof method is the commonly used method to prove holographic entropy inequalities. Existence of a contraction map corresponding to a holographic entropy inequa…

hep-th20241 cited

Revisiting holographic codes with fractal-like boundary erasures

Abhik Bhattacharjee, Joydeep Naskar

In this paper we investigate the code properties of holographic fractal geometries initiated in \cite{Pastawski:2016qrs}. We study reconstruction wedges in for black…

hep-th2024

Towards a complete classification of holographic entropy inequalities

Ning Bao, Keiichiro Furuya, Joydeep Naskar

We propose a deterministic method to find all holographic entropy inequalities that have corresponding contraction maps and argue the completeness of our method. We use a triality…