8 papers
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…
On the completeness of contraction map proof method for holographic entropy inequalities
Ning Bao, Keiichiro Furuya, Joydeep Naskar
The paper proves that for any linear holographic entropy inequality with rational coefficients, the existence of a contraction map is not only sufficient but also necessary, by sho…
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…
Topological entanglement entropy meets holographic entropy inequalities
Joydeep Naskar, Sai Satyam Samal
Topological entanglement entropy (TEE) is an efficient way to detect topological order in the ground state of gapped Hamiltonians. The seminal work of Kitaev and Preskill~\cite{pre…
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 n…
Conformal Fields from Neural Networks
James Halverson, Joydeep Naskar, Jiahua Tian
We use the embedding formalism to construct conformal fields in dimensions, by restricting Lorentz-invariant ensembles of homogeneous neural networks in dimensions to t…