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Mohsen Gheisarieha

Publications and source records attributed to Mohsen Gheisarieha.

2 recordsLinked to original sources

Integrable Spherical Brane Model at Large $N$

We study one of the simplest integrable two-dimensional quantum field theories with a boundary: $N$ free non-compact scalars in the bulk, constrained non-linearly on the boundary to lie on an $(N-1)$-sphere of radius $1/\sqrt{g}$. The $N=1$ case reduces to the single-channel Kondo problem, for $N=2$ the model describes dissipative Coulomb charging in quantum dots, and larger $N$ is analogous to higher-spin impurity or multi-channel scenarios. Adding a boundary magnetic field -- a linear boundary coupling to the scalars -- enriches the model's structure while preserving integrability. Lukyanov and Zamolodchikov (2004) conjectured an expansion for the boundary free energy on the infinite half-cylinder in powers of the magnetic field. Using large-$N$ saddle-point techniques, we confirm their conjecture to next-to-leading order in $1/N$. Renormalization of the subleading solution turns out to be highly instructive, and we connect it to the RG running of $g$ studied by Giombi and Khanchandani (2020).

hep-th↗

On the Use of Context for Predicting Citation Worthiness of Sentences in Scholarly Articles

In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles. We formulate this problem as a sequence labeling task solved using a hierarchical BiLSTM model. We contribute a new benchmark dataset containing over two million sentences and their corresponding labels. We preserve the sentence order in this dataset and perform document-level train/test splits, which importantly allows incorporating contextual information in the modeling process. We evaluate the proposed approach on three benchmark datasets. Our results quantify the benefits of using context and contextual embeddings for citation worthiness. Lastly, through error analysis, we provide insights into cases where context plays an essential role in predicting citation worthiness.

cs.CL↗