Kinjal Banerjee
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Kinjal Banerjee has a total of 35 co-authors. Here are the top co-authors by number of shared publications:
- Rudranil Basu
Department of Physics Birla Institute of Technology and Science Pilani 403726 Zuarinagar Goa India
6 shared publications - Aditya Sharma
Department of Physics BITS-Pilani K K
5 shared publications - Aditya Mehra
School of Basic and Applied Sciences, JSPM University
4 shared publications Ghanashyam Date
Institute of Mathematical Sciences Chennai
4 shared publications- Tuhin Malik
Universidade de Coimbra
4 shared publications - Yongge Ma
Beijing Normal University
4 shared publications
Latest Publications
- 27 October 2025
- Published by IOP Publishing in Classical and Quantum Gravity
- Vol. 42 (21) , 215009
Asymptotic symmetries at spatial infinity
We describe asymptotic symmetries at spatial infinity of asymptotically flat spacetimes within the context of a generalization of the Beig–Schmidt–Ashtekar–Romano-framework. We demonstrate that it is possible to relax certain smoothness requirements of the asymptotic transformations considered previously, without violating asymptotic flatness. This leads to an enhancement of the asymptotic symmetry group that includes logarithmic supertranslations at spatial infinity. Our results compliment several recent results which confirm the existence of logarithmic supertranslations at spatial infinity in the Hamiltonian formalism.
- 27 October 2025
- Published by IOP Publishing in Classical and Quantum Gravity
- Vol. 42 (21) , 215009
Asymptotic symmetries at spatial infinity
We describe asymptotic symmetries at spatial infinity of asymptotically flat spacetimes within the context of a generalization of the Beig–Schmidt–Ashtekar–Romano-framework. We demonstrate that it is possible to relax certain smoothness requirements of the asymptotic transformations considered previously, without violating asymptotic flatness. This leads to an enhancement of the asymptotic symmetry group that includes logarithmic supertranslations at spatial infinity. Our results compliment several recent results which confirm the existence of logarithmic supertranslations at spatial infinity in the Hamiltonian formalism.
- 1 November 2024
- Published by IOP Publishing in Journal of Cosmology and Astroparticle Physics
- Vol. 2024 (11)
Constructing viable interacting dark matter and dark energy models: a dynamical systems approach
We study the evolution of k = -1 FLRW cosmological models for two interacting Dark Matter-Dark Energy Models using dynamical system analysis. Since we are interested in late time evolution, the sign of the interaction term is chosen such that it facilitates the transfer of energy from dark matter to dark energy. We also explore the k = 0 invariant subspace of these models. We find that both these models have sectors which have a stable fixed point where we can recover an accelerating universe with a negative equation of state. This indicates these can be viable models for our universe. We also rule out certain sectors of these models because they do not give the correct late time observational features. We observe that although we start with a dust-like Dark Matter, its effective equation of state evolves due to its interaction with Dark Energy. As a result, the Dark Matter can display features of stiff matter and exotic matter in the course of evolution.
- 1 November 2024
- Published by IOP Publishing in Journal of Cosmology and Astroparticle Physics
- Vol. 2024 (11)
Constructing viable interacting dark matter and dark energy models: a dynamical systems approach
We study the evolution of k = -1 FLRW cosmological models for two interacting Dark Matter-Dark Energy Models using dynamical system analysis. Since we are interested in late time evolution, the sign of the interaction term is chosen such that it facilitates the transfer of energy from dark matter to dark energy. We also explore the k = 0 invariant subspace of these models. We find that both these models have sectors which have a stable fixed point where we can recover an accelerating universe with a negative equation of state. This indicates these can be viable models for our universe. We also rule out certain sectors of these models because they do not give the correct late time observational features. We observe that although we start with a dust-like Dark Matter, its effective equation of state evolves due to its interaction with Dark Energy. As a result, the Dark Matter can display features of stiff matter and exotic matter in the course of evolution.
- Open Access
Constructing Viable Interacting Dark Matter and Dark Energy Models: A Dynamical Systems Approach
We study the evolution of $k=-1$ FLRW cosmological models for two interacting Dark Matter-Dark Energy Models using dynamical system analysis. Since we are interested in late time evolution, the sign of the interaction term is chosen such that it facilitates the transfer of energy from dark matter to dark energy. We also explore the $k=0$ invariant subspace of these models. We find that both these models have sectors which have a stable fixed point where we can recover an accelerating universe with a negative equation of state. This indicates these can be viable models for our universe. We also rule out certain sectors of these models because they do not give the correct late time observational features. We observe that although we start with a dust-like Dark Matter, its effective equation of state evolves due to its interaction with Dark Energy. As a result, the Dark Matter can display features of stiff matter and exotic matter in the course of evolution.Open AccessConstructing Viable Interacting Dark Matter and Dark Energy Models: A Dynamical Systems Approach
We study the evolution of $k=-1$ FLRW cosmological models for two interacting Dark Matter-Dark Energy Models using dynamical system analysis. Since we are interested in late time evolution, the sign of the interaction term is chosen such that it facilitates the transfer of energy from dark matter to dark energy. We also explore the $k=0$ invariant subspace of these models. We find that both these models have sectors which have a stable fixed point where we can recover an accelerating universe with a negative equation of state. This indicates these can be viable models for our universe. We also rule out certain sectors of these models because they do not give the correct late time observational features. We observe that although we start with a dust-like Dark Matter, its effective equation of state evolves due to its interaction with Dark Energy. As a result, the Dark Matter can display features of stiff matter and exotic matter in the course of evolution. - Open Access
Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density ($\rho_0$) has led to the emergence of a multitude of models based on different assumptions and techniques. These EoSs, when used to describe a neutron star (NS), lead to differing values of observables. An outstanding goal in astrophysics is to constrain the dense matter EoS by exploiting astrophysical and gravitational wave measurements. Nuclear matter parameters appear as Taylor coefficients in the expansion of the EoS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically-motivated representation of the EoS. In this paper, we introduce a deep learning-based methodology to predict key neutron stars observables such as the NS mass, NS radius, and tidal deformability from a set of nuclear matter parameters. Using generated mock data, we confirm that the neural network model is able to accurately capture the underlying physics of finite nuclei and replicate inter-correlations between the symmetry energy slope, its curvature, and the tidal deformability arising from a set of physical constraints. We also test our network with mock data generated by a different class of physics model, which was not part of the training, to explore the limitations of model dependency in the results. We also study the validity of our trained model using Bayesian inference and show that the performance of our model is on par with physics-based models with the added benefit of much lower computational cost.
Open AccessRealizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density ($\rho_0$) has led to the emergence of a multitude of models based on different assumptions and techniques. These EoSs, when used to describe a neutron star (NS), lead to differing values of observables. An outstanding goal in astrophysics is to constrain the dense matter EoS by exploiting astrophysical and gravitational wave measurements. Nuclear matter parameters appear as Taylor coefficients in the expansion of the EoS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically-motivated representation of the EoS. In this paper, we introduce a deep learning-based methodology to predict key neutron stars observables such as the NS mass, NS radius, and tidal deformability from a set of nuclear matter parameters. Using generated mock data, we confirm that the neural network model is able to accurately capture the underlying physics of finite nuclei and replicate inter-correlations between the symmetry energy slope, its curvature, and the tidal deformability arising from a set of physical constraints. We also test our network with mock data generated by a different class of physics model, which was not part of the training, to explore the limitations of model dependency in the results. We also study the validity of our trained model using Bayesian inference and show that the performance of our model is on par with physics-based models with the added benefit of much lower computational cost.
- Open Access
One-Loop Quantum Effects in Carroll Scalars
Carrollian field theories at the classical level possess an infinite number of space-time symmetries, namely the supertranslations. In this article, we inquire whether these symmetries for interacting Carrollian scalar field theory survive in the presence of quantum effects. For interactions polynomial in the field, the answer is in the affirmative. We also study a renormalization group flow particularly tailored to respect the manifest Carroll invariance and analyze the consequences of introducing Carroll-breaking deformations. The renormalization group flow, with perturbative loop-level effects taken into account, indicates a new fixed point apart from the Gaussian ones.
Open AccessOne-Loop Quantum Effects in Carroll Scalars
Carrollian field theories at the classical level possess an infinite number of space-time symmetries, namely the supertranslations. In this article, we inquire whether these symmetries for interacting Carrollian scalar field theory survive in the presence of quantum effects. For interactions polynomial in the field, the answer is in the affirmative. We also study a renormalization group flow particularly tailored to respect the manifest Carroll invariance and analyze the consequences of introducing Carroll-breaking deformations. The renormalization group flow, with perturbative loop-level effects taken into account, indicates a new fixed point apart from the Gaussian ones.
- Top Cited PapersOpen Access
- 26 October 2023
- Published by American Physical Society (APS) in Physical Review D
- Vol. 108 (8) , 085022
One-loop quantum effects in Carroll scalars
Carrollian field theories at the classical level possess an infinite number of space-time symmetries, namely the supertranslations. In this article, we inquire whether these symmetries for interacting Carrollian scalar field theory survive in the presence of quantum effects. For interactions polynomial in the field, the answer is in the affirmative. We also study a renormalization group flow particularly tailored to respect the manifest Carroll invariance and analyze the consequences of introducing Carroll-breaking deformations. The renormalization group flow, with perturbative loop-level effects taken into account, indicates a new fixed point apart from the Gaussian ones.
- 26 October 2023
- Published by American Physical Society (APS) in Physical Review D
- Vol. 108 (8) , 085022
Top Cited PapersOpen AccessOne-loop quantum effects in Carroll scalars
Carrollian field theories at the classical level possess an infinite number of space-time symmetries, namely the supertranslations. In this article, we inquire whether these symmetries for interacting Carrollian scalar field theory survive in the presence of quantum effects. For interactions polynomial in the field, the answer is in the affirmative. We also study a renormalization group flow particularly tailored to respect the manifest Carroll invariance and analyze the consequences of introducing Carroll-breaking deformations. The renormalization group flow, with perturbative loop-level effects taken into account, indicates a new fixed point apart from the Gaussian ones.
- 26 September 2023
- Published by American Physical Society (APS) in Physical Review D
- Vol. 108 (6) , 063028
Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
The difficulty in describing the equation of state (EOS) for nuclear matter at densities above the saturation density () has led to the emergence of a multitude of models based on different assumptions and techniques. These equations of state, when used to describe a neutron star (NS), lead to differing values of observables. An outstanding goal in astrophysics is to constrain the dense matter EOS by exploiting astrophysical and gravitational wave measurements. Nuclear matter parameters appear as Taylor coefficients in the expansion of the EOS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically motivated representation of the EOS. In this paper, we introduce a deep learning-based methodology to predict key neutron stars observables such as the NS mass, NS radius, and tidal deformability from a set of nuclear matter parameters. Using generated mock data, we confirm that the neural network model is able to accurately capture the underlying physics of finite nuclei and replicate intercorrelations between the symmetry energy slope, its curvature, and the tidal deformability arising from a set of physical constraints. We also test our network with mock data generated by a different class of physics model, which was not part of the training, to explore the limitations of model dependency in the results. We also study the validity of our trained model using Bayesian inference and show that the performance of our model is on par with physics-based models with the added benefit of much lower computational cost.- 26 September 2023
- Published by American Physical Society (APS) in Physical Review D
- Vol. 108 (6) , 063028
Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
The difficulty in describing the equation of state (EOS) for nuclear matter at densities above the saturation density () has led to the emergence of a multitude of models based on different assumptions and techniques. These equations of state, when used to describe a neutron star (NS), lead to differing values of observables. An outstanding goal in astrophysics is to constrain the dense matter EOS by exploiting astrophysical and gravitational wave measurements. Nuclear matter parameters appear as Taylor coefficients in the expansion of the EOS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically motivated representation of the EOS. In this paper, we introduce a deep learning-based methodology to predict key neutron stars observables such as the NS mass, NS radius, and tidal deformability from a set of nuclear matter parameters. Using generated mock data, we confirm that the neural network model is able to accurately capture the underlying physics of finite nuclei and replicate intercorrelations between the symmetry energy slope, its curvature, and the tidal deformability arising from a set of physical constraints. We also test our network with mock data generated by a different class of physics model, which was not part of the training, to explore the limitations of model dependency in the results. We also study the validity of our trained model using Bayesian inference and show that the performance of our model is on par with physics-based models with the added benefit of much lower computational cost.- 15 September 2022
- Published by American Physical Society (APS) in Physical Review D
- Vol. 106 (6) , 063518
Approaching de Sitter spacetimes via a Kerr-Schild relation
Spatially homogeneous cosmological spacetimes evolving in the presence of a positive cosmological constant and matter satisfying some reasonable energy conditions, typically approach the de Sitter geometry asymptotically (at least locally). In this work, we propose an alternative way to characterize this phenomena. We focus on a subset of such models admitting a generalized Kerr-Schild representation. We argue that the functions which define such a representation can be chosen, such that, their asymptotic behavior makes the evolution toward the de Sitter spacetime manifest through the representation. We verify our claim for the Kantowski-Sachs family of cosmological spacetimes.
- 15 September 2022
- Published by American Physical Society (APS) in Physical Review D
- Vol. 106 (6) , 063518
Approaching de Sitter spacetimes via a Kerr-Schild relation
Spatially homogeneous cosmological spacetimes evolving in the presence of a positive cosmological constant and matter satisfying some reasonable energy conditions, typically approach the de Sitter geometry asymptotically (at least locally). In this work, we propose an alternative way to characterize this phenomena. We focus on a subset of such models admitting a generalized Kerr-Schild representation. We argue that the functions which define such a representation can be chosen, such that, their asymptotic behavior makes the evolution toward the de Sitter spacetime manifest through the representation. We verify our claim for the Kantowski-Sachs family of cosmological spacetimes.
- Open Access
Quantization of Interacting Galilean Field theories
We present the quantum field description of Galilean electrodynamics minimally coupled to massless Galilean fermion in (3 + 1) dimensions. At the classical level, the Lagrangian is obtained as a null reduction of a relativistic theory in one higher dimension. We use functional techniques to develop the quantum field description of the theory. Quantum corrections to the propagators and vertex are obtained upto first order and the theory is found to be renormalizable to this order. The beta function of the theory is found to grow linearly; the theory is not asymptotically free.
Open AccessQuantization of Interacting Galilean Field theories
We present the quantum field description of Galilean electrodynamics minimally coupled to massless Galilean fermion in (3 + 1) dimensions. At the classical level, the Lagrangian is obtained as a null reduction of a relativistic theory in one higher dimension. We use functional techniques to develop the quantum field description of the theory. Quantum corrections to the propagators and vertex are obtained upto first order and the theory is found to be renormalizable to this order. The beta function of the theory is found to grow linearly; the theory is not asymptotically free.
- Open Access
- 4 August 2022
- Published by Springer Nature in Journal of High Energy Physics
- Vol. 2022 (8) , 1-21
Quantization of interacting Galilean field theories
We present the quantum field description of Galilean electrodynamics minimally coupled to massless Galilean fermion in (3 + 1)-dimensions. At classical level, the Lagrangian is obtained as a null reduction of a relativistic theory in one higher dimension. We use functional techniques to develop the quantum field description of the theory. Quantum corrections to the propagators and vertex are obtained upto first order and the theory is found to be renormalizable to this order. The beta function of the theory is found to grow linearly; the theory is not asymptotically free.
- 4 August 2022
- Published by Springer Nature in Journal of High Energy Physics
- Vol. 2022 (8) , 1-21
Open AccessQuantization of interacting Galilean field theories
We present the quantum field description of Galilean electrodynamics minimally coupled to massless Galilean fermion in (3 + 1)-dimensions. At classical level, the Lagrangian is obtained as a null reduction of a relativistic theory in one higher dimension. We use functional techniques to develop the quantum field description of the theory. Quantum corrections to the propagators and vertex are obtained upto first order and the theory is found to be renormalizable to this order. The beta function of the theory is found to grow linearly; the theory is not asymptotically free.