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Researcher profile

Aritra Ghosh

Aritra Ghosh contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
gr-qchep-thMachine Learningastro-ph.GAastro-ph.IMcond-mat.stat-mechmath-phmath.MPArtificial Intelligencemath.SGphysics.class-phquant-phastro-ph.COastro-ph.EPComputer Science and Game Theorycond-mat.quant-gasnlin.SIphysics.optics

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Published work

18 published item(s)

preprint2026arXiv

Generalized virial theorem for contact Hamiltonian systems

We formulate and study a generalized virial theorem for contact Hamiltonian systems. Such systems describe mechanical systems in the presence of simple dissipative forces such as Rayleigh friction, or the vertical motion of a particle falling through a fluid (quadratic drag) under the action of constant gravity. We find a generalized virial theorem for contact Hamiltonian systems which is distinct from that obtained earlier for the symplectic case. The `contact' generalized virial theorem is shown to reduce to the earlier result on symplectic manifolds as a special case. Various examples of dissipative mechanical systems are discussed. We also formulate a generalized virial theorem in the contact Lagrangian framework.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-domain data at scales that increasingly shift the bottleneck in astronomical machine learning (ML) projects from model design to infrastructure. We present Hyrax, an open-source, modular, GPU-enabled Python framework that supports the full ML lifecycle in astronomy: from data acquisition and training to inference and experiment comparison, with capabilities including multimodal dataset support, integrated vector databases for similarity search, and interactive two- and three-dimensional latent-space exploration for unsupervised discovery. We demonstrate Hyrax's versatility through five representative applications on real survey data: (i) unsupervised representation learning on $\sim 4\times10^5$ Rubin Legacy Survey of Space and Time (LSST) Data Preview 1 (DP1) galaxies, surfacing new merger and low-surface-brightness candidates missing from reference Euclid and Dark Energy Survey catalogs, while also isolating imaging artifacts -- all without labeled training data; (ii) hybrid density-based clustering for identifying cluster-scale gravitational lens candidates in DP1 data; (iii) multimodal early-time transient classification in the Zwicky Transient Facility leveraging light curves, spectra, images, and metadata; (iv) supervised false-positive filtering in shift-and-stack searches for distant solar system objects in the Dark Energy Camera Ecliptic Exploration Project survey; and (v) supervised detection of semi-resolved dwarf galaxies in Hyper Suprime-Cam and LSST-like imaging using synthetic source injection. Together, these results demonstrate that Hyrax provides astronomy-specific ML infrastructure that enables systematic discovery and rapid methodological iteration across next-generation astronomical surveys.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Invariant measures for some dissipative systems from the Jacobi last multiplier

Hamiltonian dynamics describing conservative systems naturally preserves the standard notion of phase-space volume, a result known as the Liouville's theorem which is central to the formulation of classical statistical mechanics. In this paper, we obtain explicit expressions for invariant phase-space measures for certain (generally dissipative) mechanical systems, namely, systems described by conformal vector fields on symplectic manifolds that are cotangent bundles, contact Hamiltonian systems, and systems of the Liénard class. The latter class of systems can be described by certain generalized conformal vector fields on the cotangent bundle of the configuration space. The computation of the invariant measures is achieved by making use of the formalism of Jacobi last multipliers.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Cavity Optomechanical Quantum Memory for Twisted Photons Using a Ring BEC

We theoretically propose a photonic orbital angular momentum (OAM) quantum memory platform based on an atomic Bose-Einstein condensate confined in a ring trap and placed inside a Fabry-Perot cavity driven by Laguerre-Gaussian beams. In contrast to electromagnetically induced transparency-based protocols, our memory does not require change of internal atomic levels. The optical states are instead stored in the large Hilbert space of topologically protected and long-lived motional states (persistent currents) of the condensate, yielding a storage time three orders of magnitude better than presently available. Further, the use of a cavity provides orders of magnitude more resonances, and hence bandwidth, for reading and writing than internal atomic transitions. Finally, the analogy to cavity optomechanics suggests a natural path to wavelength conversion, OAM transduction, and nondestructive readout of the memory.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Quasi-harmonic spectra from branched Hamiltonians

We revisit the canonical quantization to assess the spectrum of the modified Emden equation $\ddot{x} + kx\dot{x} + ω^2 x + \frac{k^2}{9}x^3 = 0$, which is an isochronous case of the Liénard-Kukles equation. While its classical isochronicity and canonical quantization, leading to polynomial solutions with an exactly-equispaced spectrum have been discussed earlier, including in the recent paper [Int. J. Theor. Phys. 64, 212 (2025)], the present study focuses on the quantization of its branched Hamiltonians. For small $k$, we show numerically that the resulting energy spectrum is no longer perfectly harmonic but only approximately equispaced, exhibiting quasi-harmonic behavior characterized by deviations from uniform spacing. Our numerical results are precisely validated by analytical calculations based on perturbation theory.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters

We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology Posterior Estimation Network (GaMPEN) estimates values and uncertainties for a galaxy&#39;s bulge-to-total light ratio ($L_B/L_T$), effective radius ($R_e$), and flux ($F$). To estimate posteriors, GaMPEN uses the Monte Carlo Dropout technique and incorporates the full covariance matrix between the output parameters in its loss function. GaMPEN also uses a Spatial Transformer Network (STN) to automatically crop input galaxy frames to an optimal size before determining their morphology. This will allow it to be applied to new data without prior knowledge of galaxy size. Training and testing GaMPEN on galaxies simulated to match $z < 0.25$ galaxies in Hyper Suprime-Cam Wide $g$-band images, we demonstrate that GaMPEN achieves typical errors of $0.1$ in $L_B/L_T$, $0.17$ arcsec ($\sim 7\%$) in $R_e$, and $6.3\times10^4$ nJy ($\sim 1\%$) in $F$. GaMPEN&#39;s predicted uncertainties are well-calibrated and accurate ($<5\%$ deviation) -- for regions of the parameter space with high residuals, GaMPEN correctly predicts correspondingly large uncertainties. We also demonstrate that we can apply categorical labels (i.e., classifications such as &#34;highly bulge-dominated&#34;) to predictions in regions with high residuals and verify that those labels are $\gtrsim 97\%$ accurate. To the best of our knowledge, GaMPEN is the first machine learning framework for determining joint posterior distributions of multiple morphological parameters and is also the first application of an STN to optical imaging in astronomy.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Logarithmic corrections to black hole entropy and holography

We compute logarithmic corrections to the black hole entropy $S_{\rm bh}$ in a holographic set up where the cosmological constant $Λ$ and Newton&#39;s constant $G_D$ are taken to be thermodynamic parameters, related to variations in bulk pressure \(P\) and central charge \(c\). In the bulk, the logarithmic corrections are of the form: $\mathcal{S} = S_{\rm bh} - k \ln S_{\rm bh} + \cdots$ arising due to fluctuations in thermodynamic volume, induced by a variable $Λ$, in addition to energy fluctuations. We explicitly compute this coefficient $k$ for the BTZ black hole and show that the result matches with the one coming from the logarithmic corrections to the Cardy&#39;s formula. We propose an entropy function in the CFT, which exactly reproduces the logarithmic corrections to black hole entropy in arbitrary dimensions.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Logarithmic corrections to the entropy function of black holes in the open ensemble

An `open&#39; or $(μ,P,T)$-ensemble describes equilibrium systems whose control parameters are chemical potential $μ$, pressure $P$ and temperature $T$. Such an unconstrained ensemble is seldom used for applications to standard thermodynamic systems due to the fact that the corresponding free energy identically vanishes as a result of the Euler relation. However, an open ensemble is perfectly regular for the case of black holes, as the entropy is a quasi-homogeneous function of extensive thermodynamic variables with scaling dictated by the Smarr formula. Following a brief discussion on thermodynamics in the open ensemble, we compute the general form of logarithmic corrections to the entropy of a typical system, due to fluctuations in energy, thermodynamic volume and a generic charge $N$. This is then used to obtain the exact analytic form of the logarithmically corrected black hole entropy for charged and rotating black holes in anti-de Sitter spacetimes.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Partition of free energy for a Brownian quantum oscillator: Effect of dissipation and magnetic field

Recently, the quantum counterpart of energy equipartition theorem has drawn considerable attention. Motivated by this, we formulate and investigate an analogous statement for the free energy of a quantum oscillator linearly coupled to a passive heat bath consisting of an infinite number of independent harmonic oscillators. We explicitly demonstrate that the free energy of the Brownian oscillator can be expressed in the form $F(T) = \langle f(ω,T) \rangle $ where $f(ω,T)$ is the free energy of an individual bath oscillator. The overall averaging process involves two distinct averages: the first one is over the canonical ensemble for the bath oscillators, whereas the second one signifies averaging over the entire bath spectrum of frequencies from zero to infinity. The latter is performed over a relevant probability distribution function $\mathcal{P}(ω)$ which can be derived from the knowledge of the generalized susceptibility encountered in linear response theory. The effect of different dissipation mechanisms is also exhibited. We find two remarkable consequences of our results. First, the quantum counterpart of energy equipartition theorem follows naturally from our analysis. The second corollary we obtain is a natural derivation of the third law of thermodynamics for open quantum systems. Finally, we generalize the formalism to three spatial dimensions in the presence of an external magnetic field.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Quantum counterpart of energy equipartition theorem for fermionic systems

In this brief report, following the recent developments on formulating a quantum analogue of the classical energy equipartition theorem for open systems where the heat bath comprises of independent oscillators, i.e. bosonic degrees of freedom, we present an analogous result for fermionic systems. The most general case where the system is connected to multiple reservoirs is considered and the mean energy in the steady state is expressed as an integral over the reservoir frequencies. Physically this would correspond to summing over the contributions of the bath degrees of freedom to the mean energy of the system over a suitable distribution function $ρ(ω)$ dependent on the system parameters. This result holds for nonequilibrium steady states, even in the nonlinear regime far from equilibrium. We also analyze the zero temperature behaviour and low temperature corrections to the mean energy of the system.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Quantum counterpart of energy equipartition theorem for a dissipative charged magneto-oscillator: Effect of dissipation, memory, and magnetic field

In this paper, we formulate and study the quantum counterpart of the energy equipartition theorem for a charged quantum particle moving in a harmonic potential in the presence of a uniform external magnetic field and linearly coupled to a passive quantum heat bath through coordinate variables. The bath is modelled as a collection of independent quantum harmonic oscillators. We derive the closed form expressions for the mean kinetic and potential energies of the charged-dissipative-magneto-oscillator in the form $E_k = \langle \mathcal{E}_k \rangle$ and $E_p = \langle \mathcal{E}_p \rangle$ respectively, where $\mathcal{E}_k$ and $\mathcal{E}_p$ denote the average kinetic and potential energies of individual thermostat oscillators. The net averaging is two-fold, the first one being over the Gibbs canonical state for the thermostat, giving $\mathcal{E}_k$ and $\mathcal{E}_p$ and the second one denoted by $\langle . \rangle$ being over the frequencies $ω$ of the bath oscillators which contribute to $E_k$ and $E_p$ according to probability distributions $\mathcal{P}_k(ω)$ and $\mathcal{P}_p(ω)$ respectively. The relationship of the present quantum version of the equipartition theorem with that of the fluctuation-dissipation theorem (within the linear-response theory framework) is also explored. Further, we investigate the influence of the external magnetic field and the effect of different dissipation processes through Gaussian decay, Drude and radiation bath spectral density functions, on the typical properties of $\mathcal{P}_k(ω)$ and $\mathcal{P}_p(ω)$. Finally, the role of system-bath coupling strength and the memory effect is analyzed in the context of average kinetic and potential energies of the dissipative charged magneto-oscillator.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Thermodynamic curvature of AdS black holes with dark energy

In this paper, we study the effect of dark energy on the extended thermodynamic structure and interacting microstructures of black holes in AdS, through an analysis of thermodynamic geometry. Considering various limiting cases of the novel equation of state obtained in charged rotating black holes with quintessence, and taking enthalpy $H$ as the key potential in the extended phase space, we scrutinize the behavior of the Ruppeiner curvature scalar $R$ in the entropy-pressure $(S,P)$-plane (or equivalently in the temperature-volume ($T,V$)-plane). Analysis of $R$ empirically reveals that dark energy parameterized by $α$, significantly alters the dominant interactions of neutral, charged and slowly rotating black hole microstructures. In the Schwarzschild-AdS case: black holes smaller than a certain size continue to have attractive interactions whereas larger black holes are completely dominated by repulsive interactions which arise to due dark energy. For charged or rotating AdS black holes with quintessence, $R$ can change sign at multiple points depending upon the relation between $α$ and charge $q$ or angular momentum $J$. In particular, above a threshold value of $α$, $R$ is never negative at all, suggesting heuristically that the repulsive interactions due to quintessence are long ranged as opposed to the previously known short ranged repulsion in charged AdS black holes. A mean field interaction potential is proposed whose extrema effectively capture the points where the curvature $R$ changes sign.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Context-Aware Attentive Knowledge Tracing

Knowledge tracing (KT) refers to the problem of predicting future learner performance given their past performance in educational applications. Recent developments in KT using flexible deep neural network-based models excel at this task. However, these models often offer limited interpretability, thus making them insufficient for personalized learning, which requires using interpretable feedback and actionable recommendations to help learners achieve better learning outcomes. In this paper, we propose attentive knowledge tracing (AKT), which couples flexible attention-based neural network models with a series of novel, interpretable model components inspired by cognitive and psychometric models. AKT uses a novel monotonic attention mechanism that relates a learner&#39;s future responses to assessment questions to their past responses; attention weights are computed using exponential decay and a context-aware relative distance measure, in addition to the similarity between questions. Moreover, we use the Rasch model to regularize the concept and question embeddings; these embeddings are able to capture individual differences among questions on the same concept without using an excessive number of parameters. We conduct experiments on several real-world benchmark datasets and show that AKT outperforms existing KT methods (by up to $6\%$ in AUC in some cases) on predicting future learner responses. We also conduct several case studies and show that AKT exhibits excellent interpretability and thus has potential for automated feedback and personalization in real-world educational settings.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Galaxy Morphology Network: A Convolutional Neural Network Used to Study Morphology and Quenching in $\sim 100,000$ SDSS and $\sim 20,000$ CANDELS Galaxies

We examine morphology-separated color-mass diagrams to study the quenching of star formation in $\sim 100,000$ ($z\sim0$) Sloan Digital Sky Survey (SDSS) and $\sim 20,000$ ($z\sim1$) Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) galaxies. To classify galaxies morphologically, we developed Galaxy Morphology Network (GaMorNet), a convolutional neural network that classifies galaxies according to their bulge-to-total light ratio. GaMorNet does not need a large training set of real data and can be applied to data sets with a range of signal-to-noise ratios and spatial resolutions. GaMorNet&#39;s source code as well as the trained models are made public as part of this work ( http://www.astro.yale.edu/aghosh/gamornet.html ). We first trained GaMorNet on simulations of galaxies with a bulge and a disk component and then transfer learned using $\sim25\%$ of each data set to achieve misclassification rates of $\lesssim5\%$. The misclassified sample of galaxies is dominated by small galaxies with low signal-to-noise ratios. Using the GaMorNet classifications, we find that bulge- and disk-dominated galaxies have distinct color-mass diagrams, in agreement with previous studies. For both SDSS and CANDELS galaxies, disk-dominated galaxies peak in the blue cloud, across a broad range of masses, consistent with the slow exhaustion of star-forming gas with no rapid quenching. A small population of red disks is found at high mass ($\sim14\%$ of disks at $z\sim0$ and $2\%$ of disks at $z \sim 1$). In contrast, bulge-dominated galaxies are mostly red, with much smaller numbers down toward the blue cloud, suggesting rapid quenching and fast evolution across the green valley. This inferred difference in quenching mechanism is in agreement with previous studies that used other morphology classification techniques on much smaller samples at $z\sim0$ and $z\sim1$.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Optimal Bidding Strategy without Exploration in Real-time Bidding

Maximizing utility with a budget constraint is the primary goal for advertisers in real-time bidding (RTB) systems. The policy maximizing the utility is referred to as the optimal bidding strategy. Earlier works on optimal bidding strategy apply model-based batch reinforcement learning methods which can not generalize to unknown budget and time constraint. Further, the advertiser observes a censored market price which makes direct evaluation infeasible on batch test datasets. Previous works ignore the losing auctions to alleviate the difficulty with censored states; thus significantly modifying the test distribution. We address the challenge of lacking a clear evaluation procedure as well as the error propagated through batch reinforcement learning methods in RTB systems. We exploit two conditional independence structures in the sequential bidding process that allow us to propose a novel practical framework using the maximum entropy principle to imitate the behavior of the true distribution observed in real-time traffic. Moreover, the framework allows us to train a model that can generalize to the unseen budget conditions than limit only to those observed in history. We compare our methods on two real-world RTB datasets with several baselines and demonstrate significantly improved performance under various budget settings.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Scalable Bid Landscape Forecasting in Real-time Bidding

In programmatic advertising, ad slots are usually sold using second-price (SP) auctions in real-time. The highest bidding advertiser wins but pays only the second-highest bid (known as the winning price). In SP, for a single item, the dominant strategy of each bidder is to bid the true value from the bidder&#39;s perspective. However, in a practical setting, with budget constraints, bidding the true value is a sub-optimal strategy. Hence, to devise an optimal bidding strategy, it is of utmost importance to learn the winning price distribution accurately. Moreover, a demand-side platform (DSP), which bids on behalf of advertisers, observes the winning price if it wins the auction. For losing auctions, DSPs can only treat its bidding price as the lower bound for the unknown winning price. In literature, typically censored regression is used to model such partially observed data. A common assumption in censored regression is that the winning price is drawn from a fixed variance (homoscedastic) uni-modal distribution (most often Gaussian). However, in reality, these assumptions are often violated. We relax these assumptions and propose a heteroscedastic fully parametric censored regression approach, as well as a mixture density censored network. Our approach not only generalizes censored regression but also provides flexibility to model arbitrarily distributed real-world data. Experimental evaluation on the publicly available dataset for winning price estimation demonstrates the effectiveness of our method. Furthermore, we evaluate our algorithm on one of the largest demand-side platforms and significant improvement has been achieved in comparison with the baseline solutions.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Thermodynamic geometry and interacting microstructures of BTZ black holes

In this work, we present a study to probe the nature of interactions between black hole microstructures for the case of the BTZ black holes. Even though BTZ black holes without any angular momentum or electric charge thermodynamically behave as an ideal gas, i.e. with non-interacting microstructures; in the presence of electric charge or angular momentum, BTZ black holes are associated with repulsive interactions among the microstructures. We extend the study to the case of exotic BTZ black holes with mass $M = αm + γ\frac{j}{l}$ and angular momentum $J=αj + γl m$, for arbitrary values of $ (α, γ)$ ranging from purely exotic $(α=0,γ=1)$, slightly exotic $(α> \frac{1}{2},γ< \frac{1}{2})$ and highly exotic $(α< \frac{1}{2}, γ> \frac{1}{2})$. We find that unlike the normal BTZ black holes (the case $α=1,γ=0$), there exist both attraction as well as repulsion dominated regions in all the cases of exotic BTZ black holes.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Thermodynamic geometry for charged Gauss-Bonnet black holes in AdS spacetimes

In this paper, we study the thermodynamic geometry of charged Gauss-Bonnet black holes (and Reissner-Nordström black holes, for the sake of comparison) in AdS: in both $(T,V)$- and $(S,P)$-planes. The thermodynamic phase space is known to have an underlying contact and metric structure; Ruppeiner geometry then naturally arises in this framework. Sign of Ruppeiner curvature can be used to probe the nature of interactions between the black hole microstructures. It is found that there are both attraction and repulsion dominated regions which are in general determined by the electric charge, Gauss-Bonnet coupling and horizon radius of the black hole. The results are physically explained by considering that these black hole systems consist of charged as well as neutral microstructures much like a binary mixture of fluids.

0 citations0 reviewsNo code linkedOpen access