arXiv subjects

Arghya Chatterjee

Publications and source records attributed to Arghya Chatterjee.

At least 19 recordsLinked to original sources

arXiv2026

A System for Fast, Resilient, and Adaptable Loco-Manipulation Behaviors on Humanoid Robots

There is tremendous value in humanoid robots taking on physically demanding, hazardous, and repetitive work in spaces built for humans. However, a useful robot for these spaces must coordinate locomotion, whole-body motion, perception, contact, and operator supervision. We present a robot-local, runtime-editable behavior authoring and runtime system that addresses these challenges. We argue that behavior architecture can be a primary enabler of capability, speed, and reliability, and that runtime editability enables fast behavior creation, adaptation, extension, and combination. Our behavior architecture combines object-centric Affordance Templates, a tree structure that provides organization and logic, and runtime-editable perception through a behavior scene and primitive scene actions. Our operator interface remains continuously synchronized to the robot for runtime authoring, monitoring, and repair. Action primitives execute through a whole-body controller that supports concurrent body motions and walking. Demonstrations of our system cover six task variants on Unitree H1-2 and Alex. We execute a push door traversal in 34 seconds and sort six balls by color in 45 seconds under human disturbance. Timed authoring sessions show scratch creation of new loco-manipulation behaviors and adaptation of existing ones in hours. Comparison against the literature finds our approach to be competitive with recent learned systems.

cs.RO↗

arXiv2026

Vorticity-induced modifications of chemical freeze-out in heavy-ion collisions

We investigate the influence of global rotation on the chemical freeze-out parameters in ultra-relativistic heavy-ion collisions. Within the framework of the hadron resonance gas (HRG) model, the freeze-out parameters are determined using commonly employed freeze-out criteria, namely the fixed energy per particle and the scaled entropy density, extended here to include rotational effects. We find that the presence of rotation leads to a systematic shift of the chemical freeze-out curve toward lower temperatures in the $T\text{--}\mu_B$ phase diagram. The behavior of the electric charge and strangeness chemical potentials in the presence of rotation is also analyzed, providing the first systematic study of their rotational dependence within the HRG framework. Furthermore, we examine the impact of rotation on experimentally relevant observables, including hadron yield ratios and susceptibility ratios of conserved charges. Our results show that while particle yield ratios exhibit noticeable sensitivity to rotation, the conventional cumulant ratios remain comparatively less affected. This indicates that hadronic yield ratios may provide a more suitable observable for estimating the magnitude of rotational effects generated in heavy-ion collisions.

hep-ph↗

arXiv2025

Shear Viscosity and Electrical Conductivity of Rotating Nuclear Medium in Hadron Resonance Gas and Nambu-Jona Lasinio Models

Motivated by recent observations of spin polarization and alignment in heavy-ion collisions, we study the impact of rotation on the transport properties of strongly interacting matter within kinetic theory in the relaxation time approximation. Our analysis focuses on the anisotropic shear viscosity--parallel ($\eta_{\parallel}$), perpendicular ($\eta_{\perp}$), and Hall ($\eta_{\times}$)--and electrical conductivity--$\sigma_{\parallel}$, $\sigma_{\perp}$, and $\sigma_{\times}$--induced by the Coriolis force in a rotating medium. We employ two approaches: a combined quark-gluon plasma--hadron resonance gas (QGP--HRG) framework and a two-flavor Nambu--Jona-Lasinio (NJL) model. In the QGP--HRG description, noninteracting HRG (massless partonic) degrees of freedom are used below (above) the transition temperature. In the NJL model, rotation enters through spinorial connections in the Lagrangian, and the constituent quark masses are obtained over the full temperature range. Rotation suppresses the chiral condensate and slightly enhances the transport coefficients for phenomenologically relevant angular velocities. Assuming a temperature-dependent angular velocity consistent with standard cooling, we find that $\eta_{||,\perp,\times}/s$ and $\sigma_{\perp,\times}/T$ exhibit a valley-like temperature dependence, with reduced magnitudes compared to the isotropic $\eta/s$ and $\sigma/T$ obtained without rotation. At zero net baryon density, rotation generates a sizable nondissipative Hall-like conductivity, unlike the case with magnetic fields where baryon and antibaryon contributions cancel.

nucl-th↗

arXiv2025

An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments

This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Subterranean Challenge. Specifically, this paper presents extensions to NeBula's hardware, software, and algorithmic components that focus on increasing the range and scale of the exploration environment. From the algorithmic perspective, we discuss the following extensions to the original NeBula framework: (i) large-scale geometric and semantic environment mapping; (ii) an adaptive positioning system; (iii) probabilistic traversability analysis and local planning; (iv) large-scale POMDP-based global motion planning and exploration behavior; (v) large-scale networking and decentralized reasoning; (vi) communication-aware mission planning; and (vii) multi-modal ground-aerial exploration solutions. We demonstrate the application and deployment of the presented systems and solutions in various large-scale underground environments, including limestone mine exploration scenarios as well as deployment in the DARPA Subterranean challenge.

cs.RO↗

arXiv2024

Effect of Coriolis Force on Diffusion of D Meson

We have attempted to calculate and estimate the spatial diffusion coefficients of D meson through rotating hadron resonance gas, which can be produced in the late stage of peripheral heavy ion collisions. Employing the framework of kinetic theory in relaxation time approximation, and using Einstein's diffusion relation, one can express the spatial diffusion coefficients of D meson as a ratio of its conductivity to its susceptibility. Here, we have tuned D meson relaxation time from the knowledge of earlier works on its spatial diffusion estimations, and then we have extended the framework for the finite rotation picture of hadronic matter, where only the effect of Coriolis force is considered. Our study also revealed the anisotropic nature of diffusion in the presence of rotation with future possibilities of phenomenological signature.

hep-ph↗

arXiv2024

A Behavior Architecture for Fast Humanoid Robot Door Traversals

Towards the role of humanoid robots as squad mates in urban operations and other domains, we identified doors as a major area lacking capability development. In this paper, we focus on the ability of humanoid robots to navigate and deal with doors. Human-sized doors are ubiquitous in many environment domains and the humanoid form factor is uniquely suited to operate and traverse them. We present an architecture which incorporates GPU accelerated perception and a tree based interactive behavior coordination system with a whole body motion and walking controller. Our system is capable of performing door traversals on a variety of door types. It supports rapid authoring of behaviors for unseen door types and techniques to achieve re-usability of those authored behaviors. The behaviors are modelled using trees and feature logical reactivity and action sequences that can be executed with layered concurrency to increase speed. Primitive actions are built on top of our existing whole body controller which supports manipulation while walking. We include a perception system using both neural networks and classical computer vision for door mechanism detection outside of the lab environment. We present operator-robot interdependence analysis charts to explore how human cognition is combined with artificial intelligence to produce complex robot behavior. Finally, we present and discuss real robot performances of fast door traversals on our Nadia humanoid robot. Videos online at https://www.youtube.com/playlist?list=PLXuyT8w3JVgMPaB5nWNRNHtqzRK8i68dy.

cs.RO↗

arXiv2024

Transport Coefficients of relativistic matter: A detailed formalism with a gross knowledge of their magnitude

The present review article has attempted a compact formalism description of transport coefficient calculations for relativistic fluid, which is expected in heavy ion collision experiments. Here, we first address the macroscopic description of relativistic fluid dynamics and then its microscopic description based on the kinetic theory framework. We also address different relaxation time approximation-based models in Boltzmann transport equations, which make a sandwich between Macro and Micro frameworks of relativistic fluid dynamics and finally provide different microscopic expressions of transport coefficients like the fluid's shear viscosity and bulk viscosity. In the numeric part of this review article, we put stress on the two gross components of transport coefficient expressions: relaxation time and thermodynamic phase-space part. Then, we try to tune the relaxation time component to cover earlier theoretical estimations and experimental data-driven estimations for RHIC and LHC matter. By this way of numerical understanding, we provide the final comments on the values of transport coefficients and relaxation time in the context of the (nearly) perfect fluid nature of the RHIC or LHC matter.

nucl-th↗

arXiv2024

Effect of Coriolis Force on Electrical Conductivity Tensor for Rotating Hadron Resonance Gas

We have investigated the influence of the Coriolis force on the electrical conductivity of hadronic matter formed in relativistic nuclear collisions, employing the Hadron Resonance Gas (HRG) model. A rotating matter in the peripheral heavy ion collisions can be expected from the initial stage of quark matter to late-stage hadronic matter. Present work is focused on rotating hadronic matter, whose medium constituents - hadron resonances can face a non-zero Coriolis force, which can influence the hadronic flow or conductivity. We estimate this conductivity tensor by using the relativistic Boltzmann transport equation. In the absence of Coriolis force, an isotropic conductivity tensor for hadronic matter is expected. However, our study finds that the presence of Coriolis force can generate an anisotropic conductivity tensor with three main conductivity components - parallel, perpendicular, and Hall, similar to the effect of Lorentz force at a finite magnetic field. Our study has indicated that a noticeable anisotropy of conductivity tensor can be found within the phenomenological range of angular velocity $\Omega= 0.001-0.02$ GeV and hadronic scattering radius $a=0.2-2$ fm.

hep-ph↗

arXiv2023

A Boosted Machine Learning Framework for the Improvement of Phase and Crystal Structure Prediction of High Entropy Alloys Using Thermodynamic and Configurational Parameters

The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structures they contain. In the realm of material informatics, employing machine learning (ML) techniques to classify phases and crystal structures of HEAs has gained considerable significance. In this study, we assembled a new collection of 1345 HEAs with varying compositions to predict phases. Within this collection, there were 705 sets of data that were utilized to predict the crystal structures with the help of thermodynamics and electronic configuration. Our study introduces a methodical framework i.e., the Pearson correlation coefficient that helps in selecting the strongly co-related features to increase the prediction accuracy. This study employed five distinct boosting algorithms to predict phases and crystal structures, offering an enhanced guideline for improving the accuracy of these predictions. Among all these algorithms, XGBoost gives the highest accuracy of prediction (94.05%) for phases and LightGBM gives the highest accuracy of prediction of crystal structure of the phases (90.07%). The quantification of the influence exerted by parameters on the model's accuracy was conducted and a new approach was made to elucidate the contribution of individual parameters in the process of phase prediction and crystal structure prediction.

cs.LG↗

arXiv2022

Present and Future of SLAM in Extreme Underground Environments

This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT competition. In particular, the paper has four main goals. First, we review the algorithms, architectures, and systems adopted by the teams; particular emphasis is put on lidar-centric SLAM solutions (the go-to approach for virtually all teams in the competition), heterogeneous multi-robot operation (including both aerial and ground robots), and real-world underground operation (from the presence of obscurants to the need to handle tight computational constraints). We do not shy away from discussing the dirty details behind the different SubT SLAM systems, which are often omitted from technical papers. Second, we discuss the maturity of the field by highlighting what is possible with the current SLAM systems and what we believe is within reach with some good systems engineering. Third, we outline what we believe are fundamental open problems, that are likely to require further research to break through. Finally, we provide a list of open-source SLAM implementations and datasets that have been produced during the SubT challenge and related efforts, and constitute a useful resource for researchers and practitioners.

cs.RO↗

arXiv2022

LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments

Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale underground environments requires high-precision localization and mapping. This crucial requirement is faced with many challenges in complex and perceptually-degraded subterranean environments, as the onboard perception system is required to operate in off-nominal conditions (poor visibility due to darkness and dust, rugged and muddy terrain, and the presence of self-similar and ambiguous scenes). In a disaster response scenario and in the absence of prior information about the environment, robots must rely on noisy sensor data and perform Simultaneous Localization and Mapping (SLAM) to build a 3D map of the environment and localize themselves and potential survivors. To that end, this paper reports on a multi-robot SLAM system developed by team CoSTAR in the context of the DARPA Subterranean Challenge. We extend our previous work, LAMP, by incorporating a single-robot front-end interface that is adaptable to different odometry sources and lidar configurations, a scalable multi-robot front-end to support inter- and intra-robot loop closure detection for large scale environments and multi-robot teams, and a robust back-end equipped with an outlier-resilient pose graph optimization based on Graduated Non-Convexity. We provide a detailed ablation study on the multi-robot front-end and back-end, and assess the overall system performance in challenging real-world datasets collected across mines, power plants, and caves in the United States. We also release our multi-robot back-end datasets (and the corresponding ground truth), which can serve as challenging benchmarks for large-scale underground SLAM.

cs.RO↗

arXiv2021

Efficiency corrections for mutually inclusive variables and particle identification effect for mixed-cumulants in heavy-ion collisions

Mix-cumulants of conserved charge distributions are sensitive observables for probing properties of the QCD medium and phase transition in heavy-ion collisions. To perform precise measurements, efficiency correction is one of the most important step. In this study, using the binomial efficiency model, we derive efficiency correction formulas for mutually exclusive and inclusive variables. The UrQMD model is applied to verify the validity of these formulas for different types of correlations. Furthermore, we investigate the effect of the multiplicity loss and contamination emerging from the particle identifications. This study provides an important step toward future measurements of mixed-cumulants in relativistic heavy-ion collisions.

physics.data-an↗

arXiv2021

Memory Reduction using a Ring Abstraction over GPU RDMA for Distributed Quantum Monte Carlo Solver

Scientific applications that run on leadership computing facilities often face the challenge of being unable to fit leading science cases onto accelerator devices due to memory constraints (memory-bound applications). In this work, the authors studied one such US Department of Energy mission-critical condensed matter physics application, Dynamical Cluster Approximation (DCA++), and this paper discusses how device memory-bound challenges were successfully reduced by proposing an effective "all-to-all" communication method -- a ring communication algorithm. This implementation takes advantage of acceleration on GPUs and remote direct memory access (RDMA) for fast data exchange between GPUs. Additionally, the ring algorithm was optimized with sub-ring communicators and multi-threaded support to further reduce communication overhead and expose more concurrency, respectively. The computation and communication were also analyzed by using the Autonomic Performance Environment for Exascale (APEX) profiling tool, and this paper further discusses the performance trade-off for the ring algorithm implementation. The memory analysis on the ring algorithm shows that the allocation size for the authors' most memory-intensive data structure per GPU is now reduced to 1/p of the original size, where p is the number of GPUs in the ring communicator. The communication analysis suggests that the distributed Quantum Monte Carlo execution time grows linearly as sub-ring size increases, and the cost of messages passing through the network interface connector could be a limiting factor.

cs.DC↗

arXiv2020

Performance Analysis of a Quantum Monte Carlo Application on Multiple Hardware Architectures Using the HPX Runtime

This paper describes how we successfully used the HPX programming model to port the DCA++ application on multiple architectures that include POWER9, x86, ARM v8, and NVIDIA GPUs. We describe the lessons we can learn from this experience as well as the benefits of enabling the HPX in the application to improve the CPU threading part of the code, which led to an overall 21% improvement across architectures. We also describe how we used HPX-APEX to raise the level of abstraction to understand performance issues and to identify tasking optimization opportunities in the code, and how these relate to CPU/GPU utilization counters, device memory allocation over time, and CPU kernel-level context switches on a given architecture.

cs.DC↗

arXiv2020

Effects of centrality fluctuation and deuteron formation on proton number cumulant in Au+Au collisions at $\sqrt{s_\mathrm{NN}}$ = 3 GeV from JAM model

We studied the effects of centrality fluctuation and deuteron formation on the cumulants ($C_n$) and correlation functions ($κ_n$) of protons up to sixth order in most central ($b<3$ fm) Au+Au collisions at $\sqrt{s_\mathrm{NN}}$ = 3 GeV from a microscopic transport model (JAM). The results are presented as a function of rapidity acceptance within transverse momentum $0.4<p_{T}<2 $ GeV/$c$. We compared the results obtained by centrality bin width correction (CBWC) using charged reference particle multiplicity with CBWC done using impact parameter bins. It was found that at low energies the centrality resolution for determining the collision centrality using charged particle multiplicities is not good enough to reduce the initial volume fluctuations effect for higher-order cumulant analysis. New methods need to be developed to classify events with high centrality resolution for heavy-ion collisions at low energies. Finally, we observed that the formation of deuteron will suppress the higher-order cumulants and correlation functions of protons and is found to be similar to the efficiency effect. This work can serve as a noncritical baseline for the QCD critical point search at the high baryon density region.

nucl-ex↗

arXiv2020

Centrality selection effect on higher-order cumulants of net-proton multiplicity distributions in relativistic heavy-ion collisions

We studied the centrality selection effect on cumulants (up to fourth order) and the cumulants ratios of net-proton multiplicity distributions in Au+Au collisions at $\sqrt{s_{\mathrm{NN}}}$ = 7.7, 19.6 and 200 GeV from UrQMD model. The net-proton cumulants are calculated with collision centralities by using charged particle multiplicity from different pesudorapidity ($η$) region. By comparing the results from various collision centralities, we found that the autocorrelation effects are not significant in the results with collision centralities "refmult-3" and "refmult-2", which are using mid-rapidity charged particles but excluding (anti-)protons and analysis region, respectively. Furthermore, due to the contributions of spectator protons, we observed poor centrality resolution when using charged particles at forward $η$ region at low energies. This work can serve as a baseline for centrality selection of future fluctuations analysis in relativistic heavy-ion collisions.

nucl-ex↗

arXiv2019

Off-diagonal cumulants of net-charge, net-proton and net-kaon multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7-200 GeV from STAR

Fluctuations of conserved quantities such as net-baryon, net-charge, and net-strangeness numbers have generated considerable interest in the study of the thermodynamic properties of the hot and dense QCD matter. Theoretical calculations suggest that the off-diagonal cumulants of conserved charges along with the diagonal cumulants can help better constrain the freeze-out parameters and, therefore, help to map the QCD phase diagram. In this proceeding, we briefly outline the recent STAR measurements on the second-order off-diagonal cumulants of net-charge, net-proton, and net-kaon multiplicity distributions in Au+Au collisions from the RHIC BES-I program in the energy range of $\sqrt{s_{NN}}$ = 7.7-200 GeV. The measured cumulant ratios are compared to the predictions from both thermal (HRG) and non-thermal (UrQMD) models.

hep-ex↗

arXiv2018

Isothermal compressibility of hadronic matter formed in relativistic nuclear collisions

We present the first estimates of isothermal compressibility (\kT) of hadronic matter formed in relativistic nuclear collisions ($\sqrt{s_{\rm NN}} = 7.7$ GeV to 2.76~TeV) using experimentally observed quantities. \kT~is related to the fluctuation in particle multiplicity, temperature, and volume of the system formed in the collisions. Multiplicity fluctuations are obtained from the event-by-event distributions of charged particle multiplicities in narrow centrality bins. The dynamical components of the fluctuations are extracted by removing the contributions to the fluctuations from the number of participating nucleons. From the available experimental data, a constant value of \kT~has been observed as a function of collision energy. The results are compared with calculations from UrQMD, AMPT, and EPOS event generators, and estimations of \kT~are made for Pb-Pb collisions at the CERN Large Hadron Collider. A hadron resonance gas (HRG) model has been used to calculate \kT~as a function of collision energy. Our results show a decrease in \kT~at low collision energies to \sNN~$\sim$~20~GeV, beyond which the \kT~values remain almost constant.

nucl-ex↗