Publications

@article{goswamiTwodimensionalRMSDProjections2026,
  title = {Two-Dimensional {{RMSD}} Projections for Reaction Path Visualization and Validation},
  author = {Goswami, Rohit},
  year = {2026},
  month = {mar},
  journal = {MethodsX},
  pages = {103851},
  issn = {2215-0161},
  doi = {10.1016/j.mex.2026.103851},
  urldate = {2026-03-06},
  langid = {english},
  keywords = {journal, selected},
}

@misc{goswamiEnhancedClimbingImage2026,
  title = {Enhanced Climbing Image Nudged Elastic Band Method with Hessian Eigenmode Alignment},
  author = {Goswami, Rohit and Gunde, Miha and J{\'o}nsson, Hannes},
  year = {2026},
  month = {jan},
  eprint = {2601.12630},
  archiveprefix = {arXiv},
  primaryclass = {physics.chem-ph},
  keywords = {preprint, selected},
}

@misc{goswamiTwodimensionalRMSDProjections2025,
  title = {Two-Dimensional {{RMSD}} Projections for Reaction Path Visualization and Validation},
  author = {Goswami, Rohit},
  date = {2025-12},
  number = {arXiv:2512.07329},
  eprint = {2512.07329},
  primaryclass = {physics},
  publisher = {{arXiv}},
  doi = {10.48550/arXiv.2512.07329},
  urldate = {2025-12-09},
  archiveprefix = {arXiv},
  langid = {english},
  keywords = {preprint},
}

@article{goswamiAdaptivePruningOA2025,
  title = {Adaptive Pruning for Increased Robustness and Reduced Computational Overhead in Gaussian Process Accelerated Saddle Point Searches},
  author = {Goswami, Rohit and J{\'o}nsson, Hannes},
  journal = {ChemPhysChem (Cover feature)},
  date = {2025-11-27},
  doi = {10.1002/cphc.202500730},
  copyright = {\copyright{} 2025 The Author(s). ChemPhysChem published by Wiley-VCH GmbH},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2510.06030},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@article{sallermannFlowyHighPerformance2025,
  title = {Flowy: High Performance Probabilistic Lava Emplacement Prediction},
  shorttitle = {Flowy},
  author = {Sallermann, Moritz and Goswami, Amrita and {Pe{\~n}a-Torres}, Alejandro and Goswami, Rohit},
  year = {2025},
  month = {oct},
  journal = {Computer Physics Communications},
  volume = {315},
  pages = {109745},
  issn = {0010-4655},
  doi = {10.1016/j.cpc.2025.109745},
  urldate = {2025-08-03},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2405.20144},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@misc{bigiMetatensorMetatomicFoundational2025,
  title = {Metatensor and Metatomic: Foundational Libraries for Interoperable Atomistic Machine Learning},
  shorttitle = {Metatensor and Metatomic},
  author = {Bigi, Filippo and Abbott, Joseph W. and Loche, Philip and Mazitov, Arslan and Tisi, Davide and Langer, Marcel F. and Goscinski, Alexander and Pegolo, Paolo and Chong, Sanggyu and Goswami, Rohit and Chorna, Sofiia and Kellner, Matthias and Ceriotti, Michele and Fraux, Guillaume},
  year = {2025},
  month = {aug},
  number = {arXiv:2508.15704},
  eprint = {2508.15704},
  primaryclass = {physics},
  publisher = {arXiv},
  doi = {10.48550/arXiv.2508.15704},
  urldate = {2025-09-04},
  archiveprefix = {arXiv},
  langid = {english},
  keywords = {preprint, selected},
}

@article{goswamiBayesianHierarchicalModels2025,
  title = {Bayesian Hierarchical Models for Quantitative Estimates for Performance Metrics Applied to Saddle Search Algorithms},
  author = {Goswami, Rohit},
  journal = {AIP Advances},
  volume = {15},
  number = {8},
  pages = {85210},
  issn = {2158-3226},
  doi = {10.1063/5.0283639},
  date = {2025-08-11},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2505.13621},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@article{goswamiEfficientImplementationGaussian2025a,
  title = {Efficient {{Implementation}} of {{Gaussian Process Regression Accelerated Saddle Point Searches}} with {{Application}} to {{Molecular Reactions}}},
  author = {Goswami, Rohit and Masterov, Maxim and Kamath, Satish and {Pena-Torres}, Alejandro and J{\'o}nsson, Hannes},
  year = {2025},
  month = {jul},
  journal = {Journal of Chemical Theory and Computation},
  publisher = {American Chemical Society},
  doi = {10.1021/acs.jctc.5c00866},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2505.12519},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@article{goswamiCompositionalAnalysisFragrance2025,
  title = {Compositional Analysis of Fragrance Accords Using Femtosecond Thermal Lens Spectroscopy},
  author = {Goswami, Rohit and Rawat, Ashwini Kumar and Goswami, Sonaly and Goswami, Debabrata},
  journal = {Chemistry -- an Asian Journal},
  volume = {20},
  number = {17},
  issn = {1861-471X},
  doi = {10.1002/asia.202500521},
  urldate = {2025-06-17},
  year = {2025},
  month = {jun},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2503.20431},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@article{certikHighorderFiniteElement2023,
  title = {High-Order Finite Element Method for Atomic Structure Calculations},
  author = {Čertík, Ondřej and Pask, John E. and Fernando, Isuru and Goswami, Rohit and Sukumar, N. and family=Collins, given=Lee. A., given-i={{Lee}}A and Manzini, Gianmarco and Vackář, Jiří},
  date = {2023-12},
  journaltitle = {Computer Physics Communications},
  shortjournal = {Computer Physics Communications},
  pages = {109051},
  issn = {00104655},
  doi = {10.1016/j.cpc.2023.109051},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S001046552300396X},
  urldate = {2023-12-18},
  langid = {english},
  archivePrefix = {arXiv},
  eprint = {2307.05856},
  eprinttype = {arxiv},
  keywords = {journal},
}

@inproceedings{goswamiHPCNixRedundancy2023,
  author = {Goswami, Rohit and S, Ruhila and Goswami, Amrita and Goswami, Sonaly and Goswami, Debabrata},
  booktitle = {2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC)},
  title = {Reproducible High Performance Computing Without Redundancy with Nix},
  date = {2023-03},
  volume = {},
  number = {},
  keywords = {conference},
}

@inproceedings{goswamiReproPhylogenetics2023,
  author = {Goswami, Rohit and S, Ruhila},
  booktitle = {2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC)},
  title = {High Throughput Reproducible Literate Phylogenetic Analysis},
  date = {2023-03},
  volume = {},
  number = {},
  keywords = {conference},
}

@misc{goswamiUnifiedSoftwareDesign2023,
  title = {Unified {{Software Design Patterns}} for {{Simulated Annealing}}},
  author = {Goswami, Rohit and S., Ruhila and Goswami, Amrita and Goswami, Sonaly and Goswami, Debabrata},
  date = {2023-02-06},
  number = {arXiv:2302.02811},
  eprint = {2302.02811},
  eprinttype = {arxiv},
  primaryclass = {physics},
  publisher = {{arXiv}},
  url = {http://arxiv.org/abs/2302.02811},
  urldate = {2023-02-10},
  abstract = {Any optimization alogrithm programming interface can be seen as a black-box function with additional free parameters. In this spirit, simulated annealing (SA) can be implemented in pseudo-code within the dimensions of single slide with free parameters relating to the annealing schedule. Such an implementation however, neglects necessarily much of the structure necessary to take advantage of advances in computing resources, and algorithmic breakthroughs. Simulated annealing is often introduced in myriad disciplines, from discrete examples like the Traveling Salesman Problem (TSP) to molecular cluster potential energy exploration or even explorations of a protein's configurational space. Theoretical guarantees also demand a stricter structure in terms of statistical quantities, which cannot simply be left to the user. We will introduce several standard paradigms and demonstrate how these can be "lifted" into a unified framework using object oriented programming in Python. We demonstrate how clean, interoperable, reproducible programming libraries can be used to access and rapidly iterate on variants of Simulated Annealing in a manner which can be extended to serve as a best practices blueprint or design pattern for a data-driven optimization library.},
  archiveprefix = {arXiv},
  keywords = {preprint},
}

@article{goswamiWailordParsersReproducibility2022,
  title = {Wailord: {{Parsers}} and {{Reproducibility}} for {{Quantum Chemistry}}},
  shorttitle = {Wailord},
  author = {Goswami, Rohit},
  date = {2022-07},
  journaltitle = {Proceedings of the 21st Python in Science Conference},
  pages = {193--197},
  doi = {10.25080/majora-212e5952-021},
  url = {https://conference.scipy.org/proceedings/scipy2022/rohit_goswami_wailord.html},
  urldate = {2022-07-14},
  eventtitle = {Proceedings of the 21st {{Python}} in {{Science Conference}}},
  keywords = {conference},
}

@article{stateOfFortran2022,
  author = {Kedward, Laurence and Aradi, Balint and Certik, Ondrej and
  Curcic, Milan and Ehlert, Sebastian and Engel, Philipp and Goswami,
  Rohit and Hirsch, Michael and Lozada-Blanco, Asdrubal and Magnin,
  Vincent and Markus, Arjen and Pagone, Emanuele and Pribec,
  Ivan and Richardson, Brad and Snyder, Harris,
  and Urban, John and Vandenplas, Jeremie},
  journal = {Computing in Science \& Engineering},
  title = {The State of Fortran},
  date = {2022-04},
  archivePrefix = {arXiv},
  eprint = {2203.15110},
  eprinttype = {arxiv},
  keywords = {journal, selected},
  doi = {10.1109/MCSE.2022.3159862},
}

@inproceedings{goswamiSemiSupervisedApproachesUltrafast2021,
  title = {Semi-{{Supervised Approaches}} to {{Ultrafast Pulse
                  Shaping}}},
  booktitle = {{{ICOL}}-2019},
  author = {Goswami, Rohit and Goswami, Amrita and Goswami, Debabrata},
  editor = {Singh, Kehar and Gupta, A. K. and Khare, Sudhir and Dixit,
                  Nimish and Pant, Kamal},
  date = {2021},
  pages = {747--749},
  publisher = {{Springer}},
  location = {{Singapore}},
  doi = {10.1007/978-981-15-9259-1_172},
  url = {10.1007/978-981-15-9259-1_172},
  abstract = {Spatiotemporal control aspects of pulsed laser experiments
                  rely on the ability to modulate the shape of the generated
                  pulses efficiently. Drawing from current state-of-the-art
                  theoretical aspects of computational simulations to reduce the
                  sim-to-real bottlenecks, we devise a novel schematic for the
                  generation of on-the-fly calibrated pulse trains with more
                  accountability than existing techniques under the domain of
                  optimal control theory. The techniques presented further
                  diminish the divide between experiment and theory.},
  annotation = {00000},
  isbn = {9789811592591},
  langid = {english},
  series = {Springer {{Proceedings}} in {{Physics}}},
  keywords = {conference},
}

@article{theeyancheriTranslationalRotationalDynamics2020,
  title = {Translational and Rotational Dynamics of a Self-Propelled
                  {{Janus}} Probe in Crowded Environments},
  author = {Theeyancheri, Ligesh and Chaki, Subhasish and Samanta,
                  Nairhita and Goswami, Rohit and Chelakkot, Raghunath and
                  Chakrabarti, Rajarshi},
  date = {2020-08-05},
  journaltitle = {Soft Matter},
  shortjournal = {Soft Matter},
  publisher = {{The Royal Society of Chemistry;
                  http://web.archive.org/web/20200805122230/https://pubs.rsc.org/en/content/articlelanding/2020/sm/d0sm00339e}},
  issn = {1744-6848},
  doi = {10.1039/D0SM00339E},
  abstract = {We computationally investigate the dynamics of a
                  self-propelled Janus probe in crowded environments. The
                  crowding is caused by the presence of viscoelastic polymers or
                  non- viscoelastic disconnected monomers. Our simulations show
                  that the translational, as well as rotational mean square
                  displacements, have a distinctive three-step growth for fixed
                  values of self-propulsion force, and steadily increase with
                  self-propulsion, irrespective of the nature of the crowder. On
                  the other hand, in the absence of crowders, the rotational
                  dynamics of the Janus probe is independent of self-propulsion
                  force. On replacing the repulsive polymers with sticky ones,
                  translational and rotational mean square displacements of the
                  Janus probe show a sharp drop. Since different faces of a
                  Janus particle interact differently with the environment, we
                  show that the direction of self-propulsion also affects its
                  dynamics. The ratio of long-time translational and rotational
                  diffusivities of the self-propelled probe with a fixed
                  self-propulsion, when plotted against the area fraction of the
                  crowders, passes through a minima and at higher area fraction
                  merges to its value in the absence of the crowder. This points
                  towards the decoupling of translational and rotational
                  dynamics of the self-propelled probe at intermediate area
                  fraction of the crowders. However, such
                  translational-rotational decoupling is absent for passive
                  probes.},
  keywords = {journal},
  archivePrefix = {arXiv},
  eprint = {2008.02089},
  eprinttype = {arxiv},
  langid = {english},
}

@article{Goswami2020,
  author = {Goswami, Rohit and Goswami, Amrita and Singh, Jayant Kumar},
  title = {d-SEAMS: Deferred Structural Elucidation Analysis for
                  Molecular Simulations},
  journal = {Journal of Chemical Information and Modeling},
  year = {2020},
  month = {3},
  day = {20},
  publisher = {American Chemical Society},
  abstract = {Structural analyses are an integral part of computational
                  research on nucleation and supercooled water, whose accuracy
                  and efficiency can impact the validity and feasibility of such
                  studies. The underlying molecular mechanisms of these often
                  elusive and computationally expensive processes can be
                  inferred from the evolution of ice-like structures, determined
                  using appropriate structural analysis techniques. We present
                  d-SEAMS, a free and open-source post-processing engine for the
                  analysis of molecular dynamics trajectories, which is
                  specifically able to qualitatively classify ice structures, in
                  both strong confinement and bulk systems. For the first time,
                  recent algorithms for confined ice structure determination
                  have been implemented, along with topological network criteria
                  for bulk ice structure determination. We also propose and
                  validate a new order parameter for identifying the building
                  blocks of quasi-two-dimensional ice. Recognizing the need for
                  customization in structural analysis, d-SEAMS has a unique
                  code architecture, built with nix, employing a YAML-Lua
                  scripting pipeline. The software has been designed to be
                  user-friendly and extensible. The engine outputs are
                  compatible with popular graphics software suites, allowing for
                  immediate visual insights into the systems studied. We
                  demonstrate the features of d-SEAMS by using it to analyze
                  nucleation in the bulk regime and for quasi-one and
                  quasi-two-dimensional systems. Structural time evolution and
                  quantitative metrics are determined for heterogenous ice
                  nucleation on a silver-exposed b-AgI surface, homogenous ice
                  nucleation, flat monolayer square ice formation and freezing
                  of an ice nanotube.},
  issn = {1549-9596},
  doi = {10.1021/acs.jcim.0c00031},
  archivePrefix = {arXiv},
  eprint = {1909.09830},
  eprinttype = {arxiv},
  keywords = {journal, selected},
}

@inproceedings{goswamiQubitNetworkBarriers2019,
  title = {Qubit {{Network Barriers}} to {{Deep Learning}}},
  booktitle = {2019 {{Workshop}} on {{Recent Advances}} in {{Photonics}} ({{WRAP}})},
  author = {Goswami, Rohit and Goswami, Amrita and Goswami, Debabrata},
  date = {2019-12},
  pages = {1--3},
  issn = {null},
  doi = {10.1109/WRAP47485.2019.9013687},
  eventtitle = {2019 {{Workshop}} on {{Recent Advances}} in {{Photonics}} ({{WRAP}})},
  keywords = {conference},
}

@article{goswamiDonPullPunches2019,
  langid = {english},
  title = {Don’t Pull Punches in Peer Review},
  volume = {574},
  doi = {10.1038/d41586-019-03024-2},
  journaltitle = {Nature},
  date = {2019-10-08},
  pages = {176-176},
  author = {Goswami, Rohit},
  keywords = {journal},
}

@article{prerRoh19,
  langid = {english},
  title = {Study of Ice Nucleation on Silver Iodide Surface with
                  Defects},
  issn = {0026-8976, 1362-3028},
  doi = {10.1080/00268976.2019.1657599},
  abstract = {In this work, we have considered the crystallisation
                  behaviour of supercooled water in the presence of surface
                  defects of varying size (surface fraction, α from 1 to 0.5).
                  Ice nucleation on Ag exposed βAgI (0001 plane) surface is
                  investigated by molecular dynamics simulation at a temperature
                  of 240 K. For systems with α {$>$} 0.67, the surface layers
                  crystallise within 150 ns. In the system with defects, we
                  observe two distinct stacking patterns in the layers near the
                  surface and find that systems with AA stacking cause a
                  monotonic decrease in the early nucleation dynamics with an
                  increase in defect size. Where AB stacking (α = 0.833) is
                  observed, the effect of the defect is diminished and the
                  dynamics are similar to the plain AgI surface. This is
                  supported by the variation in the orientational dynamics,
                  hydrogen bond network stability, and tetrahedrality with
                  respect to the defects. We quantify results in terms of the
                  network topology using double-diamond cages (DDCs) and
                  hexagonal cages (HCs). The configurations of the initially
                  formed layers of ice strongly affect the subsequent growth
                  even at long timescales. We assert that the retarded ice
                  growth due to defects can be explained by the relative
                  increase in DDCs with respect to HCs.},
  journaltitle = {Molecular Physics},
  shortjournal = {Molecular Physics},
  date = {2019-08-25},
  pages = {1-13},
  keywords = {journal},
  author = {{Prerna} and Goswami, Rohit and Metya, Atanu K. and
                  Shevkunov, S. V. and Singh, Jayant K.},
}

@inproceedings{gosURSI19,
  author = {Rohit Goswami and Amrita Goswami and Debabrata Goswami},
  booktitle = {2019 URSI Asia-Pacific Radio Science Conference (AP-RASC)},
  title = {Space Filling Curves: Heuristics For Semi Classical Lasing
                  Computations},
  date = {2019},
  pages = {1-4},
  abstract = {For semi classical lasing, the FDTD (finite difference time
                  domain) formulation including nonlinearities is often used. We
                  determine the computational efficiency of such schemes
                  quantitatively and present a hueristic based on space filling
                  curves to minimize complexity. The sparse matrix kernel is
                  shown to be optimized by the utilization of Bi-directional
                  Incremental Compressed Row Storage (BICRS). Extensions to high
                  performance clusters and parallelization are also derived.},
  keywords = {conference},
  doi = {10.23919/URSIAP-RASC.2019.8738612},
  month = {3},
}

@article{RDGos16,
  author = {Rohit Goswami and Debabrata Goswami},
  title = {{Quantum Distributed Computing with Shaped Laser Pulses.}},
  journal = {13th International Conference on Fiber Optics and
                  Photonics},
  date = {2016},
  doi = {10.1364/photonics.2016.w4c.3},
  keywords = {conference},
}