Ajay Melekamburath

PhD Candidate, Virginia Tech

learn · build · scale

About

I am a PhD candidate in the Valeev Research Group at Virginia Tech. My research is on coupled-cluster methods and their application to excited states and molecular properties, and my current focus is truncated unitary coupled-cluster methods for excited states.

I also build the software these methods run on: SeQuant, which derives a method's equations symbolically and then drives their numerical evaluation, and MPQC, which runs coupled cluster across distributed-memory clusters.

Before Virginia Tech, I earned an integrated BS-MS at IISER Thiruvananthapuram, where I developed empirical interaction potentials for layered materials.

Work

SeQuant

C++ · CAS · symbolic tensor algebra

Takes a many-body method from equations to numbers by joining symbolic derivation with numerical evaluation. It automates the slow, error-prone steps in between, which shortens the path from a new idea to results. I developed SeQuant's many-body operator interface and its coupled-cluster capabilities, including alternative ansätze, linear response, and equation-of-motion methods.

Equation to numbers

Molecular properties

Massively Parallel Quantum Chemistry (MPQC)

C++ · MPI · TiledArray · MADNESS

A distributed-memory electronic structure package built on the TiledArray tensor framework and the MADNESS parallel runtime. I work on its general-order coupled-cluster code: ground and excited states, linear-response properties, and electric-field perturbations.

Sparse tiled arrays

4 × 4 distributed tiles

Katal

C++20 · CUDA · cuTENSOR

A C++20 einsum library for GPU tensor contractions. You write the equation, and Katal sets up and caches the cuTENSOR plan behind it. Deployed with SeQuant for coupled-cluster evaluations.

On the GPU

Einsum contraction

Experience

Graduate Student

Aug 2022 – present

Valeev Research Group, Virginia Tech

Research Assistant

Jun 2021 – Jun 2022

R. S. Swathi Group, IISER Thiruvananthapuram

Master's Student

Jul 2020 – Apr 2021

R. S. Swathi Group, IISER Thiruvananthapuram

Graduate Teaching Assistant, General Chemistry Lab

Aug 2022 – Apr 2023

Department of Chemistry, Virginia Tech

Publications

SeQuant framework for symbolic and numerical tensor algebra. I. Core capabilitiesThe Journal of Chemical PhysicsSeQuant is an open-source library for symbolic algebra of tensors over commutative (scalar) and non-commutative (operator) rings. The key innovation supporting most of its functionality is a graph-theoretic tensor network (TN) canonicalizer that can handle TNs with symmetries faster than their standard group-theoretic counterparts. The TN canonicalizer is used for the routine simplification of conventional tensor expressions, for optimizing the application of Wick’s theorem (used to canonicalize products of tensors over operator fields), and for the manipulation of the intermediate representation leading to the numerical evaluation. Notable features of SeQuant include support for noncovariant TNs (featuring hyperedges in their graphical representation and often arising from tensor decompositions) and for tensors with modes that depend parametrically on indices of other tensor modes (such dependencies between degrees of freedom are naturally viewed as nesting of tensors, or “tensors of tensors” arising in block-wise data compressions in data science and modern quantum simulation). SeQuant blurs the line between pure symbolic manipulation/code generation and numerical evaluation by including compiler-like components to optimize and directly interpret tensor expressions using external numerical tensor algebra frameworks. The SeQuant source code is available at https://github.com/ValeevGroup/SeQuant.2026doi:10.1063/5.0311913

2026

B. Gaudel, R. G. Adam, A. Melekamburath, C. Masteran, N. Teke, A. Besharatnik, A. Köhn, E. F. Valeev

The Journal of Chemical Physics

Adsorption of Aromatic Hydrocarbons on Graphene: From Energy Decomposition to Stable Adsorption GeometriesChemistry – An Asian JournalThe quantitative prediction of the π–π interaction energetics of the adsorption of polycyclic aromatic hydrocarbons (PAHs) on graphene remains a challenge, prompting the need for computationally efficient yet reliable methods. Herein, we investigated the intermolecular interactions of aromatic hydrocarbons, benzene, naphthalene, anthracene, pyrene, and coronene, with differently‐sized nanographene models using the symmetry‐adapted perturbation theory (SAPT) approach at the SAPT0 level. Convergence analysis of the total intermolecular interaction energies and the intervening components established circumcircumcoronene as the smallest nanographene model that can model the adsorption of the chosen aromatic hydrocarbons. The SAPT0 energies were then employed as the reference data for parametrizing an anisotropic analytic potential, namely the PAH anisotropic potential (PAHAP). The thus‐parametrized PAHAP was subsequently employed to predict the most stable adsorption geometries of aromatic hydrocarbons over graphene. The estimated interaction energies and equilibrium distances differed significantly from those obtained using the original PAHAP parametrized against SAPT(DFT) interaction energies for small PAH dimers ( J. Chem. Theory Comput ., 2010 , 6 , 683–695). Nonetheless, single‐point density functional theory electronic energy computation of both sets of PAHAP data yielded very similar energies, suggesting the competence of PAHAP parametrized against a comparatively low‐demand computational approach like SAPT0 in modeling π–π interactions.2026doi:10.1002/asia.70603

2026

M. Rajeevan, A. Melekamburath, R. S. Swathi

Chemistry – An Asian Journal

“Best” Iterative Coupled-Cluster Triples Model? More Evidence for 3CCThe Journal of Physical Chemistry ATo follow up on the unexpectedly good performance of several coupled-cluster models with approximate inclusion of 3-body clusters [ Rishi, V.; Valeev, E. F. J. Chem. Phys. 2019, 151, 064102 .] we performed a more complete assessment of the 3CC method [ Feller, D. . J. Chem. Phys. 2008, 129, 204105 .] for accurate computational thermochemistry in the standard HEAT framework. New spin-integrated implementation of the 3CC method applicable to closed- and open-shell systems utilizes a new automated toolchain for derivation, optimization, and evaluation of operator algebra in many-body electronic structure. We found that with a double-ζ basis set the 3CC correlation energies and their atomization energy contributions are almost always more accurate (with respect to the CCSDTQ reference) than the CCSDT model as well as the standard CCSD(T) model. The mean absolute errors in cc-pVDZ {3CC, CCSDT, and CCSD(T)} electronic (per valence electron) and atomization energies relative to the CCSDTQ reference for the HEAT data set [ Tajti, A. . J. Chem. Phys. 2004, 121, 11599–11613.], were {24, 70, 122} μ E h / e and {0.46, 2.00, 2.58} kJ/mol, respectively. The mean absolute errors in the complete-basis-set limit {3CC, CCSDT, and CCSD(T)} atomization energies relative to the HEAT model reference, were {0.52, 2.00, and 1.07} kJ/mol, The significant and systematic reduction of the error by the 3CC method and its lower cost than CCSDT suggests it as a viable candidate for post-CCSD(T) thermochemistry applications, as well as the preferred alternative to CCSDT in general.2024doi:10.1021/acs.jpca.4c04667

2024

N. K. Teke, A. Melekamburath, B. Gaudel, E. F. Valeev

The Journal of Physical Chemistry A

All publications →

Education

PhD, Chemistry

2022 – present

Computational and Theoretical Chemistry

Virginia Tech

Integrated BS-MS

2016 – 2021

Major in Chemical Sciences, Minor in Physical Sciences

IISER Thiruvananthapuram

Skills

Electronic structure

Coupled-cluster methods
Unitary coupled-cluster
Molecular response theory
Symbolic tensor algebra

Programming

C++
Python
CUDA
Boost

High-performance computing

MPI
MADNESS
cuTENSOR

Tooling

CMake
Git
GitHub Actions
LLDB