activity
20242026
most citedUnlocking Quantum Optimization: A Use Case Study on NISQ Systems

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.dis-nn2026

Neural Quantum States for Nuclear Magnetic Resonance Spectroscopy

Bharadwaj Chowdary Mummaneni, Bo Xing

Predicting a nuclear magnetic resonance (NMR) spectrum from first principles requires propagating a quantum state of dimension for coupled spins, which becomes intractabl…

cond-mat.str-el2026

Hidden Unit Interpretability in RBM Quantum States:Encoding Antiferromagnetic Order in Heisenberg Spin Rings

Bharadwaj Chowdary Mummaneni, Manas Sajjan

We investigate how Restricted Boltzmann Machines (RBMs) encode antiferromagnetic order when trained as variational ansätze for one-dimensional Heisenberg spin rings with periodic b…

quant-ph2025

Resource-efficient Variational Compilation of Block-Encodings

Leon Rullkötter, Sebastian Weber, Vamshi Mohan Katukuri +2

Block-encoding operators are one of the essential components in quantum algorithms based on Quantum Signal Processing. Their gate complexity largely determines the overall gate com…

quant-ph2025

Optimizing Superconducting Qubit Performance: A Theoretical Framework for Design, Analysis, and Calibration

Sirshi S Ram, Muralikrishna Molli, Vamshi Mohan Katukuri +1

Designing a qubit architecture is one of the most critical challenges in achieving scalable and fault-tolerant quantum computing as the performance of a quantum computer is heavily…

quant-ph2024

Quantum Annealing based Feature Selection in Machine Learning

Daniel Pranjic, Bharadwaj Chowdary Mummaneni, Christian Tutschku

Feature selection is crucial for enhancing the accuracy and efficiency of machine learning (ML) models. This work investigates the utility of quantum annealing for the feature sele…

quant-ph2024★ 1 cited

Unlocking Quantum Optimization: A Use Case Study on NISQ Systems

Andreas Sturm, Bharadwaj Mummaneni, Leon Rullkötter

The major advances in quantum computing over the last few decades have sparked great interest in applying it to solve the most challenging computational problems in a wide variety…