160 citations · 202 across the 7 of their papers we have counts for
8 papers
Symmetry Constraints Regularize Neural Quantum State Learning
Turbasu Chatterjee, Manas Sajjan, Songbo Xie +4
Neural quantum states (NQS) offer highly expressive variational wavefunctions, but their optimization is frequently bottlenecked by redundant parameters and poorly conditioned land…
Quantum Machine Learning for Complex Systems
Vinit Singh, Amandeep Singh Bhatia, Mandeep Kaur Saggi +2
Quantum machine learning (QML) is rapidly transitioning from theoretical promise to practical relevance across data-intensive scientific domains. In this Review, we provide a struc…
Maximal Entropy Formalism and the Restricted Boltzmann Machine
Vinit Singh, Rishabh Gupta, Manas Sajjan +3
The connection between the Maximum Entropy (MaxEnt) formalism and Restricted Boltzmann Machines (RBMs) is natural, as both give rise to a Boltzmann-like distribution with constrain…
Unlocking the power of global quantum gates with machine learning
Vinit Singh, Bin Yan
In conventional circuit-based quantum computing architectures, the standard gate set includes arbitrary single-qubit rotations and two-qubit entangling gates. This choice is not al…
Polynomially efficient quantum enabled variational Monte Carlo for training neural-network quantum states for physico-chemical applications
Manas Sajjan, Vinit Singh, Sabre Kais
Neural-network quantum states (NQS) offer a versatile and expressive alternative to traditional variational ansätze for simulating physical systems. Energy-based frameworks, like H…
Physics inspired quantum simulation of resonating valence bond states -- a prototypical template for a spin-liquid ground state
Manas Sajjan, Rishabh Gupta, Sumit Suresh Kale +3
Spin-liquids -- an emergent, exotic collective phase of matter -- have garnered enormous attention in recent years. While experimentally, many prospective candidates have been prop…
Imaginary components of out-of-time correlators and information scrambling for navigating the learning landscape of a quantum machine learning model
Manas Sajjan, Vinit Singh, Raja Selvarajan +1
We introduce and analytically illustrate that hitherto unexplored imaginary components of out-of-time correlators can provide unprecedented insight into the information scrambling…
Quantum Machine Learning for Chemistry and Physics
Manas Sajjan, Junxu Li, Raja Selvarajan +5
Machine learning (ML) has emerged into formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automat…