160 citations · 302 across the 8 of their papers we have counts for
10 papers
Benchmarking a machine-learning differential equations solver on a neutral-atom logical processor
Pauline Mathiot, Elio Garnaoui, Axel-Ugo Leriche +37
We report on a performance comparison between physical and logical computations on a prototypical machine-learning application: solving differential equations using quantum kernel…
Hamiltonian learning from time dynamics using variational algorithms
Rishabh Gupta, Raja Selvarajan, Manas Sajjan +2
The Hamiltonian of a quantum system governs the dynamics of the system via the Schrodinger equation. In this paper, the Hamiltonian is reconstructed in the Pauli basis using measur…
Dimensionality reduction with variational encoders based on subsystem purification
Raja Selvarajan, Manas Sajjan, Travis S. Humble +1
Efficient methods for encoding and compression are likely to pave way towards the problem of efficient trainability on higher dimensional Hilbert spaces overcoming issues of barren…
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…
Psitrum: An Open Source Simulator for Universal Quantum Computers
Mohammed Alghadeer, Eid Aldawsari, Raja Selvarajan +3
Quantum computing is a radical new paradigm for a technology that is capable to revolutionize information processing. Simulators of universal quantum computer are important for und…
Variational quantum circuits to prepare low energy symmetry states
Raja Selvarajan, Manas Sajjan, Sabre Kais
We explore how to build quantum circuits that compute the lowest energy state corresponding to a given Hamiltonian within a Symmetry subspace by explicitly encoding it into the cir…
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…
Prime Factorization Using Quantum Variational Imaginary Time Evolution
Raja Selvarajan, Vivek Dixit, Xingshan Cui +2
The road to computing on quantum devices has been accelerated by the promises that come from using Shor's algorithm to reduce the complexity of prime factorization. However, this p…
Training a quantum annealing based restricted Boltzmann machine on cybersecurity data
Vivek Dixit, Raja Selvarajan, Tamer Aldwairi +5
We present a real-world application that uses a quantum computer. Specifically, we train a RBM using QA for cybersecurity applications. The D-Wave 2000Q has been used to implement…
Training and Classification using a Restricted Boltzmann Machine on the D-Wave 2000Q
Vivek Dixit, Raja Selvarajan, Muhammad A. Alam +2
Restricted Boltzmann Machine (RBM) is an energy based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained u…