6 papers
Fault-Tolerant Heisenberg-Limited Quantum Sensing
Lorcan O. Conlon, Yu-Xin Wang, Erfan Abbasgholinejad +3
Quantum sensors hold great promise for achieving better sensitivity in the measurement of physical quantities compared to their classical counterparts. However, the conditions unde…
Multiparameter function estimation for general Hamiltonians
Erfan Abbasgholinejad, Sean R. Muleady, Jacob Bringewatt +2
Estimation of physical parameters encoded in a Hamiltonian is a central task in quantum sensing and learning. While the ultimate precision limit for estimating a single parameter c…
Lieb-Mattis states for robust entangled differential phase sensing
Raphael Kaubruegger, Diego Fallas Padilla, Athreya Shankar +10
We explore a two-node, entanglement-enhanced sensor network for differential phase sensing that exploits decoherence-free subspaces to suppress common-mode noise, a primary limitat…
Optimally learning functions in interacting quantum sensor networks
Erfan Abbasgholinejad, Sean R. Muleady, Jacob Bringewatt +4
Estimating extensive combinations of local parameters in distributed quantum systems is a central problem in quantum sensing, with applications ranging from magnetometry to timekee…
Theory of quantum-enhanced interferometry with general Markovian light sources
Erfan Abbasgholinejad, Daniel Malz, Ana Asenjo-Garcia +1
Quantum optical systems comprising quantum emitters interacting with engineered optical modes generate non-classical states of light that can be used as resource states for quantum…
Cosmic velocity, density and halo mass function: Insights from deep learning
Saba Etezad-Razavi, Erfan Abbasgholinejad, Mohammad-Hadi Sotoudeh +3
We discuss an implementation of a deep learning framework to gain insight into dark matter (DM) structure formation. We investigate the contribution of velocity and density field i…