collaborators

6 papers

cond-mat.stat-mech2026

Equivariant learning of a transferable three-dimensional classical density functional

Bingqing Cheng

Liquids exhibit collective behavior that depends sensitively on thermodynamic conditions, interfaces and confinement, yet predicting each new state commonly requires a separate ato…

physics.optics2026

Measurement-Adapted Eigentask Representations for Photon-Limited Optical Readout

Tianyang Chen, Mandar M. Sohoni, Saeed A. Khan +5

Optical readout in low-light imaging is fundamentally limited by measurement noise, including photon shot noise, detector noise, and quantization error. In this regime, downstream…

quant-ph2026

Quantum computational displacement sensing

Sridhar Prabhu, Saeed A. Khan, Xingrui Song +7

Quantum computational sensing (QCS) combines quantum sensing with quantum computing to extract task-relevant information from the physical world. QCS can in principle achieve an ac…

quant-ph2026

Overcoming the Coherence Time Barrier in Quantum Machine Learning on Temporal Data

Fangjun Hu, Saeed A. Khan, Nicholas T. Bronn +4

Practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a mac…

quant-ph2026

Single-shot Quantum State Classification via Nonlinear Quantum Amplification

Elif Cüce, Elif Cüce, Saeed A. Khan +4

Quantum amplifiers are intrinsically nonlinear systems whose performance limits are set by quantum mechanics. In quantum measurement, amplifier operation is conventionally optimize…

quant-ph2025

A neural processing approach to quantum state discrimination

Saeed A. Khan, Fangjun Hu, Gerasimos Angelatos +2

Although linear quantum amplification has proven essential to the processing of weak quantum signals, extracting higher-order quantum features such as correlations in principle dem…