activity
20082026
most citedClassical Shadows With Noise

109 citations · 843 across the 53 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

quant-ph2023★ 22 cited

Error-mitigated fermionic classical shadows on noisy quantum devices

Bujiao Wu, Dax Enshan Koh

Efficiently estimating fermionic Hamiltonian expectation values is vital for simulating various physical systems. Classical shadow (CS) algorithms offer a solution by reducing the…

quant-ph2023★ 2 cited

A quantum tug of war between randomness and symmetries on homogeneous spaces

Rahul Arvind, Kishor Bharti, Jun Yong Khoo +2

We explore the interplay between symmetry and randomness in quantum information. Adopting a geometric approach, we consider states as -equivalent if related by a symmetry transf…

quant-ph2023★ 20 cited

Variational Quantum Simulation of Partial Differential Equations: Applications in Colloidal Transport

Fong Yew Leong, Dax Enshan Koh, Wei-Bin Ewe +1

We assess the use of variational quantum imaginary time evolution for solving partial differential equations. Our results demonstrate that real-amplitude ansaetze with full circula…

quant-ph2023★ 2 cited

Fundamental Limitations on Communication over a Quantum Network

Junjing Xing, Tianfeng Feng, Zhaobing Fan +4

Entanglement, a fundamental feature of quantum mechanics, has long been recognized as a valuable resource in enabling secure communications and surpassing classical limits. However…

quant-ph2023★ 19 cited

Pseudorandom unitaries are neither real nor sparse nor noise-robust

Tobias Haug, Kishor Bharti, Dax Enshan Koh

Pseudorandom quantum states (PRSs) and pseudorandom unitaries (PRUs) possess the dual nature of being efficiently constructible while appearing completely random to any efficient q…

quant-ph2023★ 34 cited

An Expressive Ansatz for Low-Depth Quantum Approximate Optimisation

V. Vijendran, Aritra Das, Dax Enshan Koh +2

The quantum approximate optimisation algorithm (QAOA) is a hybrid quantum-classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple…