109 citations · 843 across the 53 of their papers we have counts for
57 papers
Training Variational Quantum Algorithms Is NP-Hard, Even Locally
Dax Enshan Koh, Triscia Mundo, Iosif Sakos +1
Variational quantum algorithms (VQAs) generally rely on classical optimization to train parameterized quantum circuits. This training seeks to minimize an objective function, and i…
Function-like pseudorandom unitaries generate pseudorandom quantum processes
Zitai Xu, Rahul Arvind, Kishor Bharti +5
Haar-random unitaries provide a canonical model of generic random quantum evolution, but they typically have exponential description and circuit complexity. Although pseudorandom u…
Verification Complexity and Extension of Classical Shadows
Georgios Karaiskos, Asad Raza, Dorian Rudolph +2
Classical shadows are an influential framework for compressing copies of a given quantum state into classical data , enabling many properties of to be predicted from rel…
Quantum Fidelity Landscape-Guided Prior Calibration for Single-Circuit QGAN Image Generation
Xue Yang, Rigui Zhou, Dax Enshan Koh +5
Quantum Generative Adversarial Networks (QGANs) have emerged as representative generative models in the Noisy Intermediate-Scale Quantum (NISQ) era and have attracted increasing at…
Practical Error Suppression and Mitigation for Reliable Quantum Computing
Han-Ze Li, Mengjie Yang, Xianquan Yan +3
Quantum computing is entering a transitional regime between noisy intermediate-scale quantum (NISQ) processing and early fault-tolerant quantum computation (FTQC), in which increas…
Real Classical Shadows with Noise
Atharva Hingane, Dax Enshan Koh
The real classical shadows protocol of West et al. replaces the unitary (Clifford) ensemble of the Huang--Kueng--Preskill scheme by the orthogonal (real Clifford) ensemble, and for…