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20212026
most citedImportance of Kernel Bandwidth in Quantum Machine Learning

64 citations · 214 across the 31 of their papers we have counts for

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14 papers · 1 filter

quant-ph2025

Compilation Pipeline for Predicting Algorithmic Break-Even in an Early-Fault-Tolerant Surface Code Architecture

Tianyi Hao, Joseph Sullivan, Sivaprasad Omanakuttan +2

Recent experimental progress in realizing surface code on hardware, including demonstrations of break-even logical memory on devices with up to hundreds of physical qubits, has mat…

quant-ph2025

Realization of a Quantum Streaming Algorithm on Long-lived Trapped-ion Qubits

Pradeep Niroula, Shouvanik Chakrabarti, Steven Kordonowy +30

Large classical datasets are often processed in the streaming model, with data arriving one item at a time. In this model, quantum algorithms have been shown to offer an unconditio…

quant-ph2025

Certified randomness amplification by dynamically probing remote random quantum states

Minzhao Liu, Pradeep Niroula, Matthew DeCross +49

Cryptography depends on truly unpredictable numbers, but physical sources emit biased or correlated bits. Quantum mechanics enables the amplification of imperfect randomness into n…

quant-ph2025

End-to-end quantum algorithms for tensor problems

Enrico Fontana, Sivaprasad Omanakuttan, Junhyung Lyle Kim +4

We present a comprehensive end-to-end quantum algorithm for tensor problems, including tensor PCA and planted kXOR, that achieves potential superquadratic quantum speedups over cla…

quant-ph2025

Spin-Boson Mapping of the Quantum Approximate Optimization Algorithm

Sami Boulebnane, Abid Khan, Minzhao Liu +4

The Quantum Approximate Optimization Algorithm (QAOA) achieves monotonically improving performance with circuit depth , yet the study of the high-depth regime has been obstructe…

quant-ph2025★ 3 cited

Threshold for Fault-tolerant Quantum Advantage with the Quantum Approximate Optimization Algorithm

Sivaprasad Omanakuttan, Zichang He, Zhiwei Zhang +9

Optimization is often cited as a promising application of quantum computers. However, the low degree of provable quantum speedups has led prior rigorous end-to-end resource analyse…

quant-ph2025

Iceberg Beyond the Tip: Co-Compilation of a Quantum Error Detection Code and a Quantum Algorithm

Yuwei Jin, Zichang He, Tianyi Hao +5

The rapid progress in quantum hardware is expected to make them viable tools for the study of quantum algorithms in the near term. The timeline to useful algorithmic experimentatio…

quant-ph2025

Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm

Anuj Apte, Shree Hari Sureshbabu, Ruslan Shaydulin +5

Quantum Approximate Optimization Algorithm (QAOA) is a promising quantum heuristic with empirical evidence of speedup over classical state-of-the-art for some problems. QAOA uses a…

quant-ph2025★ 33 cited

Certified randomness using a trapped-ion quantum processor

Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula +29

While quantum computers have the potential to perform a wide range of practically important tasks beyond the capabilities of classical computers, realizing this potential remains a…

quant-ph2025★ 3 cited

Applications of Certified Randomness

Omar Amer, Shouvanik Chakrabarti, Kaushik Chakraborty +8

Certified randomness can be generated with untrusted remote quantum computers using multiple known protocols, one of which has been recently realized experimentally. Unlike the ran…

quant-ph2025

qReduMIS: A Quantum-Informed Reduction Algorithm for the Maximum Independent Set Problem

Martin J. A. Schuetz, Romina Yalovetzky, Ruben S. Andrist +8

We propose and implement a quantum-informed reduction algorithm for the maximum independent set problem that integrates classical kernelization techniques with information extracte…

quant-ph2025★ 1 cited

Quantum Approximate Optimization Algorithm in Finite Size and Large Depth and Equivalence to Quantum Annealing

Sami Boulebnane, James Sud, Ruslan Shaydulin +1

The quantum approximate optimization algorithm (QAOA) and quantum annealing are two of the most popular quantum optimization heuristics. While QAOA is known to be able to approxima…

quant-ph2025★ 19 cited

Tensor networks for quantum computing

Aleksandr Berezutskii, Minzhao Liu, Atithi Acharya +25

In the rapidly evolving field of quantum computing, tensor networks serve as an important tool due to their multifaceted utility. In this paper, we review the diverse applications…

quant-ph2025

Non-Variational Quantum Random Access Optimization with Alternating Operator Ansatz

Zichang He, Rudy Raymond, Ruslan Shaydulin +1

Solving hard optimization problems is one of the most promising application domains for quantum computers due to the ubiquity of such problems in industry and the availability of b…