85 citations · 96 across the 10 of their papers we have counts for
9 papers · 1 filter
Variational Joint Magnetometry and Gradiometry on Dipolar Spin Chains
Priyam Srivastava, Xin Jin, Junyu Liu +4
Estimating a uniform magnetic field B0 and its spatial gradient g on a dipolar-coupled spin chain calls for a multiparameter figure of merit. The GHZ state, optimal for single-para…
Optimizing Compilation for Distributed Quantum Computing via Clustering and Annealing
Ruilin Zhou, Jinglei Cheng, Yuhang Gan +2
Efficiently mapping quantum programs onto Distributed quantum computing (DQC) are challenging, particularly when considering the heterogeneous quantum processing units (QPUs) with…
Quantum repeaters enhanced by vacuum beam guides
Yu Gan, Mohadeseh Azari, Nitish Kumar Chandra +4
The development of large-scale quantum communication networks faces critical challenges due to photon loss and decoherence in optical fiber channels. These fundamentally limit tran…
Towards identifying possible fault-tolerant advantage of quantum linear system algorithms in terms of space, time and energy
Yue Tu, Mark Dubynskyi, Mohammadhossein Mohammadisiahroudi +5
Quantum computing, a prominent non-Von Neumann paradigm beyond Moore's law, can offer superpolynomial speedups for certain problems. Yet its advantages in efficiency for tasks like…
The Stabilizer Bootstrap of Quantum Machine Learning with up to 10000 qubits
Yuqing Li, Jinglei Cheng, Xulong Tang +3
Quantum machine learning is considered one of the flagship applications of quantum computers, where variational quantum circuits could be the leading paradigm both in the near-term…
Scalable Community Detection Using Quantum Hamiltonian Descent and QUBO Formulation
Jinglei Cheng, Ruilin Zhou, Yuhang Gan +2
We present a quantum-inspired algorithm that utilizes Quantum Hamiltonian Descent (QHD) for efficient community detection. Our approach reformulates the community detection task as…
Quantum-machine-assisted Drug Discovery
Yidong Zhou, Jintai Chen, Jinglei Cheng +8
Drug discovery is lengthy and expensive, with traditional computer-aided design facing limits. This paper examines integrating quantum computing across the drug development cycle t…
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
qSIEVE: Efficient qLDPC Memory via Systolic Movement in Atom Arrays
Joshua Viszlai, Willers Yang, Sophia Fuhui Lin +4
As quantum machines have scaled up in their number of qubits, significant research has turned towards increasing their fidelity with quantum error correction codes. Although promis…