activity
20042023
most citedSupplementary information for "Quantum supremacy using a programmable superconducting processor"

7.2k citations · 16.1k across the 100 of their papers we have counts for

collaborators

106 papers

quant-ph2023★ 48 cited

Quantum algorithms: A survey of applications and end-to-end complexities

Alexander M. Dalzell, Sam McArdle, Mario Berta +10

The anticipated applications of quantum computers span across science and industry, ranging from quantum chemistry and many-body physics to optimization, finance, and machine learn…

quant-ph2023★ 61 cited

Demonstrating a long-coherence dual-rail erasure qubit using tunable transmons

Harry Levine, Arbel Haim, Jimmy S. C. Hung +110

Quantum error correction with erasure qubits promises significant advantages over standard error correction due to favorable thresholds for erasure errors. To realize this advantag…

quant-ph2023★ 20 cited

Quantum Thermal State Preparation

Chi-Fang Chen, Michael J. Kastoryano, Fernando G. S. L. Brandão +1

Preparing ground states and thermal states is essential for simulating quantum systems on quantum computers. Despite the hope for practical quantum advantage in quantum simulation,…

quant-ph2023★ 7 cited

Sparse random Hamiltonians are quantumly easy

Chi-Fang, Chen, Alexander M. Dalzell +3

A candidate application for quantum computers is to simulate the low-temperature properties of quantum systems. For this task, there is a well-studied quantum algorithm that perfor…

quant-ph2022★ 12 cited

Mind the gap: Achieving a super-Grover quantum speedup by jumping to the end

Alexander M. Dalzell, Nicola Pancotti, Earl T. Campbell +1

We present a quantum algorithm that has rigorous runtime guarantees for several families of binary optimization problems, including Quadratic Unconstrained Binary Optimization (QUB…

quant-ph2022★ 18 cited

End-to-end resource analysis for quantum interior point methods and portfolio optimization

Alexander M. Dalzell, B. David Clader, Grant Salton +8

We study quantum interior point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio optimization (PO). We provide a complete quant…