Breaking RSA Security With A Low Noise D-Wave 2000Q Quantum Annealer: Computational Times, Limitations And Prospects

预测量子退火器上伊辛模型（Ising Model）的性能

Predicting Ising Model Performance on Quantum Annealers

该研究提出判定量子退火绝热演化相对经典启发式算法优势前景的框架，分析伊辛模型项的关系可预判问题适配性，实验验证下一代D-Wave原型机性能优于现有Advantage退火器。

Quantum computing for finance: overview and prospects

We discuss how quantum computation can be applied to financial problems, providing an overview of current approaches and potential prospects. We review quantum optimization algorithms, and expose how quantum annealers can be used to optimize portfolios, find arbitrage opportunities, and perform credit scoring. We also discuss deep-learning in finance, and suggestions to improve these methods through quantum machine learning. Finally, we consider quantum amplitude estimation, and how it can result in a quantum speed-up for Monte Carlo sampling. This has direct applications to many current finan…

用于素数分解的HUBO和QUBO模型

HUBO and QUBO models for Prime factorization

本文提出一种基于D-Wave量子计算机的素数分解方法，通过将素数表示为量子比特并构建高阶无约束优化（HUBO）模型代价函数，利用混合求解器成功分解了大数，威胁了RSA密码系统的安全性。

变分相干量子退火

Variational Coherent Quantum Annealing

提出经典-量子混合的变分相干量子退火（VCQA），通过分段调度函数和首尾消失的辅助哈密顿量，在相干时间内显著降低基态误差。

Analog Errors in Quantum Annealing: Doom and Hope

Quantum annealing has the potential to provide a speedup over classical algorithms in solving optimization problems. Just as for any other quantum device, suppressing Hamiltonian control errors will be necessary before quantum annealers can achieve speedups. Such analog control errors are known to lead to $J$-chaos, wherein the probability of obtaining the optimal solution, encoded as the ground state of the intended Hamiltonian, varies widely depending on the control error. Here, we show that $J$-chaos causes a catastrophic failure of quantum annealing, in that the scaling of the time-to-solu…

工业环境中的量子计算：我们目前的处境与未来的方向？

Quantum Computing in Industrial Environments: Where Do We Stand and Where Are We Headed?

本文探讨了量子计算在工业环境中的现状与未来，介绍了基于门的量子计算机、量子退火机和张量网络三大范式，并分析了其在装箱、调度和路径规划等工业应用中的潜力与未来挑战。