Bridge of Ψ's (BOPS) is a generative model that learns to transform quantum circuits into equivalent, optimized versions using Schr"odinger bridges and a custom denoiser architecture. Trained on data engineered to challenge existing optimizers, BOPS achieves a 2.46× reduction in gate count and a 2.45× reduction in depth on 8‑qubit, 64‑depth Clifford+$T$ circuits, outperforming nine baseline optimizers. This work demonstrates the first successful application of generative machine learning to quantum circuit optimization, expanding the quantum compilation stack with learned techniques.
By Lino S. Hofstetter, Lia Yeh, Prakash Murali
arXiv:2510. 12430v2 Announce Type: replace-cross Abstract: Translating a general quantum circuit on a specific hardware topology with a reduced set of available gates, also known as transpilation, comes with a substantial increase in the length of the equivalent circuit.
By Bodo Rosenhahn, Tobias J. Osborne, Christoph Hirche
arXiv:2510. 03389v2 Announce Type: replace-cross Abstract: Current quantum computers require algorithms that use limited resources economically.
By Jonas J\"ager, Philipp Els\"asser, Elham Torabian
arXiv:2607. 29134v1 Announce Type: cross Abstract: Recent work suggests that relational database management systems (RDBMSs) can execute quantum circuit simulation by compiling the simulation into SQL workloads (primarily join-and-aggregate tensor contractions).
By Andrei Ilinescu, Aadi Patwardhan, Rihan Hai
arXiv:2606. 11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approximation parameters -- such as bond dimension thresholds -- remains a costly trial-and-error process.
By Honjar Xing, Yehong Jiang, Xianbang Wang, Zehua Wang, Zhicheng Jiang
Quantum circuit optimization for fault-tolerant computing requires exact functional equivalence while minimizing expensive non-Clifford resources such as T gates. We study this problem using a compact 44.