Building on our earlier program-evolution workflow guided by large language models (LLMs), we study weight-five bivariate bicycle (BB) and perturbed bivariate bicycle (PBB) codes. …
Quantum programs can suffer from quantum-specific code smells that cannot be captured by classical unit tests. We propose a framework that analyzes the existing programs released …
Keynote on using LLM-guided evolutionary program search (built on OpenEvolve) to discover 465 new bivariate-bicycle quantum LDPC codes, and what that stress test teaches about …
Quantum LDPC code discovery requires searching large algebraic design spaces while reliably certifying the parameters and equivalence classes of any candidates found. We present a …
We adapted Microsoft's QuantumKatas from Q# to Qiskit and turned them into a 350-task benchmark for evaluating how well LLMs write quantum code. We ran 16 models across 7 prompting …
We adapt Microsoft's QuantumKatas - a well-established quantum computing curriculum - from Q# to Qiskit, the most widely-adopted quantum computing framework, and package it with an …
Systems and techniques that facilitate intelligent unitary synthesis for quantum computing are provided. For example, a system can access a unitary matrix of a quantum payload …
A new MCP server that enables AI agents to autonomously train reinforcement learning models for quantum circuit synthesis - including permutation, linear function, and Clifford …
A computer-implemented system with machine learning capabilities designed to address quantum computing challenges. The system's recommendation component employs a machine learning …
The Curry–Howard correspondence—propositions as types, proofs as programs—offers a conceptual framework for understanding what's missing in current LLMs and what becomes possible …