Quantum Oracle Synthesis from HDL Designs via Multi Level Intermediate Representation

Quantum computing is increasingly recognized as a promising approach for tackling computationally intractable problems. However, achieving the scalability necessary for real-world applications requires substantial advancements in the quantum software stack. In this work, we introduce a compiler toolchain based on a Multi-Level Intermediate Representation (MLIR) that automatically synthesizes quantum circuits from Hardware Description Language (HDL) specifications of classical functions into quantum assembly languages. Many quantum algorithms rely on combinatorial circuits as subroutines, which traditionally require extensive resources in terms of quantum gates and qubits and are often manually optimized. Our toolchain integrates a sequence of optimization passes that combine classical compiler techniques with quantum-specific improvements, resulting in an average qubit reduction of 30% and an average gate-count reduction of 20% in widely adopted benchmark circuits, including those used in cryptographic applications.

Authors

Institutions

Publication Details

Published
2026-01-19
DOI
https://doi.org/10.1109/asp-dac66049.2026.11420750
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum Oracle Synthesis from HDL Designs via Multi Level Intermediate Representation

Gerardo Pelosi, Alessandro Barenghi, Daniele Gazzola, Giovanni Agosta et al.
Quantum Computing Algorithms and Architecture
article

Quantum Oracle Synthesis from HDL Designs via Multi Level Intermediate Representation

Gerardo Pelosi, Alessandro Barenghi, Daniele Gazzola, Giovanni Agosta, Giacomo Lancellotti, Filippo Buda, Giacomo Carugati
article en

Abstract

Quantum computing is increasingly recognized as a promising approach for tackling computationally intractable problems. However, achieving the scalability necessary for real-world applications requires substantial advancements in the quantum software stack. In this work, we introduce a compiler toolchain based on a Multi-Level Intermediate Representation (MLIR) that automatically synthesizes quantum circuits from Hardware Description Language (HDL) specifications of classical functions into quantum assembly languages. Many quantum algorithms rely on combinatorial circuits as subroutines, which traditionally require extensive resources in terms of quantum gates and qubits and are often manually optimized. Our toolchain integrates a sequence of optimization passes that combine classical compiler techniques with quantum-specific improvements, resulting in an average qubit reduction of 30% and an average gate-count reduction of 20% in widely adopted benchmark circuits, including those used in cryptographic applications.

Politecnico di Milano (IT)
Industry, innovation and infrastructure
Openalex Percentile: Top 31%
Quantum Computing Algorithms and Architecture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.