Pith. sign in

REVIEW 1 cited by

OPAQUE: Obfuscating Phase in Quantum Circuit Compilation for Efficient IP Protection

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2502.16605 v1 pith:OI5MFRNL submitted 2025-02-23 quant-ph cs.CR

classification quant-phcs.CR
keywords quantumcircuitgatesfunctionalityobfuscationanglecompilationcompilers
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Quantum compilers play a crucial role in quantum computing by converting these algorithmic quantum circuits into forms compatible with specific quantum computer hardware. However, untrusted quantum compilers present considerable risks, including the potential theft of quantum circuit intellectual property (IP) and compromise of the functionality (e.g. Trojan insertion). Quantum circuit obfuscation techniques protect quantum IP by transforming a quantum circuit into a key-dependent version before compilation and restoring the compiled circuit's functionality with the correct key. This prevents the untrusted compiler from knowing the circuit's original functionality. Existing quantum circuit obfuscation techniques focus on inserting key qubits to control key gates. One added key gate can represent at most one Boolean key bit. In this paper, we propose OPAQUE, a phase-based quantum circuit obfuscation approach where we use the angle of rotation gates as the secret keys. The rotation angle is a continuous value, which makes it possible to represent multiple key bits. Moreover, phase gates are usually implemented as virtual gates in quantum hardware, diminishing their cost and impact on accuracy.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses

    quant-ph 2025-06 conditional novelty 1.0 of 10

    A survey that categorizes known adversarial threats to quantum machine learning systems and reviews existing defenses, from logic locking to hardware-aware watermarking.

Pith tools