Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Bulletin of the American Physical Society

Novel qubit test platform

Fabio Teixeira Ferreira da Silva, Dale Li, Danielle Braje, Raymond W. Simmonds, Thomas Ohki, David P. Pappas

Published Mar 17, 2010• 0 citations
OpenAlex

Related papers

Cross-platform certification of the qubit space with a minimal number of parameters

Tomasz Rybotycki, Tomasz Białecki, Josep Amengual i Batle +2 more

We demonstrate a determinant dimension witness of a qubit space. Our test has a minimal number of independent parameters. We achieve it by mapping the Bloch sphere [Formula: see text]-rotation axis angle on the non-planar so-called Viviani curve. We ran our test on different platforms: IBM Quantum, IQM Resonance, and IonQ. Our investigations show that numerous qubits, especially from the newest IBM Heron family devices, fail the test by more than ten standard deviations. The nature of those deviations has no simple explanation as the test is robust against common imperfections.

arXiv:2404.06792•Scientific Reports•Dec 5, 2025•0 citations

Novel Qubit Designs

L. B. Ioffe

Bulletin of the American Physical Society•Mar 2, 2020•0 citations

Qubit Chip

Graham P. Collins

Scientific American•Aug 1, 1999•0 citations

Implement quantum random number generation on the IBM quantum computer platform

Nhu-Quynh Luc, Le Van Anh

Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standard

The Transport and Communications Science Journal•May 15, 2024•2 citations

IterTestQ: Assembly-Level, Cross-Platform Testing of Quantum Computing Platforms

Matteo Paltenghi, Michael Pradel

Quantum computing platforms are susceptible to quantum-specific bugs, such as incorrectly ordering qubits or incorrectly implementing quantum abstractions. These bugs are difficult to detect and require specialized expertise. The field faces challenges due to a fragmented landscape of platforms and rapid development cycles that often prioritize new features over thorough testing, severely hindering the reliability of quantum software. To address these challenges, we present IterTestQ, a novel cross-platform testing approach for quantum computing platforms. The key technical contribution is our novel ITE process, which generates equivalent quantum programs by iteratively (I)mporting them into platform-specific representations, (T)ransforming the program via optimizations and gate conversions, and (E)xporting the program again. To transfer programs across platforms and test cross-platform consistency, IterTestQ leverages QASM, an assembly-level representation supported by most platforms. The approach uses a crash oracle to detect failures during cross-platform transformations and an equivalence oracle to validate the semantic consistency of the generated assembly programs, which are expected to be equivalent by construction. We evaluate IterTestQ on widely-used quantum computing platforms, including Qiskit, PennyLane, Pytket, BQSKit, and Cirq, revealing 23 bugs, 17 of which are already confirmed or fixed. Our results also demonstrate that IterTestQ complements existing quantum fuzzers (covering tens of thousands of otherwise uncovered lines), is efficient (with 0.00089 seconds per generated program), and that the ITE process is crucial for its effectiveness.

cs.SECross-listedarXiv:2503.17322•Mar 24, 2025•0 citations

A platform for quantum computing

Owain P. H. Vaughan

Nature Electronics•May 26, 2023•3 citations
We demonstrate a determinant dimension witness of a qubit space. Our test has a minimal number of independent parameters. We achieve it by mapping the Bloch sphere [Formula: see text]-rotation axis angle on the non-planar so-called Viviani curve. We ran our test on different platforms: IBM Quantum, IQM Resonance, and IonQ. Our investigations show that numerous qubits, especially from the newest IBM Heron family devices, fail the test by more than ten standard deviations. The nature of those deviations has no simple explanation as the test is robust against common imperfections.
Random numbers are a crucial component of any encryption activity in modern cryptography. Quantum Random Number Generators (QRNGs) produce truly random output strings to replace pseudo-random ones. The principle of QRNG relies on measuring qubit states, which excel in quantum computing applications, particularly on IBM's quantum computing platform. To construct a random number generator, the authors utilized IBM Q Experience's Qiskit quantum development toolkit. We developed QRNG applications on IBM quantum computers (7-qubit, 16-qubit, and 127-qubit) and tested the program's functionality on these quantum computing platforms. The quality assessment of the random strings was conducted according to NIST and AIS-31 standards. For NIST standards, to achieve good quality, the output string must reach a minimum of 1,593,088 bits to pass 16 tests per SP800-22 standard. According to AIS-31 standards, to achieve good quality, the output string must reach a minimum of 8,000,000 bits to pass 8 tests of the standard
Quantum computing platforms are susceptible to quantum-specific bugs, such as incorrectly ordering qubits or incorrectly implementing quantum abstractions. These bugs are difficult to detect and require specialized expertise. The field faces challenges due to a fragmented landscape of platforms and rapid development cycles that often prioritize new features over thorough testing, severely hindering the reliability of quantum software. To address these challenges, we present IterTestQ, a novel cross-platform testing approach for quantum computing platforms. The key technical contribution is our novel ITE process, which generates equivalent quantum programs by iteratively (I)mporting them into platform-specific representations, (T)ransforming the program via optimizations and gate conversions, and (E)xporting the program again. To transfer programs across platforms and test cross-platform consistency, IterTestQ leverages QASM, an assembly-level representation supported by most platforms. The approach uses a crash oracle to detect failures during cross-platform transformations and an equivalence oracle to validate the semantic consistency of the generated assembly programs, which are expected to be equivalent by construction. We evaluate IterTestQ on widely-used quantum computing platforms, including Qiskit, PennyLane, Pytket, BQSKit, and Cirq, revealing 23 bugs, 17 of which are already confirmed or fixed. Our results also demonstrate that IterTestQ complements existing quantum fuzzers (covering tens of thousands of otherwise uncovered lines), is efficient (with 0.00089 seconds per generated program), and that the ITE process is crucial for its effectiveness.