Quantum Computing is a highly promising new computation paradigm. Unfortunately, quantum bits (qubits) are extremely fragile and their state can be gradually or suddenly modified by intrinsic noise or external perturbation. In this paper, we target the sensitivity of quantum circuits to radiation-induced transient faults. We consider quantum circuit cuts that split the circuit into smaller independent portions, and understand how faults propagate in each portion. As we show, the cuts have different vulnerabilities, and our methodology successfully identifies the circuit portion that is more likely to contribute to the overall circuit error rate. Our evaluation shows that a circuit cut can have a 4.6 x higher probability than the other cuts, when corrupted, to modify the circuit output. Our study, identifying the most critical cuts, moves towards the possibility of implementing a selective hardening for quantum circuits.
Quantum Computing is a highly promising new computation paradigm. Unfortunately, quantum bits (qubits) are extremely fragile and their state can be gradually or suddenly modified by intrinsic noise or external perturbation. In this paper, we target the sensitivity of quantum circuits to radiation-induced transient faults. We consider quantum circuit cuts that split the circuit into smaller independent portions, and understand how faults propagate in each portion. As we show, the cuts have different vulnerabilities, and our methodology successfully identifies the circuit portion that is more likely to contribute to the overall circuit error rate. Our evaluation shows that a circuit cut can have a 4.6 x higher probability than the other cuts, when corrupted, to modify the circuit output. Our study, identifying the most critical cuts, moves towards the possibility of implementing a selective hardening for quantum circuits.
Quantum computing is one of the most promising technology advances of the latest years. Qubits are highly sensitive to noise, which can make the output useless. Lately, it has been shown that superconducting qubits are extremely susceptible to external sources of faults, such as ionizing radiation. When adopted in large scale, radiation-induced errors are expected to become a serious challenge for qubits reliability. We propose an evaluation of the impact of transient faults in the execution of quantum circuits on superconducting chips. Inspired by the Architectural and Program Vulnerability Factors, widely used for classical computation, we propose the Quantum Vulnerability Factor (QVF) to measure the impact of qubit corruption on the circuit output. We model faults, and design a fault injector, based on the latest studies on real machines and radiation experiments. We report the finding of more than 388,000,000 fault injections, considering single and double faults, on three algorithms, identifying the faults and qubits that are more likely to impact the output. We give guidelines on how to map the qubits in real devices to reduce the output error and to reduce the probability of having a radiation-induced corruption modifying the output. Finally, we compare simulations with experiments on physical quantum computers.
Quantum computing is an emerging technology that is poised to revolutionize computational capabilities. However, errors from environmental noise and imperfect hardware can significantly affect the fidelity of the computational results of quantum circuits. In this paper, we put forth a hypothesis that similar to classical computers, not all errors have the same effect on the outputs. To study the error impact at different qubits and at different gates, we leverage the fault injection methodology from a recently proposed framework, QuFI [1], which was designed to produce a quantum vulnerability factor (QVF) heatmap based on all possible fault injections. In our work, we use a similar fault injection approach but focus on the impact of errors at different regions of a circuit. Then, we propose to apply error mitigation techniques selectively to protect the most vulnerable regions of a circuit so as to reduce the overhead of error mitigation schemes.
Quantum computing is an up-and-coming technology that is expected to revolutionize the computation paradigm in the next few years. Qubits, the primary computing elements of quantum circuits, exploit the quantum physics proprieties to increase the parallelism and speed of computation drastically. Unfortunately, besides being intrinsically noisy, qubits have also been shown to be highly susceptible to external sources of faults, such as ionizing radiation. The latest discoveries highlight a much higher radiation sensitivity of qubits than traditional transistors and identify a much more complex fault model than bit-flip.We propose a framework to identify the quantum circuits sensitivity to radiation-induced faults and the probability for a fault in a qubit to propagate to the output. Based on the latest studies and radiation experiments performed on real quantum machines, we model the transient faults in a qubit as a phase shift with a parametrized magnitude. Additionally, our framework can inject multiple qubit faults, tuning the phase shift magnitude based on the proximity of the qubit to the particle strike location. As we show in the paper, the proposed fault injector is highly flexible, and it can be used on both quantum circuit simulators and real quantum machines. We report the finding of more than 285, 249, 536 injections on the Qiskit simulator and 53, 248 injections on real IBM machines. We consider three quantum algorithms and identify the faults and qubits that are more likely to impact the output. We also consider the fault propagation dependence on the circuit scale, showing that the reliability profile for some quantum algorithms is scale-dependent, with increased impact from radiation-induced faults as we increase the number of qubits. Finally, we also consider multi qubits faults, showing that they are much more critical than single faults. The fault injector and the data presented in this paper are available in a public repository to allow further analysis.
Transpiling is a necessary step to map a logical quantum algorithm to a circuit executed on a physical quantum machine, according to the available gate set and connectivity topology. Different transpiling approaches try to minimize the most critical parameters for the current transmon technology, such as Depth and CNOT number. Crucially, these approaches do not take into account the reliability of the circuit. In particular, transpilation can modify how radiation-induced transient faults propagate. In this paper, we aim at advancing the understanding of transpilation impact on fault propagation by investigating the low-level reliability of several transpiling approaches. We considered 4 quantum algorithms transpiled for 2 different architectures, increasing the number of qubits, and all possible logical-to-physical qubit mapping, adding to a total of 4, 640 transpiled circuits. We inject a total of 202, 124 faults and track their propagation. Our experiments show that by simply choosing the proper transpilation, the reliability of the circuit can improve by up to 14%.
Quantum computing is a new computational paradigm, expected to revolutionize the computing field in the next few years. Qubits, the atomic units of a quantum circuit, exploit the quantum physics properties to increase the parallelism and speed of computation. Unfortunately, qubits are both intrinsically noisy and highly susceptible to external sources of faults, such as ionizing radiation. The latest discoveries highlight a much higher radiation sensitivity of qubits than traditional transistors and identify a much more complex fault model than bit-flip. The observed error rate is so high that researchers are questioning the large-scale adoption of quantum computers. The reliability and dependability community is asked to act to find innovative solutions to improve the reliability of quantum applications. This tutorial aims at providing the DSN community with the tools to do so and to train the attendees on quantum fault injection.
Current quantum computers suffer from a limited number of qubits and high error rates, limiting practical applicability. Different techniques exist to mitigate these effects and run larger algorithms. In this work, we analyze one of these techniques called quantum circuit cutting. With circuit cutting, a quantum circuit is decomposed into smaller sub-circuits, each of which can be run on smaller quantum hardware. We compare the performance of quantum circuit cutting with different cutting strategies, and then apply circuit cutting to a QAOA algorithm. Using simulations, we first show that Randomized Clifford measurements outperform both Pauli and random unitary measurements. Second, we show that circuit cutting has trouble providing correct answers in noisy settings, especially as the number of circuits increases.