Quantum computing promises to outperform classical systems, yet today’s Noisy Intermediate-Scale Quantum (NISQ) devices remain limited by gate errors, decoherence, and hardware variability. These challenges are compounded by the lack of built-in mechanisms to verify that quantum circuits execute as intended, especially in an untrusted quantum computer. In this work, we define quantum noise as a diagnostic signal rather than a nuisance. We propose a novel authentication method that utilizes Total Variation Distance (TVD) calculated using quantum noise. TVD compares a quantum circuit output distribution with a trusted quantum noise fingerprint. TVD offers a localized, interpretable metric for detecting structural tampering, such as gate reordering or injection. To support fine-grained verification, we introduce the concept of diagnostic ancilla qubits, non-invasive observers embedded in the circuit that store local noise signatures for post-execution analysis. While still a forward-looking concept, this proposal enables circuit-level verification. Our approach combines gate-level noise modeling with lightweight integrity checks, offering a promising path toward secure and tamper-evident quantum computation.
Quantum computing promises to outperform classical systems, yet today’s Noisy Intermediate-Scale Quantum (NISQ) devices remain limited by gate errors, decoherence, and hardware variability. These challenges are compounded by the lack of built-in mechanisms to verify that quantum circuits execute as intended, especially in an untrusted quantum computer. In this work, we define quantum noise as a diagnostic signal rather than a nuisance. We propose a novel authentication method that utilizes Total Variation Distance (TVD) calculated using quantum noise. TVD compares a quantum circuit output distribution with a trusted quantum noise fingerprint. TVD offers a localized, interpretable metric for detecting structural tampering, such as gate reordering or injection. To support fine-grained verification, we introduce the concept of diagnostic ancilla qubits, non-invasive observers embedded in the circuit that store local noise signatures for post-execution analysis. While still a forward-looking concept, this proposal enables circuit-level verification. Our approach combines gate-level noise modeling with lightweight integrity checks, offering a promising path toward secure and tamper-evident quantum computation.
In the Noisy Intermediate-Scale Quantum (NISQ) realm, efficient quantum circuit compilation is critical to ensure successful computation. Several third-party compilers are improving the compilation times and depth/gate counts. Untrusted third parties or a particular version of a trusted compiler may allow an attacker to steal, clone, and/or reverse engineer the quantum circuit. We propose to obfuscate quantum circuits by employing dummy CNOT gates to prevent such threats. If the adversary clones the obfuscated design, he/she will get faulty results. We propose a metric-based dummy gate insertion process to ensure maximum corruption of functionality measured using Total Variation Distance (TVD) and validated using IBM’s noisy simulators. Our metric guided dummy gate insertion process achieves TVD of up to 28.83%, and performs 10.14% better than the average TVD and performs within 12.45% of the best obtainable TVD for the test benchmarks. The removal of dummy gates by the designer post-compilation to restore functionality as well as other finer details have been addressed.
In this article, we analyzed the performance of several classes of quantum circuits under various errors. We executed NISQ circuits on both noisy simulator and real hardware backend publicly available from IBM Quantum. On simulation, we created noise models with both individual errors and combination of multiple errors to quantify how each type of error impact performance of quantum circuits. We utilized statistical distances such as total variation distance (TVD), Jensen-Shannon divergence (JSD), and Hellinger distance, to measure the deviation of noisy output from ideal output. Finally, we compare the noisy outputs from the simulator and outputs from the real hardware to showcase the gap between simulation and real device experiment. This gap points to the limitation of present noise models failure to exhibit the behavior of real hardware.
Evaluating the reliability of noisy quantum circuits is essential for implementing quantum algorithms on noisy quantum devices. However, current quantum hardware exhibits diverse noise mechanisms whose compounded effects make accurate and efficient reliability evaluation challenging. While state fidelity is the most faithful indicator of circuit reliability, it is experimentally and computationally prohibitive to obtain. Alternative metrics, although easier to compute, often fail to accurately reflect circuit reliability, lack universality across circuit types, or offer limited interpretability. To address these challenges, we propose a fine-grained, scalable, and interpretable framework for efficient and accurate reliability evaluation of noisy quantum circuits. Our approach performs a state-independent analysis to model how circuit reliability progressively degrades during execution. We introduce the Noise Proxy Circuit (NPC), which removes all logical operations while preserving the complete sequence of noise channels, thereby providing an abstraction of cumulative noise effects. Based on the NPC, we define Proxy Fidelity, a reliability metric that quantifies both qubit-level and circuit-level reliability. We further develop an analytical algorithm to estimate Proxy Fidelity under depolarizing, thermal relaxation, and readout error channels. The proposed framework achieves fidelity-level reliability estimation while remaining execution-free, scalable, and interpretable. Experimental results show that our method accurately estimates circuit fidelity, with an average absolute difference (AAD) ranging from 0.031 to 0.069 across diverse circuits and devices.
Optimization of quantum circuits using an efficient compiler is key to its success for NISQ computers. Several 3rd party compilers are evolving to offer improved performance for large quantum circuits. These 3rd parties, or just a certain release of an otherwise trustworthy compiler, may possibly be untrusted and this could lead to an adversary to Reverse Engineer (RE) the quantum circuit for extracting sensitive aspects e.g., circuit topology, program, and its properties. In this paper, we propose obfuscation of quantum circuits to hide the functionality. Quantum circuits have inherent margin between correct and incorrect outputs. Therefore, obfuscation (i.e., corruption of functionality) by inserting dummy gates is nontrivial. We insert dummy SWAP gates one at a time for maximum corruption of functionality before sending the quantum circuit to an untrusted compiler. If an untrusted party clones the design, they get incorrect functionality. The designer removes the dummy SWAP gate post-compilation to restore the correct functionality. Compared to a classical counterpart, the quantum chip does not reveal the circuit functionality. Therefore, an adversary cannot guess the SWAP gate and location/validate using an oracle model. Evaluation of realistic quantum circuit with/without SWAP insertion is impossible in classical computers. Therefore, we propose a metric-based SWAP gate insertion process. The objective of the metric is to ensure maximum corruption of functionality measured using Total Variation Distance (TVD). The proposed approach is validated using IBM default noisy simulation model. Our metric-based approach predicts the SWAP position to achieve TVD of upto 50%, and performs 7.5% better than average TVD, and performs within 12.3% of the best obtainable TVD for the benchmarks. We obtain an overhead of < 5% for the number of gates and circuit depth after SWAP addition.
In this article, we analyzed the performance of several classes of quantum circuits under various errors. We executed NISQ circuits on both noisy simulator and real hardware backend publicly available from IBM Quantum. On simulation, we created noise models with both individual errors and combination of multiple errors to quantify how each type of error impact performance of quantum circuits. We utilized statistical distances such as total variation distance (TVD), Jensen-Shannon divergence (JSD), and Hellinger distance, to measure the deviation of noisy output from ideal output. Finally, we compare the noisy outputs from the simulator and outputs from the real hardware to showcase the gap between simulation and real device experiment. This gap points to the limitation of present noise models failure to exhibit the behavior of real hardware.
Abstract The success of quantum circuits in providing reliable outcomes for a given problem depends on the gate count and depth in near-term noisy quantum computers. A circuit (that implements a given function) with a low gate count and short depth is more likely to give a correct solution than the circuit variant with a higher gate count and depth. As such, quantum circuit compilers that decompose high-level gates to native gates of the hardware and optimize the circuit play a key role in quantum computing. However, the quality and time complexity of the optimization process can vary significantly especially for practically relevant large-scale quantum circuits. As a result, third-party (often less-trusted/untrusted/unreliable) compilers have emerged, claiming to provide better and faster optimization of complex quantum circuits than so-called trusted compilers. However, untrusted compilers, with their varying adversarial motives ranging from semi-honest to malicious can pose severe security risks such as the theft of sensitive intellectual property (IP) embedded within the quantum circuit. We propose an obfuscation technique for quantum circuits using randomized reversible gates to protect them from such attacks during compilation. The idea is to insert a small random circuit into the original circuit and send it to the untrusted compiler. Since the circuit function is corrupted, the adversary (i.e., an untrusted compiler) may get incorrect IP. However, the user may also get incorrect output post-compilation (even though highly optimized). To circumvent this issue, we concatenate the inverse of the random circuit in the compiled circuit to recover the original functionality. We demonstrate the practicality of our method by conducting exhaustive experiments on a set of benchmark circuits and measuring the quality of obfuscation by calculating the Total Variation Distance (TVD) and Degree of Functional Corruption (DFC) metrics. Our method achieves TVD of up to 1.92, indicating substantial functional corruption, and performs at least 2x better than a previously reported obfuscation method. We also attained a DFC as low as -0.75, approaching the -1 score that represents maximal functional corruption, further ensuring the robustness of our proposed method against IP theft. We also propose a novel adversarial reverse engineering (RE) approach to extract the IP and show that the proposed obfuscation is resilient against RE attacks. The proposed technique introduces minimal degradation in fidelity ( ~ 1% to ~ 3% on average).