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arXiv:2408.00927 · ACM Great Lakes Symposium on VLSI (GLSVLSI)

Noise-Resilient and Reduced Depth Approximate Adders for NISQ Quantum Computing

Bhaskar Gaur, Travis S. Humble, Himanshu Thapliyal

Published May 31, 2023• 11 citations
arXivHTMLPDF

Abstract

The "Noisy intermediate-scale quantum" NISQ machine era primarily focuses on mitigating noise, controlling errors, and executing high-fidelity operations, hence requiring shallow circuit depth and noise robustness. Approximate computing is a novel computing paradigm that produces imprecise results by relaxing the need for fully precise output for error-tolerant applications including multimedia, data mining, and image processing. We investigate how approximate computing can improve the noise resilience of quantum adder circuits in NISQ quantum computing. We propose five designs of approximate quantum adders to reduce depth while making them noise-resilient, in which three designs are with carryout, while two are without carryout. We have used novel design approaches that include approximating the Sum only from the inputs (pass-through designs) and having zero depth, as they need no quantum gates. The second design style uses a single CNOT gate to approximate the SUM with a constant depth of O(1). We performed our experimentation on IBM Qiskit on noise models including thermal, depolarizing, amplitude damping, phase damping, and bitflip: (i) Compared to exact quantum ripple carry adder without carryout the proposed approximate adders without carryout have improved fidelity ranging from 8.34% to 219.22%, and (ii) Compared to exact quantum ripple carry adder with carryout the proposed approximate adders with carryout have improved fidelity ranging from 8.23% to 371%. Further, the proposed approximate quantum adders are evaluated in terms of various error metrics.

DOI
10.1145/3583781.3590315

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The "Noisy intermediate-scale quantum" NISQ machine era primarily focuses on mitigating noise, controlling errors, and executing high-fidelity operations, hence requiring shallow circuit depth and noise robustness. Approximate computing is a novel computing paradigm that produces imprecise results by relaxing the need for fully precise output for error-tolerant applications including multimedia, data mining, and image processing. We investigate how approximate computing can improve the noise resilience of quantum adder circuits in NISQ quantum computing. We propose five designs of approximate quantum adders to reduce depth while making them noise-resilient, in which three designs are with carryout, while two are without carryout. We have used novel design approaches that include approximating the Sum only from the inputs (pass-through designs) and having zero depth, as they need no quantum gates. The second design style uses a single CNOT gate to approximate the SUM with a constant depth of O(1). We performed our experimentation on IBM Qiskit on noise models including thermal, depolarizing, amplitude damping, phase damping, and bitflip: (i) Compared to exact quantum ripple carry adder without carryout the proposed approximate adders without carryout have improved fidelity ranging from 8.34% to 219.22%, and (ii) Compared to exact quantum ripple carry adder with carryout the proposed approximate adders with carryout have improved fidelity ranging from 8.23% to 371%. Further, the proposed approximate quantum adders are evaluated in terms of various error metrics.
Approximate quantum adders are gaining traction in NISQ-era computing for their potential to reduce quantum resource usage while preserving computational accuracy. In this work, we evaluate two 8-qubit hybrid approximate quantum adders that combine a 2-qubit approximate block, either a pass-through Copy Adder or a CNOT-based design, with a 6-qubit Cuccaro ripple-carry adder. Simulations are conducted using IBM's Qiskit framework under realistic noise models, including bit-flip, depolarizing, and thermal noise. Compared to the exact 8-bit Cuccaro adder, our designs reduce quantum cost and circuit depth by over 20 percent and achieve up to 79.3 percent higher output probability under noisy conditions. These results highlight the robustness and efficiency of approximate logic in noisy quantum environments and confirm its practicality for near-term quantum hardware.
Abstract Quantum arithmetic circuits, such as adders and multipliers, are essential for many quantum algorithms, but their practical deployment on noisy intermediate-scale quantum (NISQ) devices remains challenging due to limited coherence times and high gate error rates. In this paper, we propose Qaradox, a configurable approximate quantum multiplier architecture that achieves higher computation accuracy than its exact counterpart under realistic quantum noise. The proposed architecture introduces a novel class of controlled quantum adders that enable flexible combinations of exact, approximate, and truncated operations, allowing the quantum circuit to be tailored to hardware-specific noise characteristics. Experimental results using IBM’s 127-qubit Brisbane noise model show that Qaradox reduces the error rate (ER), normalized mean error distance (NMED), and mean relative error distance (MRED) by up to 23.7%, 80.3%, and 88.1%, respectively, compared to the fully exact multiplier. Furthermore, when applied to image sharpening, the proposed architecture improves peak signal-to-noise ratio (PSNR) by more than three times and increases structural similarity index measure (SSIM) from 0.00 to 0.83, effectively recovering visual quality lost in exact designs. These results demonstrate that approximation, when applied structurally and selectively, can enhance both robustness and correctness in quantum arithmetic for NISQ-era systems.
Quantum Computing is making significant advancements toward creating machines capable of implementing quantum algorithms in various fields, such as quantum cryptography, quantum image processing, and optimization. The development of quantum arithmetic circuits for modulo addition is vital for implementing these quantum algorithms. While it is ideal to use quantum circuits based on fault-tolerant gates to overcome noise and decoherence errors, the current Noisy Intermediate Scale Quantum (NISQ) era quantum computers cannot handle the additional computational cost associated with fault-tolerant designs. Our research aims to minimize circuit depth, which can reduce noise and facilitate the implementation of quantum modulo addition circuits on NISQ machines. This work presents quantum carry-lookahead modulo (2n - 1) adder (QCLMA), which is designed to receive two n-bit numbers and perform their addition with an O(log n) depth. Compared to existing work of O(n) depth, our proposed QCLMA reduces the depth and helps increase the noise fidelity. In order to increase error resilience, we also focus on creating a tree structure based Carry path, unlike the chain based Carry path of the current work. We run experiments on Quantum Computer IBM Cairo to evaluate the performance of the proposed QCLMA against the existing work and define Quantum State Fidelity Ratio (QSFR) to quantify the closeness of the correct output to the top output. When compared against existing work, the proposed QCLMA achieves a 47.21% increase in QSFR for 4-qubit modulo addition showcasing its superior noise fidelity.
Quantum addition is a vital building block for many quantum applications, yet exact adder architectures exhibit long carry paths and higher depth, increasing their exposure to quantum attacks. This paper presents a security driven evaluation of quantum approximate adders with carryout, having constant depth approximation and benchmarks them against two exact quantum adders. We evaluate resilience against four attack models: (1) Stuck-at∣0⟩/∣1⟩\vert 0\rangle /\vert 1\rangle∣0⟩/∣1⟩qubit attack, (2) State preparation attack, (3) Gate attack, and (4) Crosstalk attack in multi-tenant scenario. We use an emulator provided by Quantinuum that models its H1 ion trap-based 20-qubit quantum computer to conduct attacks. Our results indicate that approximate adders show higher resilience to noise, state preparation, gate, and crosstalk attacks, with AQA3 outperforming AQA4, which outperforms AQA5, due to increasing gate counts across zero, single CNOT layer, and one Toffoli gate respectively. Exact adders remain more robust against stuck-at∣0⟩/∣1⟩\vert 0\rangle /\vert 1\rangle∣0⟩/∣1⟩qubit attacks, as their carry propagation structure acts as an error absorbing mechanism, highlighting a security accuracy trade off for selecting adders in error-tolerant quantum applications.
Abstract This work presents a resource-efficient architecture for quantum 5:2 compressors, addressing the prohibitively high T-count and circuit depth of exact arithmetic in the Noisy Intermediate-Scale Quantum (NISQ) regime. We implement a Hybrid Approximate-Exact synthesis methodology that fundamentally alters the logic synthesis path to prioritize quantum cost over strict logical equivalence. The proposed design intentionally isolates and excludes the fourth input bit (í µí±¥ 4)from the critical carry computation path during the initial approximation stage, significantly pruning the required Toffoli gate count. To mitigate the induced error, the proposed approach integrate a dedicated Error Correction Module (ECM) based on half-adder logic that realigns the significance weights of the intermediate sum and carry vectors. Validation via Qiskit Aer exhaustive statevector simulation confirms that this architecture achieves a superior Pareto frontier between circuit fidelity and arithmetic precision compared to fully exact baselines. The resulting topology minimizes decoherence-induced errors by reducing the gate depth, providing a viable arithmetic primitive for error-tolerant quantum algorithms.
Progress in quantum hardware design is progressing toward machines of sufficient size to begin realizing quantum algorithms in disciplines such as encryption and physics. Quantum circuits for addition are crucial to realize many quantum algorithms on these machines. Ideally, quantum circuits based on fault-tolerant gates and error-correcting codes should be used as they tolerant environmental noise. However, current machines called Noisy Intermediate Scale Quantum (NISQ) machines cannot support the overhead associated with fault-tolerant design. In response, low depth circuits such as quantum carry lookahead adders (QCLA)s have caught the attention of researchers. The risk for noise errors and decoherence increase as the number of gate layers (or depth) in the circuit increases. This work presents an out-of-place QCLA based on Clifford+T gates. The QCLAs optimized for T gate count and make use of a novel uncomputation gate to save T gates. We base our QCLAs on Clifford+T gates because they can eventually be made fault-tolerant with error-correcting codes once quantum hardware that can support fault-tolerant designs becomes available. We focus on T gate cost as the T gate is significantly more costly to make fault-tolerant than the other Clifford+T gates. The proposed QCLAs are compared and shown to be superior to existing works in terms of T-count and therefore the total number of quantum gates. Finally, we illustrate the application of the proposed QCLAs in quantum image processing by presenting quantum circuits for bilinear interpolation.