Quantum Arithmetic Circuits in Public-Key Cryptography
- URL: http://arxiv.org/abs/2607.11713v1
- Date: Mon, 13 Jul 2026 15:40:57 GMT
- Title: Quantum Arithmetic Circuits in Public-Key Cryptography
- Abstract summary: Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack.<n> quantum arithmetic circuits serve as fundamental building blocks for various promising algorithms.<n>Despite their crucial role, the design of quantum arithmetic circuits faces challenges arising from the no-cloning theorem, qubit limitations, and circuit depth constraints.
- Score: 6.466379083643027
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack, including quantum error-correcting codes and efficient quantum algorithms. Among these, quantum arithmetic circuits serve as fundamental building blocks for various promising algorithms. Despite their crucial role, the design of quantum arithmetic circuits faces challenges arising from the no-cloning theorem, qubit limitations, and circuit depth constraints, which significantly impact the efficiency of large-scale quantum computing. We provide an overview of quantum arithmetic circuits in the context of public-key cryptanalysis, with particular emphasis on optimization strategies such as measurement-based uncomputation and conditionally clean ancilla. We review state-of-the-art designs for essential arithmetic operations in public-key cryptanalysis such as addition, multiplication, and modular exponentiation. We also present an overview of the techniques used for fault-tolerant runtime and resource estimation in quantum cryptanalysis. In brief, this chapter emphasizes strategies for designing resource-efficient quantum arithmetic circuits, providing a basis for realistic evaluations of quantum cryptanalytic capabilities.
Related papers
- Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise [49.97673761305336]
Noise remains a major obstacle to achieving reliable quantum algorithms.<n>We present a provably noise-resilient training theory and algorithm to enhance the robustness of parameterized quantum circuit classifiers.
arXiv Detail & Related papers (2025-05-24T02:51:34Z) - Circuit Folding: Modular and Qubit-Level Workload Management in Quantum-Classical Systems [5.6744988702710835]
Circuit knitting is a technique that offloads some of the computational burden from quantum circuits.<n>We propose CiFold, a novel graph-based system that identifies and leverages repeated structures within quantum circuits.<n>Our system has been extensively evaluated across various quantum algorithms, achieving up to 799.2% reduction in quantum resource usage.
arXiv Detail & Related papers (2024-12-24T23:34:17Z) - AI-Powered Algorithm-Centric Quantum Processor Topology Design [10.53761034955718]
We introduce a novel approach to dynamically tailor qubit topologies to the unique specifications of individual quantum circuits.<n>Our method marks a significant departure from previous methods that have been constrained to mapping circuits onto a fixed processor topology.
arXiv Detail & Related papers (2024-12-18T12:53:16Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [62.46800898243033]
Recent progress in quantum learning theory prompts a question: can linear properties of a large-qubit circuit be efficiently learned from measurement data generated by varying classical inputs?<n>We prove that the sample complexity scaling linearly in $d$ is required to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.<n>We propose a kernel-based method leveraging classical shadows and truncated trigonometric expansions, enabling a controllable trade-off between prediction accuracy and computational overhead.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospects [59.07692103357675]
This survey explores the feasibility of an integrated design and optimization scheme that spans from the algorithmic level to quantum hardware.<n>It becomes more possible to reduce manual design costs, enhance the precision and efficiency of execution, and facilitate the implementation and validation of the superiority of quantum algorithms on hardware.
arXiv Detail & Related papers (2024-06-30T15:50:10Z) - A Comprehensive Study of Quantum Arithmetic Circuits [3.2846181673536803]
We provide a systematically organized and easily comprehensible overview of the current state-of-the-art in quantum arithmetic circuits.
Specifically, this study covers fundamental operations such as addition, subtraction, multiplication, division and modular exponentiation.
We delve into the detailed quantum implementations of these prominent designs and evaluate their efficiency considering various objectives.
arXiv Detail & Related papers (2024-06-06T08:54:45Z) - Efficient Quantum Modular Arithmetics for the ISQ Era [0.0]
This study presents an array of quantum circuits, each precision-engineered for modular arithmetic functions.
We provide a theoretical framework and practical implementations in the PennyLane quantum software.
arXiv Detail & Related papers (2023-11-14T21:34:39Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - Quantum circuit debugging and sensitivity analysis via local inversions [62.997667081978825]
We present a technique that pinpoints the sections of a quantum circuit that affect the circuit output the most.
We demonstrate the practicality and efficacy of the proposed technique by applying it to example algorithmic circuits implemented on IBM quantum machines.
arXiv Detail & Related papers (2022-04-12T19:39:31Z) - Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state.
In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
arXiv Detail & Related papers (2021-12-27T21:15:35Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.