Quantum computers have the capacity to solve certain complex problems more efficiently than classical computers. To fully leverage these quantum advantages, adapting classical arithmetic for quantum systems in a circuit level is essential. In this paper, we introduce a depth-optimized quantum circuit of Gauss–Jordan elimination for matrices in binary. This quantum circuit is a crucial module for accelerating Information Set Decoding (ISD) using Grover’s algorithm. ISD is a cryptographic technique used in analyzing code-based cryptographic algorithms. When combined with Grover’s search, it achieves a square root reduction in complexity. The proposed method emphasizes the potential for parallelization in the quantum circuit implementation of Gauss–Jordan elimination. We allocate additional ancilla qubits to enable parallel operations within the target matrix and further reuse these ancilla qubits to minimize overhead from our additional allocation. The proposed quantum circuit for Gauss–Jordan elimination achieves the lowest Toffoli depth compared to the-state-of-art previous works.
Quantum computers have the capacity to solve certain complex problems more efficiently than classical computers. To fully leverage these quantum advantages, adapting classical arithmetic for quantum systems in a circuit level is essential. In this paper, we introduce a depth-optimized quantum circuit of Gauss–Jordan elimination for matrices in binary. This quantum circuit is a crucial module for accelerating Information Set Decoding (ISD) using Grover’s algorithm. ISD is a cryptographic technique used in analyzing code-based cryptographic algorithms. When combined with Grover’s search, it achieves a square root reduction in complexity. The proposed method emphasizes the potential for parallelization in the quantum circuit implementation of Gauss–Jordan elimination. We allocate additional ancilla qubits to enable parallel operations within the target matrix and further reuse these ancilla qubits to minimize overhead from our additional allocation. The proposed quantum circuit for Gauss–Jordan elimination achieves the lowest Toffoli depth compared to the-state-of-art previous works.
Quantum computers can efficiently model and solve certain problems on their own. Already in various fields, quantum computing is expected to outperform classical computers. In this flow, it is important to quantize classical arithmetic to achieve the benefits of quantum computing. In this paper, we efficiently implement quantum Gauss-Jordan elimination for binary matrix. Quantum Gauss-Jordan is required to accelerate Information Set Decoding, a cryptanalysis algorithm for code-based post-quantum ciphers, with Grover’s algorithm. In our understanding, the most important module when implementing ISD as a quantum version is quantum Gauss-Jordan elimination. We implement quantum Gauss-Jordan using only quantum gates (e.g., X, CX, CCX, and Swap) that replace classical operations. Finally, we analyze the quantum resources required for our implementation. For the simulation and resource estimation of our work, the quantum programming tool ProjectQ is used.
This paper presents an optimized quantum circuit for the scrypt cryptographic algorithm. We applied various optimization techniques to reduce the DW cost, which is the product of the time and space complexity of quantum circuits. In our proposed method, the number of ancilla qubits was significantly reduced through the use of optimized inverse operations, while the depth was minimized by implementing parallel structures. For the SHA-256, we devised a structure that achieves a substantial reduction in the number of ancilla qubits with only a slight increase in quantum circuit depth. By cleaning the dirty ancilla qubits used in the previous round through inverse operations, we enabled their reuse in each subsequent round. Specifically, we reduced the number of 8128 ancilla qubits, achieving this with an increase of only 6 in the full depth of the quantum circuit. Additionally, within Salsa20/8 in SMix, we reused qubits through inverse operations and performed some operations in parallel to reduce both the number of qubits and the overall quantum circuit depth. Finally, our quantum circuit for scrypt demonstrates a significant reduction in the width (the number of qubits) with only a minimal increase in the full quantum circuit depth.
Quantum computers can model and solve several problems that have posed challenges for classical super computers, leveraging their natural quantum mechanical characteristics. A large-scale quantum computer is poised to significantly reduce security strength in cryptography. In this context, extensive research has been conducted on quantum cryptanalysis.In this paper, we present optimized quantum circuits for Korean block ciphers, HIGHT and LEA. Our quantum circuits for HIGHT and LEA demonstrate the lowest circuit depth compared to previous results. Specifically, we achieve depth reductions of 48% and 74% for HIGHT and LEA, respectively. We employ multiple novel techniques that effectively reduce the quantum circuit depth with a reasonable increase in qubit count. Based on our depth-optimized quantum circuits for HIGHT and LEA block ciphers, we estimate the lowest quantum attack complexity for Grover’s key search. Our quantum circuit can be utilized for other quantum algorithms, not only for Grover’s algorithm. Furthermore, the optimization methods gathered in this work can be adopted for generic quantum implementations in cryptography.
Code-based cryptosystems are a promising option for Post-Quantum Cryptography, as neither classical nor quantum algorithms provide polynomial time solvers for their underlying hard problem. Indeed, to provide sound alternatives to lattice-based cryptosystems, U.S. National Institute of Standards and Technology (NIST) advanced all round 3 code-based cryptosystems to round 4 of its Post-Quantum standardization initiative. We present a complete implementation of a quantum circuit based on the Information Set Decoding (ISD) strategy, the best known one against code-based cryptosystems, providing quantitative measures for the security margin achieved with respect to the quantum-accelerated key recovery on AES, targeting both the current state-of-the-art approach and the NIST estimates. Our work improves the state-of-the-art, reducing the circuit depth by 2 19 to 2 30 for all the parameters of the NIST selected cryptosystems, mainly due to an improved quantum Gauss–Jordan elimination circuit with respect to previous proposals. We show how our Prange’s-based quantum ISD circuit reduces the security margin with respect to its classical counterpart. Finally, we address the concern brought forward in the latest NIST report on the parameters choice for the McEliece cryptosystem, showing that its parameter choice yields a computational effort slightly below the required target level.
The progress in building quantum computers to execute quantum algorithms has recently been remarkable. Grover's search algorithm in a binary quantum system provides a considerable speed-up over the classical paradigm. It can be extended to a d-ary (qudit) quantum system also for utilizing the advantage of larger state space, which helps to reduce the runtime of the algorithm as compared to the traditional binary quantum systems. In a qudit quantum system, an n-qudit Toffoli gate plays a significant role in the accurate implementation of Grover's algorithm. In this article, a generalized n-qudit Toffoli gate is realized using higher-dimensional qudits to attain a logarithmic depth decomposition without ancilla qudit. The circuit for Grover's algorithm has then been designed for any d-ary quantum system, where $d\ensuremath{\ge}2$, with the proposed n-qudit Toffoli gate to obtain optimized depth compared to earlier approaches. The technique for decomposing an n-qudit Toffoli gate requires access to two immediately higher-energy levels, making the design susceptible to errors. Nevertheless, we show that the percentage decrease in the probability of error is significant with both gate count and circuit depth reduced as compared to that in state-of-the-art works.
With the advancement of quantum computing, quantum circuit implementations of symmetric cryptographic algorithms are essential for evaluating their resistance to quantum attacks. As an ISO-standardized cipher, the efficient quantum circuit construction of Camellia is of great significance. Focusing on minimizing the DW-cost (qubits × Toffoli-depth) while balancing ancilla qubits and Toffoli-depth, this paper proposes an optimized quantum circuit design for Camellia. Specifically: (1) using a serial-multiplication and out-of-place inversion architecture under composite-field decomposition, combined with hierarchical screening for parallelizing bilinear multiplications, a compact in-place S-box quantum circuit is constructed with a DW-cost of 276, 28% lower than the state of the art; (2) a low-gate-count linear-layer circuit is obtained via heuristic search, and gate-sequence reordering then reduces the full depth from 9 to 7 without increasing the gate count; (3) Camellia-128/192/256 quantum circuits are constructed with DW-costs of 119,168, 257,664, and 257,664, achieving reductions of 48%, 52%, and 52% respectively over prior work. A pipelined Grover oracle is further designed and the total resources required for a full Grover search attacking Camellia are evaluated. For Camellia-128, the complete Grover search requires a T-depth of 2.10 × 2⁷⁶ and a total TDW-cost (qubits × T-depth) of 1.00 × 2⁸⁶, reducing T-depth by 75% and TDW-cost by 84% over prior work. The first full Grover search resource estimates for Camellia-192/256 are also presented, with T-depths of 7.20 × 2¹⁰⁸ and 8.11 × 2¹⁴⁰ and TDW-costs of 2.03 × 2¹²³ and 2.79 × 2¹⁵³, respectively. These results show that Grover's attack on Camellia requires fewer quantum resources than on AES at the 128-bit level, implying comparatively weaker post-quantum security at that key size, while the picture reverses at larger key sizes (Section 4).