This paper provides a new (second) way, which is completely different from Shor's algorithm, to show the optimistic potential of a D-Wave quantum computer for deciphering RSA and successfully factoring all integers within 10000. Our method significantly reduced the local field coefficient [Formula: see text] and coupling term coefficient [Formula: see text] by more than 33% and 26%, respectively, of those of Ising model, which can further improve the stability of qubit chains and improve the upper bound of integer factorization. In addition, our results obtained the best index (20-bit integer (1028171)) of quantum computing for deciphering RSA via the quantum computing software environment provided by D-Wave. Furthermore, Shor's algorithm requires approximately 40 qubits to factor the integer 1028171, which is far beyond the capacity of universal quantum computers. Thus, post quantum cryptography should further consider the potential of the D-Wave quantum computer for deciphering the RSA cryptosystem in future.This paper provides a new (second) way, which is completely different from Shor's algorithm, to show the optimistic potential of a D-Wave quantum computer for deciphering RSA and successfully factoring all integers within 10000. Our method significantly reduced the local field coefficient [Formula: see text] and coupling term coefficient [Formula: see text] by more than 33% and 26%, respectively, of those of Ising model, which can further improve the stability of qubit chains and improve the upper bound of integer factorization. In addition, our results obtained the best index (20-bit integer (1028171)) of quantum computing for deciphering RSA via the quantum computing software environment provided by D-Wave. Furthermore, Shor's algorithm requires approximately 40 qubits to factor the integer 1028171, which is far beyond the capacity of universal quantum computers. Thus, post quantum cryptography should further consider the potential of the D-Wave quantum computer for deciphering the RSA cryptosystem in future.

Scientific ReportsApr 28, 202066 citations

A quantum approach for optimal control

Hirmay Sandesara, Alok Shukla, Prakash Vedula

arXiv:2407.02864Quantum Information ProcessingMar 20, 20252 citations

Time-optimal control with finite bandwidth

Masashi Hirose, Paola Cappellaro

arXiv:1510.06801Quantum Information ProcessingFeb 28, 201821 citations

Deciphering a Million-Plus RSA Integer with Ultralow Local Field Coefficient h and Coupling Coefficient J of the Ising Model by D-Wave 2000Q

Chao Wang, Qiaoyun Hu, Haonan Yao +2 more

This work is the first to determine that a real quantum computer (including generalized and specialized) can decipher million-scale RSA relying solely on quantum algorithms, showing the real attack potential of D-Wave machines. The influence of different column widths on RSA factorization results is studied on the basis of a multiplication table, and the optimal column method is determined by traversal experiments. The traversal experiment of integer factorization within 10 000 shows that the local field and coupling coefficients are 75%-93% lower than the research of Shanghai University in 2020 and more than 85% lower than that of Purdue University in 2018. Extremely low Ising model parameters are crucial to reducing the hardware requirements, prompting factoring 1 245 407 on the D-Wave 2000Q real machine. D-Wave advantage already has more than 5000 qubits and will be expanded to 7000 qubits during 2023–2024, with remarkable improvements in decoherence and topology. This machine is expected to promote the solution of large-scale combinatorial optimization problems. One of the contributions of this paper is the discussion of the long-term impact of D-Wave on the development of post-quantum cryptography standards.This work is the first to determine that a real quantum computer (including generalized and specialized) can decipher million-scale RSA relying solely on quantum algorithms, showing the real attack potential of D-Wave machines. The influence of different column widths on RSA factorization results is studied on the basis of a multiplication table, and the optimal column method is determined by traversal experiments. The traversal experiment of integer factorization within 10 000 shows that the local field and coupling coefficients are 75%-93% lower than the research of Shanghai University in 2020 and more than 85% lower than that of Purdue University in 2018. Extremely low Ising model parameters are crucial to reducing the hardware requirements, prompting factoring 1 245 407 on the D-Wave 2000Q real machine. D-Wave advantage already has more than 5000 qubits and will be expanded to 7000 qubits during 2023–2024, with remarkable improvements in decoherence and topology. This machine is expected to promote the solution of large-scale combinatorial optimization problems. One of the contributions of this paper is the discussion of the long-term impact of D-Wave on the development of post-quantum cryptography standards.

Tsinghua Science & TechnologyDec 4, 20234 citations

AutoHF: a general Hartree-Fock solver utilizing direct energy minimization with automatic differentiation

Ryan Levy, Brandon Eskridge, Lukas Weber +2 more

We present autohf, a general, easy-to-use mean-field solver for quantum many-fermion Hamiltonians. It allows the user to bypass the process of deciphering the mean-field form for each many-body Hamiltonian $H$ and thus avoid setting up a tailored program for each $H$ . Rather, autohf finds the optimal Slater determinant $|Ψ\rangle$ , written in terms of orbital coefficients and subject to symmetry constraints, by directly minimizing the variational energy $\langle H \rangle$ . By embracing this variational approach, autohf makes use of the growing power of automatic differentiation and optimization tools developed by the machine learning community.We present autohf, a general, easy-to-use mean-field solver for quantum many-fermion Hamiltonians. It allows the user to bypass the process of deciphering the mean-field form for each many-body Hamiltonian $H$ and thus avoid setting up a tailored program for each $H$. Rather, autohf finds the optimal Slater determinant $|Ψ\rangle$, written in terms of orbital coefficients and subject to symmetry constraints, by directly minimizing the variational energy $\langle H \rangle$. By embracing this variational approach, autohf makes use of the growing power of automatic differentiation and optimization tools developed by the machine learning community.

arXiv:2607.14263Jul 15, 20260 citations

Quantum Optimal Control at Intermediate Times: Controlling Revivals in Spin Chains

Juan J. Omiste, Ignacio R. Solá

Standard Quantum Optimal Control (QOC) protocols typically maximize a physical objective just at a final target time. However, tracking or measuring the quantum state during the time evolution requires the control at intermediate stages of their evolution. In this work, we extend QOC to accommodate the simultaneous optimization of observables at arbitrary intermediate times. Using a variational approach, we show that intermediate observations induce discontinuities in the costate trajectory, which can be handled with a Krotov algorithm leading to monotonic optimization and convergent results in the limit of zero temporal measurement windows. We apply this multi-time formulation to a Heisenberg XXX spin chain to control the propagation, including field-free revivals, of a Dicke state excitation. Our results demonstrate that simultaneous optimization of the same observable reshapes the driving field to balance intermediate targets with final populations. Finally, we show how this framework enables dynamic tracking of spin excitations and the active manipulation of post-pulse quantum state revivals.Standard Quantum Optimal Control (QOC) protocols typically maximize a physical objective just at a final target time. However, tracking or measuring the quantum state during the time evolution requires the control at intermediate stages of their evolution. In this work, we extend QOC to accommodate the simultaneous optimization of observables at arbitrary intermediate times. Using a variational approach, we show that intermediate observations induce discontinuities in the costate trajectory, which can be handled with a Krotov algorithm leading to monotonic optimization and convergent results in the limit of zero temporal measurement windows. We apply this multi-time formulation to a Heisenberg XXX spin chain to control the propagation, including field-free revivals, of a Dicke state excitation. Our results demonstrate that simultaneous optimization of the same observable reshapes the driving field to balance intermediate targets with final populations. Finally, we show how this framework enables dynamic tracking of spin excitations and the active manipulation of post-pulse quantum state revivals.

quant-pharXiv:2607.28783Aug 3, 20260 citations

H

and thus avoid setting up a tailored program for each

H

. Rather, autohf finds the optimal Slater determinant

|Ψ\rangle

, written in terms of orbital coefficients and subject to symmetry constraints, by directly minimizing the variational energy

\langle H \rangle

. By embracing this variational approach, autohf makes use of the growing power of automatic differentiation and optimization tools developed by the machine learning community.