In this work, we describe the capabilities of Magnonic Holographic Memory (MHM) for parallel database search and prime factorization. MHM is a type of holographic device, which utilizes spin waves for data transfer and processing. Its operation is based on the correlation between the phases and the amplitudes of the input spin waves and the output inductive voltage. The input of MHM is provided by the phased array of spin wave generating elements allowing the producing of phase patterns of an arbitrary form. The latter makes it possible to code logic states into the phases of propagating waves and exploit wave superposition for parallel data processing. We present the results of numerical modeling illustrating parallel database search and prime factorization. The results of numerical simulations on the database search are in agreement with the available experimental data. The use of classical wave interference may results in a significant speedup over the conventional digital logic circuits in special task data processing (e.g., √n in database search). Potentially, magnonic holographic devices can be implemented as complementary logic units to digital processors. Physical limitations and technological constrains of the spin wave approach are also discussed.
In this work, we describe the capabilities of Magnonic Holographic Memory (MHM) for parallel database search and prime factorization. MHM is a type of holographic device, which utilizes spin waves for data transfer and processing. Its operation is based on the correlation between the phases and the amplitudes of the input spin waves and the output inductive voltage. The input of MHM is provided by the phased array of spin wave generating elements allowing the producing of phase patterns of an arbitrary form. The latter makes it possible to code logic states into the phases of propagating waves and exploit wave superposition for parallel data processing. We present the results of numerical modeling illustrating parallel database search and prime factorization. The results of numerical simulations on the database search are in agreement with the available experimental data. The use of classical wave interference may results in a significant speedup over the conventional digital logic circuits in special task data processing (e.g., √n in database search). Potentially, magnonic holographic devices can be implemented as complementary logic units to digital processors. Physical limitations and technological constrains of the spin wave approach are also discussed.
Quantum computers are proven to be more efficient at solving a specific class of problems compared to traditional digital computers. Superposition of states and quantum entanglement are the two key ingredients that make quantum computing so powerful. However, not all quantum algorithms require quantum entanglement (e.g., search through an unsorted database). Is it possible to utilize classical wave superposition to speed up database searching as much as by using quantum computers? There were several attempts to mimic quantum computers using classical waves. It was concluded that the use of classical wave superposition comes with the cost of an exponential increase in resources. In this work, we consider the feasibility of building classical wave-based devices able to provide fundamental speedup over digital counterparts without the exponential overhead. We present experimental data on database searching through a magnetic database using spin wave superposition. The results demonstrate the same speedup as expected for quantum computers. Also, we present examples of numerical modeling demonstrating classical wave interference for period finding. This approach may not compete with quantum computers with efficiency but outperform classical digital computers. We argue that classical wave-based devices can perform some of the quantum algorithms with the same efficiency as quantum computers as long as quantum entanglement is not required.
We propose a theoretical framework for quantum data storage based on magnon modes in magnetic media, with frequency-based addressing implemented through quantum superposition states. Unlike conventional memory architectures that rely on fixed spatial positions, the proposed approach encodes logical addresses in mode structure, reducing dependence on absolute spatial coordinates. We analyze the system within a mode-resolved Hamiltonian formalism and show that the number of independently addressable channels is fundamentally limited by spectral linewidth (Γ) and available bandwidth. Coherent signal accumulation exhibits an ideal N² scaling in the fully phase-locked limit, though practical implementations are expected to be linewidth- and decoherence-limited. Photon–magnon coupling provides a physically grounded mechanism for state transfer between optical and magnetic degrees of freedom. Additionally, recently reported p-wave magnetic structures in NiI₂ may offer a potential platform for exploring mode-defined frequency channels, although coherent storage in such materials remains experimentally unverified. This work defines quantitative operating limits and proposes falsifiable criteria for experimental validation. Keywords: quantum memory, magnon modes, linewidth-limited addressing, photon–magnon coupling, mode-based storage
Prime factorization is a procedure of determining the prime factors of a given number N that requires super-polynomial time for conventional digital computers. Peter Shor developed a polynomial-time algorithm for quantum computers. Period finding is the key part of the algorithm, which is accomplished with the help of quantum superposition of states and quantum entanglement. The period finding can be also accomplished using classical wave superposition. In this study, we present experimental data obtained on a multi-port spin wave interferometer made of Y3Fe2(FeO4)3. Number 817 was factorized by a sequence of phase measurements. We also present the results of numerical modeling on the prime factorization of larger numbers 334597,1172693,3377663,and9363239. The results of numerical modeling reveal significant shortcomings of the period-based approach. The major problems are associated with an inability to predict the period of the modular function, significant overhead over classical digital computers in some cases, and phase accuracy requirements. We argue that the same problems are inherent in classical analog and quantum computers.
Abstract A device being a pinnacle of development of an optical quantum memory should combine the capabilities of storage, inter-communication, and processing of stored information. In particular, the ability to capture a train of optical pulses, interfere them in an arbitrary way and finally, perform on-demand release could realize arbitrary optical computation. Here we demonstrate the operation of a coherent optical memory being able to store optical pulses in the form of collective spin-wave excitations in a two-dimensional wavevector space. During storage, we perform complex beamsplitter operations and demonstrate a variety of protocols implemented at the processing stage, including real-time controlled interference of a pair of spin-wave modes with 95% visibility. The highly multimode structure of the presented memory lends itself to enhancing classical optical telecommunication, as well as parallel processing of optical qubits at the single-photon level.
Efficient classical database operations are crucial for modern data processing and data management tasks. At the same time, quantum computing algorithms may offer a substantial speed-up for certain computational use cases. Quantum systems allow access to superposition and entanglement, enabling quantum parallelism and the use of interference. We define a quantum database state [8, 9] as an indexed superposition state as given, e.g., by the state returned by a quantum random access memory call (see [3, 4]). The database state is assumed to be located in the central quantum processing unit of a quantum computer. We investigate the feasibility of transferring general classical database operations to the quantum domain, with indices in superposition.
This article explores the transformative potential of quantum computing in database systems, focusing on advanced query operations that traditionally challenge conventional architectures. It examines how quantum mechanical phenomena like superposition and entanglement enable unprecedented parallel processing capabilities in database operations. The article investigates key areas including pattern matching, similarity searches, and graph traversal algorithms, where quantum advantages show particular promise. It compares quantum and classical systems, addressing scalability considerations and accuracy challenges in quantum database implementations. The article delves into hybrid quantum-classical architectures and quantum native approaches, examining their respective strengths and limitations. Special attention is given to the challenges and opportunities presented by Noisy Intermediate-Scale Quantum (NISQ) devices, including hardware limitations, algorithm development, and practical integration considerations. The article provides insights into the future directions of quantum databases, emphasizing the importance of developing robust error correction mechanisms and optimizing quantum circuits for practical database operations.