Quantum information technology (QIT) is extremely fast developing area strongly connected with achievements in modern physics. We present a review of recent achievements in implementation of solid-state scalable quantum processors with special emphasize on diamond-based quantum hardware.
This paper presents a comprehensive review of quantum computing and the technological foundations of quantum processors. Quantum computing represents a transformative computational paradigm that leverages the fundamental principles of quantum mechanics—such as superposition, entanglement, and quantum interference—to solve complex problems that are intractable for classical computers. At the core of this paradigm lies the quantum processor, a specialized hardware system designed to initialize, control, and measure quantum bits (qubits) through precise gate operations and coherent interactions. The survey examines the essential theoretical concepts underlying quantum computation and provides a structured comparison of leading quantum processor platforms. Prominent architectures, including superconducting circuits, trapped-ion systems, and photonic implementations, are analyzed in terms of their physical mechanisms, scalability, coherence properties, and engineering challenges. Each platform offers distinct advantages and faces specific technical limitations related to noise, error correction, and fabrication complexity. In addition to reviewing hardware developments, this study highlights key obstacles in advancing quantum processors toward large-scale, fault-tolerant systems. Issues such as qubit stability, error mitigation, thermal management, and system integration are discussed to present a realistic perspective on current progress. Performance indicators including gate fidelity, coherence time, connectivity, and scalability are used to compare architectural approaches. The objective of this paper is to provide a clear and organized synthesis of recent advancements in quantum computing hardware, thereby offering researchers and practitioners a foundational reference to support continued innovation and development in this rapidly evolving field.
This paper presents a collection of student-led review studies covering selected topics in modern quantum information technologies. The contributions explore a broad range of theoretical concepts, hardware architectures, and application domains, including quantum computing models, quantum sensing, photonic systems, and optimization techniques. The reviewed works examine both gate-based and alternative quantum computing paradigms, as well as hybrid quantum–classical approaches, highlighting their potential advantages and current technological limitations. Particular attention is given to the role of quantum algorithms and physical implementations in addressing computationally challenging problems, such as combinatorial optimization and simulation tasks. Overall, the paper provides a snapshot of the current landscape of quantum technologies from an interdisciplinary perspective, emphasizing ongoing challenges related to scalability, noise, and practical applicability, while outlining promising directions for future research and development.
A quantum machine may solve some complex problems that are intractable for even the most powerful classical computers. By exploiting quantum superposition and entanglement phenomena, quantum algorithms can achieve from polynomial to exponential speed up when compared to their best classical counterparts. A quantum computer will be a part of a heterogeneous, multi-core computer in which a classical processor will interact with several accelerators such as FPGAs, GPUs and also a quantum co-processor. Figure 1 shows the different layers of the quantum computer system stack [1]. Building such a quantum system requires contributions from different fields such as physics, electronics, computer science and computer engineering for addressing the following challenges: i) build scalable quantum chips integrating qubits with long coherence times and high-fidelity operations, ii) develop classical control electronics at possibly cryogenic temperatures and iii) create the microarchitecture as well as the software for quantum computation.
Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for simulating such devices using a general many-body electron-spin-resonance Hamiltonian that incorporates zero-field splitting, the Zeeman effect, hyperfine interactions, dipole-dipole spin-spin interactions, and electron-phonon decoherence. Within this framework, we combine Gray-encoded qudit-to-qubit mappings, qubit-wise commuting aggregation, and a multi-reference selected quantum Krylov fast-forwarding hybrid algorithm, aiming to access extended-time dynamics within the constraints of NISQ and early fault-tolerant hardware. Numerical simulations demonstrate the computation of operationally useful quantities including autocorrelation functions up to ∼100 ns, together with microwave absorption spectra and the ℓ1-norm of coherence, achieving 18-30% reductions in gate counts and circuit depth for Trotterized time-evolution circuits compared to unoptimized implementations. Using the nitrogen vacancy center in diamond as a testbed, we benchmark the framework against classical simulations and identify the reference-state selection in sQKFF as the primary factor governing accuracy at fixed hardware cost. This methodology provides a flexible blueprint for using quantum computers to design, compare, and optimize solid-state spin-qubit technologies under experimentally realistic conditions.
Abstract Interacting spin systems in solids underpin a wide range of quantum technologies, from quantum sensors and single-photon sources to spin-defect-based quantum registers and processors. We develop a quantum-computer-aided framework for simulating such devices using a general many-body electron-spin-resonance Hamiltonian that incorporates zero-field splitting, the Zeeman effect, hyperfine interactions, dipole–dipole spin–spin interactions, and electron-phonon decoherence. Within this framework, we combine gray-encoded qudit-to-qubit mappings, qubit-wise commuting aggregation, and a multi-reference selected quantum Krylov fast-forwarding (sQKFF) hybrid algorithm, aiming to access extended-time dynamics within the constraints of Noisy Intermediate-Scale Quantum and early fault-tolerant hardware. Numerical simulations demonstrate the computation of operationally useful quantities including autocorrelation functions up to ∼ 100 ns, together with microwave absorption spectra and the ℓ 1 -norm of coherence, achieving 18 % –30 % reductions in gate counts and circuit depth for Trotterized time-evolution circuits compared to unoptimized implementations. Using the nitrogen vacancy center in diamond as a testbed, we benchmark the framework against classical simulations and identify the reference-state selection in sQKFF as the primary factor governing accuracy at fixed hardware cost. This methodology provides a flexible blueprint for using quantum computers to design, compare, and optimize solid-state spin-qubit technologies under experimentally realistic conditions.
Quantum computing has emerged as a transformative frontier of computation. In recent years, quantum hardware has scaled at an unprecedented rate. As this momentum continues, the central challenge is shifting upward in the stack—from hardware-level feasibility toward system-level scalability. This thesis will focus on quantum computer architecture and compiler, introducing the challenges and opportunities to efficiently harness device capabilities and lower the demands on hardware technology, thereby accelerating timelines for practical quantum advantage.