This list shows a selection of the larger quantum computers as of August 2024, based on publicly available sources. The list is not exhaustive, there are many other systems that are not mentioned here. Company #Qubits + chip name Platform + notes IBM 1121 Superconducting “Condor” + Fast 127 + Precise gates “Eagle” – Limited connectivity Rigetti 79 “Aspen-M-3” 83 “Ankaa-2” Google 105 “Sycamore” University of Science and Technology of China, Hefei 66 IQM 20 “Garnet” PsiQuantum 0 Photonic Quix 20 modes + Fast University of Science and Technology of China, Hefei 100 modes, 50 photons, (equivalent to roughly 90 limited qubits). Imprecise Different formalism lonQ 36 Trapped ions “Forte” + Connectivity Quantinuum 32 + Precise “H1-2” – Slow operations 56 “H2-1” Alpine Quantum Technologies 24 Pasqal 100 as computer Cold atoms 196 as simulator + Connectivity QuEra 280 – Slow operations D-Wave 5000 D-Wave's Quantum Annealers use superconducting qubits which specialize in a single algorithm: annealing .
This list shows a selection of the larger quantum computers as of August 2024, based on publicly available sources. The list is not exhaustive, there are many other systems that are not mentioned here. Company #Qubits + chip name Platform + notes IBM 1121 Superconducting “Condor” + Fast 127 + Precise gates “Eagle” – Limited connectivity Rigetti 79 “Aspen-M-3” 83 “Ankaa-2” Google 105 “Sycamore” University of Science and Technology of China, Hefei 66 IQM 20 “Garnet” PsiQuantum 0 Photonic Quix 20 modes + Fast University of Science and Technology of China, Hefei 100 modes, 50 photons, (equivalent to roughly 90 limited qubits). Imprecise Different formalism lonQ 36 Trapped ions “Forte” + Connectivity Quantinuum 32 + Precise “H1-2” – Slow operations 56 “H2-1” Alpine Quantum Technologies 24 Pasqal 100 as computer Cold atoms 196 as simulator + Connectivity QuEra 280 – Slow operations D-Wave 5000 D-Wave's Quantum Annealers use superconducting qubits which specialize in a single algorithm: annealing .
Quantum computing has moved from a theoretical curiosity to a strategic technological priority for governments, hyperscale technology companies, and a fast-growing ecosystem of specialized start-ups. This survey provides a comprehensive, self-contained overview of the field as it stands in 2026. We first lay out the physical and mathematical foundations of quantum computation, superposition, entanglement, interference, and measurement, and contrast them systematically with classical computing. We then survey the competing hardware modalities (superconducting, trapped-ion, photonic, neutral-atom, topological, and spin qubits) and the logic gates and circuit model that operate on them, before reviewing the canonical quantum algorithms that motivate the field. We classify the major computing paradigms (gate-based, annealing, adiabatic, measurement-based, and topological), and examine the current state of the market, the national strategies of leading countries, and the roles played by IBM, Google, Microsoft, Amazon, NVIDIA, and a cohort of pure-play companies. Dedicated sections map undergraduate and graduate education pathways, including specific universities offering quantum-focused degrees, the domains in which quantum computers are expected to create value, and the career paths now opening in the field. We close with an explicit three-phase roadmap \qtoday{}, \qtomorrow{}, and the \qfuture{} and a candid discussion of the open scientific and engineering problems that stand between the present noisy intermediate-scale quantum (NISQ) era and a fault-tolerant, utility-scale quantum computing industry.
Quantum computing promises to revolutionize several scientific and industrial domains by tackling problems that are intractable for classical supercomputers. At the centre of this effort is the quantum processor unit (QPU), implemented today across multiple physical qubit platforms. This review provides a comparative analysis of the state of quantum processors as of late 2024/early 2025, focusing on superconducting qubits, trapped ions, photonic systems, neutral atoms, silicon spin qubits, and emerging topological approaches. We compile and compare recent processor generations such as IBM’s Heron family, Google’s updated Sycamore-class devices, Quantinuum’s H-series, IonQ’s Aria and Forte, neutral-atom platforms with more than 1,000 trapped atoms, and silicon spin prototypes like Tunnel Falls. Key performance metrics, including qubit count, gate and readout fidelity, coherence time, operation speed, and holistic benchmarks such as Quantum Volume (QV) and Algorithmic Qubits (#AQ) are examined with reference to concrete experimental milestones. We discuss algorithmic capabilities demonstrated on current hardware, early realizations of logical qubits and fault-tolerant primitives, and the distinction between feasibility-oriented “quantum advantage” experiments and emerging signs of practical “quantum utility”. Finally, we outline the main technical bottlenecks for each platform on the path from today’s NISQ devices toward universal fault-tolerant quantum computers.
Quantum computing is a paradigm shift in computational science, where computational tasks that cannot be computationally tackled with binary computing systems can be tackled using quantum mechanics principles, including superposition, entanglement, and quantum interference. The present paper gives a comprehensive summary of the present condition of quantum computing, including the most advanced hardware systems, such as topological qubits, photonics processors, trapped-ion systems and superconducting qubits, and their corresponding advantages and technical challenges. Also, quantum algorithms, including the Quantum Approximate Optimization Algorithm (QAOA) and the variational quantum eigen solvers (VQE), include a summary of the first algorithm, Shor's factorization method, and the second algorithm, Grover's search algorithm. Applications of such algorithms are evaluated in such areas as financial modeling, machine learning, material science, drug discovery, and cryptography. Taking into account the information provided by large research facilities and technology firms, the conditions under which quantum systems can outperform conventional technology, such a concept as quantum advantage is given specific focus in this review. Moreover, this paper pays particular attention to the key barriers to effective implementation, such as qubit decoherence, large error rates, scalability issues, and the lack of fault-tolerant quantum devices that can be sold commercially. Regarding the noisy intermediate-scale quantum (NISQ) devices that are expected to be available in the near future, we discuss novel approaches to quantum error correction, especially surface code and concatenated code. The quantum software industry, such as IBM Qiskit, Google Cirq, and Microsoft Q, and an evaluation of quantum workforce and research facility readiness across the globe is also discussed. In the end, this work highlights essential potential future paths, such as standards for post-quantum cryptography, hybrid quantum-classical computation, quantum networking and the quantum internet, and the long-term aims for universal fault- tolerant quantum computers. The review should provide researchers, graduate students, and practitioners with a systematic and up-to-date base to understand the fast-growing discipline of quantum computing and its extensive implications on science and business.
Quantum computers, if fully realized, promise to be a revolutionary technology. As a result, quantum computing has become one of the hottest areas of research in the last few years. Much effort is being applied at all levels of the system stack, from the creation of quantum algorithms to the development of hardware devices. The quantum age appears to be arriving sooner rather than later as commercially useful small-to-medium sized machines have already been built. However, full-scale quantum computers, and the full-scale algorithms they would perform, remain out of reach for now. It is currently uncertain how the first such computer will be built. Many different technologies are competing to be the first scalable quantum computer.
Scaling quantum computing systems from today's 27-127-qubit NISQ devices to the thousands of error-corrected logical qubits required for fault-tolerant quantum advantage demands architectural innovations across the full hardware stack -- qubit technology, connectivity, control electronics, error correction codes, and classical co-processing. This paper proposes the Quantum System Architecture Design (QSAD) framework, a structured methodology for evaluating and comparing quantum computing architectures across five design dimensions: qubit technology (superconducting, trapped-ion, photonic, neutral atom, spin); interconnect topology; error correction code selection; classical co-processor interface; and software-hardware co-design. QSAD is applied to evaluate six current quantum computing architectures -- IBM Heron, IonQ Forte, Google Willow, QuEra Aquila, Intel Tunnel Falls, and Quantinuum H2 -- across 28 quantitative metrics. IBM Heron and Quantinuum H2 score highest on QSAD composite (0.848 and 0.864 respectively). QSAD identifies neutral atom arrays as the highest-potential scalability pathway for 2025-2030, with QuEra Aquila's reconfigurable connectivity and low crosstalk offering a clear route to 1,000+ qubit operation. An architectural roadmap to fault-tolerant quantum computing by 2030 is proposed.