Universal control of a six-qubit quantum processor in silicon
Stephan G. J. Philips, Mateusz Tomasz Mądzik, Sergey V. Amitonov, Sander L. de Snoo, Maximilian Rimbach-Russ, Nima Kalhor, Christian Volk, William I. L. Lawrie, Delphine Brousse, Larysa Tryputen, Brian Paquelet Wuetz, Amir Sammak, Menno Veldhorst, Giordano Scappucci, Lieven M. K. Vandersypen
Abstract Future quantum computers capable of solving relevant problems will require a large number of qubits that can be operated reliably 1 . However, the requirements of having a large qubit count and operating with high fidelity are typically conflicting. Spins in semiconductor quantum dots show long-term promise 2,3 but demonstrations so far use between one and four qubits and typically optimize the fidelity of either single- or two-qubit operations, or initialization and readout 4–11 . Here, we increase the number of qubits and simultaneously achieve respectable fidelities for universal operation, state preparation and measurement. We design, fabricate and operate a six-qubit processor with a focus on careful Hamiltonian engineering, on a high level of abstraction to program the quantum circuits, and on efficient background calibration, all of which are essential to achieve high fidelities on this extended system. State preparation combines initialization by measurement and real-time feedback with quantum-non-demolition measurements. These advances will enable testing of increasingly meaningful quantum protocols and constitute a major stepping stone towards large-scale quantum computers.
Abstract Future quantum computers capable of solving relevant problems will require a large number of qubits that can be operated reliably 1 . However, the requirements of having a large qubit count and operating with high fidelity are typically conflicting. Spins in semiconductor quantum dots show long-term promise 2,3 but demonstrations so far use between one and four qubits and typically optimize the fidelity of either single- or two-qubit operations, or initialization and readout 4–11 . Here, we increase the number of qubits and simultaneously achieve respectable fidelities for universal operation, state preparation and measurement. We design, fabricate and operate a six-qubit processor with a focus on careful Hamiltonian engineering, on a high level of abstraction to program the quantum circuits, and on efficient background calibration, all of which are essential to achieve high fidelities on this extended system. State preparation combines initialization by measurement and real-time feedback with quantum-non-demolition measurements. These advances will enable testing of increasingly meaningful quantum protocols and constitute a major stepping stone towards large-scale quantum computers.
The simplicity of encoding a qubit in the state of a single electron spin and the potential for their integration into industry-standard microchips continue to drive the field of semiconductor-based quantum computing. After a series of key first-principles demonstrations validating universal gate operations, initialization and readout, three-qubit algorithms have already been realized with silicon-based quantum dots in past years. Devices containing more qubits have become available since then but experiments have not gone beyond meeting the DiVincenzo criteria. In this work, we fully exploit the capacity of a spin-qubit array and implement a six-qubit quantum circuit, the largest utilizing semiconductor quantum technology. By programming the quantum processor, we execute quantum circuits across all permutations of three, four, five, and six neighboring qubits, demonstrating successful programmable multi-qubit operation throughout the array. Using an error model that incorporates quasi-static noise allows us to qualitatively explain some key trends in our experimental results and highlight the necessity to minimize idling times through simultaneous operations, extending dephasing times, and consistently improving state preparation and measurement fidelities.
Quantum computers have gained widespread interest as they can potentially solve problems that are intractable even for today’s supercomputers, such as the simulation of quantum systems as initially proposed by Feynman. To achieve such tremendous progress, a quantum computer relies on processing the information stored in quantum bits (qubits), the fundamental units of quantum computation, similar to the bits in a classical (i.e., non-quantum) processor. In general, a quantum processor comprising several qubits is connected through a quantum-to-classical interface consisting of classical electrical circuits for manipulating and reading out their quantum state. The accuracy of an operation on a qubit is characterized using the fidelity, which is 100 % in case of a perfect operation. In practice, a fidelity between 99 % and 99.9 % is typically achieved in today’s experiments with less than 100 qubits, limited by non-idealities in the control signals and by the implementation of the physical qubit itself. Since such qubit fidelities are too low to execute relevant quantum algorithms, quantum error correction schemes have been developed which rely on a much larger number of qubits to correct for possible errors, resulting in the need for quantum processors with thousands or millions of qubits. Solid-state qubits promise the largescale integration required to scale to millions of qubits, as they exploit the lithographic fabrication techniques borrowed from the semiconductor industry. However, state-of-theart solid-state qubits, such as transmons and single-electron spin qubits, must be typically cooled to cryogenic temperatures in a dilution refrigerator to exhibit quantum behavior. Because of the limited number of qubits (< 100) in state-of-theart solid-state quantum processors, the classical controller is currently implemented by general-purpose instruments or by tailor-made controllers operating at room temperature connected via several wires to the qubits in the cryogenic chamber. However, these systems must scale to support millions of qubits. While scaling up the underlying quantum processor is already exceptionally challenging, building the electronics required to interface such a large-scale processor is just as relevant and arduous.
For the realization of a quantum computer, a good qubit design as the basic building block is a nontrivial starting point. To fully leverage the potential of quantum computing, quantum processors will likely have to incorporate billions of high-quality qubits. Several approaches are being pursued and exhibit different strength and weaknesses. The device concepts and fabrication procedures for semiconductor based qubits are very similar to those used in the semiconductor industry. Using the spin-degree of freedom, their coherence properties and the quality of single-qubit operations have now reached the required level and are on par with competing approaches. Two-qubit operations will likely follow suit in the near future. With these basic requirements being met, it is now time to think if and how increasingly large multi-qubit systems and eventually functional quantum processor can be realized. This quest raises many pertinent questions, some of which equally apply to other qubit platforms. How reproducibly can the different types of semiconductor qubits be produced? How can their operating point be adjusted efficiently and in an automated way? How can they be connected to form meaningful multi-qubit circuits? How severe are multi-qubit control issues such as crosstalk and frequency crowding, and how can they be avoided? What control system architectures are most suitable for operating large numbers of qubits? What is the limit of cryogenic electronics regarding power consumption and integration density? This paper gives a (partial) overview of the state of the art in the field and discusses future challenges associated with the realization of large-scale quantum processors, many of which will greatly benefit from input from engineering science. The guiding vision is that of a highly integrated quantum processor with an ultra-low power cryogenic control system.
Silicon-based spin qubits have emerged as a promising platform for scalable quantum computation due to their compatibility with advanced semiconductor fabrication and integration with classical CMOS electronics. As fabrication capabilities advance toward larger, higher-yield devices, the field is transitioning from academic prototypes toward processors ultimately requiring millions of qubits. This shift places increasing emphasis on developing operating techniques that scale with qubit number. In this thesis, a four qubit SiMOS processor is used to investigate three key aspects of multi-qubit operation for spin-based quantum computing. First, tuning and operation techniques for parallel double-quantum-dot unit cells are developed. Electron loading strategies enable four-qubit operation in an isolated charge configuration, and universal single- and two-qubit control is demonstrated. The native gate set is characterised using gate set tomography. The processor is operated as two unit cells that can be initialised and read out in parallel, providing two independent parity measurements per shot, without increasing operation time or degrading state preparation and measurement fidelity. Second, control techniques for generating multi-qubit entangled states and executing general quantum circuits are established. Three-qubit maximally entangled states, including cluster and Greenberger–Horne–Zeilinger states, are generated and measured with a maximum fidelity of 82.5%. A Mermin value of 3.14 is achieved, certifying genuine tripartite entanglement. A fully symmetric dynamically decoupled gate sequence is developed, extending the entanglement lifetime beyond T2* to a limit set by T2-Hahn. A workflow for compiling, executing, and analysing arbitrary circuits from OpenQASM is also demonstrated. Finally, the first mid-circuit measurements in a silicon spin-qubit system are presented. This capability is extended to feedforward control, including a novel “in-layer” method that performs conditional phase operations without routing information to the classical control layer. This approach leverages measurement-induced backaction as a control mechanism. Both in-layer and FPGA-enabled feedforward strategies are benchmarked, and their dominant error channels are identified.
Silicon spin qubits satisfy the necessary criteria for quantum information processing. However, a demonstration of high-fidelity state preparation and readout combined with high-fidelity single- and two-qubit gates, all of which must be present for quantum error correction, has been lacking. We use a two-qubit Si/SiGe quantum processor to demonstrate state preparation and readout with fidelity greater than 97%, combined with both single- and two-qubit control fidelities exceeding 99%. The operation of the quantum processor is quantitatively characterized using gate set tomography and randomized benchmarking. Our results highlight the potential of silicon spin qubits to become a dominant technology in the development of intermediate-scale quantum processors.
Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms give promise for the construction of a quantum computer based on millions of interacting qubits. However, the classical-quantum interface remains a nascent field of exploration. Here, we propose an architecture for a silicon-based quantum computer processor based on complementary metal-oxide-semiconductor (CMOS) technology. We show how a transistor-based control circuit together with charge-storage electrodes can be used to operate a dense and scalable two-dimensional qubit system. The qubits are defined by the spin state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.