Universal quantum computing promises solutions to a wide range of problems of significant scientific and socioeconomic impact that are computationally intractable using classical hardware. Since physical qubits are inherently noisy and prone to decoherence, realizing a sufficient number of logical qubits to unlock practically relevant problem classes will likely require quantum error correction, resulting in an overhead of millions of physical qubits. Among all competing hardware platforms, spin qubits in gate-defined quantum dots are uniquely positioned: single- and two-qubit gate fidelities routinely exceed the error-correction threshold, and the experimentally proven compatibility with industrial-grade semiconductor manufacturing may enable millions of qubits on a single chip. Realizing this potential, however, requires quantum processor architectures that scale to large qubit numbers with two‑dimensional connectivity while maintaining high operational fidelities. Building on the theoretical feasibility of high‑fidelity spin‑coherent electron shuttling, the SpinBus architecture is introduced to enable scaling to application-relevant qubit numbers. The SpinBus architecture leverages the conveyor-mode shuttling device named Quantum Bus (QuBus) for coherent qubit coupling over micron‑scale distances to accommodate, at the level of the quantum processor chip, wiring fan‑out and locally integrated control electronics at cryogenic temperatures. Device simulations for all relevant operations in the Si/SiGe platform validate operation fidelities exceeding 99 % as well as compatibility with the requirements of established semiconductor patterning technology. Control with room‑temperature electronics plausibly supports at least 144 qubits, while substantially larger quantum processor sizes are conceivable using cryogenic control electronics. For the experimental realization of QuBus devices, a novel high‑yield multilayer electron-beam lithography process, which can readily be adapted to different device layouts, was developed to fabricate the required > 100 aligned metallic gate electrodes. Benchmarking with a semiconductor industry‑inspired methodology and inspection of > 100 devices demonstrated 99 % gate fabrication yield and at least 5 nm overlay accuracy. Utilizing GaAs/(Al,Ga)As QuBus prototype devices with a 7 µm shuttling channel for quantized-current experiments validated key criteria for conveyor-mode shuttling, in particular linear current scaling for operation frequencies up to 40 MHz, and provided preliminary evidence consistent with quantized conveyor-mode electron transfer. These results support the viability of conveyor-mode shuttling for qubit coupling and indicate the suitability of QuBus devices for metrological applications.
Universal quantum computing promises solutions to a wide range of problems of significant scientific and socioeconomic impact that are computationally intractable using classical hardware. Since physical qubits are inherently noisy and prone to decoherence, realizing a sufficient number of logical qubits to unlock practically relevant problem classes will likely require quantum error correction, resulting in an overhead of millions of physical qubits. Among all competing hardware platforms, spin qubits in gate-defined quantum dots are uniquely positioned: single- and two-qubit gate fidelities routinely exceed the error-correction threshold, and the experimentally proven compatibility with industrial-grade semiconductor manufacturing may enable millions of qubits on a single chip. Realizing this potential, however, requires quantum processor architectures that scale to large qubit numbers with two‑dimensional connectivity while maintaining high operational fidelities. Building on the theoretical feasibility of high‑fidelity spin‑coherent electron shuttling, the SpinBus architecture is introduced to enable scaling to application-relevant qubit numbers. The SpinBus architecture leverages the conveyor-mode shuttling device named Quantum Bus (QuBus) for coherent qubit coupling over micron‑scale distances to accommodate, at the level of the quantum processor chip, wiring fan‑out and locally integrated control electronics at cryogenic temperatures. Device simulations for all relevant operations in the Si/SiGe platform validate operation fidelities exceeding 99 % as well as compatibility with the requirements of established semiconductor patterning technology. Control with room‑temperature electronics plausibly supports at least 144 qubits, while substantially larger quantum processor sizes are conceivable using cryogenic control electronics. For the experimental realization of QuBus devices, a novel high‑yield multilayer electron-beam lithography process, which can readily be adapted to different device layouts, was developed to fabricate the required > 100 aligned metallic gate electrodes. Benchmarking with a semiconductor industry‑inspired methodology and inspection of > 100 devices demonstrated 99 % gate fabrication yield and at least 5 nm overlay accuracy. Utilizing GaAs/(Al,Ga)As QuBus prototype devices with a 7 µm shuttling channel for quantized-current experiments validated key criteria for conveyor-mode shuttling, in particular linear current scaling for operation frequencies up to 40 MHz, and provided preliminary evidence consistent with quantized conveyor-mode electron transfer. These results support the viability of conveyor-mode shuttling for qubit coupling and indicate the suitability of QuBus devices for metrological applications.
Quantum processor architectures must enable scaling to large qubit numbers while providing two-dimensional qubit connectivity and exquisite operation fidelities. For microwave-controlled semiconductor spin qubits, dense arrays have made considerable progress, but are still limited in size by wiring fan-out and exhibit significant crosstalk between qubits. To overcome these limitations, we introduce the SpinBus architecture, which uses electron shuttling to connect qubits and features low operating frequencies and enhanced qubit coherence. Device simulations for all relevant operations in the Si/SiGe platform validate the feasibility with established semiconductor patterning technology and operation fidelities exceeding 99.9%. Control using room temperature instruments can plausibly support at least 144 qubits, but much larger numbers are conceivable with cryogenic control circuits. Building on the theoretical feasibility of high-fidelity spin-coherent electron shuttling as key enabling factor, the SpinBus architecture may be the basis for a spin-based quantum processor that meets the scalability requirements for practical quantum computing.
Quantum processor architectures must enable scaling to large qubit numbers while providing two-dimensional qubit connectivity and exquisite operation fidelities. For microwave-controlled semiconductor spin qubits, dense arrays have made considerable progress, but are still limited in size by wiring fan-out and exhibit significant crosstalk between qubits. To overcome these limitations, we introduce the SpinBus architecture, which uses electron shuttling to connect qubits and features low operating frequencies and enhanced qubit coherence. Device simulations for all relevant operations in the Si/SiGe platform validate the feasibility with established semiconductor patterning technology and operation fidelities exceeding 99.9 %. Control using room temperature instruments can plausibly support at least 144 qubits, but much larger numbers are conceivable with cryogenic control circuits. Building on the theoretical feasibility of high-fidelity spin-coherent electron shuttling as key enabling factor, the SpinBus architecture may be the basis for a spin-based quantum processor that meets the scalability requirements for practical quantum computing.
Abstract Small spin-qubit registers defined by single electrons confined in Si/SiGe quantum dots operate successfully and connecting these would permit scalable quantum computation. Shuttling the qubit carrying electrons between registers is a natural choice for high-fidelity coherent links provided the overhead of control signals stays moderate. Our proof-of-principle demonstrates shuttling of a single electron by a propagating wave-potential in an electrostatically defined 420 nm long Si/SiGe quantum-channel. This conveyor-mode shuttling approach requires independent from its length only four sinusoidal control signals. We discuss the tuning of the signal parameters, detect the smoothness of the electron motion enabling the mapping of potential disorder and observe a high single-electron shuttling fidelity of 99.42 ± 0.02% including a reversal of direction. Our shuttling device can be readily embedded in industrial fabrication of Si/SiGe qubit chips and paves the way to solving the signal-fanout problem for a fully scalable semiconductor quantum-computing architecture.
Dynamic qubit routing is emerging as a promising architectural path for semiconductor quantum processors. Charge carriers can be rapidly moved around on a chip using traveling-wave potentials known as conveyors, preserving the spin state with high fidelity. Originally developed for spin transport, conveyor-mode shuttling may also offer opportunities for performing qubit operations directly controlled by the motion itself. Here, we demonstrate coherent single- and two-qubit control by conveyor-mode electron shuttling, using two conceptually different approaches. First, conveyor electric-dipole spin resonance (conveyor EDSR) achieves high-fidelity rotations by resonantly shuttling spins through transverse magnetic-field gradients at their mean Larmor frequency. Second, conveyor diabatic gates exploit quantization-axis tilts for tunable bang-bang control. Combining diabatic conveyor transport with exchange activation controlled by the motion directly yields a variety of effective two-qubit interactions selectable via the shuttling speed and distance. These experimental results motivate an architectural paradigm of reconfigurable and transport-driven spin qubits.
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.
Single spin quantum dot qubits in silicon are a promising candidate for a scalable quantum processor due to their long coherence times, compact size, and ease of integration into existing fabrication technologies. Realizing a large quantum processor composed of thousands or more logical qubits requires the integration of conventional transistor circuitry \nand wiring interconnects to control each individual dot in the processor. The high density of control wiring required for these processors presents many engineering challenges. In this thesis, we propose a surface code quantum processor for silicon quantum dot qubits based on a node/network architecture. Local nodes consisting of just seven quantum dots are \nspatially separated on the order of microns to facilitate space for the necessary high density wiring. Entanglement is distributed between individual nodes via shuttling of entangled electron pairs throughout the network. X or Z stabilizer operations, necessary for operating the surface code, are realized by distributing three electron spin singlet pairs across four local nodes followed by local gate operations and ancilla measurements. Simulations of electron shuttling indicate that adiabatic transport is possible on timescales that do not bottleneck the processor speed. Phase rotation of the shuttled spin, induced by the Stark shift, can lower the overall shuttling fi delity; however, the error can be mitigated by proper electrostatic tuning of the stationary electron's g-factor. Using realistic noise models, we estimate error thresholds with respect to single and two-qubit gate fidelities as well as \nsinglet dephasing errors during shuttling. Electron shuttling is a key resource of the proposed network architecture. We continue the shuttling simulations by presenting an algorithm for finding constant-adiabatic shuttling control pulses, which enables a more rigorous study of how different conditions impact the shuttling speed and fidelity. These constant adiabatic pulses are used to optimize the physical device geometry to maximize charge shuttling speeds up to 300 nm/ns in the single-valley case. We then switch to an effective Hamiltonian representation where spin and valley degrees of freedom are accounted for during shuttling. Using realistic device and material parameters, shuttle speeds in the range 10-100 nm/ns with high spin entanglement \n fidelities are obtained when the tunneling energy exceeds the Zeeman energy. High fidelity shuttling also requires the inter-dot valley phase difference to be below a threshold determined by the ratio of tunneling and Zeeman energies, so that spin-valley-orbit mixing is weak. In this regime, we find that the primary source of infi delity is a coherent spin rotation that is correctable, in principle, using single spin rotations. Two-qubit gates in the network architecture are mediated by the exchange interaction, \nan interaction that stems from the Coulomb interaction but manifests as a rotation between the |0,1> and |1,0> two qubit states. Realizing fault tolerant two-qubit gates has proven difficult in silicon quantum dots due to charge noise which perturbs the electron orbitals states, causing decoherence. Quantitatively accurate modelling of exchange in general quantum dot networks is important towards realizing fault tolerant gates. Traditional modelling methods, such as a full con figuration interaction approach, are cumbersome due to significant computational overhead required when accounting for the electron-electron interactions in the calculation. We present a modi ed linear combination of harmonic orbitals con figuration interaction (LCHO-CI) approach which signifi cantly reduces the computational time for obtaining quantitatively accurate estimations of exchange. The method works by approximating the single electron orbitals of the quantum dot network using an orthogonal basis of harmonic orbitals. This choice of orthogonal basis allows a precalculated library of matrix elements to be used in evaluating the Coulomb interactions, which speeds up the LCHO-CI calculation. The modi ed LCHO-CI approach is then used to study how the physical device geometry impacts the charge noise sensitivity of a double quantum dot system. We fi nd that, in general, geometries which increase the dot charging energy and decrease the gate lever arms improve the system's sensitivity to charge noise. We conclude this thesis by pivoting away from theoretical studies of silicon quantum dots and towards experimental studies of electron transport in dopant-free GaAs heterostructures. In modulation doped GaAs heterostructures, a doping layer is used to induce a two-dimensional electron gas (2DEG) at the heterojunction. Dopant-free GaAs lack the doping layer which makes fabrication more difficult as local electron reservoirs must be used to bring carriers and induce a 2DEG. The lack of the doping layer offers several advantages over modulation doped heterostructures, such as gate-ability of the 2DEG and ability to make ambipolar devices (both n- and p-type ohmic contacts). Realizing n- and p-type ohmic contacts requires etching a recess pit and depositing the ohmic material at an angle in order to preventing screening of the top gate when inducing a 2DEG or two-dimensional hole gas (2DHG). Magnetotransport experiments are used to characterize an induced 2DEG and 2DHG in a Hall bar fabricated on a 310 nm deep single heterojunction. The carrier mobility and density can be tuned using the top gate, and we achieve peak mobility values of 4.5E6 cm2/Vs and 0.65E6 cm2/Vs for the 2DEG and 2DHG respectively. We then move to a one-dimensional system and study electron transport through a quantum point contact. Conductance quantization is observed, and subband spectroscopy \nmeasurements indicate a 1D subband spacing of 4.5 meV. Finally, we study dynamically driven electron transport in a zero-dimensional system using a tunable-barrier quantum dot acting as a single electron pump. Single electron pumping is observed up to T = 5 K, and fi ts to the electron cascade model suggests pumping errors of 1.87 ppm when operated at a driving frequency of f = 500 MHz.