We show how robust and scalable quantum computing can be realized on an arbitrarily large two dimensional arrays of qubits with fixed longitudinal couplings despite significant uncertainty in all the qubit-qubit and drive-qubit coupling strengths. This opens the possibility for bypassing the fabrication complexity associated with tunable couplers required in conventional quantum computing hardware. Our approach is based on driving a chosen subarray of qubits such that the total multi-qubit Hamiltonian can be decomposed into a sum of commuting few-qubit blocks and on efficient optimization of the unitary evolution within each block. Robust optimal control is then employed to implement a universal set of quantum gates with fidelities around 99.99% despite 1% uncertainty in the Hamiltonian's parameters. This robust feature is crucial for scaling up as uncertainty in the properties of qubits is substantial in large devices.
We show how robust and scalable quantum computing can be realized on an arbitrarily large two dimensional arrays of qubits with fixed longitudinal couplings despite significant uncertainty in all the qubit-qubit and drive-qubit coupling strengths. This opens the possibility for bypassing the fabrication complexity associated with tunable couplers required in conventional quantum computing hardware. Our approach is based on driving a chosen subarray of qubits such that the total multi-qubit Hamiltonian can be decomposed into a sum of commuting few-qubit blocks and on efficient optimization of the unitary evolution within each block. Robust optimal control is then employed to implement a universal set of quantum gates with fidelities around 99.99% despite 1% uncertainty in the Hamiltonian's parameters. This robust feature is crucial for scaling up as uncertainty in the properties of qubits is substantial in large devices.
Abstract We propose a scheme for scalable and robust quantum computing on two-dimensional arrays of qubits with fixed longitudinal coupling. This opens the possibility for bypassing the device complexity associated with tunable couplers required in conventional quantum computing hardware. Our approach is based on driving a subarray of qubits such that the total multi-qubit Hamiltonian can be decomposed into a sum of commuting few-qubit blocks, and efficient optimisation of the unitary evolution within each block. The driving pulses are optimised to implement a target gate on the driven qubits, and at the same time identity gates on the neighbouring undriven qubits, cancelling any unwanted evolution due to the constant qubit-qubit interaction. We show that it is possible to realise a universal set of quantum gates with high fidelity on the basis blocks, and by shifting the driving pattern one can realise an arbitrary quantum circuit on the array. Allowing for imperfect Hamiltonian characterisation, we use robust optimal control to obtain fidelities around 99.99% despite 1% uncertainty in the qubit-qubit and drive-qubit couplings, and a detuning uncertainty at 0.1% of the qubit-qubit coupling strength. This robust feature is crucial for scaling up as parameter uncertainty is significant in large devices.
Accurate and efficient implementation of parallel quantum gates is crucial for scalable quantum information processing. However, the unavoidable crosstalk between qubits in current noisy processors impedes the achievement of high gate fidelities and renders full Hilbert-space control optimization prohibitively difficult. Here, we overcome this challenge by reducing the full-system optimization to crosstalk-robust control over constant-sized subsystems, which dramatically reduces the computational cost. Our method effectively eliminates the leading-order gate operation deviations induced by crosstalk, thereby suppressing error rates. Within this framework, we construct analytical pulse solutions for parallel single-qubit gates and numerical pulses for parallel multi-qubit operations. We validate the proposed approach numerically across multiple platforms, including coupled nitrogen-vacancy centers, a nuclear-spin processor, and superconducting-qubit arrays with up to 200 qubits. As a result, the noise scaling is reduced from exponential to linear for parallel single-qubit gates, and an order-of-magnitude reduction is achieved for parallel multi-qubit gates. Moreover, our method does not require precise knowledge of crosstalk strengths and makes no assumption about the underlying qubit connectivity or lattice geometry, thereby establishing a scalable framework for parallel quantum control in large-scale quantum architectures.
A major current challenge in solid-state quantum computing is to scale qubit arrays to a larger number of qubits. This is hampered by the complexity of the control wiring for the large number of independently tunable interqubit couplings within these arrays. One approach to simplifying the problem is to use a qubit array with fixed Ising (ZZ) interactions. When simultaneously driving a specific subset of qubits in such a system, the dynamics are confined to a set of commuting su(2) subalgebras. Within these su(2)s we describe how to perform X-gates and $\frac{\ensuremath{\pi}}{2}\phantom{\rule{4pt}{0ex}}\text{ZZ}$ rotations robustly against either leakage, which is the main source of error in transmon qubits, or coupling fluctuations, which is the main source of infidelity in flux or semiconductor spin qubits. These gates together with virtual-z gates form a universal set of gates for quantum computing. We construct this set of robust gates for two-edge, three-edge, and four-edge vertices, which compose all existing superconducting qubit and semiconductor spin qubit arrays.
We introduce crosstalk-robust gate sets, which are obtained using a novel, scalable optimal control problem exploiting locality. Through the suppression of pairwise quantum crosstalk, the gate sets enable robustness that extends to multi-qubit circuits. The IBM Quantum Platform devices provide a testbed for our gate sets, where we study their efficacy via error suppression protocols and randomized parallel single-qubit circuits of up to eight qubits. Furthermore, we provide the first known assessment of the impact of complete optimal control gate sets on quantum algorithms. Using a Hamiltonian simulation of a four-qubit transverse field Ising model, we show that noise-informed gates enhance median algorithmic performance by a factor of four over baseline Gaussian gates using the same calibration procedures. Lastly, we provide numerical evidence that optimized gate sets enable larger qubit-qubit coupling strengths that can cut two-qubit gate times in half. This result confirms that hardware-software co-design using quantum optimal control can create new opportunities for quantum computing architectures.
Universal quantum computing requires the ability to perform every unitary operation, i.e., evolution operator controllability. In view of developing resource-efficient quantum processing units (QPUs), it is important to determine how many local controls and qubit-qubit couplings are required for controllability. Unfortunately, assessing the controllability of large qubit arrays is a difficult task, due to the exponential scaling of Hilbert space dimension. Here we show that it is sufficient to connect two qubit arrays that are evolution operator controllable by a single entangling two-qubit gate in order to obtain a composite qubit array that is evolution operator controllable. The proof provides a template to build up modular QPUs from smaller building blocks with reduced numbers of local controls and couplings. We illustrate the approach with two examples, consisting of 10, respectively 127 qubits, inspired by IBM quantum processors.
Building blocks of quantum computers have been demonstrated in small to intermediate-scale systems. As one of the leading platforms, the trapped ion system has attracted wide attention. A significant challenge in this system is to combine fast high-fidelity gates with scalability and convenience in ion trap fabrication. Here we propose an architecture for large-scale quantum computing with a two-dimensional array of atomic ions trapped at such large distance which is convenient for ion-trap fabrication but usually believed to be unsuitable for quantum computing as the conventional gates would be too slow. Using gate operations far outside of the Lamb–Dicke region, we show that fast and robust entangling gates can be realized in any large ion arrays. The gate operations are intrinsically parallel and robust to thermal noise, which, together with their high speed and scalability of the proposed architecture, makes this approach an attractive one for large-scale quantum computing.