Superconducting quantum devices

Abstract:

Superconducting quantum circuits are a key platform for advancing quantum information processing and simulation. Scaling efforts currently encounter challenges such as Josephson-junction fabrication yield, design frequency targeting, and long-range crosstalk arising both from spurious microwave modes and intrinsic interactions between qubits. We demonstrate a scalable 4x4 square lattice with low crosstalk, comprising 16 fixed-frequency transmon qubits with nearest-neighbor capacitive coupling that is implemented in a tileable, 3D-integrated circuit architecture with off-chip inductive shunting to mitigate spurious enclosure modes. We report on the design and comprehensive characterization, and show that our implementation achieves targeted device parameters with very low frequency spreads, long-range parasitic couplings and simultaneous single-qubit gate errors across the device. Our results provide a promising pathway toward a scalable superconducting square lattice topology for quantum error correction and simulation.

Abstract:

Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including the nascent field of quantum computing (QC). The counterintuitive nature and high-dimensional mathematics of QC make it a prime candidate for AI’s data-driven learning capabilities, and in fact, many of QC’s biggest scaling challenges may ultimately rest on developments in AI. However, bringing leading techniques from AI to QC requires drawing on disparate expertise from arguably two of the most advanced and esoteric areas of computer science. Here we aim to encourage this cross-pollination by reviewing how state-of-the-art AI techniques are already advancing challenges across the hardware and software stack needed to develop useful QC - from device design to applications. We then close by examining its future opportunities and obstacles in this space.

Abstract:

Scaling superconducting quantum processors to large qubit counts faces challenges in control-signal delivery, thermal management, and hardware complexity, particularly in achieving microwave signal multiplexing and long-distance quantum information routing at millikelvin temperatures. We propose a space-time modulated Josephson-junction metasurface architecture to generate and multiplex microwave control signals directly at millikelvin temperatures. Theoretical and numerical results demonstrate the generation of multiple frequency tones with controlled parameters, enabling efficient and scalable qubit control while minimizing thermal loads and wiring overhead. We derive the nonlinear wave equation governing this system, simulate beam steering and frequency conversion, and discuss the feasibility of experimental implementation. These results lay the groundwork for a next-generation cryogenic signal-delivery paradigm that may enable scaling of superconducting quantum processors to thousands of qubits without overwhelming limited dilution-refrigerator cooling power.