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We demonstrate strong dispersive coupling between a fluxonium superconducting qubit and a 690 megahertz mechanical oscillator, extending the reach of circuit quantum acousto-dynamics (cQAD) experiments into a new range of frequencies. We have engineered a qubit-phonon coupling rate of g≈2π×14MHz, and achieved a dispersive interaction that exceeds the decoherence rates of both systems while the qubit and mechanics are highly nonresonant (Δ/g≳10). Leveraging this strong coupling, we perform phonon-number-resolved measurements of the mechanical resonator and investigate its dissipation and dephasing properties. Our results demonstrate the potential for fluxonium-based hybrid quantum systems, and a path for developing new quantum sensing and information processing schemes with phonons at frequencies below 700 MHz to significantly expand the toolbox of cQAD.

Superconducting quantum circuits are a promising hardware platform for realizing a fault-tolerant quantum computer. Accelerating progress in this field of research demands general approaches and computational tools to analyze and design more complex superconducting circuits. We develop a framework to systematically construct a superconducting quantum circuit's quantized Hamiltonian from its physical description. As is often the case with quantum descriptions of multicoordinate systems, the complexity rises rapidly with the number of variables. Therefore, we introduce a set of coordinate transformations with which we can find bases to diagonalize the Hamiltonian efficiently. Furthermore, we broaden our framework's scope to calculate the circuit's key properties required for optimizing and discovering novel qubits. We implement the methods described in this work in an open-source Python package $\tt{SQcircuit}$. In this manuscript, we introduce the reader to the $\tt{SQcircuit}$ environment and functionality. We show through a series of examples how to analyze a number of interesting quantum circuits and obtain features such as the spectrum, coherence times, transition matrix elements, coupling operators, and the phase coordinate representation of eigenfunctions.

We can encode a qubit in the energy levels of a quantum system. Relaxation and other dissipation processes lead to decay of the fidelity of this stored information. Is it possible to preserve the quantum information for a longer time by introducing additional drives and dissipation? The existence of autonomous quantum error correcting codes answers this question in the positive. Nonetheless, discovering these codes for a real physical system, i.e., finding the encoding and the associated driving fields and bath couplings, remains a challenge that has required intuition and inspiration to overcome. In this work, we develop and demonstrate a computational approach based on adjoint optimization for discovering autonomous quantum error correcting codes given a Hamiltonian description of a physical system. We implement an optimizer that searches for a logical subspace and control parameters to better preserve quantum information. We demonstrate our method on a system of a harmonic oscillator coupled to a lossy qubit, and find that varying the Hamiltonian distance in Fock space—a proxy for the control hardware complexity—leads to discovery of different and new error correcting schemes. We discover what we call the sqrt[3] code, realizable with a Hamiltonian distance d=2, and propose a hardware-efficient implementation based on superconducting circuits.

Since the advent of bipolar transistor at Bell AT&T laboratories, the constant development of electronics industry over the past six decades have pushed the size of active semiconductor devices to its boundaries. The Moore's law which dictated doubling speed and halving physical dimensions every 18 months is now facing its end pretty soon. Current commercial technology is now being limited to the atomic spacing on one hand, and power density on the other hand. Solar power as well as quantum computing are also another relevant areas which would need certain physical implementations and materials. In short, the moving force and economic power behind this industry is enormous, however, technological bottlenecks are real and showing themselves very clearly now. Directions which may ultimately alleviate these restrictions are not too many, including two-dimensional nano-electronics, memristive networks, spintronics, compound semiconductor devices, optoelectronics interconnects, just to mention a few. This talk will address two important paradigms in this area 1) What are the real challenges in this technology? 2) What are the roots of retardation in our country and what can be done to merge into the international efforts? I will try to plant seeds to resolve some of the most basic misunderstandings in our academia and redirect the technology investments into a much more fruitful direction, with hopes that the next generation of our experts will have a much wider and relaxed atmosphere to excel and prosper.