A parametrically programmable delay line for microwave photons

  1. Takuma Makihara,
  2. Nathan Lee,
  3. Yudan Guo,
  4. Wenyan Guan,
  5. and Amir H. Safavi-Naeini
Delay lines capable of storing quantum information are crucial for advancing quantum repeaters and hardware efficient quantum computers. Traditionally, they are physically realized
as extended systems that support wave propagation, such as waveguides. But such delay lines typically provide limited control over the propagating fields. Here, we introduce a parametrically addressed delay line (PADL) for microwave photons that provides a high level of control over the dynamics of stored pulses, enabling us to arbitrarily delay or even swap pulses. By parametrically driving a three-waving mixing superconducting circuit element that is weakly hybridized with an ensemble of resonators, we engineer a spectral response that simulates that of a physical delay line, while providing fast control over the delay line’s properties and granting access to its internal modes. We illustrate the main features of the PADL, operating on pulses with energies on the order of a single photon, through a series of experiments, which include choosing which photon echo to emit, translating pulses in time, and swapping two pulses. We also measure the noise added to the delay line from our parametric interactions and find that the added noise is much less than one photon.

Analysis of arbitrary superconducting quantum circuits accompanied by a Python package: SQcircuit

  1. Taha Rajabzadeh,
  2. Zhaoyou Wang,
  3. Nathan Lee,
  4. Takuma Makihara,
  5. Yudan Guo,
  6. and Amir H. Safavi-Naeini
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 SQcircuit. In this manuscript, we introduce the reader to the 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.