Dynamical second-order noise sweetspots in resonantly driven spin qubits

Quantum dot-based quantum computation employs extensively the exchange interaction between nearby electronic spins in order to manipulate and couple different qubits. The exchange interaction, however, couples the qubit states to charge noise, which reduces the fidelity of the quantum gates that employ it. The effect of charge noise can be mitigated by working at noise sweetspots in which the sensitivity to charge variations is reduced. In this work we study the response to charge noise of a double quantum dot based qubit in the presence of ac gates, with arbitrary driving amplitudes, applied either to the dot levels or to the tunneling barrier. Tuning with an ac driving allows to manipulate the sign and strength of the exchange interaction as well as its coupling to environmental electric noise. Moreover, we show the possibility of inducing a second-order sweetspot in the resonant spin-triplet qubit in which the dephasing time is significantly increased.

Fast spin-valley-based quantum gates in Si with micromagnets

An electron spin qubit in silicon quantum dots holds promise for quantum information processing due to the scalability and long coherence. An essential ingredient to recent progress is the employment of micromagnets. They generate a synthetic spin–orbit coupling (SOC), which allows high-fidelity spin manipulation and strong interaction between an electron spin and cavity photons. To scaled-up quantum computing, multiple technical challenges remain to be overcome, including controlling the valley degree of freedom, which is usually considered detrimental to a spin qubit. Here, we show that it is possible to significantly enhance the electrical manipulation of a spin qubit through the effect of constructive interference and the large spin-valley mixing. To characterize the quality of spin control, we also studied spin dephasing due to charge noise through spin-valley mixing. The competition between the increased control strength and spin dephasing produces two sweet-spots, where the quality factor of the spin qubit can be high. Finally, we reveal that the synthetic SOC leads to distinctive spin relaxation in silicon, which explains recent experiments.

Efficient modeling of superconducting quantum circuits with tensor networks

We use a tensor network method to compute the low-energy excitations of a large-scale fluxonium qubit up to a desired accuracy. We employ this numerical technique to estimate the pure-dephasing coherence time of the fluxonium qubit due to charge noise and coherent quantum phase slips from first principles, finding an agreement with previously obtained experimental results. By developing an accurate single-mode theory that captures the details of the fluxonium device, we benchmark the results obtained with the tensor network for circuits spanning a Hilbert space as large as 15180. Our algorithm is directly applicable to the wide variety of circuit-QED systems and may be a useful tool for scaling up superconducting quantum technologies.