arXiv subjects

Sai Li

Publications and source records attributed to Sai Li.

59 records · Page 4Linked to original sources

arXiv2020

Fast holonomic quantum computation on superconducting circuits with optimal control

Geometric phases induced in quantum evolutions have built-in noise-resilient characters, and thus can find applications in many robust quantum manipulation tasks. Here, we propose a feasible and fast scheme for universal quantum computation on superconducting circuits with nonadiabatic non-Abelian geometric phases, using resonant interaction of three-level quantum system. In our scheme, arbitrary single-qubit quantum gates can be implemented in a single-loop scenario by shaping both the amplitudes and phases of the two driving microwave fields resonantly coupled to a transmon device. Moreover, nontrivial two-qubit gates can also be realized with an auxiliary transmon simultaneously coupled to the two target transmons in an effective resonant way. In particular, our proposal can be compatible to various optimal control techniques, which further enhances the robustness of the quantum operations. Therefore, our proposal represents a promising way towards fault-tolerant quantum computation on solid-state quantum circuits.

quant-ph↗

arXiv2020

High-fidelity geometric gate for silicon-based spin qubits

High-fidelity manipulation is the key for the physical realization of fault-tolerant quantum computation. Here, we present a protocol to realize universal nonadiabatic geometric gates for silicon-based spin qubits. We find that the advantage of geometric gates over dynamical gates depends crucially on the evolution loop for the construction of the geometric phase. Under appropriate evolution loops, both the geometric single-qubit gates and the CNOT gate can outperform their dynamical counterparts for both systematic and detuning noises. We also perform randomized benchmarking using noise amplitudes consistent with experiments in silicon. For the static noise model, the averaged fidelities of geometric gates are around 99.90\% or above, while for the time-dependent $1/f$-type noise, the fidelities are around 99.98\% when only the detuning noise is present. We also show that the improvement in fidelities of the geometric gates over dynamical ones typically increases with the exponent $α$ of the $1/f$ noise, and the ratio can be as high as 4 when $α\approx 3$. Our results suggest that geometric gates with judiciously chosen evolution loops can be a powerful way to realize high-fidelity quantum gates.

quant-ph↗

arXiv2018

Low-Power (1T1N) Skyrmionic Synapses for Spiking Neuromorphic Systems

In this work, we propose a `1-transistor 1-nanotrack' (1T1N) synapse based on movement of magnetic skyrmions using spin polarised current pulses. The proposed synaptic bit-cell has 4 terminals and fully decoupled spike transmission- and programming- paths. With careful tuning of programming parameters we ensure multi-level non-volatile conductance evolution in the proposed skyrmionic synapse. Through micromagnetic simulations, we studied in detail the impact of programming conditions (current density, pulse width) on synaptic performance parameters such as number of conductance levels and energy per transition. The programming parameters chosen used all further analysis gave rise to a synapse with 7 distinct conductance states and 1.2 fJ per conductance state transition event. Exploiting bidirectional conductance modulation the 1T1N synapse is able to undergo long-term potentiation (LTP) & depression (LTD) according to a simplified variant of biological spike timing dependent plasticity (STDP) rule. We present subthreshold CMOS spike generator circuit which when coupled with well known subthreshold integrator circuit, produces custom pre and post-neuronal spike shapes, responsible for implementing unsupervised learning with the proposed 1T1N synaptic bit-cell and consuming ~ 0.25 pJ/event. A spiking neural network (SNN) incorporating the characteristics of the 1T1N synapse was simulated for two seperate applications: pattern extraction from noisy video streams and MNIST classification.

physics.app-ph↗

arXiv2018

Dynamics of a magnetic skyrmionium driven by spin waves

The magnetic skyrmionium is a skyrmion-like structure but carries a zero net skyrmion number, which can be used as a building block for non-volatile information processing devices. Here, we study the dynamics of a magnetic skyrmionium driven by propagating spin waves. It is found that the skyrmionium can be effectively driven into motion by spin waves showing tiny skyrmion Hall effect, of which the mobility is much better than that of the skyrmion at the same condition. We also show that the skyrmionium mobility depends on the nanotrack width and damping coefficient, and can be controlled by an external out-of-plane magnetic field. Besides, we demonstrate the skyrmionium motion driven by spin waves is inertial. Our results indicate that the skyrmionium is a promising building block for building spin-wave spintronic devices.

cond-mat.mes-hall↗

arXiv2017

Mendelian Randomization when Many Instruments are Invalid: Hierarchical Empirical Bayes Estimation

Estimating the causal effect of an exposure on an outcome is an important task in many economical and biological studies. Mendelian randomization, in particular, uses genetic variants as instruments to estimate causal effects in epidemiological studies. However, conventional instrumental variable methods rely on some untestable assumptions, which may be violated in real problems. In this paper, we adopt a Bayesian framework and build hierarchical models to incorporate invalid effects of instruments. We introduce an empirical Bayes estimator for which some of the instruments are invalid by utilizing a Gaussian mixture prior. Theoretical performance and algorithm implementations are provided and illustrated. The reliable performance of the proposed method is demonstrated in various simulation settings and on real datasets concerning the causal effects of HDL cholesterol and LDL cholesterol on type 2 diabetes.

stat.ME↗