8 research outputs found
Cryogenic silicon surface ion trap
Trapped ions are pre-eminent candidates for building quantum information
processors and quantum simulators. They have been used to demonstrate quantum
gates and algorithms, quantum error correction, and basic quantum simulations.
However, to realise the full potential of such systems and make scalable
trapped-ion quantum computing a reality, there exist a number of practical
problems which must be solved. These include tackling the observed high
ion-heating rates and creating scalable trap structures which can be simply and
reliably produced. Here, we report on cryogenically operated silicon ion traps
which can be rapidly and easily fabricated using standard semiconductor
technologies. Single Ca ions have been trapped and used to
characterize the trap operation. Long ion lifetimes were observed with the
traps exhibiting heating rates as low as 0.33 phonons/s at an
ion-electrode distance of 230 m. These results open many new avenues to
arrays of micro-fabricated ion traps.Comment: 12 pages, 4 figures, 1 tabl
Individual addressing of ion qubits with counter-propagating optical frequency combs
We propose a new method of individual single-qubit addressing of linear
trapped-ion chains utilizing two ultrastable femtosecond frequency combs. For
that, we suggest implementing the single-qubit gates with two
counter-propagating frequency combs overlapping on the target ion and causing
the AC Stark shift between the qubit levels. With analytical calculations and
numerical modeling, we show that the arbitrary single-qubit rotations can be
indeed realized using only laser fields propagating along the ion chain. We
analyze the error sources for the proposed addressing method and prove that it
allows implementing the single-qubit gates with high fidelity
Mitigating Quantum Gate Errors for Variational Eigensolvers Using Hardware-Inspired Zero-Noise Extrapolation
Variational quantum algorithms have emerged as a cornerstone of contemporary
quantum algorithms research. Practical implementations of these algorithms,
despite offering certain levels of robustness against systematic errors, show a
decline in performance due to the presence of stochastic errors and limited
coherence time. In this work, we develop a recipe for mitigating quantum gate
errors for variational algorithms using zero-noise extrapolation. We introduce
an experimentally amenable method to control error strength in the circuit. We
utilise the fact that gate errors in a physical quantum device are distributed
inhomogeneously over different qubits and pairs thereof. As a result, one can
achieve different circuit error sums based on the manner in which abstract
qubits in the circuit are mapped to a physical device. We find that the
estimated energy in the variational approach is approximately linear with
respect to the circuit error sum (CES). Consequently, a linear fit through the
energy-CES data, when extrapolated to zero CES, can approximate the energy
estimated by a noiseless variational algorithm. We demonstrate this numerically
and further prove that the approximation is exact if the two-qubit gates in the
circuits are arranged in the form of a regular graph.Comment: 9 pages, 2 figure
A compact ion-trap quantum computing demonstrator
Quantum information processing is steadily progressing from a purely academic
discipline towards applications throughout science and industry. Transitioning
from lab-based, proof-of-concept experiments to robust, integrated realizations
of quantum information processing hardware is an important step in this
process. However, the nature of traditional laboratory setups does not offer
itself readily to scaling up system sizes or allow for applications outside of
laboratory-grade environments. This transition requires overcoming challenges
in engineering and integration without sacrificing the state-of-the-art
performance of laboratory implementations. Here, we present a 19-inch rack
quantum computing demonstrator based on optical qubits in
a linear Paul trap to address many of these challenges. We outline the
mechanical, optical, and electrical subsystems. Further, we describe the
automation and remote access components of the quantum computing stack. We
conclude by describing characterization measurements relevant to digital
quantum computing including entangling operations mediated by the
Molmer-Sorenson interaction. Using this setup we produce maximally-entangled
Greenberger-Horne-Zeilinger states with up to 24 ions without the use of
post-selection or error mitigation techniques; on par with well-established
conventional laboratory setups