Experimental Quantum Computing researcher with over a decade of experience working on design, fabrication, calibration, and benchmarking of superconducting quantum processors. Julian Kelly is the Director of Quantum Hardware at Google Quantum AI. He previously led the System Control Team which was responsible for building the hardware and software to operate and manipulate quantum computers. He began his career in quantum computing in 2008 where he joined John Martinis' physics research group at UCSB as an undergraduate and researched qubit control and benchmarking techniques. Julian stayed at UCSB and completed his PhD in 2015 in experimental quantum computing. His thesis focused on the development of highly controllable, coherent, and scalable "Xmon" transmon systems that demonstrated record fidelity entangling gate and measurement operations, culminating in a demonstration of experimental quantum error correction. Since joining Google, Julian worked to improve, scale, and integrate quantum processors and was the lead designer for the 72 qubit Bristlecone processor. Julian also developed the automated calibration framework "optimus" which is a software backbone of operating quantum processors at Google. The above technologies were critical in the team's "Quantum Supremacy" demonstration in 2019, and the first experimental demonstration of scalable quantum error correction in 2022.
Google Scholar.
Preview abstract
Lattice gauge theories (LGTs) can be used to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging, as it requires solving many-body problems that are generally beyond perturbative limits. Here we investigate the dynamics of local excitations in a LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit that prepares low-energy states that have a large overlap with the ground state; then we create charge excitations with local gates and simulate their quantum dynamics by means of a discretized time evolution. As the electric field coupling constant is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the electric field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT, from which we uncover two distinct regimes inside the confining phase: for weak confinement, the string fluctuates strongly in the transverse direction, whereas for strong confinement, transverse fluctuations are effectively frozen. We also demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a new set of techniques for investigating emergent excitations and string dynamics.View details
Preview abstract
Lattice gauge theories (LGTs) can be used to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging, as it requires solving many-body problems that are generally beyond perturbative limits. Here we investigate the dynamics of local excitations in a LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit that prepares low-energy states that have a large overlap with the ground state; then we create charge excitations with local gates and simulate their quantum dynamics by means of a discretized time evolution. As the electric field coupling constant is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the electric field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT, from which we uncover two distinct regimes inside the confining phase: for weak confinement, the string fluctuates strongly in the transverse direction, whereas for strong confinement, transverse fluctuations are effectively frozen. We also demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a new set of techniques for investigating emergent excitations and string dynamics.View details
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One of the roadblocks towards the implementation of a fault-tolerant superconducting quantum processor is impacts of ionizing radiation with the qubit substrate. Such impacts temporarily elevate the density of quasiparticles (QPs) across the device, leading to correlated qubit error bursts. The most damaging errors – T1 errors – stem from QP tunneling across the qubit Josephson junctions (JJs). Recently, we demonstrated that this type of error can be strongly suppressed by engineering the profile of superconducting gap at the JJs in a way that prevents QP tunneling. In this work, we identify a new type of correlated error that persists in the presence of gap engineering. We observe that impacts shift the frequencies of the affected qubits, and thus lead to correlated phase errors. The frequency shifts are systematically negative, reach values up to 3 MHz, and last for ~1 ms. We provide evidence that the shifts originate from the QP-qubit interactions in the JJ region. Further, we experimentally demonstrate these correlated phase errors are detrimental to the performance of quantum error correction protocols.View details
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Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain’s center, P(M). The first two moments of P(M) show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.View details
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Measurement is one of the essential components of quantum algorithms, and for superconducting qubits it is often the most error prone. Here, we demonstrate a model-based readout optimization achieving low measurement errors while avoiding detrimental side-effects. For simultaneous and mid-circuit measurements across 17 qubits we observe 1.5% error per qubit with a duration of 500 ns end-to-end and minimal excess reset error from residual resonator photons. We also suppress measurement-induced state transitions and achieve a qubit leakage rate limited by natural heating.This technique can scale to hundreds of qubits, and be used to enhance performance of error-correcting codes as well as near-term applicationsView details
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Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.View details
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A foundational assumption of quantum error correction theory is that quantum gates can be scaled to large processors without exceeding the error-threshold for fault tolerance. Two major challenges that could become fundamental roadblocks are manufacturing high-performance quantum hardware and engineering a control system that can reach its performance limits. The control challenge of scaling quantum gates from small to large processors without degrading performance often maps to non-convex, high-constraint, and time-dynamic control optimization over an exponentially expanding configuration space. Here we report on a control optimization strategy that can scalably overcome the complexity of such problems. We demonstrate it by choreographing the frequency trajectories of 68 frequency-tunable superconducting qubits to execute single- and two-qubit gates while mitigating computational errors. When combined with a comprehensive model of physical errors across our processor, the strategy suppresses physical error rates by ~3.7× compared with the case of no optimization. Furthermore, it is projected to achieve a similar performance advantage on a distance-23 surface code logical qubit with 1057 physical qubits. Our control optimization strategy solves a generic scaling challenge in a way that can be adapted to a variety of quantum operations, algorithms, and computing architectures.View details
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Quantum error correction (QEC) provides a practical path to fault-tolerant quantum computing through scaling, assuming that physical errors are rare and uncorrelated in time and space.
In superconducting qubit arrays, high-energy impact events produce correlated errors, violating this key assumption.
Following such an event, phonons with energy above the superconducting gap propagate throughout the device substrate, which in turn generate a temporary surge in quasiparticle (QP) populations across the array.
When these QPs tunnel across the qubits’ Josephson junctions, they induce correlated errors.
Engineering different superconducting gaps across the qubit's Josephson junctions (gap-engineering) provides a new method to resist QP tunneling.
By fabricating all-aluminum transmon qubits with both strong and weak gap-engineering on the same substrate, we observe a starkly different responses during single high-energy impact events.
Weakly-gap-engineered qubits show high rates of correlated $T_1$ errors, while the strongly-gap-engineered qubits do not show any degradation in $T_1$.
We also show strongly-gap-engineered qubits are robust to QP poisoning from increasing optical illumination intensity, whereas weakly-gap-engineered qubits display rapid degradation in coherence.
Based on these results, gap-engineering resolves high-energy impacts as a serious threat to QEC using superconducting qubit arrays. View details
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We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 $\Omega$ environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250-300 MHz, with input saturation powers up to $-95$~dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimate of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, and qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs.View details
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Practical quantum computing will require error rates that are well below what is achievable with
physical qubits. Quantum error correction [1, 2] offers a path to algorithmically-relevant error rates
by encoding logical qubits within many physical qubits, where increasing the number of physical
qubits enhances protection against physical errors. However, introducing more qubits also increases
the number of error sources, so the density of errors must be sufficiently low in order for logical
performance to improve with increasing code size. Here, we report the measurement of logical qubit
performance scaling across multiple code sizes, and demonstrate that our system of superconducting
qubits has sufficient performance to overcome the additional errors from increasing qubit number.
We find our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3
logical qubits on average, both in terms of logical error probability over 25 cycles and logical error
per cycle (2.914%±0.016% compared to 3.028%±0.023%). To investigate damaging, low-probability
error sources, we run a distance-25 repetition code and observe a 1.7 × 10−6 logical error per round
floor set by a single high-energy event (1.6 × 10−7 when excluding this event). We are able to
accurately model our experiment, and from this model we can extract error budgets that highlight
the biggest challenges for future systems. These results mark the first experimental demonstration
where quantum error correction begins to improve performance with increasing qubit number, and
illuminate the path to reaching the logical error rates required for computation.View details