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At least 55 records · Page 3

Measuring quasiparticle dynamics for particle impact reconstruction in a superconducting qubit chip

Quasiparticle poisoning following particle impacts poses a significant challenge to the development of fault-tolerant superconducting quantum computers, as a sudden excess of quasiparticles can simultaneously degrade the coherence of multiple qubits across large device arrays. In this work, we present a statistical analysis that models the time evolution of radiation-induced qubit energy relaxation through quasiparticle density dynamics. This study provides insight into quasiparticle loss processes by distinguishing between recombination and trapping decay channels and assessing their respective impact on qubit performance. We precisely measure quasiparticle recombination in multiple transmon qubits and uncover an unexpected dependence of qubit relaxation dynamics on deposited energy. By linking correlated relaxation events across qubits to ballistic phonon propagation, we introduce a statistical localization approach to extract the energy deposited in the substrate, which is in good agreement with Monte Carlo simulation. This work establishes the quantitative framework for using an arbitrary subset of superconducting transmon qubits in a QPU as energy-resolving witness particle detectors.

Celi, E. [Northwestern U.]↗

Visualizing heterogeneous dipole fields by terahertz light coupling in individual nano-junctions

The challenge underlying superconducting quantum computing is to remove materials bottleneck for highly coherent quantum devices. The nonuniformity and complex structural components in the underlying quantum circuits often lead to local electric field concentration, charge scattering, dissipation and ultimately decoherence. Here we visualize interface dipole heterogeneous distribution of individual Al/AlO$_{x}$/Al junctions employed in transmon qubits by broadband terahertz scanning near-field microscopy that enables the non-destructive and contactless identification of defective boundaries in nano-junctions at an extremely precise nanoscale level. Our THz nano-imaging tool reveals an asymmetry across the junction in electromagnetic wave-junction coupling response that manifests as hot (high intensity) vs cold (low intensity) spots in the spatial electrical field structures and correlates with defected boundaries from the multi-angle deposition processes in Josephson junction fabrication inside qubit devices. The demonstrated local electromagnetic scattering method offers high sensitivity, allowing for reliable device defect detection in the pursuit of improved quantum circuit fabrication for ultimately optimizing coherence times.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend on the results of measurements in the previous layer. The network is trained via simulation, but inference is performed experimentally on quantum hardware. The classical-to-quantum correspondence is controlled by an interpolation parameter, $a$, which is zero in the classical limit. Increasing $a$ introduces quantum uncertainty into the measurements, which is shown to improve network performance at moderate values of the interpolation parameter. We then focus on particular images that fail to be classified by a classical neural network but are detected correctly in the quantum network. For such borderline cases, we observe strong deviations from the simulated behavior. We attribute this to physical noise, which causes the output to fluctuate between nearby minima of the classification energy landscape. Such strong sensitivity to physical noise is absent for clear images. We further benchmark physical noise by inserting additional single-qubit and two-qubit gate pairs into the neural network circuits. Our work provides a springboard toward more complex quantum neural networks on current devices: while the approach is rooted in standard classical machine learning, scaling up such networks may prove classically non-simulable and could offer a route to near-term quantum advantage.

FOS: Physical sciences↗

Quantifying trapped magnetic vortex losses in niobium resonators at mK temperatures

Trapped magnetic vortices in niobium introduce microwave losses that degrade the performance of superconducting resonators. While such losses have been extensively studied above 1 K, we report here their direct quantification in the millikelvin and low-photon regime relevant to quantum devices. Using a high-quality factor 3D niobium cavity cooled through its superconducting transition in controlled magnetic fields, we isolate vortex-induced losses and find the resistive component of the sensitivity to trapped flux S to be approximately 2 n Ω/mG at 10 mK and 6 GHz. The decay rate is initially dominated by two-level system (TLS) losses from the native niobium pentoxide, with vortex-induced degradation of T 1 occurring above B trap ∼ 50 mG. In the absence of the oxide, even 10 mG of trapped flux limits performance, Q 0 ∼ 10 10 , or T 1 ∼ 350 ms, underscoring the need for stringent magnetic shielding. The resistive sensitivity, S, decreases with temperature and remains largely field-independent, whereas the reactive component, S′, exhibits a maximum near 0.8 K. These behaviors are well modeled within the Coffey–Clem framework in the zero-creep limit, under the assumption that vortex pinning is enhanced by thermally activated processes. Our results suggest that niobium-based transmon qubits can tolerate vortex-induced dissipation at trapped field levels up to several hundred mG, but achieving long coherence times still requires careful magnetic shielding to suppress lower-field losses from other mechanisms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Suppression of ferromagnetic correlations in hole-doped SrCo 2 As 2

We report the growth of high-quality single crystals of hole-doped composition Sr 0.95 K 0.05 Co 2 As 2 and present an investigation of its structural, electronic, thermal, and magnetic properties. Our results show that hole doping leads to a substantial suppression of ferromagnetic (FM) correlations present in SrCo 2 As 2 leading to nearly isotropic magnetic susceptibilities χ ab,c (T) of Sr 0.95 K 0.05 Co 2 As 2 . The presence of FM fluctuations is considered one of the detrimental reasons why SrCo 2 As 2 does not achieve a superconducting ground state despite having a precursor for it in the form of stripe-like antiferromagnetic fluctuations. The suppression of FM fluctuations leads to qualitative similarities between the properties of hole-doped SrCo 2 As 2 and the end member of superconducting 122 iron-arsenide family KFe 2 As 2 . Our results also infer the presence of strongly correlated electronic states in Sr 0.95 K 0.05 Co 2 As 2 . Further, they show that the electronic structure of SrCo 2 As 2 as well as this hole-doped composition is exceptionally unstable in the vicinity of Fermi level EF for small alterations in the structural parameters and sensitively depends upon the details of simulation.

36 MATERIALS SCIENCE↗

Systematic Construction of Time-Dependent Hamiltonians for Microwave-Driven Josephson Circuits

Time-dependent electromagnetic drives are fundamental for controlling complex quantum systems, including superconducting Josephson circuits. In these devices, accurate time-dependent Hamiltonian models are imperative for predicting their dynamics and designing high-fidelity quantum operations. Existing numerical methods, such as black-box quantization (BBQ) and energy-participation ratio (EPR), excel at modeling the static Hamiltonians of Josephson circuits. However, these techniques do not fully capture the behavior of driven circuits stimulated by external microwave drives, nor do they include a generalized approach to account for the inevitable noise and dissipation that enter through microwave ports. Here, we introduce numerical techniques that leverage classical microwave simulations, efficiently executable in finite-element solvers, to obtain the time-dependent Hamiltonian of microwave-driven superconducting circuits with arbitrary geometries under charge, flux, or mixed electromagnetic modulation. Importantly, our techniques do not rely on a lumped-element description of the superconducting circuit, in contrast to previous approaches to tackling this problem. We demonstrate the versatility of our approach by characterizing the driven properties of realistic circuit devices in complex electromagnetic environments, including coherent dynamics due to charge and flux modulation, as well as drive-induced relaxation and dephasing. Our techniques offer a powerful toolbox for optimizing circuit designs and advancing practical applications in superconducting quantum computing.

Lu, Yao [Yale U.; Yale U. (main); Fermilab] (ORCID↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗

Single Photon Detection with On-Chip Number Resolving Capability

Single photon detection (SPD) plays an important role in many forefront areas of fundamental science and advanced engineering applications. In recent years, rapid developments in superconducting quantum computation, quantum key distribution, and quantum sensing call for SPD in the microwave frequency range. We have explored in this LDRD project a new approach to SPD in an effort to provide deterministic photon-number-resolving capability by using topological Josephson junction structures. In this SAND report, we will present results from our experimental studies of microwave response and theoretical simulations of microwave photon number resolving detector in topological Dirac semimetal Cd 3 As 2 . These results are promising for SPD at the microwave frequencies using topological quantum materials.

47 OTHER INSTRUMENTATION↗

Improving Signal-to-Noise Ratio (SNR) for Quantum Readout Signals Using Adaptive Hardware Filters on FPGA

This research presents an innovative approach to improving the Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals, utilizing FPGA-based adaptive filtering on the control board. Our solution aims to bolster quantum computations' reliability by providing a more accurate and precise way to obtain our readout traces and achieve a higher discernability between excitation states in real-time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deriving Effective Coupling Strength With Born-Oppenheimer Approx.

Tunable couplers have been important in the development of superconducting quantum computers. The ability to maintain zero coupling between qubits during operation, a feature of high-fidelity quantum gates, has been shown to be possible with the use of tunable couplers. As an example, Sete et al., 2021 showed this was possible with a tunable coupler between transmons: the qubit-coupler and qubit-qubit couplings create a net effective coupling strength between the qubits that can be tuned to zero. However, the derivation of the effective coupling strength between the qubits is quite complex. We propose a simpler method of obtaining this effective coupling with the Born-Oppenheimer approximation.

Wichmann, Conrad↗

Low-latency quantum control using AI algorithms on cryogenic microelectronics platforms

Superconducting quantum computers are a particular technology that involve the realization of qubits by means of LC circuits with a Josephson junction. As shown in Fig. 1, this latter addition has the effect of introducing a nonlinearity (anharmonicity) that makes the frequency spacing between each energy level non-uniform. This is a desired effect for separating the two lowest levels, used for computation, from the higher ones, that are theoretically infinite and which are not desired to be used.

97 MATHEMATICS AND COMPUTING↗

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

Two-Level System Spectroscopy from Correlated Multilevel Relaxation in Superconducting Qubits

Transmon qubits are a cornerstone of modern superconducting quantum computing platforms. Temporal fluctuations of energy relaxation in these qubits are widely attributed to microscopic two-level systems (TLSs) in device dielectrics and interfaces, yet isolating individual defects typically relies on tuning the qubit or the TLS into resonance. We demonstrate a novel spectroscopy method for fixed-frequency transmons based on multilevel relaxation: repeated preparation of the second excited state and simultaneous $T_1$ extraction of the first and second excited states reveals characteristic correlations in the decay rates of adjacent transitions. From these correlations we identify one or more dominant TLSs and reconstruct their frequency drift over time. Remarkably, we find that TLSs detuned by $\gtrsim 100\,\mathrm{MHz}$ from the qubit transition can still significantly influence relaxation. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

Superconducting Radio Frequency Resonators for Quantum Computing: A Short Review

Superconducting radiofrequency (SRF) technology is being used not only in discovery science programs and basic research but also for several applications that benefit society more directly. The advantage of superconducting resonators over those made of normal-conducting metal is their ability to store electromagnetic energy with much lower dissipation. The high-quality factor and longer dissipation time provided by these superconducting resonators can deliver superior performance. Currently, the quantum processing architecture uses resonators and interconnecting circuits operating in the microwave regime with superconducting strip-line technology and low noise electronic devices for switching and communication. The performance of these devices can be enhanced by embedding them in 3D SRF cavity resonators to prolong the coherence time, which improves the utility of the device by reducing error rates and allowing more manipulations (calculations) before the quantum state decays. Here, we present a short review of current microwave technology used in quantum computers and progress towards the 3D resonators to enhance thecoherence time.

Dhakal, Pashupati↗

Building Qudit-Based Quantum Computing Processors using Superconducting RF Cavities

Superconducting radio frequency (SRF) cavities provide an excellent platform for storing quantum information as quantum d-level systems (qudits) due to their exceptionally long lifetimes and large accessible Hilbert spaces. A common strategy to manipulate the states is to use a nonlinear element like a transmon. There are, however, several challenges to building a 3D SRF architecture while maintaining a long cavity lifetime. We demonstrate our successful integration of transmons with single-cell Nb SRF cavities and the ability to prepare several non-classical states. Finally, we discuss our strategies to improve the coherence times, gate schemes, and extend the system for building a multi-qudit quantum processor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗