arXiv subjects

Irshad Ahmad

Publications and source records attributed to Irshad Ahmad.

7 recordsLinked to original sources

arXiv2026

Electrical post-fabrication tuning of aluminum Josephson junctions at room temperature

Josephson junctions are key elements of superconducting quantum technology, serving as the core building blocks of superconducting qubits. We present an experimental study on room-temperature electrical tuning of aluminum junctions, showing that voltage pulses can controllably increase their resistance and adjust the Josephson energy while maintaining qubit quality factors above 1 million. We find that the rate of resistance increase scales exponentially with pulse amplitude during manipulation. Following the manipulation, the resistance increases spontaneously through contributions proportional to both the initial resistance and the preceding manipulation. We show that this spontaneous increase halts at cryogenic temperatures, and resumes again at room temperature. Using our stepwise protocol, we achieve up to a 270% increase in junction resistance, corresponding to a reduction of nearly 2 GHz of the qubit transition frequency. These results establish the achievable range, relaxation behavior, and practical limits of electrical tuning, enabling post-fabrication mitigation of frequency crowding in quantum processors.

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arXiv2026

Learning Lindblad Dynamics of a Superconducting Quantum Processor

Accurate models of quantum processors are essential for understanding, calibrating, and improving their performance. In practice, model construction must balance physical detail against the experimental and computational effort required to reliably learn parameters. Compact descriptions therefore often rely on assumptions about which interactions, noise processes, or hidden degrees of freedom are relevant. Here we introduce LIMINAL, a data-driven framework for testing such assumptions and selecting minimal adequate Lindblad models. LIMINAL fits nested candidate models to time-resolved tomographic data and uses likelihood-ratio tests to decide when added physical mechanisms are warranted. We apply LIMINAL to a five-qubit superconducting processor, identifying an idling model with three-local Hamiltonian terms and two-local dissipation, while finding no support for three-local dissipation. We further apply it to recover driven single-qubit Hamiltonians, reconstruct a shaped-pulse Hamiltonian without assuming an analytic pulse model, and test hidden-qubit extensions in coupler-mediated dynamics, demonstrating the applicability of the framework for a wide range of tasks.

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arXiv2026

Demonstrating and Benchmarking Classical Shadows for Lindblad Tomography

Spurious couplings and decoherence degrade the performance of solid-state quantum processors, demanding careful design, calibration, and mitigation protocols. These strategies often rely on characterization of the idling processor, but tomographic recovery of (time-independent) Lindblad dynamics scales exponentially with qubit count. Here, we experimentally benchmark and demonstrate that randomized ("shadow") measurements accelerate Lindblad tomography on a superconducting transmon processor. We first implement extensible Lindblad tomography, which estimates Lindblad parameters using a complete tomographic dataset, and use it as a baseline to benchmark a shadow tomography approach, shadow Lindblad tomography. The shadow approach recycles randomized configurations to estimate the same Lindblad parameters using far fewer resources under physically motivated locality assumptions. We experimentally verify these assumptions in our processor by implementing the protocols on one- and three-qubit subsystems; here, shadow Lindblad tomography reproduces extensible Lindblad tomography within uncertainties while using exponentially fewer configurations. Leveraging this efficiency, we apply shadow Lindblad tomography to the full five-qubit processor and recover all single qubit dissipation and two-qubit coupling parameters in 9 hours of acquisition time compared to an estimated 58 hours for extensible Lindblad tomography. Additionally, our shadow implementation is compatible with conventional Gaussian error propagation, avoiding the use of median-of-means estimators. Together, these results demonstrate how randomized shadow tomography protocols can be practically implemented to learn quantum processor dynamics at an increasing qubit count.

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arXiv2026

Real-time adaptive tracking of fluctuating relaxation rates in superconducting qubits

The fidelity of operations on a solid-state quantum processor is fundamentally bounded by environmental decoherence. Characterizing environmental fluctuations is challenging because the acquisition time of nonadaptive experimental protocols limits temporal precision and can average out rapid features of the underlying dynamics. Here, we overcome this temporal-resolution limit by two orders of magnitude using a field-programmable gate-array (FPGA) powered classical controller that adaptively and continuously tracks the relaxation-time fluctuations of two fixed-frequency superconducting transmon qubits, which exhibit average relaxation times of approximately 0.17 ms and occasionally exceed 0.5 ms. We report events in which the relaxation time switches by nearly an order of magnitude over timescales of just tens of milliseconds, rather than minutes or hours as previously reported. Our real-time Bayesian estimation protocol estimates relaxation times within a few milliseconds, close to the decoherence timescale itself. Our statistical analysis further suggests that some of these fast fluctuations arise from two-level systems switching at rates up to 10 Hz, four orders of magnitude faster than earlier reports. These results redefine the timescales relevant for calibration in superconducting quantum processing units, establish a reference for rapid relaxation-rate characterization in device screening, and improve our understanding of fast relaxation dynamics.

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arXiv2025

Quantum Process Tomography with Digital Twins of Error Matrices

Accurate and robust quantum process tomography (QPT) is crucial for verifying quantum gates and diagnosing implementation faults in experiments aimed at building universal quantum computers. However, the reliability of QPT protocols is often compromised by faulty probes, particularly state preparation and measurement (SPAM) errors, which introduce fundamental inconsistencies in traditional QPT algorithms. We propose and investigate enhanced QPT for multi-qubit systems by integrating the error matrix in a digital twin of the identity process matrix, enabling statistical refinement of SPAM error learning and improving QPT precision. Through numerical simulations, we demonstrate that our approach enables highly accurate and faithful process characterization. We further validate our method experimentally using superconducting quantum gates, achieving at least an order-of-magnitude fidelity improvement over standard QPT. Our results provide a practical and precise method for assessing quantum gate fidelity and enhancing QPT on a given hardware.

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arXiv2025

Neural-network-based design and implementation of fast and robust quantum gates

We present a continuous-time, neural-network-based approach to optimal control in quantum systems, with a focus on pulse engineering for quantum gates. Leveraging the framework of neural ordinary differential equations, we construct control fields as outputs of trainable neural networks, thereby eliminating the need for discrete parametrization or predefined bases. This allows for generation of smooth, hardware-agnostic pulses that can be optimized directly using differentiable integrators. As a case study we design, and implement experimentally, a short and detuning-robust $π/2$ pulse for photon parity measurements in superconducting transmon circuits. This is achieved through simultaneous optimization for robustness and suppressing the leakage outside of the computational basis. These pulses maintain a fidelity greater than $99.9\%$ over a detuning range of $\approx \pm 20\mathrm{MHz}$, thereby outperforming traditional techniques while retaining comparable gate durations. This showcases its potential for high-performance quantum control in experimentally relevant settings.

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arXiv2024

STIRAP-Inspired Robust Gates for a Superconducting Dual-Rail Qubit

STImulated Raman Adiabatic Passage (STIRAP) is a powerful technique for robust state transfer capabilities in quantum systems. This method, however encounters challenges for its implementation as a gate in qubit-subspace due to its sensitivity to initial states. By incorporating single-photon detuning into the protocol, the sensitivity to the initial state can effectively be mitigated, enabling STIRAP to operate as a gate. In this study, we experimentally demonstrate the implementation of robust $π$ and $π$/2 rotations in a dual-rail qubit formed by two strongly coupled fixed-frequency transmon qubits. We achieve state preparation fidelity in excess of 0.98 using such rotations. Our analysis reveals these gates exhibit significant resilience to errors. Furthermore, our numerical calculations confirm that these gates can achieve fidelity levels in excess of 0.999. This work suggest a way for realizing quantum gates which are robust against minor drifts in pulse or system parameters.

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