arXiv subjects

Aleksandr Dorogov

Publications and source records attributed to Aleksandr Dorogov.

3 recordsLinked to original sources

arXiv2026

Flux-Activated Resonant Control of a Bosonic Quantum Memory

Universal control of bosonic degrees of freedom provides a hardware-efficient route for quantum information processing with high-dimensional systems. Bosonic circuit quantum electrodynamics (cQED), which leverages auxillary transmons to coherently control long-lived superconducting cavities, is well suited to this goal. However, such systems are traditionally operated in the dispersive regime, where the nearly degenerate cavity transitions prohibit the direct addressability of individual excitation levels of the bosonic mode and increase gate complexity. Here, we achieve direct oscillator control by dynamically accessing the resonant Jaynes-Cummings (JC) interactions, implemented with a hardware that integrates on-chip broadband magnetic flux delivery with a bosonic memory housed in a 3D superconducting cavity with lifetime exceeding 0.5 ms. We demonstrate deterministic preparation of Fock states and their superpositions within 100s of nanoseconds by directly climbing the JC ladder, and realise efficient arbitrary rotations between any pair of Fock states. Our resonant control scheme provides an analytical method for manipulating the entire Hilbert space of the bosonic mode at rates fundamentally more favourable than traditional dispersive strategies. This on-demand access to JC interactions opens a promising path toward realising robust Fock-basis qudits and harnessing the rich dynamics of high-dimensional bosonic systems for quantum information processing.

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arXiv2024

Hybrid quantum learning with data re-uploading on a small-scale superconducting quantum simulator

Supervised quantum learning is an emergent multidisciplinary domain bridging between variational quantum algorithms and classical machine learning. Here, we study experimentally a hybrid classifier model accelerated by a quantum simulator - a linear array of four superconducting transmon artificial atoms - trained to solve multilabel classification and image recognition problems. We train a quantum circuit on simple binary and multi-label tasks, achieving classification accuracy around 95%, and a hybrid model with data re-uploading with accuracy around 90% when recognizing handwritten decimal digits. Finally, we analyze the inference time in experimental conditions and compare the performance of the studied quantum model with known classical solutions.

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arXiv2023

On-demand transposition across light-matter interaction regimes in bosonic cQED

The diverse applications of light-matter interactions in science and technology stem from the qualitatively distinct ways these interactions manifest, prompting the development of physical platforms that can interchange between regimes on demand. Bosonic cQED employs the light field of high-Q superconducting cavities coupled to non-linear circuit elements, harnessing the rich dynamics of their interaction for quantum information processing. However, implementing fast switching of the interaction regime without deteriorating the cavity coherence is a significant challenge. We present the first experiment to achieve this feat, combining nanosecond-scale frequency tunability of a transmon coupled to a cavity with lifetime of hundreds of microseconds. Our implementation affords a range of new capabilities for quantum information processing; from fast creation of cavity Fock states using resonant interaction and interchanging tomography techniques at qualitatively distinct interaction regimes on the fly, to the suppression of unwanted cavity-transmon dynamics during idle evolution. By bringing flux tunability into the bosonic cQED toolkit, our work opens up a new paradigm to probe the full range of light-matter interaction dynamics within a single platform and provides valuable new pathways towards robust and versatile quantum information processing.

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