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Anton Frisk Kockum

Publications and source records attributed to Anton Frisk Kockum.

At least 37 records · Page 2Linked to original sources

Doublon bound states in the continuum through giant atoms

Bound states in the continuum (BICs) are spatially localized modes embedded in the spectrum of extended states, typically stabilized by symmetry or interference. While extensively studied in single-particle and linear systems, the many-body regime of BICs remains largely unexplored. Here, we demonstrate that giant atoms, quantum emitters coupled nonlocally to structured waveguides, can host robust doublon BICs, i.e., two-photon bound states stabilized by destructive interference and interactions. We first analyze a driven two-photon emission process and show how doublon BICs arise and mediate decoherence-free interaction between distant atoms. We then demonstrate that these many-body BICs also emerge under natural, undriven dynamics via a virtual two-photon emission process in three-level giant atoms. Our results reveal an interference-based mechanism for stabilizing many-body localization in open quantum systems, with potential applications in quantum simulation, non-ergodic dynamics, and protected quantum information processing.

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Generating spatially separated correlated multiphoton states in nonlinear waveguide quantum electrodynamics

Strongly correlated multi-photon states are indispensable resources for advanced quantum technologies, yet their deterministic generation remains challenging due to the inherent weak nonlinearity in most optical systems. Here, we propose a scalable architecture for producing correlated few-photon entangled states via cascaded inelastic scattering in a nonlinear waveguide. When a single photon scatters off a far detuned excited two-level emitter, it coherently converts into a propagating doublon, a bound photon pair with anomalous dispersion. This doublon can subsequently scatter off a downstream excited emitter to further convert into a triplon, and so on, thereby establishing a photon-number amplification cascade $|\cdot \rangle \!\! \rightarrow \!\! |\!\!: \rangle \!\! \rightarrow \! \! |\!\!\therefore \rangle \!\! \to \!\! ...$ Central to this process is the concept of a pseudo-giant atom, which we introduce here to capture the non-local scattering potential emergent from the wave functions of bound states. By implementing this scheme using a real giant atom with multiple engineered coupling points, we achieve unidirectional and full controllable photon conversion without backscattering. The resulting output state forms a programmable superposition of spatially and temporally isolated photon-number components, automatically sorted by their distinct group velocities. This work opens a new paradigm in quantum state engineering, enabling on-demand generation of complex multi-photon resources for quantum simulation, metrology, and scalable quantum networks.

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Tunable frequency conversion and comb generation with a superconducting artificial atom

We investigate the power spectral density emitted by a superconducting artificial atom coupled to the end of a semi-infinite transmission line and driven by two continuous radio-frequency fields. In this setup, we observe the generation of multiple frequency peaks and the formation of frequency combs with equal detuning between those peaks. The frequency peaks originate from wave mixing of the drive fields, mediated by the artificial atom, highlighting the potential of this system as both a frequency converter and a frequency-comb generator. We demonstrate precise control and tunability in generating these frequency features, aligning well with theoretical predictions, across a relatively wide frequency range (tens of MHz, exceeding the linewidth of the artificial atom). The extensive and simple tunability of this frequency converter and comb generator, combined with its small physical footprint, makes it promising for quantum optics on chips and other applications in quantum technology.

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Overhead in Quantum Circuits with Time-Multiplexed Qubit Control

When scaling up quantum processors in a cryogenic environment, it is desirable to limit the number of qubit drive lines going into the cryostat, since fewer lines makes cooling of the system more manageable and the need for complicated electronics setups is reduced. However, although time multiplexing of qubit control enables using just a few drive lines to steer many qubits, it comes with a trade-off: fewer drive lines means fewer qubits can be controlled in parallel, which leads to an overhead in the execution time for quantum algorithms. In this article, we quantify this trade-off through numerical and analytical investigations. For standard quantum processor layouts and typical gate times, we show that the trade-off is favorable for many common quantum algorithms $\unicode{x2014}$ the number of drive lines can be significantly reduced without introducing much overhead. Specifically, we show that couplers for two-qubit gates can be grouped on common drive lines without any overhead up to a limit set by the connectivity of the qubits. For single-qubit gates, we find that the serialization overhead generally scales only logarithmically in the number of qubits sharing a drive line. These results are promising for the continued progress towards large-scale quantum computers.

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Lattice surgery with Bell measurements: Modular fault-tolerant quantum computation at low entanglement cost

Modular architectures are a promising approach to scaling quantum computers to fault tolerance. Small, low-noise quantum processors connected through relatively noisy quantum links are capable of fault-tolerant operation as long as the noise can be confined to the interface. Finding protocols that implement the quantum links between modules as efficiently as possible is essential because inter-module entanglement is challenging to produce at a similar rate and fidelity as local entanglement. We introduce a protocol for lattice surgery on surface codes in which all non-local operations are Bell measurements. The protocol simultaneously confines the link noise and requires only half as many module-crossing gates as previously proposed protocols. To mitigate distance-reducing hook errors, we introduce a strategy of alternating the gate sequence between rounds of syndrome measurement, which prevents multiple hooks from simultaneously aligning with a logical operator in the code. We evaluate our protocol's performance when two logical qubits on separate modules are prepared in a logical Bell state. Circuit-level simulations under depolarizing noise show that the logical error suppression for a given entanglement rate between modules is consistently stronger compared to the best-performing alternative protocols for a wide range of link noise, with a typical 40% entanglement resource saving for a constant logical error rate. Our approach to protocol design is applicable to any quantum circuit that must be divided across processor modules and can therefore guide development of resource-efficient modular quantum computation beyond the surface code.

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Intrinsic Multi-Mode Interference for Passive Suppression of Purcell Decay in Superconducting Circuits

Decoherence due to radiative decay remains an important consideration in scaling superconducting quantum processors. We introduce a passive, interference-based methodology for suppressing radiative decay using only the intrinsic multi-mode structured environment of superconducting circuits. By taking into account the full electromagnetic mode-mode couplings within the device, we derive analytic conditions that enable destructive interference. These conditions are realized by introducing controlled geometric asymmetries -- such as localized perturbations to the transmon capacitor -- which increase mode hybridization and activate interference between multiple decay pathways. We validate this methodology using perturbation theory, full-wave electromagnetic simulations, and experimental measurements of a symmetry-broken transmon qubit with improved coherence times.

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Selective and efficient quantum state tomography for multi-qubit systems

Quantum state tomography (QST) is a crucial tool for characterizing quantum states. However, QST becomes impractical for reconstructing multi-qubit density matrices since data sets and computational costs grow exponentially with qubit number. In this Letter, we introduce selective and efficient QST (SEEQST), an approach for efficiently estimating multiple selected elements of an arbitrary $N$-qubit density matrix. We show that any $N$-qubit density matrix can be partitioned into $2^N$ subsets, each containing $2^N$ elements. With SEEQST, any such subset can be accurately estimated from just two experiments with only single-qubit measurements. The complexity for estimating any subset remains constant regardless of Hilbert-space dimension, so SEEQST can find the full density matrix using $2^{N+1} - 1$ experiments, where standard methods would use $3^N$ experiments. We provide a circuit decomposition for the SEEQST experiments, demonstrating that their maximum circuit depth scales logarithmically with $N$ assuming all-to-all connectivity. The Python code for SEEQST is publicly available at \href{https://github.com/aniket-ae/SEEQST}{github.com/aniket-ae/SEEQST}.

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Deterministic generation of frequency-bin-encoded microwave photons

A distributed quantum computing network requires a quantum communication channel between spatially separated processing units. In superconducting circuits, such a channel can be implemented based on propagating microwave photons to encode and transfer quantum information between an emitter and a receiver. However, traveling microwave photons can be lost during the transmission, leading to the failure of information transfer. Heralding protocols can be used to detect such photon losses. In this work, we propose such a protocol and experimentally demonstrate a frequency-bin encoding method of microwave photonic modes using superconducting circuits. We deterministically encode the quantum information from a superconducting qubit by simultaneously emitting its information into two photonic modes at different frequencies, with a process fidelity of 90.4%. The frequency-bin-encoded photonic modes can be used, at the receiver processor, to detect the occurrence of photon loss. Our work thus provides a reliable method to implement high-fidelity quantum state transfer in a distributed quantum computing network, incorporating error detection to enhance performance and accuracy.

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Generative flow-based warm start of the variational quantum eigensolver

Hybrid quantum-classical algorithms like the variational quantum eigensolver (VQE) show promise for quantum simulations on near-term quantum devices, but are often limited by complex objective functions and expensive optimization procedures. Here, we propose Flow-VQE, a generative framework leveraging conditional normalizing flows with parameterized quantum circuits to efficiently generate high-quality variational parameters. By embedding a generative model into the VQE optimization loop through preference-based training, Flow-VQE enables quantum gradient-free optimization and offers a systematic approach for parameter transfer, accelerating convergence across related problems through warm-started optimization. We compare Flow-VQE to a number of standard benchmarks through numerical simulations on molecular systems, including hydrogen chains, water, ammonia, and benzene. We find that Flow-VQE outperforms baseline optimization algorithms, achieving computational accuracy with fewer circuit evaluations (improvements range from modest to more than two orders of magnitude) and, when used to warm-start the optimization of new systems, accelerates subsequent fine-tuning by up to 50-fold compared with Hartree--Fock initialization. Therefore, we believe Flow-VQE can become a pragmatic and versatile paradigm for leveraging generative modeling to reduce the costs of variational quantum algorithms.

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Quantum computing and artificial intelligence: status and perspectives

This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could support the development of innovative AI solutions. It also examines use cases of classical AI that can empower research and development in quantum technologies, with a focus on quantum computing and quantum sensing. The purpose of this white paper is to provide a long-term research agenda aimed at addressing foundational questions about how AI and quantum computing interact and benefit one another. It concludes with a set of recommendations and challenges, including how to orchestrate the proposed theoretical work, align quantum AI developments with quantum hardware roadmaps, estimate both classical and quantum resources - especially with the goal of mitigating and optimizing energy consumption - advance this emerging hybrid software engineering discipline, and enhance European industrial competitiveness while considering societal implications.

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Sequential decoding of the XYZ$^2$ hexagonal stabilizer code

Quantum error correction requires accurate and efficient decoding to optimally suppress errors in the encoded information. For concatenated codes, where one code is embedded within another, optimal decoding can be achieved using a message-passing algorithm that sends conditional error probabilities from the lower-level code to a higher-level decoder. In this work, we study the XYZ$^2$ topological stabilizer code, defined on a honeycomb lattice, and use the fact that it can be viewed as a concatenation of a [[2, 1, 1]] phase-flip parity check code and the surface code with $YZZY$ stabilizers, to decode the syndrome information in two steps. We use this sequential decoding scheme to correct errors on data qubits, as well as measurement errors, under various biased error models using both a maximum-likelihood decoder (MLD) and more efficient matching-based decoders. For depolarizing noise we find that the sequential matching decoder gives a threshold of 18.3%, close to optimal, as a consequence of a favorable, effectively biased, error model on the upper-level YZZY code. For phase-biased noise on data qubits, at a bias $η= \frac{p_z}{p_x+p_y} = 10$, we find that a belief-matching-based decoder reaches thresholds of 24.1%, compared to 28.6% for the MLD. With measurement errors the thresholds are reduced to 3.4% and 4.3%, for depolarizing and biased noise respectively, using the belief-matching decoder. This demonstrates that the XYZ$^2$ code has thresholds that are competitive with other codes tailored to biased noise. The results also showcase two approaches to taking advantage of concatenated codes: 1) tailoring the upper-level code to the effective noise profile of the decoded lower-level code, and 2) making use of an upper-level decoder that can utilize the local information from the lower-level code.

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Entanglement of photonic modes from a continuously driven two-level system

The ability to generate entangled states of light is a key primitive for quantum communication and distributed quantum computation. Continuously driven sources, including those based on spontaneous parametric downconversion, are usually probabilistic, whereas deterministic sources require accurate timing of the control fields. Here, we experimentally generate entangled photonic modes by continuously exciting a quantum emitter, a superconducting qubit, with a coherent drive, taking advantage of mode matching in the time and frequency domain. Using joint quantum state tomography and logarithmic negativity, we show that entanglement is generated between modes extracted from the two sidebands of the resonance fluorescence spectrum. Because the entangled photonic modes are perfectly orthogonal, they can be transferred into distinct quantum memories. Our approach can be utilized to distribute entanglement at a high rate in various physical platforms, with applications in waveguide quantum electrodynamics, distributed quantum computing, and quantum networks.

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Lecture notes on quantum computing

These are the lecture notes of the master's course "Quantum Computing", taught at Chalmers University of Technology every fall since 2020, with participation of students from RWTH Aachen and Delft University of Technology. The aim of this course is to provide a theoretical overview of quantum computing, excluding specific hardware implementations. Topics covered in these notes include quantum algorithms (such as Grover's algorithm, the quantum Fourier transform, phase estimation, and Shor's algorithm), variational quantum algorithms that utilise an interplay between classical and quantum computers [such as the variational quantum eigensolver (VQE) and the quantum approximate optimisation algorithm (QAOA), among others], quantum error correction, various versions of quantum computing (such as measurement-based quantum computation, adiabatic quantum computation, and the continuous-variable approach to quantum information), the intersection of quantum computing and machine learning, and quantum complexity theory. Lectures on these topics are compiled into 12 chapters, most of which contain a few suggested exercises at the end, and interspersed with four tutorials, which provide practical exercises as well as further details. At Chalmers, the course is taught in seven weeks, with three two-hour lectures or tutorials per week. It is recommended that the students taking the course have some previous experience with quantum physics, but not strictly necessary.

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Simulation of Quantum Computers: Review and Acceleration Opportunities

Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Nevertheless, the development of quantum computers is still in its early stages and the available systems have still very limited resources. As such, currently, the most practical way to develop and test quantum algorithms is to use classical simulators of quantum computers. In addition, the development of new quantum computers and their components also depends on simulations. Given the characteristics of a quantum computer, their simulation is a very demanding application in terms of both computation and memory. As such, simulations do not scale well in current classical systems. Thus different optimization and approximation techniques need to be applied at different levels. This review provides an overview of the components of a quantum computer, the levels at which these components and the whole quantum computer can be simulated, and an in-depth analysis of different state-of-the-art acceleration approaches. Besides the optimizations that can be performed at the algorithmic level, this review presents the most promising hardware-aware optimizations and future directions that can be explored for improving the performance and scalability of the simulations.

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Gradient-descent methods for fast quantum state tomography

Quantum state tomography (QST) is a widely employed technique for characterizing the state of a quantum system. However, it is plagued by two fundamental challenges: computational and experimental complexity grows exponentially with the number of qubits, rendering experimental implementation and data post-processing arduous even for moderately sized systems. Here, we introduce gradient-descent (GD) algorithms for the post-processing step of QST in discrete- and continuous-variable systems. To ensure physically valid state reconstruction at each iteration step of the algorithm, we use various density-matrix parameterizations: Cholesky decomposition, Stiefel manifold, and projective normalization. These parameterizations have the added benefit of enabling a rank-controlled ansatz, which simplifies reconstruction when there is prior information about the system. We benchmark the performance of our GD-QST techniques against state-of-the-art methods, including constrained convex optimization, conditional generative adversarial networks, and iterative maximum likelihood estimation. Our comparison focuses on time complexity, iteration counts, data requirements, state rank, and robustness against noise. We find that rank-controlled ansatzes in our stochastic mini-batch GD-QST algorithms effectively handle noisy and incomplete data sets, yielding significantly higher reconstruction fidelity than other methods. Simulations achieving full-rank seven-qubit QST in under three minutes on a standard laptop, with 18 GB of RAM and no dedicated GPU, highlight that GD-QST is computationally more efficient and outperforms other techniques in most scenarios, offering a promising avenue for characterizing noisy intermediate-scale quantum devices. Our Python code for GD-QST algorithms is publicly available at https://github.com/mstorresh/GD-QST.

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Impact of decoherence on the fidelity of quantum gates leaving the computational subspace

The fidelity of quantum operations is often limited by incoherent errors, which typically can be modeled by fundamental Markovian noise processes such as amplitude damping and dephasing. In Phys. Rev. Lett. 129, 150504 (2022; https://doi.org/10.1103/PhysRevLett.129.150504), we presented an analytical result for the average gate fidelity of a general multiqubit operation in terms of the dissipative rates and the corresponding Lindblad jump operators, provided that the operation remains in the computational subspace throughout the time evolution. Here we generalize this expression for the average gate fidelity to include the cases where the system state temporarily leaves the computational subspace during the gate. Such gate mechanisms are integral to several quantum-computing platforms, and our formula is applicable to all of them; as examples, we employ it for the two-qubit controlled-Z gate in both superconducting qubits and neutral atoms. We also obtain the average gate fidelity for simultaneous operations applied in multiqubit systems. These results are useful for understanding the error budgets of quantum gates while scaling up quantum computers.

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Unconventional and robust light-matter interactions based on the non-Hermitian skin effect

Lattice models featuring the non-Hermitian skin effect have attracted rapidly growing interest due to their nontrivial spectral topology and the exotic field dynamics they enable. Such non-Hermitian lattices provide a promising paradigm for engineering exotic light-matter interactions which benefit from the intrinsic chirality and unconventional (non-Bloch) band theory. Here we study a series of unconventional light-matter interactions between quantum emitters and the prototypical Hatano--Nelson model, and briefly discuss the case with an extended lattice model dubbed the bosonic Kitaev chain. We focus on the robustness of the dynamics against various imperfections and elucidate the underlying mechanisms. We consider both small emitters, which interact with the lattice at single sites, and giant emitters coupling at multiple sites. The latter exhibit an exclusive amplification mechanism, which we find enables decoherence-free dynamics even in the presence of extra dissipation in the system. The protection from dissipation arises from the cooperation of the non-Hermiticity and the self-interference effect, and is therefore lacking for small emitters. These results not only provide deeper insights into the interplay of non-Hermiticity and various interference effects, but also have potential applications in engineering exotic spin Hamiltonians and quantum networks.

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Entangling Schrödinger's cat states by bridging discrete- and continuous-variable encoding

In quantum information processing, two primary research directions have emerged: one based on discrete variables (DV) and the other on the structure of quantum states in a continuous-variable (CV) space. Integrating these two approaches could unlock new potentials, overcoming their respective limitations. Here, we show that such a DV-CV hybrid approach, applied to superconducting Kerr parametric oscillators (KPOs), enables us to entangle a pair of Schrödinger's cat states by two methods. The first involves the entanglement-preserving conversion between Bell states in the Fock-state basis (DV encoding) and those in the cat-state basis (CV encoding). The second method implements a $\sqrt{\textrm{iSWAP}}$ gate between two cat states following the procedure for Fock-state encoding. This simple and fast gate operation completes a universal quantum gate set in a KPO system. Our work offers powerful applications of DV-CV hybridization and marks a first step toward developing a multi-qubit platform based on planar KPO systems.

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