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Generating graph states with a single quantum emitter and the minimum number of fusions

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Physical Review A 2025年第5期111卷 052604-052604页

作者： Matthias C. Löbl Love A. Pettersson Andrew Jena Luca Dellantonio Stefano Paesani Anders S. Sørensen Department of Combinatorics and Optimization University of Waterloo and Institute for Quantum Computing University of Waterloo Ontario Canada Department of Physics and Astronomy University of Exeter Stocker Road Exeter EX4 4QL United Kingdom NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Blegdamsvej 17 DK-2100 Copenhagen Ø Denmark

Graph states are the key resources for measurement- and fusion-based quantum computing with photons, yet their creation is experimentally challenging. We optimize a hybrid graph-state generation scheme using a single quantum emitter and linear optics Bell-state measurements called fusions. We first generate a restricted class of states from a single quantum emitter and then apply fusions to create a target graph state, where we use a dynamic programming approach to find the construction that requires the lowest possible number of fusions. Our analysis yields a lookup table for constructing ≈2.8×107 nonisomorphic graph states with the minimum number of fusions. The lookup table covers all graph states with up to eight qubits and several other ones with up to 14 qubits. We present construction protocols of selected graph states and provide the lookup table. For large graph states that are not in the lookup table, we derive bounds for the required number of fusions using graph-theoretic properties. Finally, we use the lookup table to search for the best graph codes for loss-tolerant encodings, given a fixed number of fusions for their construction.

关键词： Qubits

Many-body effects of two-level systems in superconducting qubits

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arXiv 2025年

作者： Heath, Joshuah T. Tyner, Alexander C. Thann, Thue Christian Michal, Vincent P. Krogstrup, Peter Svendsen, Mark Kamper Balatsky, Alexander V. Nordita Stockholm University KTH Royal Institute of Technology Hannes Alfvéns väg 12 StockholmSE-106 91 Sweden Department of Physics University of Connecticut StorrsCT06269 United States NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Denmark

Superconducting qubits are often adversely affected by two-level systems (TLSs) within the Josephson junction, which contribute to decoherence and subsequently limit the performance of the qubit. By treating the TLS as a soft (i.e., low-frequency) bosonic mode localized in real space, we find that a single TLS in either the amorphous oxide surface or the superconducting bulk may result in a localized "hot spot" of amplified Josephson energy. Such amplification is shown to have a non-negligible effect on the T1 time of certain superconducting qubits, regardless of whether or not the TLS is on resonance with the qubit frequency. With this study, we identify sources of decoherence unique to the superconducting element of superconducting quantum devices. © 2025, CC BY.

关键词： Qubits

Scalable entanglement of nuclear spins mediated by electron exchange

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arXiv 2025年

作者： Stemp, Holly G. van Blankenstein, Mark R. Asaad, Serwan Mądzik, Mateusz T. Joecker, Benjamin Firgau, Hannes R. Laucht, Arne Hudson, Fay E. Dzurak, Andrew S. Itoh, Kohei M. Jakob, Alexander M. Johnson, Brett C. Jamieson, David N. Morello, Andrea School of Electrical Engineering and Telecommunications UNSW Sydney SydneyNSW2052 Australia ARC Centre of Excellence for Quantum Computation and Communication Technology NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Denmark Diraq Pty. Ltd. SydneyNSW Australia School of Fundamental Science and Technology Keio University Kohoku-ku Yokohama Japan School of Physics University of Melbourne MelbourneVIC3010 Australia School of Science RMIT University MelbourneVIC3000 Australia

The use of nuclear spins for quantum computation is limited by the difficulty in creating genuine quantum entanglement between distant nuclei. Current demonstrations of nuclear entanglement in semiconductors rely upon coupling the nuclei to a common electron, which is not a scalable strategy. Here we demonstrate a two-qubit Control-Z logic operation between the nuclei of two phosphorus atoms in a silicon device, separated by up to 20 nanometers. Each atoms binds separate electrons, whose exchange interaction mediates the nuclear two-qubit gate. We prove that the nuclei are entangled by preparing and measuring Bell states with a fidelity of 76+5−5% and a concurrence of 0.67+0.05−0.05. With this method, future progress in scaling up semiconductor spin qubits can be extended to the development of nuclear-spin based quantum computers. © 2025, CC BY-NC-ND.

关键词： Qubits

Modular Autonomous Virtualization System for Two-Dimensional Semiconductor quantum Dot Arrays

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Physical Review X 2025年第2期15卷 021034-021034页

作者： Anantha S. Rao Donovan Buterakos Barnaby van Straaten Valentin John Cécile X. Yu Stefan D. Oosterhout Lucas Stehouwer Giordano Scappucci Menno Veldhorst Francesco Borsoi Justyna P. Zwolak Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Department of Physics University of Maryland College Park Maryland 20742 USA National Institute of Standards and Technology Gaithersburg Maryland 20899 USA QuTech and Kavli Institute of Nanoscience Delft University of Technology P.O. Box 5046 2600 GA Delft The Netherlands QuTech and Netherlands Organisation for Applied Scientific Research (TNO) Delft The Netherlands Present address: NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Blegdamsvej 17 2100 Copenhagen Denmark.

Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Hamiltonian parameters that define the electrostatic environment. However, due to the tight gate pitch, capacitive crosstalk between gates hinders independent tuning of chemical potentials and interdot couplings. While virtual gates offer a practical solution, determining all the required cross-capacitance matrices accurately and efficiently in large quantum dot registers is an open challenge. Here, we establish a modular automated virtualization system (MAViS)—a general and modular framework for autonomously constructing a complete stack of multilayer virtual gates in real time. Our method employs machine learning techniques to rapidly extract features from two-dimensional charge stability diagrams. We then utilize computer vision and regression models to self-consistently determine all relative capacitive couplings necessary for virtualizing plunger and barrier gates in both low- and high-tunnel-coupling regimes. Using MAViS, we successfully demonstrate accurate virtualization of a dense two-dimensional array comprising ten quantum dots defined in a high-quality Ge/SiGe heterostructure. Our work offers an elegant and practical solution for the efficient control of large-scale semiconductor quantum dot systems.

关键词： Semiconductor quantum dots

Subgap transport in superconductor-semiconductor hybrid islands: Weak and strong coupling regimes

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Physical Review Research 2025年第2期7卷 023022-023022页

作者： Marco Valentini Rubén Seoane Souto Maksim Borovkov Peter Krogstrup Yigal Meir Martin Leijnse Jeroen Danon Georgios Katsaros Institute of Science and Technology Austria Am Campus 1 3400 Klosterneuburg Austria Instituto de Ciencia de Materiales de Madrid Consejo Superior de Investigaciones Científicas (ICMM-CSIC) Madrid 28049 Spain NanoLund and Solid State Physics Lund University Box 118 22100 Lund Sweden Center for Quantum Devices Niels Bohr Institute University of Copenhagen 2100 Copenhagen Denmark NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Universitetsparken 5 2100 Copenhagen Denmark Department of Physics Ben-Gurion University of the Negev Beer-Sheva 84105 Israel Department of Physics Norwegian University of Science and Technology NO-7491 Trondheim Norway

Superconductor–semiconductor hybrid systems play a crucial role in realizing nanoscale quantum devices, including hybrid qubits, Majorana bound states, and Kitaev chains. For such hybrid devices, subgap states play a prominent role in their operation. In this paper, we study these subgap states via Coulomb and tunneling spectroscopy through a superconducting island defined in a semiconductor nanowire fully coated by a superconductor. We systematically explore regimes ranging from an almost decoupled island to the open configuration. In the weak-coupling regime, the experimental observations are very similar in the absence of a magnetic field and when one flux quantum pierces the superconducting shell. Conversely, in the strong-coupling regime, significant distinctions emerge between the two cases. We attribute this distinct behavior to the existence of subgap states at one flux quantum, which become observable only for sufficiently strong coupling to the leads. We support our interpretation using a simple model to describe transport through the island. Our study highlights the importance of studying a broad range of tunnel couplings for understanding the rich physics of hybrid devices.

关键词： quantum optics

Machine Learning Approach towards quantum Error Mitigation for Accurate Molecular Energetics

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arXiv 2025年

作者： Patil, Srushti Mondal, Dibyendu Maitra, Rahul NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Jagtvej 155 A Copenhagen N DK Copenhagen2200 Denmark Department of Chemistry Indian Institute of Technology Bombay Powai Mumbai400076 India Centre of Excellence in Quantum Information Computing Science & Technology Indian Institute of Technology Bombay Powai Mumbai400076 India

Despite significant efforts, the realization of the hybrid quantum-classical algorithms has predominantly been confined to proof-of-principles, mainly due to the hardware noise. With fault-tolerant implementation being a long-term goal, going beyond small molecules with existing error mitigation (EM) techniques with current noisy intermediate scale quantum (NISQ) devices has been a challenge. That being said, statistical learning methods are promising approaches to learning the noise and its subsequent mitigation. We devise a graph neural network and regression-based machine learning (ML) architecture for practical realization of EM techniques for molecular Hamiltonian without the requirement of the exponential overhead. Given the short coherence time of the quantum hardware, the ML model is trained with either ideal or mitigated expectation values over a judiciously chosen ensemble of shallow sub-circuits adhering to the native hardware architecture. The hardware connectivity network is mapped to a directed graph which encodes the information of the native gate noise profile to generate the features for the neural network. The training data is generated on-the-fly during ansatz construction thus removing the computational overhead. We demonstrate orders of magnitude improvements in predicted energy over a few strongly correlated molecules. © 2025, CC BY.

关键词： Hamiltonians

Machine Learning Enhanced Calculation of quantum-Classical Binding Free Energies

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arXiv 2025年

作者： Bensberg, Moritz Eckhoff, Marco Thomasen, F. Emil Bro-Jørgensen, William Teynor, Matthew S. Sora, Valentina Weymuth, Thomas Husistein, Raphael T. Knudsen, Frederik E. Krogh, Anders Lindorff-Larsen, Kresten Reiher, Markus Solomon, Gemma C. ETH Zurich Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 2 Zurich8093 Switzerland University of Copenhagen Department of Biology Linderstrøm-Lang Centre for Protein Science Ole Maaløes Vej 5 Copenhagen NDK-2200 Denmark University of Copenhagen Department of Chemistry and Nano-Science Center Universitetsparken 5 Copenhagen ØDK-2100 Denmark University of Copenhagen Niels Bohr Institute NNF Quantum Computing Programme Blegdamsvej 21 Copenhagen ØDK-2100 Denmark University of Copenhagen Department of Computer Science Universitetsparken 1 Copenhagen ØDK-2100 Denmark Center for Health Data Science Department of Public Health Denmark

Binding free energies are a key element in understanding and predicting the strength of protein–drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs including transition metal atoms often require quantum chemical methods for an accurate description. We propose a general and automated workflow that samples the potential energy surface with hybrid quantum mechanics/molecular mechanics (QM/MM) calculations and trains a machine learning (ML) potential on the QM energies and forces to enable efficient alchemical free energy simulations. To represent systems including many different chemical elements efficiently and to account for the different description of QM and MM atoms, we propose an extension of element-embracing atom-centered symmetry functions for QM/MM data as an ML descriptor. The ML potential approach takes electrostatic embedding and long-range electrostatics into account. We demonstrate the applicability of the workflow on the well-studied protein–ligand complex of myeloid cell leukemia 1 and the inhibitor 19G and on the anti-cancer drug NKP1339 acting on the glucose-regulated protein 78. Copyright © 2025, The Authors. All rights reserved.

关键词： Ligands

Origin of surface and subband states at the InAs(111)A surface

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Physical Review Materials 2023年第6期7卷 066201-066201页

作者： Rajib Batabyal Steffen Zelzer Alec P. Romagosa Derek Dardzinski Fabiano Corsetti Noa Marom Peter Krogstrup NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen 2100 Copenhagen Denmark

The atomic structure of surfaces and interfaces plays a vital role in the electronic quality and properties of quantum devices. The interplay between the surface and confined bulk subband states in terms of their susceptibility has been investigated in relation to crystal defects on an InAs(111)A-(2×2) reconstructed surface, using low-temperature scanning tunneling microscopy and spectroscopy. We measure the two-dimensional quantized subband states arising from the confined potential imposed by downward bending of the conduction band edge. Furthermore, we show evidence of the existence of surface Bloch states within the confined bulk band gap projected on the surface spectrum which have originated from the surface reconstruction. As expected, larger confined bulk band gaps at the surface and conduction band offset are measured to be 0.58 and 0.31 eV, respectively. We further show the scattering of these quantum states at different surface defects and demonstrate that surface states are more susceptible to the defect potential when compared with the corresponding subband states. This apparent contrast follows from the length scale at which these defect potentials actively interact on or near the surface. Our observed experimental results are supported by empirical tight-binding simulations for the subband states and first-principles density functional theory simulations for the surface states present on the surface.

关键词： Defects Density of states Electronic structure Spin-orbit coupling Surface reconstruction Surface states

Hierarchical quantum embedding by machine learning for large molecular assemblies

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arXiv 2025年

作者： Bensberg, Moritz Eckhoff, Marco Husistein, Raphael T. Teynor, Matthew S. Sora, Valentina Bro-Jørgensen, William Thomasen, F. Emil Krogh, Anders Lindorff-Larsen, Kresten Solomon, Gemma C. Weymuth, Thomas Reiher, Markus ETH Zurich Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 2 Zurich8093 Switzerland University of Copenhagen Department of Chemistry and Nano-Science Center Universitetsparken 5 Copenhagen ØDK-2100 Denmark University of Copenhagen Niels Bohr Institute NNF Quantum Computing Programme Blegdamsvej 17 Copenhagen ØDK-2100 Denmark University of Copenhagen Department of Computer Science Universitetsparken 1 Copenhagen ØDK-2100 Denmark University of Copenhagen Department of Biology Linderstrøm-Lang Centre for Protein Science Ole Maaløes Vej 5 Copenhagen NDK-2200 Denmark University of Copenhagen Center for Health Data Science Department of Public Health Øster Farimagsgade 5 Copenhagen ØDK-1353 Denmark

We present a quantum-in-quantum embedding strategy coupled to machine learning potentials to improve on the accuracy of quantum-classical hybrid models for the description of large molecules. In such hybrid models, relevant structural regions (such as those around reaction centers or pockets for binding of host molecules) can be described by a quantum model that is then embedded into a classical molecular-mechanics environment. However, this quantum region may become so large that only approximate electronic structure models are applicable. To then restore accuracy in the quantum description, we here introduce the concept of quantum cores within the quantum region that are amenable to accurate electronic structure models due to their limited size. Huzinaga-type projection-based embedding, for example, can deliver accurate electronic energies obtained with advanced electronic structure methods. The resulting total electronic energies are then fed into a transfer learning approach that efficiently exploits the higher-accuracy data to improve on a machine learning potential obtained for the original quantum-classical hybrid approach. We explore the potential of this approach in the context of a well-studied protein-ligand complex for which we calculate the free energy of binding using alchemical free energy and non-equilibrium switching simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecules