npj Quantum Information最新文献

Entanglement plays a crucial role in advancing quantum technologies and exploring quantum many-body simulations. Here, we introduce a protocol aided by neural networks for measuring entanglement in both equilibrium and non-equilibrium states of local Hamiltonians, with a favorable amount of training data. Our numerical simulations across various Hamiltonian models and qubit configurations reveal that this approach can predict comprehensive entanglement metrics, such as Rényi entropy, for up to 100 qubits using only single-qubit and two-qubit Pauli measurements. Excitingly, future entanglement dynamics beyond the measurement window can be predicted based solely on previous single-qubit traces. Experimentally, we utilize a nuclear spin quantum processor and a neural network to measure entanglement in the ground and dynamical states of a one-dimensional spin chain. The results demonstrate the feasibility of our method in practical experiments. Therefore, our approach offers a promising method for experimentally measuring entanglement in systems with dozens to hundreds of qubits.

We present a framework to split quantum circuits of variational quantum algorithms (VQAs) to allow for parallel training and execution to solve problems larger than the number of available qubits in a quantum device. We apply this method to combinatorial optimization problems, where inherent structures can be identified, and show how to implement these parallelized quantum circuits. We show how to formulate an objective function for the classical optimizer to guide the optimization towards meaningful solutions. We test our framework by creating a parallelized version of the Quantum Approximate Optimization Algorithm and a variational version of quantum annealing and explain how our framework applies to other quantum optimization algorithms. We provide results obtained both from simulation and experiments on real hardware. Our results show that the information lost by splitting the quantum circuits can be partially recovered by optimizing a global objective function evaluated with the separate circuit samples.

We devise an autonomous quantum thermal machine consisting of three pairwise-interacting qubits, two of which are locally coupled to thermal reservoirs. The machine operates autonomously, as it requires no time-coherent control, external driving or quantum bath engineering, and is instead propelled by a chemical potential bias. Under ideal conditions, we show that this out-of-equilibrium system can deterministically generate a maximally entangled steady-state between two of the qubits, or any desired pure two-qubit entangled state, emerging as a dark state of the system. We study the robustness of entanglement production with respect to several relevant parameters, obtaining nearly-maximally-entangled states well-away from the ideal regime of operation. Furthermore, we show that our machine architecture can be generalised to a configuration with 2n − 1 qubits, in which only a potential bias and two-body interactions are sufficient to generate genuine multipartite maximally entangled steady states in the form of a W state of n qubits.

A periodically driven superconducting nonlinear resonator can implement a Kerr-cat qubit, which provides a promising route to a quantum computer with a long lifetime. However, the system is vulnerable to pure dephasing, which causes unwanted excitations outside the qubit subspace. Therefore, we require a refrigeration technology that confines the system in the qubit subspace. We theoretically study on-chip refrigeration for Kerr-cat qubits based on photon-assisted electron tunneling at tunneling junctions, called quantum circuit refrigerators (QCR). Rates of QCR-induced deexcitations of the system can be changed by more than four orders of magnitude by tuning a bias voltage across the tunneling junctions. Unwanted QCR-induced bit flips are greatly suppressed due to quantum interference in the tunneling process, and thus the long lifetime is preserved. The QCR can serve as a tunable dissipation source that stabilizes Kerr-cat qubits.

We present an experimental demonstration of the Contextual Subspace Variational Quantum Eigensolver on superconducting hardware. Calculating the potential energy curve of molecular nitrogen proves challenging for many conventional quantum chemistry techniques, since static correlation dominates in the dissociation limit. Our quantum simulations retain good agreement with the Full Configuration Interaction energy, outperforming all benchmarked single-reference wavefunction techniques in capturing the bond-breaking appropriately. Moreover, our methodology is competitive with multiconfigurational approaches but at a saving of quantum resource, meaning larger active spaces can be treated for a fixed qubit allowance. To achieve this result, we deploy an error mitigation/suppression strategy comprised of Dynamical Decoupling, Measurement-Error Mitigation and Zero-Noise Extrapolation. Circuit parallelization also provides passive noise-averaging and improves the effective shot yield to reduce the measurement overhead. Furthermore, we introduce a modified adaptive ansatz construction algorithm that incorporates hardware awareness into our variational circuits, minimizing the transpilation cost for the target qubit topology.

We present a protocol for the ground-state cooling of a tripartite hybrid quantum system, in which a macroscopic oscillator acts as a mediator between a single-probe spin and a remote spin ensemble. In the presence of weak dispersive coupling between the spins and the oscillator, cooling of the oscillator and the ensemble spins can be achieved by exploiting the feedback from frequent measurements of the single-probe spin. We explore the parameter regimes necessary to cool the ensemble, the oscillator, or both to their thermal ground states. This novel cooling protocol shows that, even with only weak dispersive coupling, energy transfer-like effects can be obtained by simply manipulating the probe spin. These results not only contribute to the development of a practical solution for cooling/polarizing large spin ensembles but also provide a relatively simple means of tuning the dynamics of a hybrid system. The proposed protocol thus has broader implications for advancing various quantum technology applications, such as macroscopic quantum state generation and remote sensing.

Adiabatic measurements, followed by feedback and erasure protocols, have often been considered as a model to embody Maxwell’s Demon paradox and to study the interplay between thermodynamics and information processing. Such studies have led to the conclusion, now widely accepted in the community, that Maxwell’s Demon and the second law of thermodynamics can peacefully coexist because any gain provided by the demon must be offset by the cost of performing the measurement and resetting the demon’s memory to its initial state. Statements of this kind are collectively referred to as second laws of information thermodynamics and have recently been extended to include quantum theoretical scenarios. However, previous studies in this direction have made several assumptions, particularly about the feedback process and the demon’s memory readout, and thus arrived at statements that are not universally applicable and whose range of validity is not clear. In this work, we fill this gap by precisely characterizing the full range of quantum feedback control and erasure protocols that are overall consistent with the second law of thermodynamics. This leads us to conclude that the second law of information thermodynamics is indeed universal: it must hold for any quantum feedback control and erasure protocol, regardless of the measurement process involved, as long as the protocol is overall compatible with thermodynamics. Our comprehensive analysis not only encompasses new scenarios but also retrieves previous ones, doing so with fewer assumptions. This simplification contributes to a clearer understanding of the theory.

Gate set tomography (GST) allows for a self-consistent characterization of noisy quantum information processors (QIPs). The standard approach treats QIPs as black boxes only constrained by the laws of physics, attaining full generality at a considerable resource cost: numerous circuits must be run in order to amplify each of the gate set parameters. In this work, we show that a microscopic parametrization of quantum gates under time-correlated noise on the driving phase, motivated by recent experiments with trapped-ion gates, enables a more efficient version of GST. Adopting the formalism of filter functions over the noise spectral densities, we discuss the minimal parametrizations of the gate set that include the effect of non-Markovian quantum evolutions during the individual gates. We compare the estimated gate sets obtained by our method and the standard long-sequence GST, discussing their accuracies and showcasing the advantages of the parametrized approach in terms of the sampling complexity.

Time-bin encoding is a robust method for implementing quantum key distribution (QKD) on optical fiber channels, minimizing drift-induced errors. However, interferometric structures make achieving stable and low intrinsic Quantum Bit Error Rate (QBER) challenging. A key device for decoy-state QKD is the state encoder, which must produce low-error, stable states with varying photon mean values. Here, we introduce the MacZac (Mach-Zehnder-Sagnac), a time-bin encoder with ultra-low QBER (<2 × 10⁻⁵) and high stability. Based on nested Sagnac and Mach-Zehnder interferometers, it uses a single phase modulator for both decoy and state preparation, simplifying the optical setup. The encoder requires no active compensation and can generate states of arbitrary dimension. We experimentally tested it as a standalone component and in a QKD experiment. With its low QBER, stability, and simplicity, this device is a key building block for high-performance, low-cost QKD systems.

Efficient single-photon generation remains a big challenge in quantum photonics. A promising approach to overcome this challenge is to employ active multiplexing—repeating a nondeterministic photon pair generation process across orthogonal degrees of freedom and exploiting heralding to actively route the heralded photon to the desired single output mode via feedforward. The main barriers of multiplexing schemes, however, are minimizing resource requirements to allow scalability and the lack of availability of high-speed, low-loss switches. Here, we present an on-chip temporal multiplexing scheme utilizing thin-film lithium niobate (TFLN) photonics to effectively address these challenges. Our time-multiplexed source, operating at a rate of 62.2 MHz, enhances single-photon probability by a factor of 3.37 ± 0.05 without introducing additional multi-photon noise. This demonstration highlights the feasibility and potential of TFLN photonics for large-scale complex quantum information technologies.