npj Quantum Information最新文献

We demonstrate aluminum-on-silicon planar transmon qubits with time-averaged T₁ energy relaxation times of up to 270 μs, corresponding to Q = 5 million, and a highest observed value of 501 μs. Through materials analysis techniques and numerical simulations we investigate the dominant source of energy loss, and devise and demonstrate a strategy toward its mitigation. Growing aluminum films thicker than 300 nm reduces the presence of oxide, a known host of defects, near the substrate-metal interface, as confirmed by time-of-flight secondary ion mass spectrometry. A loss analysis of coplanar waveguide resonators shows that this results in a reduction of dielectric loss due to two-level system defects. The correlation between the enhanced performance of our devices and the film thickness is due to the aluminum growth in columnar structures of parallel grain boundaries: transmission electron microscopy shows larger grains in the thicker film, and consequently fewer grain boundaries containing oxide near the substrate-metal interface.

The electron pair approximation offers an efficient variational quantum eigensolver (VQE) approach for chemistry simulations on quantum computers. With the number of entangling gates scaling quadratically with system size and a constant measurement overhead, the orbital optimized unitary pair coupled cluster double (oo-upCCD) ansatz strikes a balance between accuracy and efficiency. However, the electron pair approximation prevents the method from achieving quantitative accuracy. To improve it, we explore the theory of second order perturbation (PT2) correction to oo-upCCD. PT2 accounts for the missing broken-pair contributions in oo-upCCD, while retaining its efficiencies. For molecular bond stretching and chemical reactions, the method significantly improves the predicted energy accuracy, reducing oo-upCCD’s error by up to 90%. On IonQ’s quantum computers, we find that the PT2 energy correction is highly noise-resilient. The predicted VQE-PT2 reaction energies are in excellent agreement with noise-free simulators after applying simple error mitigations solely on the VQE energies.

Attribute to their robustness against loss and external noise, nonreciprocal photonic devices hold great promise for applications in quantum information processing. Recent advancements have demonstrated that nonreciprocal optical transmission in linear systems can be achieved through the strategic introduction of loss. However, a crucial question remains unanswered: can loss be harnessed as a resource for generating nonreciprocal quantum correlations? Here, we take a counterintuitive stance by engineering loss to generate a vital form of nonreciprocal quantum correlations, termed nonreciprocal photon blockade. We examine a dissipative three-cavity system comprising two nonlinear cavities and a linear cavity. The interplay of loss and nonlinearity leads to a robust nonreciprocal single- and two-photon blockade, facilitated by destructive quantum interference. Furthermore, we demonstrate the tunability of this nonreciprocal photon blockade by manipulating the relative phase between the two nonlinear cavities. Remarkably, this allows for the reversal of the direction of nonreciprocity. Our study not only sheds a light on the concept of loss-engineered quantum nonreciprocity but also opens up a pathway for the design of quantum nonreciprocal photonic devices.

Quantum networks comprised of entangled end nodes serve stronger than the classical correlation for unparalleled quantum internet applications. However, practical quantum networking is affected by noise, which at its worst, causes end nodes to be described by pre-existing classical data. In such untrusted networks, determining quantum network fidelity and genuine multi-node entanglement becomes crucial. Here, we show that determining quantum network fidelity and genuine N-node entanglement in an untrusted star network requires only N + 1 measurement settings. This method establishes a semi-trusted framework, allowing some nodes to relax their assumptions. Our network determination method is enabled by detecting genuine N-node Einstein-Podolsky-Rosen steerability. Experimentally, using spontaneous parametric down-conversion entanglement sources, we demonstrate the determinations of genuine 3-photon and 4-photon quantum networks and the false positives of the widely used entanglement witness, the fidelity criterion of 1/2. Our results provide a scalable method for the determination of multipartite entanglement in realistic quantum networks.

We design a quantum method for classical information compression that exploits the hidden subgroup quantum algorithm. We consider sequence data in a database with a priori unknown symmetries of the hidden subgroup type. We prove that data with a given group structure can be compressed with the same query complexity as the hidden subgroup problem, which is exponentially faster than the best-known classical algorithms. We moreover design a quantum algorithm that variationally finds the group structure and uses it to compress the data. There is an encoder and a decoder, along the paradigm of quantum autoencoders. After the training, the encoder outputs a compressed data string and a description of the hidden subgroup symmetry, from which the input data can be recovered by the decoder. In illustrative examples, our algorithm outperforms the classical autoencoder on the mean squared value of test data. This classical-quantum separation in information compression capability has thermodynamical significance: the free energy assigned by a quantum agent to a system can be much higher than that of a classical agent. Taken together, our results show that a possible application of quantum computers is to efficiently compress certain types of data that cannot be efficiently compressed by current methods using classical computers.

Our study evaluates the limitations and potentials of Quantum Random Access Memory (QRAM) within the principles of quantum physics and relativity. QRAM is crucial for advancing quantum algorithms in fields like linear algebra and machine learning, purported to efficiently manage large data sets with ({{{mathcal{O}}}}(log N)) circuit depth. However, its scalability is questioned when considering the relativistic constraints on qubits interacting locally. Utilizing relativistic quantum field theory and Lieb–Robinson bounds, we delve into the causality-based limits of QRAM. Our investigation introduces a feasible QRAM model in hybrid quantum acoustic systems, capable of supporting a significant number of logical qubits across different dimensions-up to ~10⁷ in 1D, ~10¹⁵ to ~10²⁰ in 2D, and ~10²⁴ in 3D, within practical operation parameters. This analysis suggests that relativistic causality principles could universally influence quantum computing hardware, underscoring the need for innovative quantum memory solutions to navigate these foundational barriers, thereby enhancing future quantum computing endeavors in data science.

The negatively charged silicon vacancy center (({{rm{V}}}_{{rm{Si}}}^{-})) in silicon carbide (SiC) is an emerging color center for quantum technology covering quantum sensing, communication, and computing. Yet, limited information currently available on the internal spin-optical dynamics of these color centers prevents us from achieving the optimal operation conditions and reaching the maximum performance especially when integrated within quantum photonics. Here, we establish all the relevant intrinsic spin dynamics of the ({{rm{V}}}_{{rm{Si}}}^{-}) center at cubic lattice site (V2) in 4H-SiC by an in-depth electronic fine structure modeling including the intersystem-crossing and deshelving mechanisms. With carefully designed spin-dependent measurements, we obtain all the previously unknown spin-selective radiative and non-radiative decay rates. To showcase the relevance of our work for integrated quantum photonics, we use the obtained rates to propose a realistic implementation of time-bin entangled multi-photon GHZ and cluster state generation. We find that up to three-photon GHZ or cluster states are readily within reach using the existing nanophotonic cavity technology.

Silicon spin qubits are promising candidates for scalable quantum computers, due to their coherence and compatibility with CMOS technology. Advanced industrial processes ensure wafer-scale uniformity and high device yield, but traditional transistor processes cannot be directly transferred to qubit structures. To leverage the micro-electronics industry expertise, we customize a 300 mm wafer fabrication line for silicon MOS qubit integration. With careful optimization of the gate stack, we report uniform quantum dot operation at the Si/SiO₂ interface at mK temperature. We measure a record-low average noise with a value of 0.61 ({rm{mu }}{rm{eVH}}{{rm{z}}}^{-0.5}) at 1 Hz and even below 0.1 ({rm{mu }}{rm{eVH}}{{rm{z}}}^{-0.5}) for some operating conditions. Statistical analysis of the charge noise measurements show that the noise source can be described by a two-level fluctuator model. This reproducible low noise level, in combination with uniform operation of our quantum dots, marks CMOS manufactured spin qubits as a mature platform towards scalable high-fidelity qubits.

Enhancing the performance of noisy quantum processors requires improving our understanding of error mechanisms and the ways to overcome them. A judicious selection of qubit design parameters plays a pivotal role in improving the performance of quantum processors. In this study, we identify optimal ranges for qubit design parameters, grounded in comprehensive noise modeling. To this end, we also analyze the effect of a charge-parity switch caused by quasiparticles on a two-qubit gate. Due to the utilization of the second excited state of a transmon, where the charge dispersion is significantly larger, a charge-parity switch will affect the conditional phase of the two-qubit gate. We derive an analytical expression for the infidelity of a diabatic controlled-Z gate and see effects of similar magnitude in adiabatic controlled-phase gates in the tunable coupler architecture. Moreover, we show that the effect of a charge-parity switch can be the dominant quasiparticle-related error source of a two-qubit gate. We also demonstrate that charge-parity switches induce a residual longitudinal interaction between qubits in a tunable-coupler circuit. Furthermore, we introduce a performance metric for quantum circuit execution, encompassing the fidelity and number of single- and two-qubit gates in an algorithm, as well as the state preparation fidelity. This comprehensive metric, coupled with a detailed noise model, enables us to determine an optimal range for the qubit design parameters, as confirmed by numerical simulation. Our systematic analysis offers insights and serves as a guiding framework for the development of the next generation of transmon-based quantum processors.

We demonstrate that the contextuality of measurement selection can enhance the precision of quantum metrology with a simple linear optical experiment. Contextuality is a nonclassical property known as a resource for various quantum information processing tasks. Recent studies show that contextuality by anomalous weak values can be utilized to enhance metrological precision, unraveling the role of contextuality in quantum metrology. Our contextual quantum metrology (coQM) scheme can elevate the precision of the optical polarimetry as much as 6 times the precision limit given by the Quantum Fisher Information. We achieve the contextuality-enabled enhancement with two mutually complementary measurements, whereas, in the conventional method, some optimal measurements to achieve the precision limit are either theoretically challenging to find or experimentally infeasible to realize. These results highlight that the contextuality of measurement selection is applicable in practice for quantum metrology.