npj Quantum Information最新文献

Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational cost of training more complicated nonlinear models. On the other hand, quantum information scrambling (QIS) quantifies how the spread of quantum information into correlations makes it irretrievable from local measurements. Here, we explore the tight relation between QIS and the predictive power of QELMs. In particular, we show efficient state estimation is possible even beyond the scrambling time, for many different types of dynamics — in fact, we show that in all the cases we studied, the reconstruction efficiency at long interaction times matches the optimal one offered by random global unitary dynamics. These results offer promising venues for robust experimental QELM-based state estimation protocols, as well as providing novel insights into the nature of QIS from a state estimation perspective.

Over the past decade, integrated quantum photonic technologies have shown great potential as a platform for studying quantum phenomena and realizing large-scale quantum information processing. Recently, there have been proposals for utilizing waveguide lattices to implement quantum gates, providing a more compact and robust solution compared to discrete implementation with directional couplers and phase shifters. We report on the first demonstration of precise control of single photon states on an 11-dimensional continuously-coupled programmable waveguide array. Through electro-optical control, the array is subdivided into decoupled subcircuits and the degree of on-chip quantum interference can be tuned with a maximum visibility of 0.962 ± 0.013. Furthermore, we show simultaneous control of two subcircuits on a single device. Our results demonstrate the potential of using this technology as a building block for quantum information processing applications.

The unique property of tantalum, particularly its exceptional resistance to both acid and alkali, makes it promising for superconducting quantum processors. Here, we propose a novel lift-off method for fabricating tantalum airbridges with separate or fully-capped structures. This method introduces an aluminum film as a barrier layer to separate two layers of photoresist, which is then etched away before depositing tantalum film. We experimentally characterize these tantalum airbridges as control line jumpers, ground plane crossovers and coupling elements, and further validate the overall adaptability by a 13-qubit quantum processor with a median T₁ exceeding 100 μs. The median single-qubit gate fidelity is measured at 99.95(2)% for isolated Randomized Benchmarking and 99.94(2)% for the simultaneous one. Additionally, the experimental achievement of airbridge coupling with a controlled-Z gate fidelity surpassing 99.2(2)% in a separate two-qubit quantum chip may facilitate scalable quantum computation and quantum error correction with entirely tantalum elements.

Spin qubits in germanium gate-defined quantum dots have made considerable progress within the last few years, partially due to their strong spin-orbit coupling and site-dependent g-tensors. While this characteristic of the g-factors removes the need for micromagnets and allows for the possibility of all-electric qubit control, relying on these g-tensors necessitates the need to understand their sensitivity to the confinement potential that defines the quantum dots. Here, we demonstrate a S − T_ qubit whose frequency is a strong function of the voltage applied to the barrier gate shared by the quantum dots. We find a g-factor that can be approximately increased by an order of magnitude adjusting the barrier gate voltage only by 12 mV. We show how this strong dependence could potentially be attributed to the dots moving through a variable strain environment in our device. This work not only reinforces previous findings that site-dependent g-tensors in germanium can be utilized for qubit manipulation, but reveals the sensitivity and tunability these g-tensors have to the electrostatic confinement of the quantum dot.

High-dimensional quantum key distribution (QKD) offers secure communication with key rates that surpass those of QKD protocols utilizing two-dimensional encoding. However, existing high-dimensional QKD protocols require additional experimental resources, such as multiport interferometers and multiple detectors, thereby increasing the cost of high-dimensional systems and limiting their use. We introduce and analyze a high-dimensional QKD protocol that requires only standard two-dimensional hardware. We provide security analysis against individual and coherent attacks, establishing upper and lower bounds on the secure key rates. We tested our protocol on a standard two-dimensional QKD system over a 40 km fiber link, achieving a twofold increase in secure key rate compared to the standard two-dimensional coherent one-way protocol, without any hardware modifications. This work offers a significant improvement in the performance of already deployed QKD systems through simple software updates and holds broad applicability across various QKD schemes, making high-dimensional QKD practical for widespread use.

Simulating quantum many-body systems is crucial for advancing physics but poses substantial challenges for classical computers. Quantum simulations overcome these limitations, with analog simulators offering unique advantages over digital methods, such as lower systematic errors and reduced circuit depth, making them efficient for studying complex quantum phenomena. However, unlike their digital counterparts, analog quantum simulations face significant limitations due to the absence of effective error mitigation techniques. This work introduces two novel error mitigation strategies—Hamiltonian reshaping and Hamiltonian rescaling—in analog quantum simulation for tasks like eigen-energy evaluation. Hamiltonian reshaping uses random unitary transformations to generate new Hamiltonians with identical eigenvalues but varied eigenstates, allowing error reduction through averaging. Hamiltonian rescaling mitigates errors by comparing eigenvalue estimates from energy-scaled Hamiltonians. Numerical calculations validate both methods, demonstrating their significant practical effectiveness in enhancing the accuracy and reliability of analog quantum simulators.

Entanglement-assisted classical communication (EACC) aims to enhance communication systems using entanglement as an additional resource. However, there is a scarcity of explicit protocols designed for finite transmission scenarios, which presents a challenge for real-world implementation. In response, we introduce a new EACC scheme capable of correcting a fixed number of erasures/errors. It can be adjusted to the available amount of entanglement and sends classical information over a quantum channel. We establish a general framework to accomplish such a task by reducing it to a classical problem. Comparing with specific bounds, we identify optimal parameter ranges. The scheme requires only the implementation of super-dense coding which has been demonstrated successfully in experiments. Furthermore, our results show that an adaptable entanglement use confers a communication advantage. Overall, our work sheds light on how entanglement can elevate various finite-length communication protocols, opening new avenues for exploration in the field.

Generating quantum entanglement is plagued by decoherence. Distillation and error-correction are employed against such noise, but designing a good distillation circuit, especially on today’s imperfect hardware, is challenging. We develop a simulation algorithm for distillation circuits with per-gate complexity of ({mathcal{O}}(1)), drastically faster than ({mathcal{O}}(N)) Clifford simulators or ({mathcal{O}}({2}^{N})) wavefunction simulators over N qubits. This simulator made it possible to optimize distillation circuits much larger than previously feasible. We design distillation circuits from n raw Bell pairs to k purified pairs and study the use of these circuits in the teleportation of logical qubits. The resulting purification circuits are the best-known for finite-size noisy hardware and can be fine-tuned for specific error-models. Furthermore, we design purification circuits that shape the correlations of errors in the purified pairs such that the performance of potential error-correcting codes is greatly improved.

Increasing the density of superconducting circuits requires compact components, however, superconductor-based capacitors typically perform worse as dimensions are reduced due to loss at surfaces and interfaces. Here, parallel plate capacitors composed of aluminum-contacted, crystalline silicon fins are shown to be a promising technology for use in superconducting circuits by evaluating the performance of lumped element resonators and transmon qubits. High aspect ratio Si-fin capacitors having widths below 300 nm with an approximate total height of 3 μm are fabricated using anisotropic wet etching of Si(110) substrates followed by aluminum metallization. The single-crystal Si capacitors are incorporated in lumped element resonators and transmons by shunting them with lithographically patterned aluminum inductors and conventional Al/AlO_x/Al Josephson junctions respectively. Microwave characterization of these devices suggests state-of-the-art performance for superconducting parallel plate capacitors with low power internal quality factor of lumped element resonators greater than 500 k and qubit T₁ times greater than 25 μs. These results suggest that Si-Fins are a promising technology for applications that require low-loss, compact, superconductor-based capacitors with minimal stray capacitance.

We study an open quantum system simulation on quantum hardware, which demonstrates robustness to hardware errors even with deep circuits containing up to two thousand entangling gates. We simulate two systems of electrons coupled to an infinite thermal bath: 1) a system of dissipative free electrons in a driving electric field; and 2) the thermalization of two interacting electrons in a single orbital in a magnetic field—the Hubbard atom. These problems are solved using IBM quantum computers, showing no signs of decreasing fidelity at long times. Our results demonstrate that algorithms for simulating open quantum systems are able to far outperform similarly complex non-dissipative algorithms on noisy hardware. Our two examples show promise that the driven-dissipative quantum many-body problem can eventually be solved on quantum computers.