量子物理
Quantum imaging, which harnesses quantum correlations to achieve imaging with multiple advantages over classical optics, has been in development for several years. Here, we explore sunlight, serving as the pump beam, to excite spontaneous…
Optical switching remains a key outstanding challenge for scalable fault-tolerant photonic quantum computing due to the trade-off between speed, bandwidth, and loss. Scalable quantum photonics demands all three, to enable high computational…
We propose an efficient classical algorithm to estimate the Neural Tangent Kernel (NTK) associated with a broad class of quantum neural networks. These networks consist of arbitrary unitary operators belonging to the Clifford group…
In a work by Granovskii and Zhedanov, a surprising family of scar states exhibiting zero entanglement was discovered in the XYZ spin chain, remarkably, nearly three decades before the concept of many-body scars became a subject of active…
Artificial atoms non-locally coupled to waveguides -- the so-called giant atoms -- offer new opportunities for the control of light and matter. In this work, we show how to use an array of non-locally coupled transmon "molecules" to…
Accurate computation of multiple eigenvalues of quantum Hamiltonians is essential in quantum chemistry, materials science, and molecular spectroscopy. Estimating excited-state energies is challenging for classical algorithms due to…
Scalable quantum technologies demand long-range interactions between many distant quantum emitters (QEs). We introduce non-local metasurfaces supporting bound-states-in-the-continuum (BICs) as a promising platform to achieve this goal. We…
Dissipation in quantum many-body systems provides a more general and experimentally realistic perspective on particle transport than closed quantum systems. In this work, we determine the maximal speed of macroscopic particle transport in…
We experimentally optimize the frequency of flux-tunable couplers in a superconducting quantum processor to minimize the impact of spectator transmons during quantum operations (single-qubit gates, two-qubit gates and readout) on other…
Quantum key distribution (QKD) has emerged as a promising solution to protect current cryptographic systems against the threat of quantum computers. As QKD transitions from laboratories to real-world applications, its implementation under…
Making use of the simple fact that all separable complex Hilbert spaces of given dimension are isomorphic, we show that there are just six basic ways to define generalized coordinate operators in Quantum Mechanics. In each case a…
We express the dynamics of the two probability amplitudes in the elementary Landau-Zener problem in terms of the solution of the corresponding Riccati differential equation and identify three key features: (i) The solution of the Riccati…
The maximum likelihood (ML) decoder in the two-dimensional surface code with generic unitary errors is governed by a statistical mechanics model with complex weights, which can be simulated via (1+1)D transfer matrix contraction.…
Distributed quantum computing (DQC) has emerged as a promising approach to overcome the scalability limitations of monolithic quantum processors in terms of computational capability. However, realising the full potential of DQC requires…
Many current quantum error-correcting codes that achieve full fault tolerance suffer from having low ratios of logical to physical qubits and significant overhead. This makes them difficult to implement on current noisy intermediate-scale…
A quasi-one-dimensional Bose-Einstein condensate loaded into a quasi-periodic potential created by two sub-lattices of comparable amplitudes and incommensurate periods is considered. Although the conventional tight-binding approximation is…
Measurement-induced quantum computation with continuous-variable cluster states utilizes teleportation to transmit and alter quantum states via measurement-and-feedforward control. One of the key challenges of this approach is the…
The data encoding circuits used in quantum support vector machine (QSVM) kernels play a crucial role in their classification accuracy. However, manually designing these circuits poses significant challenges in terms of time and performance.…
Standard quantum inference converts quantum data into classical outputs. We study an alternative inference setting in which the desired output is quantum, preserving coherence. Such settings include quantum purity amplification (QPA),…
Hybrid tensor networks offer a promising route to enhance the expressivity of classical tensor network methods by incorporating quantum states prepared on a quantum computer. Existing approaches are limited by the variational optimization…