Quantum Physics (quant-ph)

Abstract: The Aharonov-Bohm (AB) cage enables localized confinement with nondiffractive propagation for arbitrary excitation. In this study, we introduce an anti-parity-time (anti-$\mathcal{PT}$) symmetric imaginary coupling in a generalized Creutz ladder to construct a non-Hermitian AB cage with tunable flat-band energy. We investigate compact localized states and complete localization dynamics, and show that non-Hermiticity affects the localization probability distributions and increases the oscillation period of the AB cage dynamics. Non-Hermitian engineering of the decoupled core of the AB cage is the essential point in our proposal. Our approach is widely applicable to a more general situation and can facilitate the manipulation of localization in physics.

Abstract: Disorder in one-dimensional (1D) many-body systems emerges abundant phases such as many-body localization (MBL), and thermalization. However, it remains unclear regarding their existence and behavior within hybrid quantum systems. Here, based on a simple bosonic-spin hybrid model, as known as the Jaynes-Cummings-Hubbard (JCH) array, we investigate the effect of disorder comparing to the phenomena in the clean system with the variation of atom-photon coupling strength. By using the level-spacing ratio, entanglement entropy, and the properties of observable diagonal and off-diagonal matrix elements, we find that strong disorder results in the appearance of MBL phase in the JCH model that strongly violate eigenstate thermalization hypothesis (ETH), while a conditional prethermal behavior can exist in weak disorder or weak coupling regime. The conditional prethermal dynamics is based on the choice of initial product states. This work systematically reveals abundant many-body phases in the 1D JCH model and clarifies the discrepancies in the thermalization properties of systems with and without disorder.

Abstract: We introduce a continuous time model of many-body quantum dynamics based on infinitesimal random unitary operations, combined with projective measurements. We consider purification dynamics in this model, where the system is initialized in a mixed state, which then purifies over time as a result of the measurements. By mapping our model to a family of effective 1D quantum Hamiltonians, we are able to derive analytic expressions that capture how the entropy of the system decays in time. Our results confirm the existence of two distinct dynamical phases, where purification occurs over a timescale that is exponential vs. constant in system size. We compare our analytic expressions for this microscopic model to results derived from field theories that are expected to capture such measurement-induced phase transitions, and find quantitative agreement between the two.

Abstract: Generative models realized with machine learning techniques are powerful tools to infer complex and unknown data distributions from a finite number of training samples in order to produce new synthetic data. Diffusion models are an emerging framework that have recently overcome the performance of the generative adversarial networks in creating synthetic text and high-quality images. Here, we propose and discuss the quantum generalization of diffusion models, i.e., three quantum-noise-driven generative diffusion models that could be experimentally tested on real quantum systems. The idea is to harness unique quantum features, in particular the non-trivial interplay among coherence, entanglement and noise that the currently available noisy quantum processors do unavoidably suffer from, in order to overcome the main computational burdens of classical diffusion models during inference. Hence, we suggest to exploit quantum noise not as an issue to be detected and solved but instead as a very remarkably beneficial key ingredient to generate much more complex probability distributions that would be difficult or even impossible to express classically, and from which a quantum processor might sample more efficiently than a classical one. Therefore, our results are expected to pave the way for new quantum-inspired or quantum-based generative diffusion algorithms addressing more powerfully classical tasks as data generation/prediction with widespread real-world applications ranging from climate forecasting to neuroscience, from traffic flow analysis to financial forecasting.

Abstract: Quantum systems have historically been formidable to simulate using classical computational methods, particularly as the system size grows. The Heisenberg Model, pivotal in understanding magnetic materials, is a quintessential example where classical simulations face scalability issues. The Variational Quantum Eigensolver (VQE) algorithm is a system composed of a quantum circuit as well as a classical optimizer that can efficiently prepare the Heisenberg ground state by iteratively optimizing the variational parameters. We assess the efficacy and scalability of VQE by preparing the ground states of isotropic and anisotropic Heisenberg models. This paper also aims to provide insights into the precision and time consumption involved in classical and optimized sampling approaches in the calculation of expectation values. In preparing the ground state for the Heisenberg models, this paper paves the way for more efficient quantum algorithms and contributes to the broader field of condensed matter physics.

Abstract: We propose a digital-analog quantum algorithm for simulating the Hubbard-Holstein model, describing strongly-correlated fermion-boson interactions, in a suitable architecture with superconducting circuits. It comprises a linear chain of qubits connected by resonators, emulating electron-electron (e-e) and electron-phonon (e-p) interactions, as well as fermion tunneling. Our approach is adequate for a digital-analog quantum computing (DAQC) of fermion-boson models including those described by the Hubbard-Holstein model. We show the reduction in the circuit depth of the DAQC algorithm, a sequence of digital steps and analog blocks, outperforming the purely digital approach. We exemplify the quantum simulation of a half-filling two-site Hubbard-Holstein model. In such example we obtain fidelities larger than 0.98, showing that our proposal is suitable to study the dynamical behavior of solid-state systems. Our proposal opens the door to computing complex systems for chemistry, materials, and high-energy physics.

Abstract: We show a dissipative phase transition in a driven nonlinear quantum oscillator in which a discrete time-translation symmetry is broken either continuously or discretely. The corresponding regimes display either continuous or discrete time crystals, which we analyze numerically and analytically beyond the classical limit addressing observable dynamics, Liouvillian spectral features, and quantum fluctuations. Via an effective semiclassical description, we show that phase diffusion dominates when the symmetry is broken continuously, which manifests as a band of eigenmodes with a lifetime growing linearly with the mean-field excitation number. Instead, in the discrete symmetry broken phase, the leading fluctuation process corresponds to quantum activation with a single mode that has an exponentially growing lifetime. Interestingly, the transition between these two regimes manifests itself already in the quantum regime as a spectral singularity, namely as an exceptional point mediating between phase diffusion and quantum activation. Finally, we discuss this transition between different time-crystal orders in the context of synchronization phenomena.

Abstract: The task of Multiple Sequence Alignment (MSA) is a constrained combinatorial optimization problem that is generally considered a complex computational problem. In this paper, we first present a binary encoding of MSA and devise a corresponding soft-constrained cost-function that enables a Hamiltonian formulation and implementation of the MSA problem with the variational Quantum Approximate Optimization Algorithm (QAOA). Through theoretical analysis, a bound on the ratio of the number of feasible states to the size of the Hilbert space is determined. Furthermore, we consider a small instance of our QAOA-MSA algorithm in both a quantum simulator and its performance on an actual quantum computer. While the ideal solution to the instance of MSA investigated is shown to be the most probable state sampled for a shallow p<5 quantum circuit in the simulation, the level of noise in current devices is still a formidable challenge for the kind of MSA-QAOA algorithm developed here. In turn, we are not able to distinguish the feasible solutions from other states in the quantum hardware output data at this point. This indicates a need for further investigation into both the strategy utilized for compiling the quantum circuit, but also the possibility of devising a more compact ansatz, as one might achieve through constraint-preserving mixers for QAOA.

Abstract: LiDAR systems that rely on classical signals are susceptible to intercept-and-recent spoofing attacks, where a target attempts to avoid detection. To address this vulnerability, we propose a quantum-secured LiDAR protocol that utilizes Gaussian modulated coherent states for both range determination and spoofing attack detection. By leveraging the Gaussian nature of the signals, the LiDAR system can accurately determine the range of the target through cross-correlation analysis. Additionally, by estimating the excess noise of the LiDAR system, the spoofing attack performed by the target can be detected, as it can introduce additional noise to the signals. We have developed a model for target detection and security check, and conducted numerical simulations to evaluate the Receiver Operating Characteristic (ROC) of the LiDAR system. The results indicate that an intercept-and-recent spoofing attack can be detected with a high probability at a low false-alarm rate. Furthermore, the proposed method can be implemented using currently available technology, highlighting its feasibility and practicality in real-world applications.

Abstract: We consider a quantum Otto cycle with an interacting Bose-Einstein condensate at finite temperature. We present a procedure to evolve this system in time in three spatial dimensions, in which closed (adiabatic) strokes are described by the Gross-Pitaevskii equation, and open (isochoric) strokes are modeled using a stochastic Ginzburg-Landau equation. We analyze the effect on the thermodynamic efficiency of the strength of interactions, the frequency of the harmonic trap, and the temperatures of the reservoirs. The efficiency has little sensitivity to changes in the temperatures, but decreases as interactions increase. However, stronger interactions allow for faster cycles and for substantial increases in power.

Abstract: In multiphon interference processes, the commonly assumed direct link between boson bunching and particle indistinguishability has recently been challenged in Seron $\textit{et al.}$ [Nat. Photon. 17, 702 (2023)]. Exploiting the connection between optical interferometry and matrix permanents, it appeared that bunching effects may surprisingly be enhanced in some interferometers by preparing specific states of partially distinguishable photons. Interestingly, all the states giving rise to such an anomalous bunching were found to be $\textit{far from}$ the state of perfectly indistinguishable particles, raising the question of whether this intriguing phenomenon might even exist for $\textit{nearly indistinguishable}$ particles. Here, we answer positively this physically motivated question by exploiting some mathematical conjecture on matrix permanents, whose physical interpretation had not yet been unveiled. Using a recently found counterexample to this conjecture, we demonstrate that there is an optical set-up involving 8~photons in 10~modes for which the probability that all photons bunch into two output modes can be enhanced by applying a suitable perturbation to the polarization states starting from photons with the same polarization. We also find out that the perturbation that decreases the bunching probability the most is not the one that takes the perfectly indistinguishable state towards a fully distinguishable state, as could naively be expected.