Quantum identity authentication (QIA) has emerged as a crucial technology for secure communication systems, particularly in the burgeoning era of quantum communications. This paper proposes a novel QIA protocol based on non-classical characteristics of squeezed light fields. By exploiting quantum noise reduction properties of quadrature squeezed coherent states, the protocol fundamentally thwarts eavesdropping attempts by Heisenberg-limited uncertainty constraints. The fidelity parameter for decoy states is utilized to detect spoofing attacks, and the dynamic key update mechanism fundamentally eliminates vulnerabilities caused by key reuse. Security information ratio analysis shows that the protocol is able to resist Gaussian-cloner attacks and detect eavesdropping. Moreover, the security threshold can be further enhanced with higher squeezing, allowing tunable protection levels adaptable to different threat scenarios. Compared with binary-squeezed protocols, our proposed four-direction (quaternary-dimensional) squeezing halves the eavesdropper's guessing probability and enlarges the fidelity gap by 29
In this paper, we examine thermodynamically driven dissipative processes that lead to an active thermodynamic equilibrium system. These processes are modeled using a quantum collision framework, in which the dissipative contribution is explicitly derived via jump operators. The system under consideration involves either a single qubit or two qubits. In both cases, the system under consideration undergoes repeated interactions with a composed environment of a set of independent ancillas. Hence, by performing a truncated series expansion of the unitary operator, we derive an effective master equation that captures the dissipative effects. Then, our study explores the relationship between quantum speed limit time and various thermodynamic and geometric quantities, particularly in the context of quantum battery charging. The results are interpreted physically by highlighting the impact of repeated interactions on the system's behavior and its evolution toward a stationary regime characterized by active thermodynamic equilibrium.
Large surface-electrode ion traps with multiple trapping regions and junctions are a natural approach to scaling trapped ion quantum computers, supporting the connectivity and ion counts necessary for complex quantum algorithms. However, a major hurdle in this scaling is on-chip power dissipation from the applied RF voltage, which increases at a rate between linear and cubic relative to trap size, depending on whether the losses are dielectric or Ohmic. Here, we present two versions of a trap with features designed to reduce both types of RF power dissipation. The first variant contains a raised RF electrode that increases the electrode-ground distance to reduce capacitance. Different DC voltage sources are demonstrated on this trap to show that technical noise before the filter remains the dominant source of voltage noise and therefore motional heating. The second variant additionally includes a method for removing dielectric from beneath the RF electrode to further reduce dielectric losses. These traps were demonstrated at room temperature with Ca-40(+) ions. The similar heating rates and heating rate axial frequency dependencies between 2.4 and 3.0 MHz illustrate that this dielectric modification is not detrimental to trap performance.
This perspective paper explores quantum-safe networks as the convergence of technology innovation and regulatory frameworks. With cryptographically relevant quantum computers potentially arriving within a decade, organizations face immediate risks from harvest-now-decrypt-later attacks. The paper presents a dual-technology approach combining Quantum Key Distribution and Post-Quantum Cryptography, analyzes global regulatory timelines converging on 2030-2035 migration deadlines, and provides concrete use cases across finance, government, healthcare, telecommunications, and critical infrastructure sectors.
We explore an array of quantum emitters as non-equilibrium probes, coupled to a one-dimensional photonic waveguide, aiming to estimate its properties such as wave number which encodes the waveguide's frequency and dispersive characteristics. By considering transient dynamics following initial excitation, we show that the quantum Fisher information (QFI) can be significantly enhanced through careful emitter positioning. For two-emitter probes, optimal spacing stabilizes populations and coherences in the single-excitation subspace, suppressing superradiant decay and extending both the magnitude and longevity of QFI. Randomized emitter configurations also reveal that vanishing waveguide-mediated cross decay maximizes both achievable sensitivity and the temporal duration over which information about the parameter remains accessible. Extending to multipartite probes, we demonstrate that the maximum QFI and its temporal integral scale with system size, exceeding the Heisenberg limit for all positioning strategies. Our results highlight the potential of waveguide-coupled emitter arrays as versatile quantum sensors, where collective radiative dynamics can be harnessed to achieve tunable, long-lived, and enhanced precision.
This article presents a comprehensive analysis of two classes of quantum radars, including quantum direct-detection and quantum-entangled noise radars. In the first case, inspired by the well-established concept of single-photon LiDARs, we investigated the performance of single-photon radars, in which state-of-the-art single microwave-photon detectors are employed to enhance the detection sensitivity and enable the detection of weaker signals. We derived analytical expressions for the maximum detection range of both classes of quantum radars in terms of the Lambert W function, by considering all relevant system, target, and environmental parameters. Our formulation facilitates direct comparison of noise radars with direct-detection radars and suggests that a quantum-entangled noise radar can be regarded as an enhanced direct-detection radar with an effective threshold signal-to-noise ratio. Furthermore, we applied this framework to classical-correlated noise radars and defined the parameter range enhancement factor (REF) to quantify the superiority of quantum-entangled noise radars over their classical counterparts. Moreover, we introduced a rule-of-thumb for approximating the REF. We also examined the influence of limitations imposed by various microwave detection technologies. Our analysis shows that the conventional antennas limit the potential benefits of quantum-entangled noise radar systems. We also demonstrated that the optimal detection method for these radars is a microwave detector based on a quantum transducer combined with a single optical-photon detector. We showed that, with the current technology, implementing a quantum-entangled noise radar with the maximum detection range on the order of few kilometers is possible. Finally, we explored the potential applications of quantum-entangled noise radars.
Optical nanofibers provide a way of coupling quantum information in cold atoms across large distances, however, this coupling requires atoms to reside close to the nanofiber surface. Atoms can be trapped close to the surface using a two-color dipole trap. Here we present our experimental realization of a two-color dipole trap. We optimize the number of trapped atoms using a machine learning algorithm and measure the optical density via the transmission. We estimate the number of atoms in the trap to be approximately 1400 and the lifetime of the atoms in the trap to be 28 ms. Machine-learning optimization improved the on-resonance optical depth from 0.5 in the initial optimization stage to optical depths exceeding 15.
Space geodesy has a great interest in real-time observations of the rotational motion of the Earth. Apart from the rotation rate, this includes the orientation of the rotation axis, usually referred to as the polar motion. Large ring lasers and passive gyroscopes, both have a resonant traveling wave cavity in common, and this cavity solely defines the rotation sensing ability. In this paper, we examine and compare the advantages and disadvantages of the active and the passive operation. Apart from some similarities, each technique suffers from a different set of limitations, and it is not yet clear which approach will eventually go further. (c) 2026 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
We investigate the fluorescence dynamics of the rare-earth ions europium, terbium, and gadolinium, with particular emphasis on quantifying non-Markovian behavior. By employing fluorescence as a probe, we characterize deviations from memoryless dynamics and identify clear distinctions between Markovian and non-Markovian regimes. Our analysis demonstrates how these profiles manifest in optical spectroscopy, providing direct insight into system-environment interactions. Beyond their fundamental implications, these insights may support the rational design of rare-earth-doped materials for applications in multicolor phosphors, hybrid optoelectronic architectures, and emerging quantum sensing technologies.
What defines the operational boundary between quantum information and classical magnetism? We present a model-independent methodology for detecting characteristic scales in quantum systems through generalized susceptibility analysis chi(sigma)=|d < O >/d sigma|, where sigma represents observation scales across spatial, temporal, and decoherence dimensions. Through comprehensive experiments on a Rigetti Ankaa-3 quantum processor, we identify an operational threshold at gamma(c)=0.6737 +/- 0.036 under tested noise profiles, exhibiting exceptional peak clarity kappa=8.58-the sharpest signal observed across all phenomena. This pronounced transition, validated through bootstrap analysis and multiple susceptibility metrics, suggests critical-like behavior in the quantum-to-classical crossover, though we carefully refrain from claiming a thermodynamic phase transition. The framework successfully extracts characteristic scales without prior theoretical knowledge: correlation length xi=8.00 qubits, distinct ordering timescales for ferromagnetic ( t(c)=0.36) versus antiferromagnetic ( t(c)=0.91) systems, and the quantum critical field h(c)=1.821 in the transverse-field Ising model. Robustness analysis confirms stability across smoothing parameters, methods, and metric definitions. Beyond providing actionable guidance for noisy intermediate-scale quantum-era quantum computing, our findings suggest that magnetic correlations exhibit characteristic transitions at specific decoherence scales-an operational perspective connecting quantum information theory and condensed matter physics. While framing this as methodological advance rather than fundamental physics, the identification of critical-like information-to-physics transitions provides practical diagnostics for quantum device characterization and optimization.
Advances in quantum computing algorithms and hardware are unlocking novel solutions to numerous classically intractable problems in the physical and computational sciences. In the context of chemical screening of precursors for etch processes in integrated circuit fabrication, it is shown in this work that two critical simulation tasks-(1) generating high-accuracy ab initio chemistry data, and (2) training molecular dynamics potentials-can both be reliably performed using present-day hybrid quantum-classical approaches, namely, variational quantum eigensolvers (VQEs) and variational quantum learning models (VQLMs). First, an adaptive-VQE approach is employed to demonstrate the accuracy of quantum algorithms for bond dissociation curves and to provide a heuristic demonstration of computational scaling behavior relative to brute-force classical methods. Next, a VQLM is trained to develop a quantum machine learning-based interatomic potential to probe the chemical influence of F atoms on the dissociation of the Si-Si bond, a well-studied and highly important reaction motif in etch chemistry. It is then shown that the VQLM-following appropriate hyperparameter optimization-achieves comparable performance with the underlying ab initio training data. Through this work, we illustrate how quantum computing approaches may provide valuable tools for research and development in the semiconductor fabrication industry as the technology matures.
Microplastics are a serious threat to human health and the environment, mainly because of their persistence and entry into the food chain through marine life. The weathering of these particles, caused by prolonged exposure to UV radiation and heat, accelerates chemical changes that can harm ecosystems and human health and make them hard to identify. Therefore, it is important to accurately identify and classify microplastics to assess their impact and creating efficient mitigation measures. This study includes quantum machine learning together with traditional deep learning methods, such as autoencoders, and statistical approaches like principal component analysis and linear discriminant analysis, to classify Raman spectra of different microplastic samples. The model proposed classifies microplastics into weathered and standard samples with an accuracy of 94%, distinguishing between distinct types of plastics, such as polyvinyl chloride, polyethylene terephthalate, polypropylene, polyethylene, and polyamide at 98.5% accuracy. In order to further improve this research forward, the model was run on live quantum computing hardware using Amazon Braket services. The end-to-end pipeline was run on both Braket's SV1 state vector simulator and the IonQ Aria quantum hardware, utilizing the compute resources of AWS's quantum environment. The model recorded a performance level of 97%-98% in the focused tasks, establishing the applicability of embedding quantum computing into practical applications. By improving the precision of microplastic identification, this study adds to the better understanding of their environmental impact and aids wider efforts toward reducing related ecological risks.
We propose a method for extracting the phase from atom interference fringes based on orthogonal subspace projection. By projecting the shear interference fringes from an atom interferometer into an orthogonal subspace, this method characterizes and removes the atomic ensemble envelope, thereby isolating the interference phase information. We systematically investigate the phase extraction accuracy of this method under various conditions, including different atomic ensemble envelope shapes and fringe contrasts, and apply it to analyze experimental data from two practical atom interferometers. The study demonstrates that, compared to the conventional direct model fitting method, our approach more accurately extracts the interference phase under conditions involving nonideal and dynamically varying atomic ensemble envelopes as well as low-contrast fringes, thereby improving the accuracy and robustness of the atom interferometer. This makes it particularly valuable for application-oriented atom shear interferometers operating in complex environments.
Quantum Process Tomography (QPT) is a fundamental technique to characterize quantum operations. However, its precision gets hampered while running in real quantum hardware due to inherent noise. In our study, we propose a post-processing method using principal component analysis (PCA) to improve the fidelity of noisy gates. We first implemented the standard QPT on various gates ranging from single-qubit to three-qubit in simulation under depolarizing error scenarios and on Fake IBM_Brisbane and ran single and two-qubit gates (H, CX, and SQSCZ) on real quantum hardware (IBM_Brisbane); the three-qubit CCX is evaluated in simulation only. After that, the reconstructed Choi matrix is decomposed into real and imaginary components. Then, by applying a PCA-based approach, we show steady improvements in a variety of quantitative performance indicators in addition to process fidelity while also maintaining the physical constraints of the Choi matrix. Additionally, PCA performed better or similarly when compared to CVX-based maximum-likelihood reconstruction and linear inversion. Although PCA improves QPT reconstructions, it is unable to address the fundamental scalability issue of QPT since it cannot overcome the exponential scaling with qubit number.
Topological properties of solid-state materials arise when crossings occur in their band-structure eigenvalues, which give rise to discontinuities in the associated Bloch-function eigenvectors once these are mapped over the whole Brillouin zone. These nonanalytic properties have direct consequences on the spatial decay of the corresponding Wannier functions, leading to what is nowadays referred to as the "obstruction to finding symmetric Wannier functions" for a given set of bands, as well as on the need for shifting the Wannier functions to interstitial positions, related to what is nowadays known as the "bulk-boundary correspondence." The importance of nonanalytic points of Bloch eigenfunctions and their consequences for the spatial decay of Wannier functions were historically anticipated back in 1978 [G. Strinati, Phys. Rev. B 18, 4104-4119 (1978)], somewhat before the work of Berry on what came to be referred to as the "Berry phase" [M. V. Berry, Proc. R. Soc. London, Ser. A 392, 45 (1984)]. In particular, the former paper identified key precursors and physical insights that are now understood, in hindsight, to be closely related to the later developments mentioned above. Here, we recap the essential features of these key issues in a rather pedagogical way, by considering in full details two instructing examples for which the origin of the discontinuities in the eigenvectors can be readily traced and mapped out, and the rate of the spatial falloff of the associated Wannier functions can be fully determined. For this analysis to be as complete as possible, two cases, one for noninteracting and one for interacting fermions, are considered on equal footing.
We present an asymptotic approach toward the standard Landau-Zener problem based on two linearly independent elementary waves of constant amplitude but time-dependent phase. The two contributions to this phase are quadratic and logarithmic in time and result from the linear chirp of the energies and the lowest order correction in the coupling between the two levels in the long-time limit. Indeed, our solutions, subjected to initial conditions at a large but finite time in the past, are valid for large negative and large positive times. Due to their asymptotic nature, they are not valid in the neighborhood of the moment when the levels cross. However, as the starting point of the dynamics moves further into the past, the time interval of the break-down of our asymptotic solutions shrinks and vanishes in the limit of the infinite past, which corresponds to the standard Landau-Zener situation. Our approach explains not only every feature of the exact solution but yields deeper insight into the origin of the effects. In particular, it (i) brings to light the subtleties involved in the asymptotic limit leading to the standard expressions for the Landau-Zener transition amplitudes, (ii) identifies the logarithmic phase as the origin of the exponential transition probability amplitude, and (iii) reveals the structure of the lowest order corrections to the Landau-Zener result when the starting point is not in the infinite past.
Matter-wave interferometry has become a ubiquitous and reliable tool for studying fundamental forces and phenomena and for realizing sensitive measurements. Our recent experiments with metal clusters have allowed us to demonstrate the quantum-wave nature of nanoparticles exceeding 170 kDa. Interestingly, the same experiments also allow for the preparation of moir & eacute; fringes of objects in the megadalton range. In this work, we demonstrate such moir & eacute; fringes of large sodium nanoparticles and, owing to the platform's stability, resolve nanometer-scale fringe displacements between successive contrast revivals, directly observing the predicted pi-phase flip as a half-period shift. We further discuss how this feature turns the interferometer into a device for advanced sensing, even when operating in the regime where the predictions of quantum and classical physics merge.
We show how the dynamics of a specific subset of states can be separated from the dynamic of the total quantum state via a time-dependent projector-based formalism of adiabatic elimination. Within our formalism, we assume an explicit time dependency in the coupling between both subsystems. Additionally, we do not assume that the elements of the Hamiltonian commute, as in matter-wave optics, this is not given in general. Here, the center-of-mass degrees of freedom frequently need to be taken into account. Assuming non-commutativity also enables the application of this formalism to matrices of arbitrary dimension and the treatment of the adiabatic elimination in high dimensional systems, where the elimination may be needed to reduce the overall complexity. In particular, we apply our formalism to typical mechanisms in matter-wave optics, Raman, and Bragg diffraction.
This study examines a quantum sensor consisting of two qubits modeled in an XXZ Heisenberg spin chain under a homogeneous magnetic field, for use in quantum thermometry and magnetometry. The sensor is subjected to a common classical environment driven by static noise and is in thermal equilibrium with a heat bath. We analyze the impact of spin-spin, Dzyaloshinskii-Moriya, and Kaplan-Shekhtman-Entin-Wohlman-Aharony interactions, as well as the static noise characterized by the disorder parameter, on the sensor's time-evolved state. We also assess the influence of magnetic field homogeneity on performance. Employing quantum Fisher information criteria, we determine the sensor's metrological precision. The performance of the proposed sensor in estimating the external magnetic field and temperature in weak and strong field regimes is different over time with temperature variations. In the strong magnetic field regime, static noise reduces the sensitivity of quantum sensing, while in the weak field regime, this effect is negligible. Our sensor achieves optimal sensitivity and precision for temperature and magnetic field estimation in the presence of static noise and in the weak magnetic field and low temperature regime. Finally, we demonstrate that the quantum sensor achieves a stable sensitivity and precision in its performance over time in quantum magnetometry and thermometry, which can be very valuable in quantum sensing. Moreover, we propose some experimental platforms for the realization of our quantum sensor.
