arXiv subjects

Khabat Heshami

Publications and source records attributed to Khabat Heshami.

At least 19 recordsLinked to original sources

arXiv2026

Entanglement, loss, and quantumness: When balanced beam splitters are best

Quantum optics routinely uses beam splitters to generate entanglement, including in pioneering experiments conducted by Hanbury-Brown and Twiss and Hong, Ou, and Mandel. The quantum interference at beam splitters lies at the heart of what makes boson sampling hard to emulate by classical computers and is a vital component of quantum computation with light. Yet, despite overwhelming positive evidence, the conjecture that beam splitters with equal reflection and transmission probabilities generate the most entanglement for any state interfered with the vacuum has remained unproven for almost two decades [Asbóth et al., Phys. Rev. Lett. 94, 173602 (2005)]. We prove this conjecture for ubiquitous entanglement monotones including mixed-state generalizations of entanglement entropy and purity by uncovering monotonicity and convexity with respect to photon loss for these monotones. At the same time, we highlight an infinite class of lesser-used monotones for which the conjecture fails. Because beam splitters are so fundamental, our results yield numerous corollaries for quantum optics, including proof of a recent conjecture for the evolution of a measure of quantumness through loss and a more efficient computational strategy for optimizing entanglement generation over linear optics. These results justify the value of seeking mathematical rigour behind commonly accepted facts and the danger of trusting them unconditionally.

quant-ph↗

arXiv2026

Magnetometry with Broadband Microwave Fields in Nitrogen-Vacancy Centers in Diamond

Nitrogen-vacancy (NV) centers in diamond are optically addressable and versatile light-matter interfaces with practical application in magnetic field sensing, offering the ability to operate at room temperature and reach sensitivities below pT/$\sqrt{\mathrm{Hz}}$. We propose an approach to simultaneously probe all of the magnetically sensitive states using a broadband microwave field and demonstrate that it can be used to measure the external DC magnetic field strength with sensitivities on the order of 10~pT/$\sqrt{\mathrm{Hz}}$. We develop tools for analyzing the temporal signatures in the transmitted broadband microwaves to estimate the magnetic field, comparing maximum likelihood estimation based on minimizing the Kullback-Leibler divergence to various neural network models, and both methods independently reach practical sensitivities. These results are achieved without optimizing parameters such as the bandwidth, and shape of the probing microwave field such that further improvements in sensitivity can be envisioned. Our results motivate novel implementations of NV-based magnetic sensors with the potential for vectorial magnetic field detection at 1-10 kHz update rates and improved sensitivities without requiring a bias magnetic field.

cond-mat.mes-hall↗

arXiv2026

Vector Magnetometry with Broadband Microwave Fields in Nitrogen-Vacancy Centers in Diamond

We present a novel method for full vector magnetometry using nitrogen-vacancy (NV) centers. In contrast to conventional optically detected magnetic resonance techniques, our method employs two distinct broadband microwave pulses and measures them after transmission through the NV sensor medium, thus capturing the line splitting of the ground state triplet due to the Zeeman effect. Two orthogonally polarized microwave pulses allow resolving all magnetic field components independently by reading out differently oriented NV centers. Simulated data is analyzed using deep neural networks, whose efficacy we expect to translate very well to experiments. Our method yields sensitivities between $5~\mathrm{pT}/\sqrt{\mathrm{Hz}}$ and $100~\mathrm{pT}/\sqrt{\mathrm{Hz}}$ across different magnetic field vector components, while achieving approximately $\mathrm{nT}$ accuracy at a signal-to-noise (SNR) ratio of $70~\mathrm{dB}$. By being capable of accurately measuring magnetic fields down to $25~\mathrm{μT}$, the need for a bias field beyond Earth's magnetic field is eliminated.

quant-ph↗

arXiv2026

Recurrent Quantum Feature Maps for Reservoir Computing

Reservoir computing promises a fast method for handling large amounts of temporal data. This hinges on constructing a good reservoir--a dynamical system capable of transforming inputs into a high-dimensional representation while remembering properties of earlier data. In this work, we introduce a reservoir based on recurrent quantum feature maps where a fixed quantum circuit is reused to encode both current inputs and a classical feedback signal derived from previous outputs. We evaluate the model on the Mackey-Glass time-series prediction task using our recently introduced CP feature map, and find that it achieves lower mean squared error than standard classical baselines, including echo state networks and multilayer perceptrons, while maintaining compact circuit depth and qubit requirements. We further analyze memory capacity and show that the model effectively retains temporal information, consistent with its forecasting accuracy. Finally, we study the impact of realistic noise and find that performance is robust to several noise channels but remains sensitive to two-qubit gate errors, identifying a key limitation for near-term implementations.

quant-ph↗

arXiv2026

A Resource Efficient Quantum Kernel

Quantum processors may enhance machine learning by mapping high-dimensional data onto quantum systems for processing. Conventional feature maps, for encoding data onto a quantum circuit are currently impractical, as the number of entangling gates scales quadratically with the dimension of the dataset and the number of qubits. In this work, we introduce a quantum feature map designed to handle high-dimensional data with a significantly reduced number of qubits and entangling operations. Our approach preserves essential data characteristics while promoting computational efficiency, as evidenced by extensive experiments on benchmark datasets that demonstrate a marked improvement in both accuracy and resource utilization when using our feature map as a kernel for characterization, as compared to state-of-the-art quantum feature maps. Our noisy simulation results, combined with lower resource requirements, highlight our map's ability to function within the constraints of noisy intermediate-scale quantum devices. Through numerical simulations and small-scale implementation on a superconducting circuit quantum computing platform, we demonstrate that our scheme performs on par or better than a set of classical algorithms for classification. While quantum kernels are typically stymied by exponential concentration, our approach is affected with a slower rate with respect to both the number of qubits and features, which allows practical applications to remain within reach. Our findings herald a promising avenue for the practical implementation of quantum machine learning algorithms on near future quantum computing platforms.

quant-ph↗

arXiv2025

Quantum Wasserstein distance for Gaussian states

Optimal transport between classical probability distributions has been proven useful in areas such as machine learning and random combinatorial optimization. Quantum optimal transport, and the quantum Wasserstein distance as the minimal cost associated with transforming one quantum state to another, is expected to have implications in quantum state discrimination and quantum metrology. In this work, following the formalism introduced in [De Palma, G. and Trevisan, D. Ann. Henri Poincaré, {\bf 22} (2021), 3199-3234] to compute the optimal transport plan between two quantum states, we give a general formula for the Wasserstein distance of order 2 between any two one-mode Gaussian states. We discuss how the Wasserstein distance between classical Gaussian distributions and the quantum Wasserstein distance by De Palma and Trevisan for thermal states can be recovered from our general formula for Gaussian states. This opens the path to directly compare various known distance measures with the Wasserstein distance through their closed-form solutions.

quant-ph↗

arXiv2025

Adaptive Non-Gaussian Quantum State Engineering

Non-Gaussian quantum states of bosons are a key resource in quantum information science with applications ranging from quantum metrology to fault-tolerant quantum computation. Generation of photonic non-Gaussian resource states, such as Schrödinger's cat and Gottesman-Kitaev-Preskill states, is challenging. In this work, we extend on existing passive architectures and explore a broad set of adaptive schemes. Our numerical results demonstrate a consistent improvement in the probability of success and fidelity of generating these non-Gaussian quantum states with equivalent resources. We also explore the effect of loss as the primary limiting factor and observe that adaptive schemes lead to more desirable outcomes in terms of overall probability of success and loss tolerance. Our work offers a versatile framework for non-Gaussian resource state generation with the potential to guide future experimental implementations.

quant-ph↗

arXiv2025

Exact simulation of realistic Gottesman-Kitaev-Preskill cluster states

We describe a method for simulating and characterizing realistic Gottesman-Kitaev-Preskill (GKP) cluster states, rooted in the representation of resource states in terms of sums of Gaussian distributions in phase space. We apply our method to study the generation of single-mode GKP states via cat state breeding, and the formation of multimode GKP cluster states via linear optical circuits and homodyne measurements. We characterize resource states by referring to expectation values of their stabilizers, and witness operators constructed from them. Our method reproduces the results of standard Fock-basis simulations, while being more efficient, and being applicable in a broader parameter space. We also comment on the validity of the heuristic Gaussian random noise (GRN) model, through comparisons with our exact simulations: We find discrepancies in the stabilizer expectation values when homodyne measurement is involved in cluster state preparation, yet we find a close agreement between the two approaches on average.

quant-ph↗

arXiv2025

Investigating the Performance of Adaptive Optics on Different Bases of Spatial Modes in Turbulent Channels

Quantum key distribution (QKD) allows secure key exchange based on the principles of quantum mechanics, with higher-dimensional photonic states offering enhanced channel capacity and resilience to noise. Free-space QKD is crucial for global networks where fibres are impractical, but atmospheric turbulence introduces severe states distortions, particularly for spatial modes. Adaptive optics (AO) provides a pathway to correct these errors, though its effectiveness depends on the encoding basis. Here, we experimentally evaluate a high-speed AO system for orbital angular momentum (OAM) modes, mutually unbiased bases (MUB), and symmetric, informationally complete, positive operator-valued measures (SIC-POVM) up to dimension $d=8$ in a turbulent free-space channel. While OAM states are strongly distorted, their cylindrical symmetry makes them optimally corrected by AO, yielding error rates below QKD security thresholds. MUB and SIC-POVM exhibit greater intrinsic robustness to turbulence but are less precisely corrected, though their performance remains within protocol tolerances. These results establish AO as a key enabler of secure, high-dimensional QKD and highlight the role of basis choice in optimizing resilience and correction.

quant-ph↗

arXiv2025

Unwanted couplings can induce amplification in quantum memories despite negligible apparent noise

Theoretical quantum memory design often involves selectively focusing on certain energy levels to mimic an ideal $Λ$-configuration, a common approach that may unintentionally overlook the impact of neighboring levels or undesired couplings. While this simplification may be justified in certain protocols or platforms, it can significantly distort the achievable memory performance. Through numerical semi-classical analysis, we show that the presence of unwanted energy levels and undesired couplings in an NV-center-based absorptive memory can significantly amplify the signal, resulting in memory efficiencies exceeding unity, a clear indication of unwanted noise at the quantum level. Strikingly, this effect occurs even when the apparent noise i.e., output in the absence of an input field, is negligible. We then generalize our results using semi-analytical estimations to analyze this amplification, and propose a strategy to reduce its effect. Our findings extend to memory platforms beyond NV centers; as an example, we also analyze a cavity-based rubidium memory that experiences the same issue.

quant-ph↗

arXiv2025

Imaging at the quantum limit with convolutional neural networks

Deep neural networks have been shown to achieve exceptional performance for computer vision tasks like image recognition, segmentation, and reconstruction or denoising. Here, we evaluate the ultimate performance limits of deep convolutional neural network models for image reconstruction, by comparing them against the standard quantum limit set by shot-noise and the Heisenberg limit on precision. We train U-Net models on images of natural objects illuminated with coherent states of light, and find that the average mean-squared error of the reconstructions can surpass the standard quantum limit, and in some cases reaches the Heisenberg limit. Further, we train models on well-parameterized images for which we can calculate the quantum Cramér-Rao bound to determine the minimum possible measurable variance of an estimated parameter for a given probe state. We find the mean-squared error of the model predictions reaches these bounds calculated for the parameters, across a variety of parameterized images. These results suggest that deep convolutional neural networks can learn to become the optimal estimators allowed by the laws of physics, performing parameter estimation and image reconstruction at the ultimate possible limits of precision for the case of classical illumination of the object.

cs.LG↗

arXiv2025

High-Dimensional Quantum Key Distribution with Qubit-like States

Quantum key distribution (QKD) protocols most often use two conjugate bases in order to verify the security of the quantum channel. In the majority of protocols, these bases are mutually unbiased to one another, which is to say they are formed from balanced superpositions of the entire set of states in the opposing basis. Here, we introduce a high-dimensional QKD protocol using qubit-like states, referred to as Fourier-qubits (or $\textit{F}$-qubits). In our scheme, each $\textit{F}$-qubit is a superposition of only two computational basis states with a relative phase that can take $d$ distinct values, where $d$ is the dimension of the computational basis. This non-mutually unbiased approach allows us to bound the information leaked to an eavesdropper, maintaining security in high-dimensional quantum systems despite the states' seemingly two-dimensional nature. By simplifying state preparation and measurement, our protocol offers a practical alternative for secure high-dimensional quantum communications. We experimentally demonstrate this protocol for a noisy high-dimensional QKD channel using the orbital angular momentum degree of freedom of light and discuss the potential benefits for encoding in other degrees of freedom.

quant-ph↗

arXiv2025

Metrological Advantages in Seeded and Lossy Nonlinear Interferometers

The quantum Fisher information (QFI) bounds the sensitivity of a quantum measurement, heralding the conditions for quantum advantages when compared with classical strategies. Here, we calculate analytical expressions for the QFI of nonlinear interferometers under lossy conditions and with coherent-state seeding. We normalize the results based on the number of photons going through the sample that induces a phase shift on the incident quantum state, which eliminates some of the previously declared metrological advantages. We analyze the performance of nonlinear interferometers in a variety of geometries and robustness of the quantum advantage with respect to internal and external loss through direct comparison with a linear interferometer. We find the threshold on the internal loss at which the quantum advantage vanishes, specify when and how much coherent-state seeding optimally counters internal loss, and show that a sufficient amount of squeezing confers to the quantum advantages robustness against external loss and inefficient detection.

quant-ph↗

arXiv2025

Equalities and inequalities from entanglement, loss, and beam splitters

Quantum optics bridges esoteric notions of entanglement and superposition with practical applications like metrology and communication. Throughout, there is an interplay between information theoretic concepts such as entropy and physical considerations such as quantum system design, noise, and loss. Therefore, a fundamental result at the heart of these fields has numerous ramifications in development of applications and advancing our understanding of quantum physics. Our recent proof for the entanglement properties of states interfering with the vacuum on a beam splitter led to monotonicity and convexity properties for quantum states undergoing photon loss [Lupu-Gladstein et al., arXiv:2411.03423 (2024)] by breathing life into a decades-old conjecture. In this work, we extend these fundamental properties to measures of similarity between states, provide inequalities for creation and annihilation operators beyond the Cauchy-Schwarz inequality, prove a conjecture [Hertz et al., PRA 110, 012408 (2024)] dictating that nonclassicality through the quadrature coherence scale is uncertifiable beyond a loss of 50%, and place constraints on quasiprobability distributions of all physical states. These ideas can now circulate afresh throughout quantum optics.

quant-ph↗

arXiv2024

Single-Photon Generation: Materials, Techniques, and the Rydberg Exciton Frontier

Due to their quantum nature, single-photon emitters generate individual photons in bursts or streams. They are paramount in emerging quantum technologies such as quantum key distribution, quantum repeaters, and measurement-based quantum computing. Many such systems have been reported in the last three decades, from Rubidium atoms coupled to cavities to semiconductor quantum dots and color centers implanted in waveguides. This review article highlights different material systems with deterministic and controlled single photon generation. We discuss and compare the performance metrics, such as purity and indistinguishability, for these sources and evaluate their potential for different applications. Finally, a new potential single-photon source, based on the Rydberg exciton in solid state metal oxide thin films, is introduced, briefly discussing its promising qualities and advantages in fabricating quantum chips for quantum photonic applications.

quant-ph↗

arXiv2024

Frequency- and dissipation-dependent entanglement advantage in spin-network Quantum Reservoir Computing

We study the performance of an Ising spin network for quantum reservoir computing (QRC) in linear and non-linear memory tasks. We investigate the extent to which quantumness enhances performance by monitoring the behaviour of quantum entanglement, which we quantify by the partial transpose of the density matrix. In the most general case where the effects of dissipation are incorporated, our results indicate that the strength of the entanglement advantage depends on the frequency of the input signal; the benefit of entanglement is greater with more rapidly fluctuating signals, whereas a low-frequency input is better suited to a non-entangled reservoir. This may be understood as a condition for an entanglement advantage to manifest itself: the system's quantum memory must survive for long enough for the temporal structure of the input signal to reveal itself. We also find that quantum entanglement empowers a spin-network quantum reservoir to remember a greater number of temporal features.

quant-ph↗

arXiv2024

Multiphoton interference in a single-spatial-mode quantum walk

Multiphoton interference is crucial to many photonic quantum technologies. In particular, interference forms the basis of optical quantum information processing platforms and can lead to significant computational advantages. It is therefore interesting to study the interference arising from various states of light in large interferometric networks. Here, we implement a quantum walk in a highly stable, low-loss, multiport interferometer with up to 24 ultrafast time bins. This time-bin interferometer comprises a sequence of birefringent crystals which produce pulses separated by 4.3\,ps, all along a single optical axis. Ultrafast Kerr gating in an optical fiber is employed to time-demultiplex the output from the quantum walk. We measure one-, two-, and three-photon interference arising from various input state combinations, including a heralded single-photon state, a thermal state, and an attenuated coherent state at one or more input ports. Our results demonstrate that ultrafast time bins are a promising platform to observe large-scale multiphoton interference.

quant-ph↗

arXiv2024

Quadrature Coherence Scale of Linear Combinations of Gaussian Functions in Phase Space

The quadrature coherence scale (QCS) is a recently introduced measure that was shown to be an efficient witness of nonclassicality. It takes a simple form for pure and Gaussian states, but a general expression for mixed states tends to be prohibitively unwieldy. In this paper, we introduce a method for computing the quadrature coherence scale of quantum states characterized by Wigner functions expressible as linear combinations of Gaussian functions. Notable examples within this framework include cat states, GKP states, and states resulting from Gaussian transformations, measurements, and breeding protocols. In particular, we show that the quadrature coherence scale serves as a valuable tool for examining the scalability of nonclassicality in the presence of loss. Our findings lead us to put forth a conjecture suggesting that, subject to 50% loss or more, all pure states lose any QCS-certifiable nonclassicality. We also consider the quadrature coherence scale as a measure of quality of the output state of the breeding protocol.

quant-ph↗