arXiv subjects

Maximilian Reichert

Publications and source records attributed to Maximilian Reichert.

8 recordsLinked to original sources

arXiv2026

Quantum Barankin bounds beyond local unbiasedness: Analytic results for Gaussian states via a right-division framework

We propose a quantum version of the Barankin bound as an alternative to the quantum Cramér-Rao bound for quantum parameter estimation. The quantum Barankin bound provides a lower bound on the mean squared error of estimators satisfying arbitrarily chosen bias constraints at arbitrarily chosen parameter points. In particular, unbiasedness over the entire parameter space can be imposed, yielding precision limits for globally unbiased quantum parameter estimation. In contrast to the recently derived quantum Barankin bound, which is based on a symmetric division superoperator, our bound is based on a nonsymmetric right-division superoperator. This formulation enables us to find analytic expressions for the Barankin matrix for Gaussian states, which allows for an efficient calculation of the bound. We demonstrate the usefulness of our results by applying them to various examples that exhibit the threshold effect in the few-shot regime, which is invisible to the standard quantum Cramér-Rao bound approach.

quant-ph↗

arXiv2026

Resource-optimal quantum mode parameter estimation with multimode Gaussian states

Quantum mode parameter estimation determines parameters governing the shape of electromagnetic modes occupied by a quantum state of radiation. Canonical examples, time delays and frequency shifts, underpin radar, lidar, and optical clocks. A comprehensive framework recently established that broad families of quantum states can attain the Heisenberg limit, surpassing any classical strategy. This raises a fundamental question: among all quantum-enhanced strategies, which is truly optimal? Answering this requires identifying physically meaningful resources governing each estimation task, so quantum states can be compared on equal footing. We show these resources are connected to the eigenmode basis of the generator of the relevant mode transformation. For time-shift estimation, whose generator is diagonal in the frequency domain, the pertinent resources are the mean frequency and bandwidth; analogous quantities emerge for other transformations. Our framework unifies two historically separate perspectives: the particle-number aspect and the mode-structure of quantum light, providing a coherent picture of quantum-enhanced sensing with multimode radiation. Within this unified framework, we derive a tight upper bound on the quantum Fisher information for multimode Gaussian states, expressed in terms of these natural resources, and analytically identify the optimal Gaussian states saturating it. These optimal states take a particularly transparent form in the generator eigenbasis, a structural simplicity reflecting the deep connection between the geometry of the mode transformation and the architecture of the optimal probe. We further demonstrate that multimode homodyne detection constitutes the optimal measurement, achieving this bound and completing the end-to-end characterization of optimal quantum metrology strategies for mode parameter estimation.

quant-ph↗

arXiv2025

Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation

We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless scenario, we show that the mean-squared errors of both range and velocity estimations are inversely proportional to the squared number of signal photons, simultaneously attaining the Heisenberg limit. This is achieved by engineering the multi-photon squeezed state of the temporal modes and adopting standard homodyne detection. To assess the robustness of the quantum protocol, we incorporate photon losses and detuning of the homodyne receiver. Our findings reveal a quantum advantage over the best-known classical strategy across a wide range of round-trip transmissivities. Particularly, the quantum advantage is substantial for sufficiently small losses, even when compared to the optimal -- potentially unattainable -- classical performance limit. The quantum advantage also extends to the practical case where quantum engineering is done on top of a strong classical coherent state with watts of power. This, together with the robustness against losses and the feasibility of the measurement with state-of-the-art technology, make the protocol highly promising for near-term implementation.

quant-ph↗

arXiv2023

Quantum Illumination with a Hetero-Homodyne Receiver and Sequential Detection

We propose a hetero-homodyne receiver for quantum illumination (QI) target detection. Unlike prior QI receivers, it uses a cascaded positive operator-valued measurement (POVM) that does not require a quantum interaction between QI's returned radiation and its stored idler. When used without sequential detection its performance matches the 3 dB quantum advantage over optimum classical illumination (CI) that Guha and Erkmen's [Phys. Rev. A 80, 052310 (2009)] phase-conjugate and parametric amplifier receivers enjoy. When used in a sequential detection QI protocol, the hetero-homodyne receiver offers a 9 dB quantum advantage over a conventional CI radar, and a 3 dB advantage over a CI radar with sequential detection. Our work is a significant step forward toward a practical quantum radar for the microwave region, and, more generally, emphasizes the potential offered by cascaded POVMs for quantum radar.

quant-ph↗

arXiv2022

Quantum-enhanced Doppler lidar

We propose a quantum-enhanced lidar system to estimate a target's radial velocity which employs squeezed and frequency entangled signal and idler beams. We compare its performance against a classical protocol using a coherent state with the same pulse duration and energy, showing that quantum resources provide a precision enhancement in the estimation of the velocity of the object. We identify three distinct parameter regimes characterized by the amount of squeezing and frequency entanglement. In two of them, a quantum advantage exceeding the standard quantum limit is achieved assuming no photon losses. Additionally, we show that an optimal measurement to attain these results in the lossless case is frequency-resolved photon counting. Finally, we consider the effect of photon losses for the high-squeezing regime, which leads to a constant factor quantum advantage higher than $3$ dB in the variance of the estimator, given a roundtrip lidar-to-target-to-lidar transmissivity larger than $50\%$.

quant-ph↗

arXiv2022

Propagating Quantum Microwaves: Towards Applications in Communication and Sensing

The field of propagating quantum microwaves has started to receive considerable attention in the past few years. Motivated at first by the lack of an efficient microwave-to-optical platform that could solve the issue of secure communication between remote superconducting chips, current efforts are starting to reach other areas, from quantum communications to sensing. Here, we attempt at giving a state-of-the-art view of the two, pointing at some of the technical and theoretical challenges we need to address, and while providing some novel ideas and directions for future research. Hence, the goal of this paper is to provide a bigger picture, and -- we hope -- to inspire new ideas in quantum communications and sensing: from open-air microwave quantum key distribution to direct detection of dark matter, we expect that the recent efforts and results in quantum microwaves will soon attract a wider audience, not only in the academic community, but also in an industrial environment.

quant-ph↗

arXiv2021

Nonlinear quantum error correction

We introduce a theory of quantum error correction (QEC) for a subclass of states within a larger Hilbert space. In the standard theory of QEC, the set of all encoded states is formed by an arbitrary linear combination of the codewords. However, this can be more general than required for a given quantum protocol which may only traverse a subclass of states within the Hilbert space. Here we propose the concept of nonlinear QEC (NLQEC), where the encoded states are not necessarily a linear combination of codewords. We introduce a sufficiency criterion for NLQEC with respect to the subclass of states. The new criterion gives a more relaxed condition for the formation of a QEC code, such that under the assumption that the states are within the subclass of states, the errors are correctable. This allows us, for instance, to effectively circumvent the no-go theorems regarding optical QEC for Gaussian states and channels, for which we present explicit examples.

quant-ph↗

arXiv2018

Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks

The lethal nature of pancreatic ductal adenocarcinoma (PDAC) calls for early differential diagnosis of pancreatic cysts, which are identified in up to 16% of normal subjects, and some of which may develop into PDAC. Previous computer-aided developments have achieved certain accuracy for classification on segmented cystic lesions in CT. However, pancreatic cysts have a large variation in size and shape, and the precise segmentation of them remains rather challenging, which restricts the computer-aided interpretation of CT images acquired for differential diagnosis. We propose a computer-aided framework for early differential diagnosis of pancreatic cysts without pre-segmenting the lesions using densely-connected convolutional networks (Dense-Net). The Dense-Net learns high-level features from whole abnormal pancreas and builds mappings between medical imaging appearance to different pathological types of pancreatic cysts. To enhance the clinical applicability, we integrate saliency maps in the framework to assist the physicians to understand the decision of the deep learning method. The test on a cohort of 206 patients with 4 pathologically confirmed subtypes of pancreatic cysts has achieved an overall accuracy of 72.8%, which is significantly higher than the baseline accuracy of 48.1%, which strongly supports the clinical potential of our developed method.

cs.CV↗