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Quantum-enhanced parameter estimation is critical in various fields, including distributed sensing. In this study, we focus on estimating multiple unknown phases at different spatial nodes using multiphoton polarization-entangled states. Previous research has relied on a much weaker Cram\'er-Rao bound rather than precise bounds from exact quantum Fisher information matrices. We present exact results for the distributed sensing. We find that, due to its singular nature, direct use of the quantum Fisher information matrix is not possible. We analyze the reasons for this singularity, which has prevented the determination of quantum Cram\'er-Rao bounds. We demonstrate that not all phases in distributed sensing with multiphoton entangled states are independent. We obtain non-singular matrices by identifying and removing the redundant phase from the calculation. This allows us to derive exact quantum Cram\'er-Rao bounds, which we verify are saturated by projective measurements. These bounds enable Heisenberg-limited sensing for the average phase. Our analysis is specifically applicable to N-photon GHZ states distributed across multiple nodes. This advancement is significant as it paves the way for more precise and efficient distributed sensing, enhancing the overall capabilities of quantum sensing technologies based on N photon GHZ states., Comment: 8 pages, 2 figures

The rise of generative AI presents new opportunities for the understanding and practice of self-care through its capability to generate varied content, including self-care suggestions via text and images, and engage in dialogue with users over time. However, there are also concerns about accuracy and trustworthiness of self-care advice provided via AI. This paper reports our findings from workshops, diaries, and interviews with five researchers and 24 participants to explore their experiences and use of generative AI for self-care. We analyze our findings to present a framework for the use of generative AI to support five types of self-care, - advice seeking, mentorship, resource creation, social simulation, and therapeutic self-expression - mapped across two dimensions - expertise and modality. We discuss how these practices shift the role of technologies for self-care from merely offering information to offering personalized advice and supporting creativity for reflection, and we offer suggestions for using the framework to investigate new self-care designs., Comment: 28 pages, 4 figures, to be published in the proceedings of the ACM Designing Interactive Systems Conference (DIS '24)

Absorption and gain processes are fundamental to any light-matter interaction and a precise measurement of these parameters is important for various scientific and technological applications. Quantum probes, specifically the squeezed states have proved very successful, particularly in the applications that deal with phase shift and force measurements. In this paper, we focus on improving the sensitivity of the estimation of the photon loss coefficient of a weakly absorbing medium as well as the estimation of the gain parameter using a two-mode bright squeezed state. The generation of this state combines the advantage of a coherent beam for its large photon number with the quantum properties of the two-mode squeezing operation in an optical parametric amplifier. We present two measurement schemes: balanced photodetection and time-reversed metrology, both utilizing two-mode bright squeezed light. The maximum quantum advantage we can achieve using two-mode bright squeezed light is 3.7 times for the absorption parameter $\alpha = 0.05$ and 8.4 times for $\alpha = 0.01$ as compared to using only the coherent state. Similarly, the maximum quantum advantage for the estimation of optical gain is found around 2.81 times for the gain coefficient $G=1.05$ and around 6.28 times for $G=1.01$. We discuss the significance of using one measurement scheme over the other under different squeezing conditions. We compare our results with the Cram\'er-Rao bound for a two-mode bright squeezed state to assess the quality of the proposed methodologies., Comment: 9 pages, 4 figures

We prove the existence of topological solutions to the self-dual Chern-Simons model and the Abelian Higgs system on the lattice graphs Z^n for n>1. This extends the results in Huang, Lin and Yau [HLY20] from finite graphs to lattice graphs.

Particle Identification (PID) plays a central role in associating the energy depositions in calorimeter cells with the type of primary particle in a particle flow oriented detector system. In this paper, we propose novel PID methods based on the Residual Network (ResNet) architecture which enable the training of very deep networks, bypass the need to reconstruct feature variables, and ensure the generalization ability among various geometries of detectors, to classify electromagnetic showers and hadronic showers. Using Geant4 simulation samples with energy ranging from 5 GeV to 120 GeV, the efficacy of Residual Connections is validated and the performance of our model is compared with Boosted Decision Trees (BDT) and other pioneering Artificial Neural Network (ANN) approaches. In shower classification, we observe an improvement in background rejection over a wide range of high signal efficiency ($> 95\%$). These findings highlight the prospects of ANN with Residual Blocks for imaging detectors in the PID task of particle physics experiments.

Quantum estimation of parameters defining open-system dynamics may be enhanced by using ancillas that are entangled with the probe but are not submitted to the dynamics. Here we consider the important problem of estimation of transmission of light by a sample, with losses due to absorption and scattering. We show, through the determination of the quantum Fisher information, that the ancilla strategy leads to the best possible precision in single-mode estimation, the one obtained for a Fock state input, through joint photon-counting of probe and ancilla, which are modes of a bimodal squeezed state produced by an optical parametric amplifier. This proposal overcomes the challenge of producing and detecting high photon-number Fock states, and it is quite robust against additional noise: we show that it is immune to phase noise and the precision does not change if the incoming state gets disentangled. Furthermore, the quantum gain is still present under moderate photon losses of the input beams. We also discuss an alternative to joint photon counting, which is readily implementable with present technology, and approaches the quantum Fisher information result for weak absorption, even with moderate photons losses of the input beams before the sample is probed: a time-reversal procedure, placing the sample between two optical parametric amplifiers, with the second undoing the squeezing produced by the first one. The precision of estimation of the loss parameter is obtained from the average outgoing total photon number and its variance. In both procedures, the state of the probe and the detection procedure are independent of the value of the parameter., Comment: 14 pages, 7 figures

We introduce the the fractional Laplacian on a subgraph of a graph with Dirichlet boundary condition. For a lattice graph, we prove the upper and lower estimates for the sum of the first $k$ Dirichlet eigenvalues of the fractional Laplacian, extending the classical results by Li-Yau and Kr\"{o}ger.

Quantum frequency up-conversion is a cutting-edge technique that leverages the interaction between photons and quantum systems to shift the frequency of single photons from a lower frequency to a higher frequency. If the photon before up-conversion was one of the entangled pair, then it is important to understand how much entanglement is preserved after up-conversion. In this study, we present a theoretical analysis of the transformation of the time-dependent second-order quantum correlations in photon pairs and find the preservation of such correlations under fairly general conditions. We also analyze the two-photon Hong-Ou-Mandel interference between the frequency-converted idler photon and the signal photon. The visibility of the two-photon interference is sensitive to the magnitude of the frequency conversion, and it improves when the frequency separation between two photons goes down.

We demonstrate how the Hong-Ou-Mandel (HOM) interference with polarization-entangled photons can be used to probe ultrafast dephasing. We can infer the optical properties like the real and imaginary parts of the complex susceptibility of the medium from changes in the position and the shape of the HOM dip. From the shift of the HOM dip, we are able to measure 22 fs dephasing time using a continuous-wave (CW) laser even with optical loss > 97%, while the HOM dip visibility is maintained at 92.3~\% (which can be as high as 96.7%). The experimental observations, which are explained in terms of a rigorous theoretical model, demonstrate the utility of HOM interference in probing ultrafast dephasing., Comment: 12 pages, 7 figures

In order to perform machine learning among multiple parties while protecting the privacy of raw data, privacy-preserving machine learning based on secure multi-party computation (MPL for short) has been a hot spot in recent. The configuration of MPL usually follows the peer-to-peer architecture, where each party has the same chance to reveal the output result. However, typical business scenarios often follow a hierarchical architecture where a powerful, usually privileged party, leads the tasks of machine learning. Only the privileged party can reveal the final model even if other assistant parties collude with each other. It is even required to avoid the abort of machine learning to ensure the scheduled deadlines and/or save used computing resources when part of assistant parties drop out. Motivated by the above scenarios, we propose pMPL, a robust MPL framework with a privileged part}. pMPL supports three-party training in the semi-honest setting. By setting alternate shares for the privileged party, pMPL is robust to tolerate one of the rest two parties dropping out during the training. With the above settings, we design a series of efficient protocols based on vector space secret sharing for pMPL to bridge the gap between vector space secret sharing and machine learning. Finally, the experimental results show that the performance of pMPL is promising when we compare it with the state-of-the-art MPL frameworks. Especially, in the LAN setting, pMPL is around $16\times$ and $5\times$ faster than TF-encrypted (with ABY3 as the back-end framework) for the linear regression, and logistic regression, respectively. Besides, the accuracy of trained models of linear regression, logistic regression, and BP neural networks can reach around 97%, 99%, and 96% on MNIST dataset respectively., Comment: This paper is the full version of a paper to appear in CCS 2022

This paper presents a visual SLAM system that uses both points and lines for robust camera localization, and simultaneously performs a piece-wise planar reconstruction (PPR) of the environment to provide a structural map in real-time. One of the biggest challenges in parallel tracking and mapping with a monocular camera is to keep the scale consistent when reconstructing the geometric primitives. This further introduces difficulties in graph optimization of the bundle adjustment (BA) step. We solve these problems by proposing several run-time optimizations on the reconstructed lines and planes. Our system is able to run with depth and stereo sensors in addition to the monocular setting. Our proposed SLAM tightly incorporates the semantic and geometric features to boost both frontend pose tracking and backend map optimization. We evaluate our system exhaustively on various datasets, and show that we outperform state-of-the-art methods in terms of trajectory precision. The code of PLP-SLAM has been made available in open-source for the research community (https://github.com/PeterFWS/Structure-PLP-SLAM)., Comment: Accepted to ICRA 2023, supplementary materials attached, code open-source: https://github.com/PeterFWS/Structure-PLP-SLAM

Circular dichroism (CD) is a widely used technique for investigating optically chiral molecules, especially for biomolecules. It is thus of great importance that these parameters be estimated precisely so that the molecules with desired functionalities can be designed. In order to surpass the limits of classical measurements, we need to probe the system with quantum light. We develop quantum Fisher information matrix (QFIM) for precision estimates of the circular dichroism and the optical rotary dispersion for a variety of input quantum states of light. The Cramer-Rao bounds, for all four chirality parameters are obtained, from QFIM for (a) single photon input states with a specific linear polarization and for (b) NOON states having two photons with both either left polarized or right polarized. The QFIM bounds, using quantum light, are compared with bounds obtained for classical light beams i.e., beams in coherent states. Quite generally, both the single photon state and the NOON state exhibit superior precision in the estimation of absorption and phase shift in relation to a coherent source of comparable intensity, especially in the weak absorption regime. In particular, the NOON state naturally offers the best precision among the three. We compare QFIM bounds with the error sensitivity bounds, as the latter are relatively easier to measure whereas the QFIM bounds require full state tomography. We also outline an empirical scheme for estimating the measurement sensitivities by projective measurements with single-photon detectors.