arXiv subjects

Zihao Li

Publications and source records attributed to Zihao Li.

At least 253 records · Page 14Linked to original sources

arXiv2021

Minimum number of experimental settings required to verify bipartite pure states and unitaries

Efficient verification of quantum states and gates is crucial to the development of quantum technologies. Although the sample complexities of quantum state verification and quantum gate verification have been studied by many researchers, the number of experimental settings has received little attention and is poorly understood. In this work we study systematically quantum state verification and quantum gate verification with a focus on the number of experimental settings. We show that any bipartite pure state can be verified by only two measurement settings based on local projective measurements. Any bipartite unitary in dimension $d$ can be verified by $2d$ experimental settings based on local operations. In addition, we introduce the concept of entanglement-free verification and clarify its connection with minimal-setting verification. Finally, we show that any two-qubit unitary can be verified with at most five experimental settings; moreover, a generic two-qubit unitary (except for a set of measure zero) can be verified by an entanglement-free protocol based on four settings. In the course of study we clarify the properties of Schmidt coefficients of two-qubit unitaries, which are of independent interest.

quant-ph↗

arXiv2021

Optimal Verification of the Bell State and Greenberger-Horne-Zeilinger States in Untrusted Quantum Networks

Bipartite and multipartite entangled states are basic ingredients for constructing quantum networks and their accurate verification is crucial to the functioning of the networks, especially for untrusted networks. Here we propose a simple approach for verifying the Bell state in an untrusted quantum network in which one party is not honest. Only local projective measurements are required for the honest party. It turns out each verification protocol is tied to a probability distribution on the Bloch sphere and its performance has an intuitive geometric meaning. This geometric picture enables us to construct the optimal and simplest verification protocols, which are also very useful to detecting entanglement in the untrusted network. Moreover, we show that our verification protocols can achieve almost the same sample efficiencies as protocols tailored to standard quantum state verification. Furthermore, we establish an intimate connection between the verification of Greenberger-Horne-Zeilinger states and the verification of the Bell state. By virtue of this connection we construct the optimal protocol for verifying Greenberger-Horne-Zeilinger states and for detecting genuine multipartite entanglement.

quant-ph↗

arXiv2021

The mass-metallicity relation at cosmic noon in overdense environments: first results from the MAMMOTH-Grism HST slitless spectroscopic survey

The MAMMOTH-Grism slitless spectroscopic survey is a Hubble Space Telescope (HST) cycle-28 medium program, which is obtaining 45 orbits of WFC3/IR grism spectroscopy in the density peak regions of three massive galaxy protoclusters at $z=2-3$ discovered using the MAMMOTH technique. We introduce this survey by presenting the first measurement of the mass-metallicity relation (MZR) at high redshift in overdense environments via grism spectroscopy. From the completed MAMMOTH-Grism observations in the field of the BOSS1244 protocluster at $z=2.24\pm0.02$, We secure a sample of 36 protocluster member galaxies at $z\sim2.24$, showing strong nebular emission lines ([O III], H$β$ and [O II]) in their G141 spectra. Using the multi-wavelength broad-band deep imaging from HST and ground-based telescopes, we measure their stellar masses in the range of $[10^{9},10^{10.4}]M_\odot$, instantaneous star formation rates (SFR) from 10 to 240$M_\odot yr^{-1}$, and global gas-phase metallicities [$\frac{1}{3}$,1] of solar. Compared with similarly selected field galaxy sample at the same redshift, our galaxies show on average increased SFRs by $\sim$0.06dex and $\sim$0.18dex at $\sim$10$^{10.1}M_\odot$ and $\sim$10$^{9.8}M_\odot$, respectively. Using the stacked spectra of our sample galaxies, we derive the MZR in the BOSS1244 protocluster core as $12+\log({\rm O/H})=(0.136\pm0.018)\times\log(M_\ast/M_\odot)+(7.082\pm0.175)$, showing significantly shallower slope than that in the field. This shallow MZR slope is likely caused by the combined effects of efficient recycling of feedback-driven winds and cold-mode gas accretion in protocluster environments. The former effect helps low-mass galaxies residing in overdensities retain their metal production, whereas the latter effect dilutes the metal content of high-mass galaxies, making them more metal poor than their coeval field counterparts.

astro-ph.GA↗

arXiv2021

Variable Augmented Network for Invertible Modality Synthesis-Fusion

As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinical applications such as disease diagnosis and treatment planning. In this paper, an invertible and variable augmented network (iVAN) is proposed for medical image synthesis and fusion. In iVAN, the channel number of the network input and output is the same through variable augmentation technology, and data relevance is enhanced, which is conducive to the generation of characterization information. Meanwhile, the invertible network is used to achieve the bidirectional inference processes. Due to the invertible and variable augmentation schemes, iVAN can not only be applied to the mappings of multi-input to one-output and multi-input to multi-output, but also be applied to one-input to multi-output. Experimental results demonstrated that the proposed method can obtain competitive or superior performance in comparison to representative medical image synthesis and fusion methods.

eess.IV↗

arXiv2021

Experimental Masking of Real Quantum States

Masking of quantum information is a way of hiding information in correlations such that no information is accessible to any local observer. Although the set of all quantum states as a whole cannot be masked into bipartite correlations according to the no-masking theorem, the set of real states is maskable and is a maximal maskable set. In this work, we experimentally realize a masking protocol of the real ququart by virtue of a photonic quantum walk. Our experiment clearly demonstrates that quantum information of the real ququart can be completely hidden in bipartite correlations of two-qubit hybrid entangled states, which are encoded in two different degrees of freedom of a single photon. The hidden information is not accessible from each qubit alone, but can be faithfully retrieved with a fidelity of about 99% from correlation measurements. By contrast, any superset of the set of real density matrices cannot be masked.

quant-ph↗

arXiv2021

Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss

The Stackelberg prediction game (SPG) has been extensively used to model the interactions between the learner and data provider in the training process of various machine learning algorithms. Particularly, SPGs played prominent roles in cybersecurity applications, such as intrusion detection, banking fraud detection, spam filtering, and malware detection. Often formulated as NP-hard bi-level optimization problems, it is generally computationally intractable to find global solutions to SPGs. As an interesting progress in this area, a special class of SPGs with the least squares loss (SPG-LS) have recently been shown polynomially solvable by a bisection method. However, in each iteration of this method, a semidefinite program (SDP) needs to be solved. The resulted high computational costs prevent its applications for large-scale problems. In contrast, we propose a novel approach that reformulates a SPG-LS as a single SDP of a similar form and the same dimension as those solved in the bisection method. Our SDP reformulation is, evidenced by our numerical experiments, orders of magnitude faster than the existing bisection method. We further show that the obtained SDP can be reduced to a second order cone program (SOCP). This allows us to provide real-time response to large-scale SPG-LS problems. Numerical results on both synthetic and real world datasets indicate that the proposed SOCP method is up to 20,000+ times faster than the state of the art.

math.OC↗

arXiv2021

Improved Lyman Alpha Tomography using Optimized Reconstruction with Constraints on Absorption (ORCA)

In this work, we propose an improved approach to reconstruct the three-dimensional intergalactic medium from observed Lyman-$α$ forest absorption features. We present our new method, the Optimized Reconstruction with Constraints on Absorption (ORCA), which outperforms the current baseline Wiener Filter (WF) when tested on mock Lyman Alpha forest data generated from hydrodynamical simulations. We find that both reconstructed flux errors and cosmic web classification improve substantially with ORCA, equivalent to 30-40\% additional sight-lines with the standard WF. We use this method to identify and classify extremal objects, i.e. voids and (proto)-clusters, and find improved reconstruction across all summary statistics explored. We apply ORCA to existing Lyman Alpha forest data from the COSMOS Lyman Alpha Mapping and Tomography Observations (CLAMATO) Survey and compare it to the WF reconstruction.

astro-ph.GA↗

arXiv2021

Verification of phased Dicke states

Dicke states are typical examples of quantum states with genuine multipartite entanglement. They are valuable resources in many quantum information processing tasks, including multiparty quantum communication and quantum metrology. Phased Dicke states are a generalization of Dicke states and include antisymmetric basis states as a special example. These states are useful in atomic and molecular physics besides quantum information processing. Here we propose practical and efficient protocols based on adaptive local projective measurements for verifying all phased Dicke states, including $W$ states and qudit Dicke states. To verify any $n$-partite phased Dicke state within infidelity $ε$ and significance level $δ$, the number of tests required is only $O(nε^{-1}\lnδ^{-1})$, which is linear in $n$ and is exponentially more efficient than traditional tomographic approaches. In the case of $W$ states, the number of tests can be further reduced to $O(\sqrt{n}\,ε^{-1}\lnδ^{-1})$. Moreover, we construct an optimal protocol for any antisymmetric basis state; the number of tests required decreases (rather than increases) monotonically with $n$. This is the only optimal protocol known for multipartite nonstabilizer states.

quant-ph↗

arXiv2021

Fair Division of Mixed Divisible and Indivisible Goods

We study the problem of fair division when the resources contain both divisible and indivisible goods. Classic fairness notions such as envy-freeness (EF) and envy-freeness up to one good (EF1) cannot be directly applied to the mixed goods setting. In this work, we propose a new fairness notion envy-freeness for mixed goods (EFM), which is a direct generalization of both EF and EF1 to the mixed goods setting. We prove that an EFM allocation always exists for any number of agents. We also propose efficient algorithms to compute an EFM allocation for two agents and for $n$ agents with piecewise linear valuations over the divisible goods. Finally, we relax the envy-free requirement, instead asking for $ε$-envy-freeness for mixed goods ($ε$-EFM), and present an algorithm that finds an $ε$-EFM allocation in time polynomial in the number of agents, the number of indivisible goods, and $1/ε$.

cs.GT↗

arXiv2021

Interaction between optical pulse and tumor using finite element analysis

Photoacoustic imaging is an emerging technology based on the photoacoustic effect that has developed rapidly in recent years. It combines the high contrast of optical imaging and the high penetration and high resolution of acoustic imaging. As a non-destructive biological tissue imaging technology, photoacoustic imaging has important application value in the field of biomedicine. With its high efficiency bi-oimaging capabilities and excellent biosafety performance, it has been favored by researchers. The visualization of photoacoustic imaging has great research signifi-cance in the early diagnosis of some diseases, especially tumors. In photoacoustic imaging, light transmission and thermal effects are important processes. This article is based on COMSOL software and uses finite element analysis to construct a physi-cal model for simulation. Through laser pulses into the stomach tissue containing tumor, the physical process of light transmission and biological heat transfer was studied, and a photothermal model composed of two physical fields was built, and finally a series of visualization graphics were obtained. This work has certain theo-retical guiding significance for further promoting the application of photoacoustic imaging in the field of biomedicine.

physics.bio-ph↗

arXiv2020

Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices

Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D context modeling is of great significance for developing automated lesion detection algorithms. In this work, we propose a Modified Pseudo-3D Feature Pyramid Network (MP3D FPN) that leverages depthwise separable convolutional filters and a group transform module (GTM) to efficiently extract 3D context enhanced 2D features for universal lesion detection in CT slices. To facilitate faster convergence, a novel 3D network pre-training method is derived using solely large-scale 2D object detection dataset in the natural image domain. We demonstrate that with the novel pre-training method, the proposed MP3D FPN achieves state-of-the-art detection performance on the DeepLesion dataset (3.48% absolute improvement in the sensitivity of FPs@0.5), significantly surpassing the baseline method by up to 6.06% (in MAP@0.5) which adopts 2D convolution for 3D context modeling. Moreover, the proposed 3D pre-trained weights can potentially be used to boost the performance of other 3D medical image analysis tasks.

cs.CV↗

arXiv2020

An Adaptive Gas Cost Mechanism for Ethereum to Defend Against Under-Priced DoS Attacks

The gas mechanism in Ethereum charges the execution of every operation to ensure that smart contracts running in EVM (Ethereum Virtual Machine) will be eventually terminated. Failing to properly set the gas costs of EVM operations allows attackers to launch DoS attacks on Ethereum. Although Ethereum recently adjusted the gas costs of EVM operations to defend against known DoS attacks, it remains unknown whether the new setting is proper and how to configure it to defend against unknown DoS attacks. In this paper, we make the first step to address this challenging issue by first proposing an emulation-based framework to automatically measure the resource consumptions of EVM operations. The results reveal that Ethereum's new setting is still not proper. Moreover, we obtain an insight that there may always exist exploitable under-priced operations if the cost is fixed. Hence, we propose a novel gas cost mechanism, which dynamically adjusts the costs of EVM operations according to the number of executions, to thwart DoS attacks. This method punishes the operations that are executed much more frequently than before and lead to high gas costs. To make our solution flexible and secure and avoid frequent update of Ethereum client, we design a special smart contract that collaborates with the updated EVM for dynamic parameter adjustment. Experimental results demonstrate that our method can effectively thwart both known and unknown DoS attacks with flexible parameter settings. Moreover, our method only introduces negligible additional gas consumption for benign users.

cs.CR↗

arXiv2020

Optimal Verification of Greenberger-Horne-Zeilinger States

We construct optimal protocols for verifying qubit and qudit GHZ states using local projective measurements. When the local dimension is a prime, an optimal protocol is constructed from Pauli measurements only. Our protocols provide a highly efficient way for estimating the fidelity and certifying genuine multipartite entanglement. In particular, they enable the certification of genuine multipartite entanglement using only one test when the local dimension is sufficiently large. By virtue of adaptive local projective measurements, we then construct protocols for verifying GHZ-like states that are optimal over all protocols based on one-way communication. The efficiency can be improved further if additional communications are allowed. Finally, we construct optimal protocols for verifying GHZ states and nearly optimal protocols for GHZ-like states in the adversarial scenario.

quant-ph↗

arXiv2019

MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection

Universal lesion detection (ULD) on computed tomography (CT) images is an important but underdeveloped problem. Recently, deep learning-based approaches have been proposed for ULD, aiming to learn representative features from annotated CT data. However, the hunger for data of deep learning models and the scarcity of medical annotation hinders these approaches to advance further. In this paper, we propose to incorporate domain knowledge in clinical practice into the model design of universal lesion detectors. Specifically, as radiologists tend to inspect multiple windows for an accurate diagnosis, we explicitly model this process and propose a multi-view feature pyramid network (FPN), where multi-view features are extracted from images rendered with varied window widths and window levels; to effectively combine this multi-view information, we further propose a position-aware attention module. With the proposed model design, the data-hunger problem is relieved as the learning task is made easier with the correctly induced clinical practice prior. We show promising results with the proposed model, achieving an absolute gain of $\mathbf{5.65\%}$ (in the sensitivity of FPs@4.0) over the previous state-of-the-art on the NIH DeepLesion dataset.

cs.CV↗

arXiv2019

Efficient verification of bipartite pure states

We propose practical and efficient protocols for verifying bipartite pure states for any finite dimension, which can also be applied to fidelity estimation. Our protocols are based on adaptive local projective measurements with either one-way or two-way communications, which are very easy to implement in practice. They can extract the key information much more efficiently than known protocols based on tomography or direct fidelity estimation, and their efficiencies are comparable to the best protocols based on entangling measurements. These protocols highlight the significance of mutually unbiased bases (MUBs) and complex projective 2-designs in quantum state verification and fidelity estimation. Moreover, our protocols can be applied to the adversarial scenario, in which states are controlled by a malicious adversary. In this case, surprisingly, one of our protocols based on local measurements is even optimal among protocols without locality restriction.

quant-ph↗

arXiv2019

Implicit Progressive-Iterative Approximation for Curve and Surface Reconstruction

Implicit curve and surface reconstruction attracts the attention of many researchers and gains a wide range of applications, due to its ability to describe objects with complicated geometry and topology. However, extra zero-level sets or spurious sheets arise in the reconstruction process makes the reconstruction result challenging to be interpreted and damage the final result. In this paper, we proposed an implicit curve and surface reconstruction method based on the progressive-iterative approximation method, named implicit progressive-iterative approximation (I-PIA). The proposed method elegantly eliminates the spurious sheets naturally without requiring any explicit minimization procedure, thus reducing the computational cost greatly and providing high-quality reconstruction results. Numerical examples are provided to demonstrate the efficiency and effectiveness of the proposed method.

math.NA↗

arXiv2019

Implementation of generalized measurements on a qudit via quantum walks

Quantum measurements play a fundamental role in quantum mechanics and quantum information processing, but it is not easy to implement generalized measurements, the most powerful measurements allowed by quantum mechanics. Here we propose a simple recipe for implementing generalized measurements on a qudit via quantum walks. With this recipe, any discrete quantum measurement can be implemented via a one-dimensional discrete quantum walk; the number of steps is only two times the number of measurement outcomes. As an illustration, we present a unified solution for implementing arbitrary symmetric informationally complete measurements in dimension 3.

quant-ph↗

arXiv2017

A Distributed Power Routing Method between Regional Markets based on Bellman-Ford Algorithm

With the deregulation of power industry, large power users can buy electricity directly from power producers. For trades between different regional markets, it is necessary to research on the method to find the cheapest route for power exchanging. Moreover, as there exists no coordinator above regional markets, the power routing problem must be solved in a distributed way. Most previous research are based on power electronic transformers. Some research proposed EMS of sub-networks as energy routers, but failed to consider the power flow constraints or did not converge in some specific cases. Our method is based on the EMS of multiple markets, which saves cost by eliminating expensive electronic transformers and has high efficiency in systems with numerous nodes by considering the regional markets as generalized nodes. We take transmission costs and congestion costs into consideration, and uses Bellman-Ford algorithm to determine the cheapest route for power transmission between different regional markets and make convergence analysis about our algorithm. This method proves effective and convergent when there is no loop among the markets. A four-market loop-free case was used to illustrate the efficiency of the method.

math.OC↗