arXiv subjects

Bo Fu

Publications and source records attributed to Bo Fu.

At least 73 records · Page 4Linked to original sources

arXiv2023

Anomalous Coherence Length of Majorana Zero Modes at Vortices in Superconducting Topological Insulators

The coherence length of two Majorana zero energy modes in a p-wave topological superconductor is inversely proportional to the superconducting order parameter. We studied the finite size effect of the Majorana zero modes at vortices in a topological insulator/superconductor heterostructure in the presence of a vortex and found that the the coherence length of the two zero energy modes at the terminals of a vortex line is independent of superconducting order parameter, and determined by the intrinsic properties of the topological insulator. This anomalous property illustrates that the superconducting topological insulator is topologically distinct, contrary to a $p$-wave topological superconductor.

cond-mat.supr-con↗

arXiv2023

AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images

The survival analysis on histological whole-slide images (WSIs) is one of the most important means to estimate patient prognosis. Although many weakly-supervised deep learning models have been developed for gigapixel WSIs, their potential is generally restricted by classical survival analysis rules and fully-supervised learning requirements. As a result, these models provide patients only with a completely-certain point estimation of time-to-event, and they could only learn from the labeled WSI data currently at a small scale. To tackle these problems, we propose a novel adversarial multiple instance learning (AdvMIL) framework. This framework is based on adversarial time-to-event modeling, and integrates the multiple instance learning (MIL) that is much necessary for WSI representation learning. It is a plug-and-play one, so that most existing MIL-based end-to-end methods can be easily upgraded by applying this framework, gaining the improved abilities of survival distribution estimation and semi-supervised learning. Our extensive experiments show that AdvMIL not only could often bring performance improvement to mainstream WSI survival analysis methods at a relatively low computational cost, but also enables these methods to effectively utilize unlabeled data via semi-supervised learning. Moreover, it is observed that AdvMIL could help improving the robustness of models against patch occlusion and two representative image noises. The proposed AdvMIL framework could promote the research of survival analysis in computational pathology with its novel adversarial MIL paradigm.

eess.IV↗

arXiv2023

DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis

The cancer prognosis on gigapixel Whole-Slide Images (WSIs) has always been a challenging task. To further enhance WSI visual representations, existing methods have explored image pyramids, instead of single-resolution images, in WSIs. In spite of this, they still face two major problems: high computational cost and the unnoticed semantical gap in multi-resolution feature fusion. To tackle these problems, this paper proposes to efficiently exploit WSI pyramids from a new perspective, the dual-stream network with cross-attention (DSCA). Our key idea is to utilize two sub-streams to process the WSI patches with two resolutions, where a square pooling is devised in a high-resolution stream to significantly reduce computational costs, and a cross-attention-based method is proposed to properly handle the fusion of dual-stream features. We validate our DSCA on three publicly-available datasets with a total number of 3,101 WSIs from 1,911 patients. Our experiments and ablation studies verify that (i) the proposed DSCA could outperform existing state-of-the-art methods in cancer prognosis, by an average C-Index improvement of around 4.6%; (ii) our DSCA network is more efficient in computation -- it has more learnable parameters (6.31M vs. 860.18K) but less computational costs (2.51G vs. 4.94G), compared to a typical existing multi-resolution network. (iii) the key components of DSCA, dual-stream and cross-attention, indeed contribute to our model's performance, gaining an average C-Index rise of around 2.0% while maintaining a relatively-small computational load. Our DSCA could serve as an alternative and effective tool for WSI-based cancer prognosis.

eess.IV↗

arXiv2023

Causal Inference with Confounders MNAR under Treatment-independent Missingness Assumption

Causal inference in observational studies can be challenging when confounders are subject to missingness. Generally, the identification of causal effects is not guaranteed even under restrictive parametric model assumptions when confounders are missing not at random. To address this, We propose a general framework to establish the identification of causal effects when confounders are subject to treatment-independent missingness, which means that the missing data mechanism is independent of the treatment, given the outcome and possibly missing confounders. We give special consideration to commonly-used models for continuous and binary outcomes and provide counterexamples when identification fails. For estimation, we provide a weighted estimation equation estimating method for model parameters and purpose three estimators for the average causal effect based on the estimated models. We evaluate the finite-sample performance of the estimators via simulations. We further illustrate the proposed method with real data sets from the National Health and Nutrition Examination Survey.

stat.ME↗

arXiv2022

Robust Task Scheduling for Heterogeneous Robot Teams under Capability Uncertainty

This paper develops a stochastic programming framework for multi-agent systems where task decomposition, assignment, and scheduling problems are simultaneously optimized. The framework can be applied to heterogeneous mobile robot teams with distributed sub-tasks. Examples include pandemic robotic service coordination, explore and rescue, and delivery systems with heterogeneous vehicles. Due to their inherent flexibility and robustness, multi-agent systems are applied in a growing range of real-world problems that involve heterogeneous tasks and uncertain information. Most previous works assume one fixed way to decompose a task into roles that can later be assigned to the agents. This assumption is not valid for a complex task where the roles can vary and multiple decomposition structures exist. Meanwhile, it is unclear how uncertainties in task requirements and agent capabilities can be systematically quantified and optimized under a multi-agent system setting. A representation for complex tasks is proposed: agent capabilities are represented as a vector of random distributions, and task requirements are verified by a generalizable binary function. The conditional value at risk (CVaR) is chosen as a metric in the objective function to generate robust plans. An efficient algorithm is described to solve the model, and the whole framework is evaluated in two different practical test cases: capture-the-flag and robotic service coordination during a pandemic (e.g., COVID-19). Results demonstrate that the framework is generalizable, scalable up to 140 agents and 40 tasks for the example test cases, and provides low-cost plans that ensure a high probability of success.

cs.RO↗

arXiv2022

Learning Task Requirements and Agent Capabilities for Multi-agent Task Allocation

This paper presents a learning framework to estimate an agent capability and task requirement model for multi-agent task allocation. With a set of team configurations and the corresponding task performances as the training data, linear task constraints can be learned to be embedded in many existing optimization-based task allocation frameworks. Comprehensive computational evaluations are conducted to test the scalability and prediction accuracy of the learning framework with a limited number of team configurations and performance pairs. A ROS and Gazebo-based simulation environment is developed to validate the proposed requirements learning and task allocation framework in practical multi-agent exploration and manipulation tasks. Results show that the learning process for scenarios with 40 tasks and 6 types of agents uses around 12 seconds, ending up with prediction errors in the range of 0.5-2%.

cs.RO↗

arXiv2022

On the sample-dependent minimal conductivity in weakly disordered graphene

We present a unified understanding of the experimentally observed minimal dc conductivity in weakly disordered graphene. Firstly, based on linear response theory, we reveal that randomness or disorder inevitably induces momentum dependent corrections to the electron self-energy function, which naturally yields a sample-dependent minimal conductivity. Taking the long-ranged Gaussian and Coulomb potentials as examples, we derive the momentum dependent self-energy function within the Born approximation, and further validate it via numerical simulations using the large-scale Lanczos algorithm. The explicit momentum dependences of the self-energy on the intensity, concentration and range of potential are critically addressed. Therefore, our results provide a reasonable interpretation of the sample-dependent minimal conductivity observed in graphene samples.

cond-mat.mes-hall↗

arXiv2022

Half-Quantized Hall Effect at the Parity-Invariant Fermi Surface

Condensed matter realization of a single Dirac cone of fermions in two dimensions is a long-standing issue. Here we report the discovery of a single gapless Dirac cone of half-quantized Hall conductance in a magnetically-doped topological insulator heterostructure. It demonstrates that the Hall conductance is half-quantized in the unit e^{2}/h when the parity symmetry is invariant near the Fermi surface. The gapless Dirac point is stable and protected by the local parity symmetry and the topologically nontrivial band structure of the topological insulator. The one-half Hall conductance observed in a recent experiment [Mogi et al, Nat. Phys. 18, 390 (2022)] is attributed to the existence of the gapless Dirac cone. The results suggest a condensed matter realization of a topological phase with a one-half topological invariant.

cond-mat.mes-hall↗

arXiv2022

Signature of parity anomaly in the measurement of optical Hall conductivity in quantum anomalous Hall systems

Parity anomaly is a quantum mechanical effect that the parity symmetry in a two-dimensional classical action is failed to be restored in any regularization of the full quantum theory and is characterized by a half-quantized Hall conductivity. Here we propose a scheme to explore the experimental signature from parity anomaly in the measurement of optical Hall conductivity, in which the optical Hall conductivity is nearly half quantized for a proper range of frequency. The behaviors of optical Hall conductivity are studied for several models, which reveal the appearance of half-quantized Hall conductivity in low or high-frequency regimes. The optical Hall conductivity can be extracted from the measurement of Kerr and Faraday rotations and the absorption rate of the circularly polarized light. This proposal provides a practical method to explore the signature of parity anomaly in topological quantum materials.

cond-mat.mes-hall↗

arXiv2022

Fractional Electromagnetic Response in Three-Dimensional Chiral Anomalous Semimetal

The magnetoelectric coupling of electrons in a three-dimensional solid can be effectively described by axion electrodynamics. Here we report the discovery of the fractional magnetoelectric effect in chiral anomalous semimetals of the three-dimensional massless Wilson fermions, which have linear dispersions at the energy crossing point, and break the chiral symmetry at generic momenta. In the presence of electric and magnetic fields, the time-reversal and parity symmetry breaking give rise to the quarter-quantized topological magnetoelectric effect, which is directly related to the winding number 1/2 of the band structure, and is only one half of that for topological insulators. The fractional electromagnetic response can be revealed by the surface Hall conductance and extracted from the measurement of the topological Kerr and Faraday rotation. The transition-metal pentatelluride \mathrm{ZrTe_{5}} with a strain-tunable band gap provides a potential platform to test the effect experimentally.

cond-mat.mes-hall↗

arXiv2022

Quantum Anomalous Semimetals

The topological states of matter and topological materials have been attracting extensive interests as one of the frontier topics in condensed matter physics and materials science since the discovery of quantum Hall effect in 1980s. So far all the topological phases such as quantum Hall effect, quantum spin Hall effect and topological insulators and superconductors are characterized by a nonzero integer or Z and Z2 topological invariant. None is a half-integer or fractional. Here we propose a novel type of semimetals which hosts a single cone of Wilson fermions instead of Dirac fermions. The Wilson fermions possess linear dispersion near the energy crossing point, but breaks the chiral or parity symmetry such that an unpaired Dirac cone can be realized on a lattice. They are not prohibited by the Nielsen-Ninomiya theorem and avoid the fermion doubling problem. We find that the system can be classified by the relative homotopy group, and the topological invariant is a half-integer. We term the unexpected and nontrivial quantum phase as "quantum anomalous semimetal". The topological phase is a synergy of topology of band structure in solid and quantum anomaly in quantum field theory. The work opens the door towards exploring novel states of matter with fractional topological charge.

cond-mat.mes-hall↗

arXiv2022

Half-Quantized Hall Effect and Power Law Decay of Edge Current Distribution

The half-quantized Hall conductance is characteristic of quantum systems with parity anomaly. Here we investigate topological and transport properties of a class of parity anomalous semimetals, in which massive Dirac fermions coexist with massless Dirac fermions in momentum space or real space, and uncovered a distinct bulk-edge correspondence that the half-quantized Hall effect is realized via the bulk massless Dirac fermions while the nontrivial Berry curvature is provided by the massive Dirac fermions. The spatial distribution of the edge current decays away from the boundary in a power law instead of an exponential law in integer quantum Hall effect. We further address physical relevance of parity anomalous semimetal to three-dimensional semi-magnetic topological insulators and two-dimensional photonic crystals.

cond-mat.mes-hall↗

arXiv2022

Simultaneous Human-robot Matching and Routing for Multi-robot Tour Guiding under Time Uncertainty

This work presents a framework for multi-robot tour guidance in a partially known environment with uncertainty, such as a museum. In the proposed centralized multi-robot planner, a simultaneous matching and routing problem (SMRP) is formulated to match the humans with robot guides according to their selected places of interest (POIs) and generate the routes and schedules for the robots according to uncertain spatial and time estimation. A large neighborhood search algorithm is developed to efficiently find sub-optimal low-cost solutions for the SMRP. The scalability and optimality of the multi-robot planner are evaluated computationally under different numbers of humans, robots, and POIs. The largest case tested involves 50 robots, 250 humans, and 50 POIs. Then, a photo-realistic multi-robot simulation platform was developed based on Habitat-AI to verify the tour guiding performance in an uncertain indoor environment. Results demonstrate that the proposed centralized tour planner is scalable, makes a smooth trade-off in the plans under different environmental constraints, and can lead to robust performance with inaccurate uncertainty estimations (within a certain margin).

cs.RO↗

arXiv2022

Tailoring Quadrupole Topological Insulators with Periodic Driving and Disorder

The quadrupole topological insulator (QTI) has attracted intense studies as a prototype of symmetry-protected higher-order topological phases of matter with a quantized quadrupole moment. The realization of QTIs has been reported in various static settings with periodic structures. Here, we theoretically investigate topological phase transitions and establish the QTI phase in a periodically driven system with disorder. In the clean limit, the Floquet QTI phase emerges from a topologically trivial band structure driven by elliptically polarized irradiation. More strikingly, starting from a pure and static system with trivial topology, we unveil an intriguing QTI phase which necessitates the simultaneous presence of disorder and periodic driving. Furthermore, we reveal that particle-hole symmetry is sufficient to protect the QTI. Our work not only establishes a new strategy to design QTIs but also enriches the symmetry-protected mechanism of higher-order topology.

cond-mat.mes-hall↗

arXiv2021

Helical Symmetry Breaking and Quantum Anomaly in Massive Dirac Fermions

Helical symmetry of massive Dirac fermions is broken explicitly in the presence of electric and magnetic fields. Here we present two equations for the divergence of helical and axial-vector currents following the Jackiw-Johnson approach to the anomaly of the neutral axial vector current. We discover the contribution from the helical symmetry breaking is attributed to the occupancy of the two states at the top of the valence band and the bottom of the conduction band. The explicit symmetry breaking fully cancels the anomalous correction from the quantum fluctuation in the band gap. The chiral anomaly can be derived from the helical symmetry breaking. It provides an alternative route to understand the chiral anomaly from the point of view of the helical symmetry breaking. The pertinent physical consequences in condensed matter are the helical magnetic effect which means a charge current circulating at the direction of the magnetic field, and the mass-dependent positive longitudinal magnetoconductivity as a transport signature. The discovery not only reflects anomalous magneto-transport properties of massive Dirac materials but also reveals the close relation between the helical symmetry breaking and the physics of chiral anomaly in quantum field theory and high energy physics.

cond-mat.mes-hall↗

arXiv2021

The Bulk-Hinge Correspondence and Three-Dimensional Quantum Anomalous Hall Effect in Second Order Topological Insulators

The chiral hinge modes are the key feature of a second order topological insulator in three dimensions. Here we propose a quadrupole index in combination of a slab Chern number in the bulk to characterize the flowing pattern of chiral hinge modes along the hinges at the intersection of the surfaces of a sample. We further utilize the topological field theory to demonstrate the correspondent connection of the chiral hinge modes to the quadrupole index and the slab Chern number, and present a picture of three-dimensional quantum anomalous Hall effect as a consequence of chiral hinge modes. The two bulk topological invariants can be measured in electric transport and magneto-optical experiments. In this way we establish the bulk-hinge correspondence in a three-dimensional second order topological insulator.

cond-mat.mes-hall↗

arXiv2020

Dirac Polarons and Resistivity Anomaly in ZrTe5 and HfTe5

Resistivity anomaly, a sharp peak of resistivity at finite temperatures, in the transition-metal pentatellurides ZrTe5 and HfTe5 was observed four decades ago, and more exotic and anomalous behaviors of electric and thermoelectric transport were revealed recent years. Here we present a theory of Dirac polarons, composed by massive Dirac electrons and holes in an encircling cloud of lattice displacements or phonons at finite temperatures. The chemical potential of Dirac polarons sweeps the band gap of the topological band structure by increasing the temperature, leading to the resistivity anomaly. Formation of a nearly neutral state of Dirac polarons accounts for the anomalous behaviors of the electric and thermoelectric resistivity.

cond-mat.mes-hall↗

arXiv2020

Robust localization for planar moving robot in changing environment: A perspective on density of correspondence and depth

Visual localization for planar moving robot is important to various indoor service robotic applications. To handle the textureless areas and frequent human activities in indoor environments, a novel robust visual localization algorithm which leverages dense correspondence and sparse depth for planar moving robot is proposed. The key component is a minimal solution which computes the absolute camera pose with one 3D-2D correspondence and one 2D-2D correspondence. The advantages are obvious in two aspects. First, the robustness is enhanced as the sample set for pose estimation is maximal by utilizing all correspondences with or without depth. Second, no extra effort for dense map construction is required to exploit dense correspondences for handling textureless and repetitive texture scenes. That is meaningful as building a dense map is computational expensive especially in large scale. Moreover, a probabilistic analysis among different solutions is presented and an automatic solution selection mechanism is designed to maximize the success rate by selecting appropriate solutions in different environmental characteristics. Finally, a complete visual localization pipeline considering situations from the perspective of correspondence and depth density is summarized and validated on both simulation and public real-world indoor localization dataset. The code is released on github.

cs.RO↗