H. L. Shi - MIT, Kavli Institute for Astrophysics and Space Research

H. L. Shi
Are you H. L. Shi?

Claim your profile, edit publications, add additional information:

Contact Details

H. L. Shi
MIT, Kavli Institute for Astrophysics and Space Research
United States

Pubs By Year

Pub Categories

Physics - Instrumentation and Detectors (13)
Computer Science - Computer Vision and Pattern Recognition (9)
Nuclear Experiment (8)
Physics - Strongly Correlated Electrons (7)
Quantum Physics (7)
Computer Science - Learning (4)
Instrumentation and Methods for Astrophysics (4)
Computer Science - Computation and Language (3)
Physics - Computational Physics (3)
Computer Science - Information Theory (2)
Statistics - Machine Learning (2)
Mathematics - Optimization and Control (2)
Mathematics - Information Theory (2)
Physics - Optics (1)
High Energy Physics - Theory (1)
Mathematics - Numerical Analysis (1)
Physics - Accelerator Physics (1)
Physics - Superconductivity (1)
Physics - Atmospheric and Oceanic Physics (1)
Computer Science - Artificial Intelligence (1)
Nuclear Theory (1)
Physics - Atomic Physics (1)

Publications Authored By H. L. Shi

POLAR is space-borne detector designed for a precise measurement of gamma-ray polarization of the prompt emissions of Gamma-Ray Bursts in the energy range 50 keV - 500 keV. POLAR is a compact Compton polarimeter consisting of 40$\times$ 40 plastic scintillator bars read out by 25 multi-anode PMTs. In May 2015, we performed a series of tests of the POLAR flight model with 100\% polarized x-rays beams at the European Synchrotron Radiation Facility beam-line ID11 aming to study thresholds, crosstalk between channels and responses of POLAR flight model to polarized X-ray beams. Read More

We are experimentally investigating possible violations of standard quantum mechanics predictions in the Gran Sasso underground laboratory in Italy. We test with high precision the Pauli Exclusion Principle and the collapse of the wave function (collapse models). We present our method of searching for possible small violations of the Pauli Exclusion Principle (PEP) for electrons, through the search for anomalous X-ray transitions in copper atoms, produced by fresh electrons (brought inside the copper bar by circulating current) which can have the probability to undergo Pauli-forbidden transition to the 1 s level already occupied by two electrons and we describe the VIP2 (VIolation of PEP) experiment under data taking at the Gran Sasso underground laboratories. Read More

By performing X-rays measurements in the "cosmic silence" of the underground laboratory of Gran Sasso, LNGS-INFN, we test a basic principle of quantum mechanics: the Pauli Exclusion Principle (PEP), for electrons. We present the achieved results of the VIP experiment and the ongoing VIP2 measurement aiming to gain two orders of magnitude improvement in testing PEP. We also use a similar experimental technique to search for radiation (X and gamma) predicted by continuous spontaneous localization models, which aim to solve the "measurement problem". Read More

As a space-borne detector POLAR is designed to conduct hard X-ray polarization measurements of gamma-ray bursts on the statistically significant sample of events and with an unprecedented accuracy. During its development phase a number of tests, calibrations runs and verification measurements were carried out in order to validate instrument functionality and optimize operational parameters. In this article we present results on gain optimization togeter with verification data obtained in the course of broad laboratory and environmental tests. Read More

We are experimentally investigating possible violations of standard quantum mechanics predictions in the Gran Sasso underground laboratory in Italy. We test with high precision the Pauli Exclusion Principle and the collapse of the wave function (collapse models). We present our method of searching for possible small violations of the Pauli Exclusion Principle (PEP) for electrons, through the search for anomalous X-ray transitions in copper atoms. Read More

Saliency computation has become a popular research field for many applications due to the useful information provided by saliency maps. For a saliency map, local relations around the salient regions in multi-channel perspective should be taken into consideration by aiming uniformity on the region of interest as an internal approach. And, irrelevant salient regions have to be avoided as much as possible. Read More

A two-phase Smoothed Particle Hydrodynamics (SPH) model has been developed on the basis of GPUSPH, which is an open-source implementation of the weakly compressible SPH method on graphics processing units, to investigate oil dispersion under breaking waves. By assuming that the multiple phases are immiscible, the two-phase model solves the same set of governing equations for both phases. Density in each phase is preserved by renormalization, and the harmonic mean of viscosities is used in the transition zone. Read More

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. Read More

The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the unlabeled Chinese corpus. Although the computer-generated translations for both English and Chinese corpus are provided in the dataset, these translations contain errors and careless use of them can easily hurt the performance of the built trackers. To address this problem, we propose a multichannel Convolutional Neural Networks (CNN) architecture, in which we treat English and Chinese language as different input channels of one single CNN model. Read More

Previous researches have shown that learning multiple representations for polysemous words can improve the performance of word embeddings on many tasks. However, this leads to another problem. Several vectors of a word may actually point to the same meaning, namely pseudo multi-sense. Read More

Competing inhomogeneous orders are a central feature of correlated electron materials including high-temperature superconductors. The two-dimensional Hubbard model serves as the canonical microscopic physical model. Multiple orders have been proposed in the underdoped ground-state phase diagram, which corresponds to a regime of maximum numerical difficulty. Read More

Gamma-ray polarimetry is a new powerful tool to study the processes responsible for the emission from astrophysical sources and the environments in which this emission takes place. Few successful polarimetric measurements have however been performed thus far in the gamma-ray energy band due to the difficulties involved. POLAR is a dedicated polarimeter designed to perform high precision measurements of the polarization of the emission from gamma-ray burst in the 50-500 keV energy range. Read More

Sparse coding has achieved a great success in various image processing studies. However, there is not any benchmark to measure the sparsity of image patch/group because sparse discriminant conditions cannot keep unchanged. This paper analyzes the sparsity of group based on the strategy of the rank minimization. Read More


China's stock market is the largest emerging market all over the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependence. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic variance ratio test and the generalized spectral test. Read More

We describe the computational ingredients for an approach to treat interacting fermion systems in the presence of pairing fields, based on path-integrals in the space of Hartree-Fock-Bogoliubov (HFB) wave functions. The path-integrals can be evaluated by Monte Carlo, via random walks of HFB wave functions whose orbitals evolve stochastically. The approach combines the advantage of HFB theory in paired fermion systems and many-body quantum Monte Carlo (QMC) techniques. Read More

Person re-identification is challenging due to the large variations of pose, illumination, occlusion and camera view. Owing to these variations, the pedestrian data is distributed as highly-curved manifolds in the feature space, despite the current convolutional neural networks (CNN)'s capability of feature extraction. However, the distribution is unknown, so it is difficult to use the geodesic distance when comparing two samples. Read More

We investigate the role of coherence in the Grover search algorithm by using several typical measures of quantum coherence and quantum correlations. By using the relative entropy of coherence measure, we show that the success probability depends on the depletion of coherence. Explicitly, in the limit case of few searcher items j/N<<1 in large database N>>1, the cost performance about coherence in enhancing the success probability of Grover search is related to the ratio j/N. Read More

This monograph presents a class of algorithms called coordinate descent algorithms for mathematicians, statisticians, and engineers outside the field of optimization. This particular class of algorithms has recently gained popularity due to their effectiveness in solving large-scale optimization problems in machine learning, compressed sensing, image processing, and computational statistics. Coordinate descent algorithms solve optimization problems by successively minimizing along each coordinate or coordinate hyperplane, which is ideal for parallelized and distributed computing. Read More

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem. The constraint involves an input trial wave function which restricts the random walks. Read More

High-resolution pionic-atom x-ray spectroscopy was performed with an x-ray spectrometer based on a 240-pixel array of superconducting transition-edge-sensor (TES) microcalorimeters at the piM1 beam line of the Paul Scherrer Institute. X-rays emitted by pionic carbon via the 4f->3d transition and the parallel 4d->3p transition were observed with a full-width-at-half-maximum energy resolution of 6.8 eV at 6. Read More

Natural language processing, as a data analytics related technology, is used widely in many research areas such as artificial intelligence, human language processing, and translation. At present, due to explosive growth of data, there are many challenges for natural language processing. Hadoop is one of the platforms that can process the large amount of data required for natural language processing. Read More

With the agreement of my coauthors, I Zhangyang Wang would like to withdraw the manuscript "Stacked Approximated Regression Machine: A Simple Deep Learning Approach". Some experimental procedures were not included in the manuscript, which makes a part of important claims not meaningful. In the relevant research, I was solely responsible for carrying out the experiments; the other coauthors joined in the discussions leading to the main algorithm. Read More

We investigate the cluster size convergence of the energy and observables using two forms of density matrix embedding theory (DMET): the original cluster form (CDMET) and a new formulation motivated by the dynamical cluster approximation (DCA-DMET). Both methods are applied to the half-filled one- and two-dimensional Hubbard models using a sign-problem free auxiliary-field quantum Monte Carlo (AFQMC) impurity solver, which allows for the treatment of large impurity clusters of up to 100 sites. While CDMET is more accurate at smaller impurity cluster sizes, DCA- DMET exhibits faster asymptotic convergence towards the thermodynamic limit (TDL). Read More

We address the calculation of dynamical correlation functions for many fermion systems at zero temperature, using the auxiliary-field quantum Monte Carlo method. The two-dimensional Hubbard hamiltonian is used as a model system. Although most of the calculations performed here are for cases where the sign problem is absent, the discussions are kept general for applications to physical problems when the sign problem does arise. Read More

This letter is focused on quantized Compressed Sensing, assuming that Lasso is used for signal estimation. Leveraging recent work, we provide a framework to optimize the quantization function and show that the recovered signal converges to the actual signal at a quadratic rate as a function of the quantization level. We show that when the number of observations is high, this method of quantization gives a significantly better recovery rate than standard Lloyd-Max quantization. Read More

The low-energy strong interaction of antikaons (K-) with nuclei has many facets and rep- resents a lively and challenging research field. It is interconnected to the peculiar role of strangeness, since the strange quark is rather light, but still much heavier than the up and down quarks. Thus, when strangeness is involved one has to deal with spontaneous and explicit symmetry breaking in QCD. Read More

Ground state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3, 0. Read More

The strong interaction of antikaons with nucleons and nuclei in the low-energy regime represents an active research field connected intrinsically with few-body physics. There are important open questions like the question of antikaon nuclear bound states. A unique and rather direct experimental access to the antikaon-nucleon scattering lengths is provided by precision X-ray spectroscopy of transitions in low-lying states of light kaonic atoms like kaonic hydrogen isotopes. Read More

We study both massive and massless particle's geodesic motion in the background of general dimensional AdS-Sol space-time. We find that the massive particles oscillate along the radial direction, while massless particles experience one-time bouncing as they approach the "horizon" line of the soliton. Our results provide a direct way to understand the negative energy/masses leading to the AdS-Sol geometry. Read More

We measured the $K$-series X-rays of the $K^{-}p$ exotic atom in the SIDDHARTA experiment with a gaseous hydrogen target of 1.3 g/l, which is about 15 times the $\rho_{\rm STP}$ of hydrogen gas. At this density, the absolute yields of kaonic X-rays, when a negatively charged kaon stopped inside the target, were determined to be 0. Read More

Video object detection is challenging because objects that are easily detected in one frame may be difficult to detect in another frame within the same clip. Recently, there have been major advances for doing object detection in a single image. These methods typically contain three phases: (i) object proposal generation (ii) object classification and (iii) post-processing. Read More

The recent experimental realization of spin-orbit coupled Fermi gases provides a unique opportunity to study the interplay between strong interaction and SOC in a tunable, disorder-free system. We present here precision ab initio numerical results on the two-dimensional, unpolarized, uniform Fermi gas with attractive interactions and Rashba SOC. Using auxiliary-field quantum Monte Carlo and incorporating recent algorithmic advances, we carry out exact calculations on sufficiently large system sizes to provide accurate results systematically as a function of experimental parameters. Read More

This letter proposes a synthetic aperture radar (SAR) image registration method named Feature-Area Optimization (FAO). First, the traditional area-based optimization model is reconstructed and decomposed into three key but uncertain factors: initialization, slice set and regularization. Next, structural features are extracted by scale invariant feature transform (SIFT) in dual-resolution space (SIFT-DRS), a novel SIFT-Like method dedicated to FAO. Read More

The Pauli Exclusion Principle (PEP) was famously discovered in 1925 by the austrian physicist Wolfgang Pauli. Since then, it underwent several experimental tests. Starting in 2006, the VIP (Violation of the Pauli Principle) experiment looked for 2p to 1s X-ray transitions in copper, where 2 electrons are present in the 1s state before the transition happens. Read More

The Pauli Exclusion Principle (PEP) was introduced by the austrian physicist Wolfgang Pauli in 1925. Since then, several experiments have checked its validity. From 2006 until 2010, the VIP (VIolation of the Pauli Principle) experiment took data at the LNGS underground laboratory to test the PEP. Read More

We present the idea of searching for X-rays as a signature of the mechanism inducing the spontaneous collapse of the wave function. Such a signal is predicted by the continuous spontaneous localization theories, which are solving the "measurement problem" by modifying the Schrodinger equation. We will show some encouraging preliminary results and discuss future plans and strategy. Read More

The VIP (Violation of Pauli exclusion principle) experiment and its follow-up experiment VIP-2 at the Laboratori Nazionali del Gran Sasso (LNGS) search for X-rays from Cu atomic states that are prohibited by the Pauli Exclusion Principle (PEP). The candidate events, if they exist, will originate from the transition of a $2p$ orbit electron to the ground state which is already occupied by two electrons. The present limit on the probability for PEP violation for electron is 4. Read More

A performance evaluation of superconducting transition-edge sensors (TESs) in the environment of a pion beam line at a particle accelerator is presented. Averaged across the 209 functioning sensors in the array, the achieved energy resolution is 5.2 eV FWHM at Co $K_{\alpha}$ (6. Read More

In the exotic atoms where one atomic $1s$ electron is replaced by a $K^{-}$, the strong interaction between the $K^{-}$ and the nucleus introduces an energy shift and broadening of the low-lying kaonic atomic levels which are determined by only the electromagnetic interaction. By performing X-ray spectroscopy for Z=1,2 kaonic atoms, the SIDDHARTA experiment determined with high precision the shift and width for the $1s$ state of $K^{-}p$ and the $2p$ state of kaonic helium-3 and kaonic helium-4. These results provided unique information of the kaon-nucleus interaction in the low energy limit. Read More

We propose two practical non-convex approaches for learning near-isometric, linear embeddings of finite sets of data points. Given a set of training points $\mathcal{X}$, we consider the secant set $S(\mathcal{X})$ that consists of all pairwise difference vectors of $\mathcal{X}$, normalized to lie on the unit sphere. The problem can be formulated as finding a symmetric and positive semi-definite matrix $\boldsymbol{\Psi}$ that preserves the norms of all the vectors in $S(\mathcal{X})$ up to a distortion parameter $\delta$. Read More

The subject of optomechanics involves interactions between optical and mechanical degrees of freedom, and is currently of great interest as an enabler of fundamental investigations in quantum mechanics, as well as a platform for ultrasensitive measurement devices. The majority of optomechanical configurations rely on the exchange of linear momentum between light and matter. We will begin this tutorial with a brief description of such systems. Read More

In this paper, we compare and catalog the performance of various greedy quantized compressed sensing algorithms that reconstruct sparse signals from quantized compressed measurements. We also introduce two new greedy approaches for reconstruction: Quantized Compressed Sampling Matching Pursuit (QCoSaMP) and Adaptive Outlier Pursuit for Quantized Iterative Hard Thresholding (AOP-QIHT). We compare the performance of greedy quantized compressed sensing algorithms for a given bit-depth, sparsity, and noise level. Read More

The AMADEUS experiment deals with the investigation of the low-energy kaon-nuclei hadronic interaction at the DA{\Phi}NE collider at LNF-INFN, which is fundamental to respond longstanding questions in the non-perturbative QCD strangeness sector. The antikaon-nucleon potential is investigated searching for signals from possible bound kaonic clusters, which would open the possibility for the formation of cold dense baryonic matter. The confirmation of this scenario may imply a fundamental role of strangeness in astrophysics. Read More

Gamma Ray Bursts (GRBs) are the strongest explosions in the universe which might be associated with creation of black holes. Magnetic field structure and burst dynamics may influence polarization of the emitted gamma-rays. Precise polarization detection can be an ultimate tool to unveil the true GRB mechanism. Read More

Face alignment, which fits a face model to an image and extracts the semantic meanings of facial pixels, has been an important topic in CV community. However, most algorithms are designed for faces in small to medium poses (below 45 degree), lacking the ability to align faces in large poses up to 90 degree. The challenges are three-fold: Firstly, the commonly used landmark-based face model assumes that all the landmarks are visible and is therefore not suitable for profile views. Read More

Person re-identification aims to re-identify the probe image from a given set of images under different camera views. It is challenging due to large variations of pose, illumination, occlusion and camera view. Since the convolutional neural networks (CNN) have excellent capability of feature extraction, certain deep learning methods have been recently applied in person re-identification. Read More

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, lattice QCD calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied upon to provide definitive answers. Read More

This paper described a measurement of accelerator neutron radiation field at a transport beam line of Beijing-TBF. The experiment place was be selected around a Faraday Cup with a graphite target impacted by electron beam at 2.5GeV. Read More