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Neutron star (NS) has many extreme physical conditions, and one may obtain some important informations about NS via accreting neutron star binary (ANSB) systems. The upcoming Chinese Space Station Telescope (CSST) provides an opportunity to search for a large sample of ANSB candidates. Our goal is to check the completeness of the potential ANSB samples from CSST data. In this paper, we generate some ANSBs and normal binaries under CSST photometric system by binary evolution and binary population synthesis method and use a machine learning method to train a classification model. Although the Precision ($94.56~ \%$) of our machine learning model is as high as before study, the Recall is only about $63.29~ \%$. The Precision/Recall is mainly determined by the mass transfer rate between the NSs and their companions. In addition, we also find that the completeness of ANSB samples from CSST photometric data by the machine learning method also depends on the companion mass and the age of the system. ANSB candidates with low initial mass companion star ($0.1~ {\rm M}_\odot$ to $1~ {\rm M}_\odot$) have a relatively high Precision ($94.94~ \%$) and high Recall ($86.32~ \%$), whereas ANSB candidates with higher initial mass companion star ($1.1~ {\rm M}_\odot$ to $3~ {\rm M}_\odot$) have similar Precision ($93.88~ \%$) and quite low Recall ($42.67~ \%$). Our results indicate that although the machine learning method may obtain a relative pure sample of ANSBs, a completeness correction is necessary for one to obtain a complete sample., Comment: 12 pages, 5 figures

We consider the effects of relaxing the assumption that gravitational waves composing the stochastic gravitational wave background (SGWB) are uncorrelated between frequencies in analyses of the data from Pulsar Timing Arrays (PTAs). While individual monochromatic plane waves are often a good approximation, a background composed of astrophysical sources cannot be monochromatic since an infinite plane wave carries no signal. We consider how relaxing this assumption allows us to extract potential information about modified dispersion relations and other fundamental physics questions, as both the group and phase velocity of waves become relevant. After developing the formalism we carry out simple Gaussian wavepacket examples and then consider more realistic waveforms, such as that from binary inspirals. When the frequency evolves only slowly across the PTA temporal baseline, the monochromatic assumption at an effective mean frequency remains a good approximation and we provide scaling relations that characterize its accuracy., Comment: 30 pages, 6 figures

Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-dependent. Other non-neural unsupervised summarization approaches mostly rely on key sentence extraction, which can lead to information loss. To address these challenges, we propose a lightweight yet effective unsupervised approach called GLIMMER: a Graph and LexIcal features based unsupervised Multi-docuMEnt summaRization approach. It first constructs a sentence graph from the source documents, then automatically identifies semantic clusters by mining low-level features from raw texts, thereby improving intra-cluster correlation and the fluency of generated sentences. Finally, it summarizes clusters into natural sentences. Experiments conducted on Multi-News, Multi-XScience and DUC-2004 demonstrate that our approach outperforms existing unsupervised approaches. Furthermore, it surpasses state-of-the-art pre-trained multi-document summarization models (e.g. PEGASUS and PRIMERA) under zero-shot settings in terms of ROUGE scores. Additionally, human evaluations indicate that summaries generated by GLIMMER achieve high readability and informativeness scores. Our code is available at https://github.com/Oswald1997/GLIMMER., Comment: 19 pages, 7 figures. Accepted by ECAI 2024

Recent breakthroughs have ushered the quantum network into a new era, where quantum information can be stored, transferred, and processed across multiple nodes on a metropolitan scale. A key challenge in this new era is enhancing the capabilities of individual nodes, providing precise and robust control over multiple qubits and advanced functionality for scalable quantum networks. Here, we report on precise and complex control in a hybrid quantum node based on a diamond color center. We demonstrate hybrid coherent control by entangling three types of qubits: an electron spin as an interface qubit, a nuclear spin with long memory time, and a flying photonic qubit, with their qubit frequencies spanning three distinct regimes from the optical domain to the rf domain. By incorporating two additional memory qubits, we encode three memory qubits into a logical state using the three-qubit repetition code and entangle this logical qubit with a photonic qubit. Leveraging hybrid qubits and precise control, we repeatedly read out the error syndromes of memory qubits through the electron spin, serving as an auxiliary qubit, then apply a real-time feedback operation to correct bit-flip errors. We execute and verify active error correction for up to twelve rounds and demonstrate the improvement over the uncorrected counterpart. Our results demonstrate the feasibility of several key functionalities for next-generation quantum repeaters, paving the way towards full-fledged metropolitan-scale quantum networks for a wide range of practical applications., Comment: 8 pages, 3 figures

The impressive performance of Large Language Models (LLMs) across various natural language processing tasks comes at the cost of vast computational resources and storage requirements. One-shot pruning techniques offer a way to alleviate these burdens by removing redundant weights without the need for retraining. Yet, the massive scale of LLMs often forces current pruning approaches to rely on heuristics instead of optimization-based techniques, potentially resulting in suboptimal compression. In this paper, we introduce ALPS, an optimization-based framework that tackles the pruning problem using the operator splitting technique and a preconditioned conjugate gradient-based post-processing step. Our approach incorporates novel techniques to accelerate and theoretically guarantee convergence while leveraging vectorization and GPU parallelism for efficiency. ALPS substantially outperforms state-of-the-art methods in terms of the pruning objective and perplexity reduction, particularly for highly sparse models. On the OPT-30B model with 70% sparsity, ALPS achieves a 13% reduction in test perplexity on the WikiText dataset and a 19% improvement in zero-shot benchmark performance compared to existing methods.

The origin of intermediate helium (He)-rich hot subdwarfs are still unclear. Previous studies have suggested that some surviving Type Ia supernovae (SNe Ia) companions from the white dwarf~+~main-sequence (WD+MS) channel may contribute to the intermediate He-rich hot subdwarfs. However, previous studies ignored the impact of atomic diffusion on the post-explosion evolution of surviving companion stars of SNe Ia, leading to that they could not explain the observed surface He abundance of intermediate He-rich hot subdwarfs. In this work, by taking the atomic diffusion and stellar wind into account, we trace the surviving companions of SNe Ia from the WD+MS channel using the one-dimensional stellar evolution code \textsc{MESA} until they evolve into hot subdwarfs. We find that the surface He-abundances of our surviving companion models during their core He-burning phases are in a range of $-1 \lesssim {\rm log}(N_{\rm He}/N_{\rm H}) \lesssim 0$, which are consistent with those observed in intermediate He-rich hot subdwarfs. This seems to further support that surviving companions of SNe Ia in the WD+MS channel are possible to form some intermediate He-rich hot subdwarfs., Comment: 10 pages, 5 figures

The increasing computational demands of modern neural networks present deployment challenges on resource-constrained devices. Network pruning offers a solution to reduce model size and computational cost while maintaining performance. However, most current pruning methods focus primarily on improving sparsity by reducing the number of nonzero parameters, often neglecting other deployment costs such as inference time, which are closely related to the number of floating-point operations (FLOPs). In this paper, we propose FALCON, a novel combinatorial-optimization-based framework for network pruning that jointly takes into account model accuracy (fidelity), FLOPs, and sparsity constraints. A main building block of our approach is an integer linear program (ILP) that simultaneously handles FLOP and sparsity constraints. We present a novel algorithm to approximately solve the ILP. We propose a novel first-order method for our optimization framework which makes use of our ILP solver. Using problem structure (e.g., the low-rank structure of approx. Hessian), we can address instances with millions of parameters. Our experiments demonstrate that FALCON achieves superior accuracy compared to other pruning approaches within a fixed FLOP budget. For instance, for ResNet50 with 20% of the total FLOPs retained, our approach improves the accuracy by 48% relative to state-of-the-art. Furthermore, in gradual pruning settings with re-training between pruning steps, our framework outperforms existing pruning methods, emphasizing the significance of incorporating both FLOP and sparsity constraints for effective network pruning.

Structured pruning is a promising approach for reducing the inference costs of large vision and language models. By removing carefully chosen structures, e.g., neurons or attention heads, the improvements from this approach can be realized on standard deep learning hardware. In this work, we focus on structured pruning in the one-shot (post-training) setting, which does not require model retraining after pruning. We propose a novel combinatorial optimization framework for this problem, based on a layer-wise reconstruction objective and a careful reformulation that allows for scalable optimization. Moreover, we design a new local combinatorial optimization algorithm, which exploits low-rank updates for efficient local search. Our framework is time and memory-efficient and considerably improves upon state-of-the-art one-shot methods on vision models (e.g., ResNet50, MobileNet) and language models (e.g., OPT-1.3B -- OPT-30B). For language models, e.g., OPT-2.7B, OSSCAR can lead to $125\times$ lower test perplexity on WikiText with $2\times$ inference time speedup in comparison to the state-of-the-art ZipLM approach. Our framework is also $6\times$ -- $8\times$ faster. Notably, our work considers models with tens of billions of parameters, which is up to $100\times$ larger than what has been previously considered in the structured pruning literature.

Human pose analysis has garnered significant attention within both the research community and practical applications, owing to its expanding array of uses, including gaming, video surveillance, sports performance analysis, and human-computer interactions, among others. The advent of deep learning has significantly improved the accuracy of pose capture, making pose-based applications increasingly practical. This paper presents a comprehensive survey of pose-based applications utilizing deep learning, encompassing pose estimation, pose tracking, and action recognition.Pose estimation involves the determination of human joint positions from images or image sequences. Pose tracking is an emerging research direction aimed at generating consistent human pose trajectories over time. Action recognition, on the other hand, targets the identification of action types using pose estimation or tracking data. These three tasks are intricately interconnected, with the latter often reliant on the former. In this survey, we comprehensively review related works, spanning from single-person pose estimation to multi-person pose estimation, from 2D pose estimation to 3D pose estimation, from single image to video, from mining temporal context gradually to pose tracking, and lastly from tracking to pose-based action recognition. As a survey centered on the application of deep learning to pose analysis, we explicitly discuss both the strengths and limitations of existing techniques. Notably, we emphasize methodologies for integrating these three tasks into a unified framework within video sequences. Additionally, we explore the challenges involved and outline potential directions for future research., Comment: 47 pages

Astrometry holds the potential for testing fundamental physics through the effects of the Stochastic Gravitational Wave Background (SGWB) in the $\sim 1-100$ nHz frequency band on precision measurements of stellar positions. Such measurements are complementary to tests made possible by the detection of the SGWB using Pulsar Timing Arrays. Here, the feasibility of using astrometry for the identification of parity-violating signals within the SGWB is investigated. This is achieved by defining and quantifying a non-vanishing $EB$ correlation function within astrometric correlation functions, and investigating how one might estimate the detectability of such signals., Comment: Match the published version, adding references. 8 pages, 2 figures

This paper proposes a new task in the field of Answering Subjective Induction Question on Products (SUBJPQA). The answer to this kind of question is non-unique, but can be interpreted from many perspectives. For example, the answer to 'whether the phone is heavy' has a variety of different viewpoints. A satisfied answer should be able to summarize these subjective opinions from multiple sources and provide objective knowledge, such as the weight of a phone. That is quite different from the traditional QA task, in which the answer to a factoid question is unique and can be found from a single data source. To address this new task, we propose a three-steps method. We first retrieve all answer-related clues from multiple knowledge sources on facts and opinions. The implicit commonsense facts are also collected to supplement the necessary but missing contexts. We then capture their relevance with the questions by interactive attention. Next, we design a reinforcement-based summarizer to aggregate all these knowledgeable clues. Based on a template-controlled decoder, we can output a comprehensive and multi-perspective answer. Due to the lack of a relevant evaluated benchmark set for the new task, we construct a large-scale dataset, named SupQA, consisting of 48,352 samples across 15 product domains. Evaluation results show the effectiveness of our approach., Comment: 1. There are some errors in the data analysis table in the dataset SupQA, which needs to be corrected. 2. There is something wrong with the partial expression of the formula. 3. It will be resubmitted after modification

The $S_8$ tension between low-redshift galaxy surveys and the primary CMB signals a possible breakdown of the $\Lambda$CDM model. Recently differing results have been obtained using low-redshift galaxy surveys and the higher redshifts probed by CMB lensing, motivating a possible time-dependent modification to the growth of structure. We investigate a simple phenomenological model in which the growth of structure deviates from the $\Lambda$CDM prediction at late times, in particular as a simple function of the dark energy density. Fitting to galaxy lensing, CMB lensing, BAO, and Supernovae datasets, we find significant evidence - 2.5 - 3$\sigma$, depending on analysis choices - for a non-zero value of the parameter quantifying a deviation from $\Lambda$CDM. The preferred model, which has a slower growth of structure below $z\sim 1$, improves the joint fit to the data over $\Lambda$CDM. While the overall fit is improved, there is weak evidence for galaxy and CMB lensing favoring different changes in the growth of structure., Comment: Match the published version. Add more references. 6 pages, 5 figures, 1 table

A successful measurement of the Stochastic Gravitational Wave Background (SGWB) in Pulsar Timing Arrays (PTAs) would open up a new window through which to test the predictions of General Relativity (GR). We consider how these measurements might reveal deviations from GR by studying the overlap reduction function -- the quantity that in GR is approximated by the Hellings-Downs curve -- in some sample modifications of gravity, focusing on the generic prediction of a modified dispersion relation for gravitational waves. We find a distinct signature of such modifications to GR -- a shift in the minimum angle of the angular distribution -- and demonstrate that this shift is quantitatively sensitive to any change in the phase velocity. In a given modification of gravity, this result can be used, in some regions of parameter space, to distinguish the effect of a modified dispersion relation from that due to the presence of extra polarization modes., Comment: v2: add references and discussions. 23 pages, 4 figures

The sheer size of modern neural networks makes model serving a serious computational challenge. A popular class of compression techniques overcomes this challenge by pruning or sparsifying the weights of pretrained networks. While useful, these techniques often face serious tradeoffs between computational requirements and compression quality. In this work, we propose a novel optimization-based pruning framework that considers the combined effect of pruning (and updating) multiple weights subject to a sparsity constraint. Our approach, CHITA, extends the classical Optimal Brain Surgeon framework and results in significant improvements in speed, memory, and performance over existing optimization-based approaches for network pruning. CHITA's main workhorse performs combinatorial optimization updates on a memory-friendly representation of local quadratic approximation(s) of the loss function. On a standard benchmark of pretrained models and datasets, CHITA leads to significantly better sparsity-accuracy tradeoffs than competing methods. For example, for MLPNet with only 2% of the weights retained, our approach improves the accuracy by 63% relative to the state of the art. Furthermore, when used in conjunction with fine-tuning SGD steps, our method achieves significant accuracy gains over the state-of-the-art approaches.

Although type Ia supernovae are so important in many astrophysical field, e.g. in cosmology, their explosion mechanism and progenitor system are still unclear. In physics, the relative equivalent width (REW) of the Si II 635.5 nm absorption feature reflects the velocity interval of silicon in the supernova ejecta and then may provide constraints on the explosion mechanism of SNe Ia. In this paper, we divide the SNe Ia into broad line (BL) and normal line (NL) subsamples based on their REW of Si II 635.5 nm absorption lines around maximum light, and find that the BL SNe Ia have a dimmer mean brightness than NL ones, which possibly results from their different metallicities. However, based on the pixel statistics study on the environments of two subsamples, we do not find any significant potential difference on the environments between BL and NL SNe Ia, which implies that the explosion mechanism of SNe Ia could be independent of their progenitor populations., Comment: 17 pages, 13 figures, accepted for publication in ApJ

Early dark energy (EDE), whose cosmological role is localized in time around the epoch of matter-radiation equality in order to resolve the Hubble tension, introduces a new coincidence problem: why should the EDE dynamics occur near equality if EDE is decoupled from both matter and radiation? The resolution of this problem may lie in an {\it early dark sector} (EDS), wherein the dark matter mass is dependent on the EDE scalar field. Concretely, we consider a Planck-suppressed coupling of EDE to dark matter, as would naturally arise from breaking of the global $U(1)$ shift symmetry of the former by quantum gravity effects. With a sufficiently flat potential, the rise to dominance of dark matter at matter-radiation equality itself triggers the rolling and subsequent decay of the EDE. We show that this {\it trigger} EDS (tEDS) model can naturally resolve the EDE coincidence problem at the background level without any fine tuning of the coupling to dark matter or of the initial conditions. When fitting to current cosmological data, including that from the local distance ladder and the low-redshift amplitude of fluctuations, the tEDS maximum-likelihood model performs comparably to EDE for resolving the Hubble tension, achieving $H_0 =71.2$ km/s/Mpc. However, fitting the \emph{Planck} cosmic microwave background data requires a specific range of initial field positions to balance the scalar field fluctuations that drive acoustic oscillations, providing testable differences with other EDE models., Comment: 12 pages, 6 figures

Decision trees are one of the most useful and popular methods in the machine learning toolbox. In this paper, we consider the problem of learning optimal decision trees, a combinatorial optimization problem that is challenging to solve at scale. A common approach in the literature is to use greedy heuristics, which may not be optimal. Recently there has been significant interest in learning optimal decision trees using various approaches (e.g., based on integer programming, dynamic programming) -- to achieve computational scalability, most of these approaches focus on classification tasks with binary features. In this paper, we present a new discrete optimization method based on branch-and-bound (BnB) to obtain optimal decision trees. Different from existing customized approaches, we consider both regression and classification tasks with continuous features. The basic idea underlying our approach is to split the search space based on the quantiles of the feature distribution -- leading to upper and lower bounds for the underlying optimization problem along the BnB iterations. Our proposed algorithm Quant-BnB shows significant speedups compared to existing approaches for shallow optimal trees on various real datasets.

Low-energy alternatives to General Relativity (GR) generically modify the phase of gravitational waves (GWs) during their propagation. As detector sensitivities increase, it becomes key to understand how these modifications affect the GW higher modes and to disentangle possible degeneracies with astrophysical phenomena. We apply a general formalism -- the WKB approach -- for solving analytically wave propagation in the spatial domain with a modified dispersion relation (MDR). We compare this WKB approach to applying a stationary phase approximation (SPA) in the temporal domain with time delays associated to the group or particle velocity. To this end, we extend the SPA to generic signals with higher modes, keeping careful track of reference phases and arrival times. We find that the WKB approach coincides with the SPA using the group velocity, in agreement with the principles of wave propagation. We then explore the degeneracies between a GW propagation with an MDR and a strongly-lensed GW in GR, since the latter can introduce a frequency-independent phase shift which is not degenerate with source parameters in the presence of higher modes. We find that for a particular MDR there is an exact degeneracy for wave propagation, unlike with the SPA for particle propagation. For the other cases, we search for the values of the MDR parameters that minimize the $\chi^2$ and conclude that strongly-lensed GR GWs could be misinterpreted as GWs in modified gravity. Future MDR constraints with higher mode GWs should include the possibility of frequency-independent phase shifts, allowing for the identification of modified gravity and strong lensing distortions at the same time., Comment: 32 pages, 6 figures. Match the published version

We consider the interplay of the Early Dark Energy (EDE) model, the Swampland Distance Conjecture (SDC), and cosmological parameter tensions. EDE is a proposed resolution of the Hubble tension relying upon a near-Planckian scalar field excursion, while the SDC predicts an exponential sensitivity of masses of other fields to such an excursion, $m\propto e^{-c|\Delta \phi|/M_{\rm pl}}$ with $c\sim{\cal O}(1)$. Meanwhile, EDE is in tension with large-scale structure (LSS) data, due to shifts in the standard $\Lambda$CDM parameters necessary to fit the cosmic microwave background (CMB). One might hope that a proper treatment of the model, e.g., accounting for the SDC, may ameliorate the tension with LSS. Motivated by these considerations, we introduce the Early Dark Sector (EDS) model, wherein the mass of dark matter is exponentially sensitive to super-Planckian field excursions of the EDE scalar. The EDS model exhibits new phenomenology in both the early and late universe, the latter due to an EDE-mediated dark matter self-interaction. This dark matter-philic "fifth force", while constrained to be small, remains active in the late universe and is not screened in virialized halos. We find that the new interaction with dark matter partially resolves the LSS tension. However, the marginalized posteriors are nonetheless consistent with $f_{\rm EDE}=0$ at 95$\%$ CL once the Dark Energy Survey Year 3 measurement of $S_8$ is included. We study constraints on the model from Atacama Cosmology Telescope data, and find a factor of two improvement on the error bar on the SDC parameter $c$, along with an increased preference for the EDE component. We discuss the implications of these constraints for the SDC, and find the tightest observational constraints to date on a swampland parameter, suggesting that an EDE description of cosmological data is in tension with the SDC., Comment: v2: version published in Phys. Rev. D

We study the cosmological propagation of gravitational waves (GWs) beyond general relativity (GR) across homogeneous and isotropic backgrounds. We consider scenarios in which GWs interact with an additional tensor field and use a parametrized phenomenological approach that generically describes their coupled equations of motion. We analyze four distinct classes of derivative and non-derivative interactions: mass, friction, velocity, and chiral. We apply the WKB formalism to account for the cosmological evolution and obtain analytical solutions to these equations. We corroborate these results by analyzing numerically the propagation of a toy GW signal. We then proceed to use the analytical results to study the modified propagation of realistic GWs from merging compact binaries, assuming that the GW signal emitted is the same as in GR. We generically find that tensor interactions lead to copies of the originally emitted GW signal, each one with its own possibly modified dispersion relation. These copies can travel coherently and interfere with each other leading to a scrambled GW signal, or propagate decoherently and lead to echoes arriving at different times at the observer that could be misidentified as independent GW events. Depending on the type of tensor interaction, the detected GW signal may exhibit amplitude and phase distortions with respect to a GW waveform in GR, as well as birefringence effects. We discuss observational probes of these tensor interactions with both individual GW events, as well as population studies for both ground- and space-based detectors., Comment: Updated to journal version

Data-adaptive (machine learning-based) effect estimators are increasingly popular to reduce bias in high-dimensional bioinformatic and clinical studies (e.g. real-world data, target trials, -omic discovery). Their relative statistical efficiency (high power) is particularly invaluable in these contexts since sample sizes are often limited due to practical and cost concerns. However, these methods are subject to technical limitations that are dataset specific and involve computational trade-offs. Thus, it is challenging for analysts to identify when such methods may offer benefits or select amongst statistical methods. We present extensive simulation studies of several cutting-edge estimators, evaluating both performance and computation time. Critically, rather than use arbitrary simulation data, we generate synthetic datasets mimicking the observed data structure (plasmode simulation) of a real molecular epidemiologic cohort. We find that machine learning approaches may not always be indicated in such data settings, but that performance is highly context dependent. We present a user-friendly Shiny app REFINE2 (Realistic Evaluations of Finite sample INference using Efficient Estimators) that enables analysts to simulate synthetic data from their own datasets and directly evaluate the performance of several cutting-edge algorithms in those settings. This tool may greatly facilitate the proper selection and implementation of machine-learning-based effect estimators in bioinformatic and clinical study contexts., Comment: 31 pages, 6 figures

The single degenerate (SD) model, one of the leading models for the progenitors of Type Ia supernovae (SNe Ia), predicts that there should be binary companions that survive the supernova explosion which, in principle, should be detectable in the Galaxy. The discovery of such surviving companions could therefore provide conclusive support for the SD model. Several years ago, a new type of mysterious variables was discovered, the so-called blue large-amplitude pulsators (BLAPs). Here we show that all the properties of BLAPs can be reasonably well reproduced if they are indeed such surviving companions, in contrast to other proposed channels. This suggests that BLAPs could potentially be the long-sought surviving companions of SNe Ia. Our model also predicts a new channel for forming single hot subdwarf stars, consistent with a small group in the present hot-subdwarf-star sample., Comment: 21 pages, 13 figures, accepted for publication in ApJ

The canonical acoustic dark energy model (cADE), which is based on a scalar field with a canonical kinetic term that rapidly converts potential to kinetic energy around matter radiation equality, alleviates the Hubble tension found in $\Lambda$CDM. We show that it successfully passes new consistency tests in the CMB damping tail provided by the ACT data, while being increasingly constrained and distinguished from alternate mechanisms by the improved CMB acoustic polarization data from Planck. The best fit cADE model to a suite of cosmological observations, including the SH0ES $H_0$ measurement, has $H_0=70.25$ compared with $68.23$ (km s$^{-1}$ Mpc$^{-1}$) in $\Lambda$CDM and a finite cADE component is preferred at the $2.8\sigma$ level. The ability to raise $H_0$ is now mainly constrained by the improved Planck acoustic polarization data, which also plays a crucial role in distinguishing cADE from the wider class of early dark energy models. ACT and Planck TE polarization data are currently mildly discrepant in normalization and drive correspondingly different preferences in parameters. Improved constraints on intermediate scale polarization approaching the cosmic variance limit will be an incisive test of the acoustic dynamics of these models and their alternatives., Comment: v2: Added more references; matched the published version. 10 pages, 8 figures

Quantum signal processing (QSP) is a powerful quantum algorithm to exactly implement matrix polynomials on quantum computers. Asymptotic analysis of quantum algorithms based on QSP has shown that asymptotically optimal results can in principle be obtained for a range of tasks, such as Hamiltonian simulation and the quantum linear system problem. A further benefit of QSP is that it uses a minimal number of ancilla qubits, which facilitates its implementation on near-to-intermediate term quantum architectures. However, there is so far no classically stable algorithm allowing computation of the phase factors that are needed to build QSP circuits. Existing methods require the usage of variable precision arithmetic and can only be applied to polynomials of relatively low degree. We present here an optimization based method that can accurately compute the phase factors using standard double precision arithmetic operations. We demonstrate the performance of this approach with applications to Hamiltonian simulation, eigenvalue filtering, and the quantum linear system problems. Our numerical results show that the optimization algorithm can find phase factors to accurately approximate polynomials of degree larger than $10,000$ with error below $10^{-12}$., Comment: 26 pages, 17 figures

Quantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation., Comment: 8 pages, 4 figures

We discuss the difference between various gauge-invariant quantities typically used in single-field inflation, namely synchronous $\zeta_s$, comoving $\zeta_c$, and unitary $\zeta_u$ curvatures. We show that conservation of $\zeta_c$ outside the horizon is quite restrictive on models as it leads to conservation of $\zeta_s$ and $\zeta_u$, whereas the reverse does not hold. We illustrate the consequence of these differences with two inflationary models: ultra-slow-roll (USR) and braiding-ultra-slow-roll (BUSR). In USR, we show that out of the three curvatures, only $\zeta_s$ is conserved outside the horizon, and we connect this result to the concepts of separate universe and the usage of the $\delta N$ formalism. We find that even though $\zeta_s$ is conserved, there is still a mild violation of the separate universe approximation in the continuity equation. Nevertheless, the $\delta N$ formalism can still be applied to calculate the primordial power spectrum of some gauge-invariant quantities such as $\zeta_u$, although it breaks down for others such as the uniform-density curvature. In BUSR, we show that both $\zeta_u$ and $\zeta_s$ are conserved outside the horizon, but take different values. Additionally, since $\zeta_u\not=\zeta_c$ we find that the prediction for observable curvature fluctuations after inflation does not reflect $\zeta_c$ at horizon crossing during inflation and moreover involves not just $\zeta_u$ at that epoch but also the manner in which the braiding phase ends.

A successful robot-assisted feeding system requires bite acquisition of a wide variety of food items. It must adapt to changing user food preferences under uncertain visual and physical environments. Different food items in different environmental conditions require different manipulation strategies for successful bite acquisition. Therefore, a key challenge is how to handle previously unseen food items with very different success rate distributions over strategy. Combining low-level controllers and planners into discrete action trajectories, we show that the problem can be represented using a linear contextual bandit setting. We construct a simulated environment using a doubly robust loss estimate from previously seen food items, which we use to tune the parameters of off-the-shelf contextual bandit algorithms. Finally, we demonstrate empirically on a robot-assisted feeding system that, even starting with a model trained on thousands of skewering attempts on dissimilar previously seen food items, $\epsilon$-greedy and LinUCB algorithms can quickly converge to the most successful manipulation strategy., Comment: To appear in IROS 2020; 8 pages incl. references, 8 figures; Abstract presented in IJCAI 2019 AIxFood Workshop; v3: Added simulation and experimental results for conference submission; v4: Added extra results to Experiment 2 for camera-ready submission

Optimization with nonnegative orthogonality constraints has wide applications in machine learning and data sciences. It is NP-hard due to some combinatorial properties of the constraints. We first propose an equivalent optimization formulation with nonnegative and multiple spherical constraints and an additional single nonlinear constraint. Various constraint qualifications, the first- and second-order optimality conditions of the equivalent formulation are discussed. By establishing a local error bound of the feasible set, we design a class of (smooth) exact penalty models via keeping the nonnegative and multiple spherical constraints. The penalty models are exact if the penalty parameter is sufficiently large other than going to infinity. A practical penalty algorithm with postprocessing is then developed. It uses a second-order method to approximately solve a series of subproblems with nonnegative and multiple spherical constraints. We study the asymptotic convergence of the penalty algorithm and establish that any limit point is a weakly stationary point of the original problem and becomes a stationary point under some additional mild conditions. Extensive numerical results on the projection problem, orthogonal nonnegative matrix factorization problems and the K-indicators model show the effectiveness of our proposed approach., Comment: 32 pages, 4 figures, 7 tables

The portfolio optimisation problem, first raised by Harry Markowitz in 1952, has been a fundamental and central topic to understanding the stock market and making decisions. There has been plenty of works contributing to development of the mean-variance optimisation (MVO) so far. In this paper, one kind of them, namely, dynamic mean-variance optimisation (DMVO) is mainly discussed. One can apply either precommitment or game-theoritical approach to address time-inconsistency in DMVO. We use the second approach to seek for a time-consistent strategy. After obtaining the optimal strategy, we extend the result to a CEV-driven economy. In order to prove the usefulness of them, strategies are fit into both real market data and simulated data. It turns out that the strategy whose assumptions are close to market conditions generally gives a better result. Lastly, a selected strategy is chosen to compare with another strategy came up by deep learning technique., Comment: National University of Singapore, Quantitative Finance (Department of Mathematics) Undergraduate Thesis. Advisor: Chao Zhou

We discuss the ability of a dark fluid becoming relevant around the time of matter radiation equality to significantly relieve the tension between local measurements of the Hubble constant and CMB inference, within the $\Lambda$CDM model. We show that the gravitational impact of acoustic oscillations in the dark fluid balance the effects on the CMB and result in an improved fit to CMB measurements themselves while simultaneously raising the Hubble constant. The required balance favors a model where the fluid is a scalar field that converts its potential to kinetic energy around matter radiation equality which then quickly redshifts away. We derive the requirements on the potential for this conversion mechanism and find that a simple canonical scalar with two free parameters for its local slope and amplitude robustly improves the fit to the combined data by $\Delta\chi^2 \approx 12.7$ over $\Lambda$CDM. We uncover the CMB polarization signatures that can definitively test this scenario with future data., Comment: v3: matched the published version

The braiding of two non-Abelian Majorana modes is important for realizing topological quantum computation. It can be achieved through tuning the coupling between the two Majorana modes to be exchanged and two ancillary Majorana modes. However, this coupling also makes the braiding subject to environment-induced decoherence. Here, we study the effects of decoherence on the diabatic errors in the braiding process for a set of time-dependent Hamiltonians with finite smoothness. To this end, we employ the master equation to calculate the diabatic excitation population for three kinds of decoherence processes. (1) Only pure dehasing: the scaling of the excitation population changed from $T^{-2k-2}$ to $T^{-1}$ ($k$ is the number of the Hamiltonian's time derivatives vanishing at the initial and final times) as the braiding duration $T$ exceeds a certain value. (2) Only relaxation: the scaling transforms from $T^{-2k-2}$ to $T^{-2}$ for $k=0$ and to $T^{-a}$ ($a>3$) for $k>0$. (3) Pure dephasing and relaxation: the original scaling switches to $T^{-1}$ firstly and then evolves to $T^{-2}$ in the adiabatic limit. Interestingly, the third scaling-varying style holds even when the expectation of pure dephasing rate is much smaller than that of the relaxation rate, which is attributed to the vanishing relaxation at the turning points of the braiding., Comment: 7 pages, 4 figures

We discuss the phenomenological imprints of modifications to gravity in the early universe with a specific focus on the time of recombination. We derive several interesting results regarding the effect that such modifications have on cosmological observables, especially on the driving and phasing of acoustic oscillations, observed in the CMB and BAO, as well as the weak gravitational lensing of the CMB and of galaxy shapes. This widens the pool of measurements that can be used to test gravity with present and future surveys, in particular realizing the full constraining power of the structure of the primary peaks of the CMB spectrum. We investigate whether such a phenomenology can relax tensions between cosmological measurements and find that a modification of the gravitational constant at recombination would help in reconciling measurements of the CMB with local measurements of the Hubble constant., Comment: 22 pages, 21 figures

The temperature of the semiconductor diode increases under strong light illumination whether thermoelectric cooler is installed or not, which changes the output wavelength of the laser (Lee M. S. et al., 2017). However, other characteristics also vary as temperature increases. These variations may help the eavesdropper in practical quantum key distribution systems. We study the effects of temperature increase on gain-switched semiconductor lasers by simulating temperature dependent rate equations. The results show that temperature increase may cause large intensity fluctuation, decrease the output intensity and lead the signal state and decoy state distinguishable. We also propose a modified photon number splitting attack by exploiting the effects of temperature increase. Countermeasures are also proposed., Comment: Accepted by Optics Communications. 7 Figures

Quantum key distribution (QKD) protocol has been proved to provide unconditionally secure key between two remote legitimate users in theory. Key distribution signals are transmitted in a quantum channel which is established by the calibration process to meet the requirement of high count rate and low error rate. All QKD security proofs implicitly assume that the quantum channel has been established securely. However, the eavesdropper may attack the calibration process to break the security assumption of QKD and provide precondition to steal information about the final key successfully. Inspired by N. Jain et al., Phys. Rev. Lett.107,110501(2011), we reveal the security risk of the calibration process of a passive-basis-choice BB84 QKD system by launching a quantum man-in-the-middle attack which intercepts all calibration signals and resends faked ones. Large temporal bit-dependent or basis-dependent detector efficiency mismatch can be induced. Then we propose a basis-dependent detector efficiency mismatch (BEM) based faked states attack on a single photon BB84 QKD to stress the threat of BEM. Moreover, the security of single photon QKD systems with BEM is studied simply and intuitively. Two effective countermeasures are suggested to remove the general security risk of the calibration process., Comment: 7 figures

Analyses of biomedical studies often necessitate modeling longitudinal causal effects. The current focus on personalized medicine and effect heterogeneity makes this task even more challenging. Towards this end, structural nested mean models (SNMMs) are fundamental tools for studying heterogeneous treatment effects in longitudinal studies. However, when outcomes are binary, current methods for estimating multiplicative and additive SNMM parameters suffer from variation dependence between the causal parameters and the non-causal nuisance parameters. This leads to a series of difficulties in interpretation, estimation and computation. These difficulties have hindered the uptake of SNMMs in biomedical practice, where binary outcomes are very common. We solve the variation dependence problem for the binary multiplicative SNMM via a reparametrization of the non-causal nuisance parameters. Our novel nuisance parameters are variation independent of the causal parameters, and hence allow for coherent modeling of heterogeneous effects from longitudinal studies with binary outcomes. Our parametrization also provides a key building block for flexible doubly robust estimation of the causal parameters. Along the way, we prove that an additive SNMM with binary outcomes does not admit a variation independent parametrization, thereby justifying the restriction to multiplicative SNMMs., Comment: To appear in Biometrics

Result on the locations of the tricritical points of $N_f=2$ lattice QCD with imaginary chemical potential is presented. Simulations are carried out with Symanzik improved gauge action and Asqtad fermion action. With imaginary chemical potential $i\mu_I=i\pi T$, previous studies show that the Roberge-Weiss (RW) transition endpoints are triple points at both large and small quark masses, and second order transition points at intermediate quark masses. The triple and second order endpoints are separated by two tricritical ones. Our simulations are carried out at 7 values of quark mass $am$ ranging from 0.024 to 0.070 on lattice volume $12^3\times 4, 16^3\times 4,\, 20^3\times4$. The susceptibility and Binder cumulant of the imaginary part of Polyakov loop are employed to determine the nature of RW transition endpoints. The simulations suggest that the two tricritical points are within the range $0.024-0.026$ and $0.040-0.050$, respectively., Comment: 8 pages, 16 figures. arXiv admin note: substantial text overlap with arXiv:1405.2425

In recent years, direct detection, indirect detection, and collider experiments have placed increasingly stringent constraints on particle dark matter, exploring much of the parameter space associated with the WIMP paradigm. In this paper, we focus on the subset of WIMP models in which the dark matter annihilates in the early universe through couplings to either the Standard Model $Z$ or the Standard Model Higgs boson. Considering fermionic, scalar, and vector dark matter candidates within a model-independent context, we find that the overwhelming majority of these dark matter candidates are already ruled out by existing experiments. In the case of $Z$ mediated dark matter, the only scenarios that are not currently excluded are those in which the dark matter is a fermion with an axial coupling and with a mass either within a few GeV of the $Z$ resonance ($m_{\rm DM} \simeq m_Z/2$) or greater than 200 GeV, or with a vector coupling and with $m_{\rm DM} > 6$ TeV. Several Higgs mediated scenarios are currently viable if the mass of the dark matter is near the Higgs pole ($m_{\rm DM} \simeq m_H/2$). Otherwise, the only scenarios that are not excluded are those in which the dark matter is a scalar (vector) heavier than 400 GeV (1160 GeV) with a Higgs portal coupling, or a fermion with a pseudoscalar (CP violating) coupling to the Standard Model Higgs boson. With the exception of dark matter with a purely pseudoscalar coupling to the Higgs, it is anticipated that planned direct detection experiments will probe nearly the entire range of models considered in this study., Comment: Corrected an error on the relic abundance curves in the high mass region for the Z mediated models and for fermionic dark matter mediated by the Higgs. Some figures changed accordingly. Conclusions remain unchanged but for the case of a fermionic dark matter with purely axial couplings to the Z. References added

Let $m\ge3$ be an integer. The polygonal numbers of order $m+2$ are given by $p_{m+2}(n)=m\binom n2+n$ $(n=0,1,2,\ldots)$. A famous claim of Fermat proved by Cauchy asserts that each nonnegative integer is the sum of $m+2$ polygonal numbers of order $m+2$. For $(a,b)=(1,1),(2,2),(1,3),(2,4)$, we study whether any sufficiently large integer can be expressed as $$p_{m+2}(x_1) + p_{m+2}(x_2) + ap_{m+2}(x_3) + bp_{m+2}(x_4)$$ with $x_1,x_2,x_3,x_4$ nonnegative integers. We show that the answer is positive if $(a,b)\in\{(1,3),(2,4)\}$, or $(a,b)=(1,1)\ \&\ 4\mid m$, or $(a,b)=(2,2)\ \&\ m\not\equiv 2\pmod 4$. In particular, we confirm a conjecture of Z.-W. Sun which states that any natural number can be written as $p_6(x_1) + p_6(x_2) + 2p_6(x_3) + 4p_6(x_4)$ with $x_1,x_2,x_3,x_4$ nonnegative integers., Comment: 22 pages

We suggest stellar oscillations are responsible for the strange radio behaviors of Anomalous X-ray pulsars and soft Gamma-ray repeaters (AXP/SGRs), within the framework of both solid quark star model and magnetar model. In solid quark star model, the extra voltage provided by oscillations activates the star from under death line to above death line. In magnetar model, oscillations enlarge the radio beam so that increase the possibility to detect it. Later radio emission decays and vanishes as oscillations damp., Comment: Proceedings of Quarks and Compact Stars 2014. 3pages, 1 figure

The quantum entangled degrees of entangled states become smaller with the transmission distance increasing, how to keep the purity of quantum entangled states is the puzzle in quantum communication. In the paper, we have designed a new type entanglement degrees amplifier by one-dimensional photonic crystal, which is similar as the relay station of classical electromagnetic communication. We find when the entangled states of two-photon and three-photon pass through photonic crystal, their entanglement degrees can be magnified, which make the entanglement states can be long range propagation and the quantum communication can be really realized.

In this paper, we have proposed the compound structure of one-dimensional photonic crystal (PC), which includes series connection and parallel connection PC. We have studied the transmission characteristics of series connection and parallel connection PC, and obtained some new results. In addition, we have proved the series connection one-dimensional PC can realize the logical AND operation, and the parallel connection one-dimensional PC can realize the logical OR operation. The compound structure of one-dimensional PC can design more new type structure optical devices, and will provide the basic for designing quantum computer., Comment: arXiv admin note: substantial text overlap with arXiv:1509.03824

We investigate the behavior of the chiral condensate in lattice QCD at finite temperature and finite chemical potential. The study was done using two flavors of light quarks and with a series of $\beta$ and $ma$ at the lattice size $24\times12^{2}\times6$. The calculation was done in the Taylar expansion formalism. We are able to calculate the first and second order derivatives of $\langle\bar{\psi}\psi\rangle$ in both isoscalar and isovector channels. With the first derivatives being small, we find that the second derivatives are sizable close to the phase transition and the magnitude of $\bar{\psi}\psi$ decreases under the influence of finite chemical potential in both channels., Comment: 4 pages, 4 figures, to be submitted to Chinese Physics C

Let $m>2$ and $q>0$ be integers with $m$ even or $q$ odd. We show the supercongruence $$\sum_{k=0}^{p-1}(-1)^{km}\binom{p/m-q}{k}^m\equiv0\pmod{p^3}.$$ for any prime $p>mq$. This confirms a conjecture of Sun., Comment: 6 pages, final published version

We study the magnetospheric activity in the polar cap region of pulsars under stellar oscillations. The toroidal oscillation of the star propagates into the magnetosphere, which provides additional voltage due to unipolar induction, changes Goldreich-Julian charge density from the traditional value due to rotation, and hence, influences particle acceleration. We present a general solution of the effect of oscillations within the framework of the inner vacuum gap model, and consider three different inner gap modes controlled by curvature radiation, inverse Compton scattering, and two photon annihilation, respectively. With different pulsar parameters and oscillation amplitudes, one of three modes would play a dominant role in defining the gap properties. When the amplitude of oscillation exceeds a critical value, mode changing would occur. Oscillations also lead to change of the size of the polar cap. As applications, we show the inner gap properties under oscillations in both normal pulsars and anomalous X-ray pulsars / soft gamma-ray repeaters (AXPs/SGRs). We interpret the onset of radio emission after glitches/flares in AXPs/SGRs as due to oscilation-driven magnetic activities in these objects, within the framework of both the magnetar model and the solid quark star model. Within the magnetar model, radio activation may be caused by the enlargement of the effective polar cap angle and the radio emission beam due to oscillation; whereas within the solid quark star angle, it may be caused by activation of the pulsar inner gap from below the radio emission death line due to an oscillation-induced voltage enhancement. The model can also explain the glitch-induced radio profile change observed in PSR J1119-6127., Comment: 12 pages, 5 figures, 1 table. Accepted for publication in ApJ

The phase structure of QCD with imaginary chemical potential provides information on the phase diagram of QCD with real chemical potential. With imaginary chemical potential $i\mu_I=i\pi T$, previous studies show that the Roberge-Weiss (RW) transition end points are triple points at both large and small quark masses, and second order transition points at intermediate quark masses. The triple and second order end points are separated by two tricritical ones. We present simulations with $ N_f=2 $ Wilson fermions to investigate the nature of RW transition end points. The simulations are carried out at 8 values of the hopping parameter $\kappa$ ranging from 0.020 to 0.140 on different lattice volumes. The Binder cumulant, susceptibility and reweighted distribution of the imaginary part of Polyakov loop are employed to determine the nature of RW transition end points. The simulations show that the two tricritical points are within the range $0.070-0.080$ and $0.120-0.140$, respectively., Comment: 8 pages, 15 figures; conclusion modified. arXiv admin note: substantial text overlap with arXiv:1303.0336

We make simulations with 2 flavor Wilson fermions to investigate the nature of the end points of Roberge-Weiss (RW) first order phase transition lines. The simulations are carried out at 9 values of the hopping parameter $\kappa$ ranging from 0.155 to 0.198 on different lattice spatial volume. The Binder cumulants, susceptibilities and reweighted distributions of the imaginary part of Polyakov loop are employed to determine the nature of the end points of RW transition lines. The simulations show that the RW end points are of first order at the values of $\kappa$ in our simulations., Comment: 23 figures, 9 pages; 23 figures,10 pages; some slight changes

We present a study for charmonium radiative transitions: $J/\psi\rightarrow\eta_c\gamma$, $\chi_{c0}\rightarrow J/\Psi\gamma$ and $h_c\rightarrow\eta_c\gamma$ using $N_f=2$ twisted mass lattice QCD gauge configurations. The single-quark vector form factors for $\eta_c$ and $\chi_{c0}$ are also determined. The simulation is performed at a lattice spacing of $a= 0.06666$ fm and the lattice size is $32^3\times 64$. After extrapolation of lattice data at nonzero $Q^2$ to 0, we compare our results with previous quenched lattice results and the available experimental values., Comment: typeset with revtex, 15 pages, 11 figures, 4 tables

Type Ia supernovae (SNe Ia) play a key role in measuring cosmological parameters, in which the Phillips relation is adopted. However, the origin of the relation is still unclear. Several parameters are suggested, e.g. the relative content of carbon to oxygen (C/O) and the central density of the white dwarf (WD) at ignition. These parameters are mainly determined by the WD's initial mass and its cooling time, respectively. Using the progenitor model developed by Meng and Yang, we present the distributions of the initial WD mass and the cooling time. We do not find any correlation between these parameters. However, we notice that the range of the WD's mass decreases, while its average value increases with the cooling time. These results could provide a constraint when simulating the SN Ia explosion, i.e. the WDs with a high C/O ratio usually have a lower central density at ignition, while those having the highest central density at ignition generally have a lower C/O ratio. The cooling time is mainly determined by the evolutionary age of secondaries, and the scatter of the cooling time decreases with the evolutionary age. Our results may indicate that WDs with a long cooling time have more uniform properties than those with a short cooling time, which may be helpful to explain why SNe Ia in elliptical galaxies have a more uniform maximum luminosity than those in spiral galaxies., Comment: 8 pages, 3 figures, in press, by language editor

In this paper, we demonstrate the LHC discovery potential of new charged vector boson $W_1^{\pm}$ predicted by the Minimal Higgsless model in the process $pp\to W_1^{\pm}qq^{\prime}\to W^{\pm}Z^0qq^\prime\to \ell^{\pm}\ell^+\ell^-\nu qq^{\prime}(\ell=e,\mu)$ by analyzing the generator level events of the signal and backgrounds. The generator for the signal $pp \to {W_1}^{\pm}qq^\prime\to W^{\pm}Z^0qq^\prime$ at tree level is developed with the Minimal Higgsless model and then interfaced with PYTHIA for the parton showers and hadronization. The backgrounds are produced with PYTHIA and ACERMC. We give integrated luminosities required to discover 5$\sigma$ signal as a function of $W_1^{\pm}$ mass., Comment: Version for Nucl.Phys.B (in Press), 12pp

Low-energy scattering of $D^*$ and $D_1$ meson are studied using quenched lattice QCD with improved lattice actions on anisotropic lattices. The calculation is performed within L\"uscher's finite-size formalism which establishes the relation between the scattering phase in the infinite volume and the exact energy level in the finite volume. The threshold scattering parameters, namely the scattering length $a_0$ and the effective range $r_0$, for the s-wave scattering in $J^P=0^-$ channel are extracted. After the chiral and continuum extrapolations, we obtain: $a_0=2.52(47)$fm and $r_0=0.7(1)$fm where the errors are purely statistical. Based on these results, we discuss the possibility of a shallow bound state for the two charmed mesons within the non-relativistic potential scattering model. It is argued that, albeit the interaction between the two charmed mesons being attractive, it is unlikely that they can form a shallow bound state in this channel. This calculation provides some useful information on the nature of the newly discovered resonance-like structure $Z^+(4430)$ by the Belle Collaboration., Comment: 30 pages,10 figures