Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum state engineering by steering in the presence of errors

Quantum state engineering plays a vital role in various applications in the field of quantum information. Different strategies, including drive-and-dissipation, adiabatic cooling, and measurement-based steering, have been proposed in the past for state generation and manipulation, each with its upsides and downsides. Here, we address a class of measurement-based state engineering protocols where a sequence of generalized measurements is employed to steer a quantum system toward a desired target state. Previously studied measurement-based protocols relied on idealized procedures and avoided exploration of the effects of various errors stemming from imperfections of experimental realizations and external noise. We employ the quantum trajectory formalism to provide a detailed analysis of the robustness of these steering protocols against various errors. We study a set of errors that can be classified as dynamic or static, depending on whether they remain unchanged while running the protocol. More specifically, we investigate the impact of erroneous choice of system-detector coupling, re-initialization of the detector state following a measurement step, fluctuating steering directions, and environmentally induced errors in the system-detector interaction. We show that the protocol remains fully robust against the erroneous choice of system-detector coupling parameters and presents reasonable robustness against other errors. We employ various quantifiers such as fidelity, trace distance, and linear entropy to characterize the protocol's robustness and provide analytical results. Subsequently, we demonstrate the commutation between the classical expectation value and the time-ordering operator of the exponential of a Hamiltonian with multiplicative white noise, as well as the commutation of the expectation value and the partial trace with respect to detector outcomes.
Structured Epipolar Matcher for Local Feature Matching

Local feature matching is challenging due to textureless and repetitive patterns. Existing methods focus on using appearance features and global interaction and matching, while the importance of geometry priors in local feature matching has not been fully exploited. Different from these methods, in this paper, we delve into the importance of geometry prior and propose Structured Epipolar Matcher (SEM) for local feature matching, which can leverage the geometric information in an iterative matching way. The proposed model enjoys several merits. First, our proposed Structured Feature Extractor can model the relative positional relationship between pixels and high-confidence anchor points. Second, our proposed Epipolar Attention and Matching can filter out irrelevant areas by utilizing the epipolar constraint. Extensive experimental results on five standard benchmarks demonstrate the superior performance of our SEM compared to state-of-the-art methods. Project page: https://sem2023.github. io.
Cusum Charts for Monitoring an Autocorrelated Process

Control charts for process monitoring have traditionally been designed and evaluated under the assumption that observations on the process output at different times are independent. However, autocorrelation may be present in many processes, and may have a strong impact on the properties of control charts. This paper investigates CUSUM control charts for monitoring the process mean for the situation in which observations from the process can be modeled as an AR(1) process plus an additional random error. CUSUM charts based on plotting the residuals from model forecasts, or on plotting the original observations, are considered. CUSUM charts based on the original observations perform as well as CUSUM charts of residuals, except in the case in which the level of autocorrelation is high and the shift in the process mean is large. A method for designing the CUSUM chart of the observations in the presence of autocorrelation is given. The CUSUM charts are compared to Shewhart and EWMA charts based on the residuals or on the original observations. The CUSUM and EWMA charts perform similarly in terms of the ability to detect shifts in the process mean.
Communication protocols and QECCs from the perspective of TQFT, Part I: Constructing LOCC protocols and QECCs from TQFTs

Topological quantum field theories (TQFTs) provide a general, minimal-assumption language for describing quantum-state preparation and measurement. They therefore provide a general language in which to express multi-agent communication protocols, e.g. local operations, classical communication (LOCC) protocols. Here we construct LOCC protocols using TQFT, and show that LOCC protocols generically induce quantum error-correcting codes (QECCs). Using multi-observer scenarios described by quantum Darwinism and Bell/EPR experiments as examples, we show how these LOCC-induced QECCs effectively convert entanglement into classical redundancy. In the accompanying Part II, we show that such QECCs can be regarded as implementing, or inducing the emergence of, spacetimes on the boundaries between interacting systems. We investigate this connection between inter-agent communication and spacetime using BF and Chern-Simons theories, and then using topological M-theory.
End-to-End n-ary Relation Extraction for Combination Drug Therapies

Combination drug therapies are treatment regimens that involve two or more drugs, administered more commonly for patients with cancer, HIV, malaria, or tuberculosis. Currently there are over 350K articles in PubMed that use the combination drug therapy MeSH heading with at least 10K articles published per year over the past two decades. Extracting combination therapies from scientific literature inherently constitutes an n-ary relation extraction problem. Unlike in the general n-ary setting where n is fixed (e.g., drug-gene-mutation relations where n =3), extracting combination therapies is a special setting where n ≥2 is dynamic, depending on each instance. Recently, Tiktinsky et al. (NAACL 2022) introduced a first of its kind dataset, CombDrugExt, for extracting such therapies from literature. Here, we use a sequence-to-sequence style end-to-end extraction method to achieve an F1-Score of 66.7% on the CombDrugExt test set for positive (or effective) combinations. This is an absolute ≈5% F1-score improvement even over the prior best relation classification score with spotted drug entities (hence, not end-to-end). Thus our effort introduces a state-of-the-art first model for end-to-end extraction that is already superior to the best prior non end-to-end model for this task. Our model seamlessly extracts all drug entities and relations in a single pass and is highly suitable for dynamic n-ary extraction scenarios.
Detecting Entanglement by State Preparation and a Fixed Measurement

It is shown that a fixed measurement setting, e.g., a measurement in the computational basis, can detect all entangled states by preparing multipartite quantum states, called network states. We present network states for both cases to construct decomposable entanglement witnesses (EWs) equivalent to the partial transpose criteria and also non-decomposable EWs that detect undistillable entangled states beyond the partial transpose criteria. Entanglement detection by state preparation can be extended to multipartite states such as graph states, a resource for measurement-based quantum computing. Our results readily apply to a realistic scenario, for instance, an array of superconducting qubits. neutral atoms, or photons, in which the preparation of a multipartite state and a fixed measurement are experimentally feasible.
Quantum interference and controllable magic cavity QED via a giant atom in a coupled resonator waveguide

We study the Markovian and Non-Markovian dynamics in a giant atom system which couples to a coupled resonator waveguide (CRW) via two distant sites. Under certain conditions, we find that the giant atom population can exhibit an oscillating behavior and the photon can be trapped in the giant atom regime. These phenomena are induced by the interference effect among the bound states both in and outside the continuum. As an application of the photon trapping, we theoretically propose a magic cavity model where the giant atom serve as either a perfect or leaky cavity, depending on the distance between the coupling sites. The controllability of the magic cavity from perfect to leaky one can not be realized in the traditional cavity or circuit QED setup. The predicted effects can be probed in state-of-the-art waveguide QED experiments and provide a striking example of how the different kinds of bound states modify the dynamics of quantum open system in a structured environment.
New Primal-dual Interior-point Methods Based on Kernel Functions

Two important classes of polynomial-time interior-point method (IPMs) are small- and large-update methods, respectively. The theoretical complexity bound for large-update methods is a factor $\sqrt{n}$ worse than the bound for small-update methods, where $n$ denotes the number of (linear) inequalities in the problem. In practice the situation is opposite: implementations of large-update methods are much more efficient than those of small-update methods. This so-called irony of IPMs motivated the present work. Recently J. Peng C. Roos and T. Terlaky were able to design new IPMs with large-updates whose complexity is only a factor $\log n$ worse than for small-update methods. This means that the factor $\sqrt{n}$ was reduced to $\log n$, thus significantly reducing the gap between the theoretical behavior of large- and small-update methods. They made use of so-called self-regular barrier (or proximity) functions. Each such barrier function is determined by its (univariate) self-regular kernel function. In these thesis we introduce a new class of kernel functions which differs from the class of self-regular kernel functions. The class is defined by some simple conditions on the kernel function which concern the growth and the barrier behavior of the kernel function. These properties enable us to derive many new and tight estimates that greatly simplify the analysis of IPMs based on these kernel functions. In Chapter 2 we consider ten specific (classes of) kernel functions belonging to the new class, and using the new estimates present a complete complexity analysis for each of these functions. Some of these functions are self-regular and others are not. Iterations bounds both for large- and small-update methods are derived. It is shown that small-update methods based on the new kernel functions all have the same complexity as the classical primal-dual IPM, namely $O(\sqrt{n}\,\log\frac{n}{\e})$. For large-update methods the best obtained bound is $O(\sqrt{n}\,\br{\log n}\,\log\frac{n}{\e})$, which is up till now the best known bound for such methods. The results of Chapter 2 for LO are extended to semidefinite optimization in Chapter 3, where we it is shown that at some point the analysis boils down to exactly the same analysis as for the LO case. In Chapter 4 some numerical results are presented. These results show that one of the new kernel functions, with finite barrier term and with the best possible theoretical complexity, performs surprisingly well in our experiments.
Ray tracing of electrostatic waves in a hot plasma and its application to the generation of terrestrial myriametric radiation

The first results from the program HOTRAY for ray tracing electrostatic and electromagnetic waves in a hot plasma are presented. The calculations are applied to the linear mode-conversion window theory for the generation of Terrestrial Myriametric Radiation corresponding to a specific event observed by the DE-1 satellite. Results show that backward propagating electrostatic waves can refract in a density gradient normal to the magnetic field to become Z-mode waves and can have access to the radio window. During propagation the waves remain minimally damped. Variations of approximately 0.01° in the initial wave normal angle ψ can result in a large difference in the transmitted wave intensities. However, if such variations do occur, waves from different locations can still access the radio window so that energy transfer to the conversion point remains efficient. Strong refraction of electrostatic waves at latitudes > 1° show that the magnetic equator is the preferred location for mode conversion to take place.
TraVaG: Differentially Private Trace Variant Generation Using GANs

Process mining is rapidly growing in the industry. Consequently, privacy concerns regarding sensitive and private information included in event data, used by process mining algorithms, are becoming increasingly relevant. State-of-the-art research mainly focuses on providing privacy guarantees, e.g., differential privacy, for trace variants that are used by the main process mining techniques, e.g., process discovery. However, privacy preservation techniques for releasing trace variants still do not fulfill all the requirements of industry-scale usage. Moreover, providing privacy guarantees when there exists a high rate of infrequent trace variants is still a challenge. In this paper, we introduce TraVaG as a new approach for releasing differentially private trace variants based on \text{Generative Adversarial Networks} (GANs) that provides industry-scale benefits and enhances the level of privacy guarantees when there exists a high ratio of infrequent variants. Moreover, TraVaG overcomes shortcomings of conventional privacy preservation techniques such as bounding the length of variants and introducing fake variants. Experimental results on real-life event data show that our approach outperforms state-of-the-art techniques in terms of privacy guarantees, plain data utility preservation, and result utility preservation.
Facial recognition technology and human raters can predict political orientation from images of expressionless faces even when controlling for demographics and self-presentation.

Carefully standardized facial images of 591 participants were taken in the laboratory while controlling for self-presentation, facial expression, head orientation, and image properties. They were presented to human raters and a facial recognition algorithm: both humans (r = .21) and the algorithm (r = .22) could predict participants' scores on a political orientation scale (Cronbach's α = .94) decorrelated with age, gender, and ethnicity. These effects are on par with how well job interviews predict job success, or alcohol drives aggressiveness. The algorithm's predictive accuracy was even higher (r = .31) when it leveraged information on participants' age, gender, and ethnicity. Moreover, the associations between facial appearance and political orientation seem to generalize beyond our sample: The predictive model derived from standardized images (while controlling for age, gender, and ethnicity) could predict political orientation (r ≈ .13) from naturalistic images of 3,401 politicians from the United States, the United Kingdom, and Canada. The analysis of facial features associated with political orientation revealed that conservatives tended to have larger lower faces. The predictability of political orientation from standardized images has critical implications for privacy, the regulation of facial recognition technology, and understanding the origins and consequences of political orientation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Peer Prediction for Peer Review: Designing a Marketplace for Ideas

The paper describes a potential platform to facilitate academic peer review with emphasis on early-stage research. This platform aims to make peer review more accurate and timely by rewarding reviewers on the basis of peer prediction algorithms. The algorithm uses a variation of Peer Truth Serum for Crowdsourcing (Radanovic et al., 2016) with human raters competing against a machine learning benchmark. We explain how our approach addresses two large productive inefficiencies in science: mismatch between research questions and publication bias. Better peer review for early research creates additional incentives for sharing it, which simplifies matching ideas to teams and makes negative results and p-hacking more visible.
Tuning infrared guided-mode resonances with graphene

We report a strategy to modulate the Fano-like signature of a guided-mode resonance supported by a graphene-based grating. The shape of the resonance is controlled by the amount of damping introduced by graphene. A symmetric-to-asymmetric line shape transition and a significant narrowing of the linewidth occur at relatively moderate levels of chemical potential. Further increases of the chemical potential lead to a blueshift of the Fano resonance due to the modification of the imaginary part of the conductivity of graphene. Our results are supported by a quasi-normal mode analysis of the grating. Using a perturbative approach, we provide analytical expressions for both the resonance wavelength shift and the linewidth modulation induced by changes of the graphene’s chemical potential. Electrostatic or electrochemical gating of graphene in the proposed structure provides dynamic control of the Fano-like resonance of the grating, suggesting new opportunities for the design of tunable photonic and optoelectronic devices at infrared wavelengths.
Conservation and Expansion of Transcriptional Factor Repertoire in the Fusarium oxysporum Species Complex

The Fusarium oxysporum species complex (FOSC) includes both plant and human pathogens that cause devastating plant vascular wilt diseases and threaten public health. Each F. oxysporum genome comprises core chromosomes (CCs) for housekeeping functions and accessory chromosomes (ACs) that contribute to host-specific adaptation. This study inspects global transcription factor profiles (TFomes) and their potential roles in coordinating CC and AC functions to accomplish host-specific interactions. Remarkably, we found a clear positive correlation between the sizes of TFomes and the proteomes of an organism. With the acquisition of ACs, the FOSC TFomes were larger than the other fungal genomes included in this study. Among a total of 48 classified TF families, 14 families involved in transcription/translation regulations and cell cycle controls were highly conserved. Among the 30 FOSC expanded families, Zn2-C6 and Znf_C2H2 were most significantly expanded to 671 and 167 genes per family including well-characterized homologs of Ftf1 (Zn2-C6) and PacC (Znf_C2H2) that are involved in host-specific interactions. Manual curation of characterized TFs increased the TFome repertoires by 3% including a disordered protein Ren1. RNA-Seq revealed a steady pattern of expression for conserved TF families and specific activation for AC TFs. Functional characterization of these TFs could enhance our understanding of transcriptional regulation involved in FOSC cross-kingdom interactions, disentangle species-specific adaptation, and identify targets to combat diverse diseases caused by this group of fungal pathogens.
Update on ladder plates for mandibular angle fractures

Purpose of review Fractures of the mandibular angle are surgically challenging with high rates of postoperative complications. Among established fixation techniques for these injuries, Champy's tension band approach with miniplate fixation has held prominence. Rigid fixation, using two plates, also remains commonly used. More recently, geometric ladder plates, which confer greater three-dimensional stability have been developed to overcome the shortcomings of conventional fixation approaches. Herein, we aim to summarize the recent evidence surrounding the use of ladder plates and offer our own opinion for optimal treatment of these fractures. Recent findings In high-powered studies, the rates of hardware failure, malocclusion, and malunion are lower among cohorts managed with ladder plates relative to miniplate groups. Rates of infection and paresthesia remain similar. Ladder plates have also been shown to decrease operative time in preliminary study. Summary Ladder plates show superiority to miniplate approaches across several outcomes. However, the relatively larger strut plate constructs may not be necessary for minor, uncomplicated fractures. It is our belief that reasonable outcomes may be achieved with either approach depending on surgeon experience and comfort with the given fixation technique.
Factors influencing attitudes toward vaccine safety and vaccine effectiveness amongst UK healthcare professionals prior to and at the time of COVID-19 vaccine rollout: Insights from the CoPE-HCP cohort study

ABSTRACT Given the potential for nosocomial outbreaks, we must understand factors associated with negative vaccine attitudes amongst healthcare professionals (HCPs) before the rollout of a newly developed vaccine in a pandemic setting. The aim of this prospective cohort study was to study the impact of preexisting and prevailing mental health on United Kingdom HCPs’ attitudes towards a newly developed COVID-19 vaccine. Two online surveys were distributed: first during vaccine development (July–September, 2020) and second during nationwide vaccine rollout (December 2020–March 2021). Mental health (PHQ-9 for depression; GAD-7 for anxiety) was assessed in both surveys. Negative attitude regarding vaccine safety and vaccine effectiveness was assessed at vaccine rollout. A series of logistic regression models were developed relating mental health (preexisting during vaccine development, ongoing and new-onset during rollout, and changes in symptom severity) to negative vaccine attitudes. In 634 HCPs, the presence of depression and/or anxiety during vaccine development was associated with elevated negative attitude towards vaccine safety (adj. OR 1.74 [95% CI 1.10–2.75], p = .02), but not vaccine effectiveness (1.13 [0.77–1.66], p = .53) at rollout. This was independent of other characteristics: age, ethnicity, professional role, and history of contracting COVID-19. Ongoing depression and/or anxiety (1.72 [1.10–2.69], p = .02) was associated with elevated negative attitude regarding vaccine effectiveness, but not vaccine safety. Worsened combined symptom scores over time were associated with elevated negative vaccine effectiveness attitudes (1.03 [1.00–1.05], p < .05), but not vaccine safety. Overall, adverse mental health can impact on HCPs’ attitudes towards a newly developed vaccine. Further work is required to understand how this translates to vaccine uptake.
On Kubota's Dirichlet series

Abstract Kubota [T. Kubota, Some results concerning reciprocity law and real analytic automorphic functions, in: 1969 Number Theory Institute (Proc. Sympos. Pure Math. XX, State Univ. New York, Stony Brook, N.Y., 1969), Amer. Math. Soc. , Providence, R.I. (1971), 382–395. ] showed how the theory of Eisenstein series on the higher metaplectic covers of SL2 (which he discovered) can be used to study the analytic properties of Dirichlet series formed with n-th order Gauss sums. In this paper we will prove a functional equation for such Dirichlet series in the precise form required by the companion paper [B. Brubaker, D. Bump, G. Chinta, S. Friedberg, and J. Hostein, Weyl group multiple Dirichlet series I, preprint, http://sporadic.stanford. edu/bump/wmd.pdf. ]. Closely related results are in Eckhardt and Patterson [C. Eckhardt and S. J. Patterson, On the Fourier coefficients of biquadratic theta series, Proc. London Math. Soc. (3) 64(2) (1992), 225–264. ].