Update Constraints Research Articles

Observational constraints on early dark energy

In this paper, we review and update constraints on the Early Dark Energy (EDE) model from cosmological data sets, in particular Planck PR3 and PR4 cosmic microwave background (CMB) data and large-scale structure (LSS) data sets including galaxy clustering and weak lensing data from the Dark Energy Survey, Subaru Hyper Suprime-Cam and KiDS+VIKING-450, as well as BOSS/eBOSS galaxy clustering and Lyman-[Formula: see text] forest data. We detail the fit to CMB data, and perform the first analyses of EDE using the CAMSPEC and Hillipop likelihoods for Planck CMB data, rather than Plik, both of which yield a tighter upper bound on the allowed EDE fraction than that found with Plik. We then supplement CMB data with LSS data in a series of new analyses. All these analyses are concordant in their Bayesian preference for [Formula: see text]CDM over EDE, as indicated by marginalized posterior distributions. We perform a series of tests of the impact of priors in these results, and compare with frequentist analyses based on the profile likelihood, finding qualitative agreement with the Bayesian results. All these tests suggest prior volume effects are not a determining factor in analyses of EDE. This work provides both a review of existing constraints and several new analyses.

Implementation of Lung Nodule Detection Model Based on Incremental Meta-Learning

In response to the issue that traditional lung nodule detection models cannot dynamically optimize and update with the increase of new data, a new lung nodule detection model-task incremental meta-learning model (TIMLM) is proposed. This model comprises of two loops: the inner loop imposes incremental learning regularization update constraints, while the outer loop employs a meta-update strategy to sample old and new knowledge and learn a set of generalized parameters that adapt to old and new data. Under the condition that the main structure of the model is not changed as much as possible, it preserves the old knowledge that was learned previously. Experimental verification on the publicly available lung dataset showed that, compared with traditional deep network models and mainstream incremental models, TIMLM has greatly improved in terms of accuracy, sensitivity, and other indicators, demonstrating good continuous learning and anti-forgetting capabilities.

Constraints on the spectral signatures of superconducting cosmic strings

ABSTRACT If they exist, networks of superconducting cosmic strings are capable of injecting copious amounts of electromagnetic energy into the background over a broad range of frequencies. We study this injection both analytically, as well as numerically using the thermalization code CosmoTherm. With our refined analytic formalism, we update constraints from CMB spectral distortions by following the injection of entropy, as well as energy, on the amplitude of the μ-distortion, leading to a significant improvement in those limits. Furthermore, we utilize the full shape of the distorted spectrum from CosmoTherm to include constraints from non-μ, non-y type distortions. Additionally, we use the outputs for the ionization history and global 21-cm signal to derive and update constraints on string model parameters using measurements from other data sets. Analysis of CMB anisotropies provides the most stringent constraints, though with a slightly modified shape and strength when compared to previous results. Modifications of the reionization history provide new bounds in the high current domain, and we also find that the observations of the low-frequency radio background probe a small region of parameter space not explored by other data sets. We also analyse global 21-cm constraints, and find that the inclusion of soft photon heating plays a crucial role, essentially removing any constraints in the considered parameter domain. Spectral distortion measurements from COBE/FIRAS are covered by other constraints, but our conservative forecast shows that a PIXIE-type satellite would probe important unexplored regions of parameter space.

Updated constraints and future prospects on majoron dark matter

Majorons are (pseudo-)Nambu-Goldstone bosons associated with lepton number symmetry breaking due to the Majorana mass term of neutrinos introduced in the seesaw mechanism. They are good dark matter candidates since their lifetime is suppressed by the lepton number breaking scale. We update constraints and discuss future prospects on majoron dark matter in the singlet majoron models based on neutrino, gamma-ray, and cosmic-ray telescopes in the mass region of MeV–10 TeV.

Constraints on τ NL from Planck temperature and polarization

We update constraints on the amplitude of the primordial trispectrum, using the final Planck mission temperature and polarization data. In the squeezed limit, a cosmological local trispectrum would be observed as a spatial modulation of small-scale power on the CMB sky. We reconstruct this signal as a source of statistical anisotropy via quadratic estimator techniques. We systematically demonstrate how the estimated power spectrum of a reconstructed modulation field can be translated into a constraint on τ NL via likelihood methods, demonstrating the procedures effectiveness by inferring known τ NL signal(s) from simulations. Our baseline results constrain τ NL < 1700 at the 95% confidence level, providing the most stringent constraints to date.

Primordial black hole dark matter in the context of extra dimensions

Theories of large extra dimensions (LEDs) such as the Arkani-Hamed, Dimopoulos & Dvali scenario predict a "true" Planck scale $M_\star$ near the TeV scale, while the observed $M_{pl}$ is due to the geometric effect of compact extra dimensions. These theories allow for the creation of primordial black holes (PBHs) in the early Universe, from the collisional formation and subsequent accretion of black holes in the high-temperature plasma, leading to a novel cold dark matter (sub)component. Because of their existence in a higher-dimensional space, the usual relationship between mass, radius and temperature is modified, leading to distinct behaviour with respect to their 4-dimensional counterparts. Here, we derive the cosmological creation and evolution of such PBH candidates, including the greybody factors describing their evaporation, and obtain limits on LED PBHs from direct observation of evaporation products, effects on big bang nucleosynthesis, and the cosmic microwave background angular power spectrum. Our limits cover scenarios of 2 to 6 extra dimensions, and PBH masses ranging from 10 to $10^{21}$ g. We find that for two extra dimensions, LED PBHs represent a viable dark matter candidate with a range of possible black hole masses between $10^{17}$ and $10^{23}$ g depending on the Planck scale and reheating temperature. For $M_\star = 10$ TeV, this corresponds to PBH dark matter with a mass of $M \simeq 10^{21}$ g, unconstrained by current observations. We further refine and update constraints on "ordinary" four-dimension black holes.

Target tracking algorithm of intermittently updated template based on reliability evaluation

In the siamese network tracking method based on the target matching idea, the tracking performance is closely related to the similarity between the tracking template and the tracking target. The UpdateNet algorithm updates the tracking results of each frame prediction into the template during tracking, which undoubtedly guarantees the real-time correlation between the template and the tracking target. However, tracking targets will encounter tracking challenges such as occlusion and short-term severe deformation. The tracking results predicted under this tracking challenge will be mixed with messy information that has nothing to do with the tracking target. If the UpdateNet algorithm updates the tracking results that are rich in messy information into the template, the purity of the template will decrease. This paper proposes a method of intermittently updating templates by proposing template update constraints, so that the UpdateNet algorithm discards the low-confidence tracking results. This guarantees the purity of the tracking template to a certain extent, which improves the relevance of the tracking template and the tracking target. In addition, this article also conducts optimal training on the UpdateNet algorithm.

Muonic boson limits: Supernova redux

Making use of modern supernova simulations which include muon effects, the authors update constraints on light muon-specific (pseudo) scalars and generic axion-like particles. They find that such scalar solutions to the muon g-2 excess are in conflict with astrophysical observations.

Adaptive fuzzy PI controller for permanent magnet synchronous motor drive based on predictive functional control

The high-performance speed control is hard to achieve for the permanent magnet synchronous motor (PMSM) drive system under uncertain disturbances, input saturation, and system delay. To address this challenge, a novel adaptive fuzzy proportional-integral (AFPI) control scheme is investigated in this paper. An anti-saturation PI (ASPI) controller is proposed serving as the main control unit that drives PMSM to track the desired profiles, which is optimized online by a designed adaptive fuzzy tuner. Specifically, together with the parameter update constraints, an improved anti-integral saturation mechanism is suggested for the ASPI controller. Meanwhile, the adaptive fuzzy tuner with the self-tuning input domain enhances the optimization ability to effectively tackle the system uncertainties. Then, a predictive functional control method is incorporated into the tuner to mitigate the control lag caused by error-driven characteristics, which ensures the dynamic tracing control performance in the presence of system delay. The stability and the H∞ robustness of the AFPI controller are guaranteed based on d-decomposition theory. Simulations and real-time experiments are performed, and the results illustrate that the designed scheme has superior performance in terms of dynamic tracking control and anti-disturbance capabilities as compared to conventional methods.

Genetic optimization method of ship strong frame based on sequential surrogate model

Objectives The optimization design of a ship strong frame structure under the requirements of common structural rules (CSR) is a complex and time-consuming problem, moreover, it has tremendous constraints so that the feasibility of a design scheme is hard to identify. When adopting the static surrogate assisted evolutionary algorithm to solve this problem, since the approach aims at global accuracy, the prediction of key area will be distorted in the case of small size samples. However, the active-learning surrogate-based approach can solve this bottleneck since it can improve the accuracy of key area sequentially by adding samples to refine the surrogate model purposely. Therefore, this method can obtain better optimization scheme and save computational burden compared with the former one. Methods Aiming at the problem, an optimization method for strong frame based on sequential surrogate assisted genetic algorithm is proposed. Firstly, the constraints on strong frame structure based on CSR are analyzed, and all 675 constraints are reduced to 2 positive constraints according to the type of constraints. Then surrogates for objective function and constraints functions are constructed. Next, feasibility principle based genetic algorithm is adopted to solve it. After optimized solution is obtained, its true response is calculated and surrogates will be updated. In addition, expected feasibility function criterion is applied to update constraints surrogates, the purpose of which is to refine the prediction accuracy at the constraints boundary. Iterate the above procedures for several times, the optimized global feasible solution will be obtained finally. Results It is found that the proposed method is able to get better solution than static surrogate based algorithm with less computation resource and the weight of design area is reduced by 15.55% finally. Conclusions Proposed sequential surrogate based algorithm is superior to static surrogate based algorithm and has good application value in the optimization of ship structure under complex constraints.

Update constraints on neutrino mass and mass hierarchy in light of dark energy models

Combining cosmic microwave (CMB) background data from Planck satellite data, Baryon Acoustic Oscillations (BAO) measurements and Type Ia supernovae (SNe Ia) data, we obtain the bounds on total neutrino masses [Formula: see text] with the approximation of degenerate neutrino masses and for three dark energy models: the cosmological constant ([Formula: see text]CDM) model, a phenomenological emergent dark energy (PEDE) model and a model-independent quintessential parametrization (HBK). The bounds on the sum of neutrino masses [Formula: see text] depend on the dark energy (DE) models. In the HBK model, we confirm the conclusion from some previous work that the quintessence prior of DE tends to tighten the cosmological constraint on [Formula: see text]. On the other hand, the PEDE model leads to larger [Formula: see text] and a nonzero lower bound. Besides, we also explore the correlation between three different neutrino hierarchies and DE models.

Updated constraints on superconducting cosmic strings from the astronomy of fast radio bursts

In this article we update constraints on superconducting cosmic strings (SCSs) in the light of the recent observational developments of fast radio bursts (FRBs) astronomy. Assuming strings follow an exponential distribution characterized by a current, we show that two parameters in our context, which are the characteristic tension (Gmu ) and a parameter which describes the aforementioned exponential distribution (I_c), can be constrained by FRB experiments. Particularly, we investigate data sets from Parkes and ASKAP. We looked at a parameter space where Gmu sim [10^{-17}, 10^{-12}] and I_csim [10^{-1}, 10^{2}] GeV, and found our results show that Parkes jointly with ASKAP can constrain the parameter space for SCSs.

Scrutinizing a massless dark photon: Basis independence

A new U(1)X gauge boson field X can have renormalizable kinetic mixing with the standard model (SM) U(1)Y gauge boson field Y. This mixing induces interactions of X with SM particles even though X starts as a dark photon without such interactions. If the U(1)X is not broken, both the dark photon field X and the photon field A are massless. One cannot determine which one of them is the physical dark photon or the photon by just looking at kinetic terms in the Lagrangian. We revisit this issue and show explicitly that when all contributions are included, all physical processes do not depend on which basis is used and the kinetic mixing effects do not show up in electromagnetic and weak interactions if only SM particles are involved in the calculations. On the other hand, the kinetic mixing provides a portal for probing the dark sector beyond the SM. We update constraints on the millicharged dark sector particles from the Lamb shift and lepton g−2 measurements.

Constraining Dark Matter-Dark Radiation interactions with CMB, BAO, and Lyman-α

Several interesting Dark Matter (DM) models invoke a dark sector leading to two types of relic particles, possibly interacting with each other: non-relativistic DM, and relativistic Dark Radiation (DR) . These models have interesting consequences for cosmological observables, and could in principle solve problems like the small-scale cold DM crisis, Hubble tension, and/or low σ8 value. Their cosmological behaviour is captured by the ETHOS parametrisation, which includes a DR-DM scattering rate scaling like a power-law of the temperature, Tn. Scenarios with n=0, 2, or 4 can easily be realised in concrete dark sector set-ups. Here we update constraints on these three scenarios using recent CMB, BAO, and high-resolution Lyman-α data. We introduce a new Lyman-α likelihood that is applicable to a wide range of cosmological models with a suppression of the matter power spectrum on small scales. For n=2 and 4, we find that Lyman-α data strengthen the CMB+BAO bounds on the DM-DR interaction rate by many orders of magnitude. However, models offering a possible solution to the missing satellite problem are still compatible with our new bounds. For n=0, high-resolution Lyman-α data bring no stronger constraints on the interaction rate than CMB+BAO data, except for extremely small values of the DR density. Using CMB+BAO data and a theory-motivated prior on the minimal density of DR, we find that the n=0 model can reduce the Hubble tension from 4.1σ to 2.7σ, while simultaneously accommodating smaller values of the σ8 and S8 parameters hinted by cosmic shear data.

Constraints from thermal Sunyaev-Zel’dovich cluster counts and power spectrum combined with CMB

The thermal Sunyaev-Zel’dovich (tSZ) effect is one of the recent probes of cosmology and large-scale structures. We update constraints on cosmological parameters from galaxy clusters observed by thePlancksatellite in a first attempt to combine cluster number counts and the power spectrum of hot gas; we used a new value of the optical depth and, at the same time, sampling on cosmological and scaling-relation parameters. We find that in the ΛCDM model, the addition of a tSZ power spectrum provides small improvements with respect to number counts alone, leading to the 68% c.l. constraints Ωm= 0.32 ± 0.02,σ8= 0.76 ± 0.03, andσ8(Ωm/0.3)1/3= 0.78 ± 0.03 and lowering the discrepancy with results for cosmic microwave background (CMB) primary anisotropies (updated with the new value ofτ) to ≃1.8σonσ8. We analysed extensions to the standard model, considering the effect of massive neutrinos and varying the equation of state parameter for dark energy. In the first case, we find that the addition of the tSZ power spectrum helps in improving cosmological constraints with respect to number count alone results, leading to the 95% upper limit ∑mν&lt; 1.88 eV. For the varying dark energy equation of state scenario, we find no important improvements when adding tSZ power spectrum, but still the combination of tSZ probes is able to provide constraints, producingw= −1.0 ± 0.2. In all cosmological scenarios, the mass bias to reconcile CMB and tSZ probes remains low at (1 −b) ≲ 0.67 as compared to estimates from weak lensing and X-ray mass estimate comparisons or numerical simulations.

Two-season Atacama Cosmology Telescope polarimeter lensing power spectrum

We report a measurement of the power spectrum of cosmic microwave background (CMB) lensing from two seasons of Atacama Cosmology Telescope Polarimeter (ACTPol) CMB data. The CMB lensing power spectrum is extracted from both temperature and polarization data using quadratic estimators. We obtain results that are consistent with the expectation from the best-fit Planck LCDM model over a range of multipoles L=80-2100, with an amplitude of lensing A_lens = 1.06 +/- 0.15 (stat.) +/- 0.06 (sys.) relative to Planck. Our measurement of the CMB lensing power spectrum gives sigma_8 Omega_m^0.25 = 0.643 +/- 0.054; including baryon acoustic oscillation scale data, we constrain the amplitude of density fluctuations to be sigma_8 = 0.831 +/- 0.053. We also update constraints on the neutrino mass sum. We verify our lensing measurement with a number of null tests and systematic checks, finding no evidence of significant systematic errors. This measurement relies on a small fraction of the ACTPol data already taken; more precise lensing results can therefore be expected from the full ACTPol dataset.

Axial, scalar, and tensor charges of the nucleon from2+1+1-flavor Lattice QCD

We present results for the isovector axial, scalar and tensor charges $g^{u-d}_A$, $g^{u-d}_S$ and $g^{u-d}_T$ of the nucleon needed to probe the Standard Model and novel physics. The axial charge is a fundamental parameter describing the weak interactions of nucleons. The scalar and tensor charges probe novel interactions at the TeV scale in neutron and nuclear $\beta$-decays, and the flavor-diagonal tensor charges $g^{u}_T$, $g^{d}_T$ and $g^{s}_T$ are needed to quantify the contribution of the quark electric dipole moment (EDM) to the neutron EDM. The 9 ensembles, generated by the MILC Collaboration using the HISQ action with 2+1+1 dynamical flavors, span three lattice spacings $a \approx 0.06, 0.09$ and 0.12 fm and light-quark masses corresponding to the pion masses $M_\pi \approx 135, 225$ and 315 MeV. High-statistics estimates on five ensembles using the all-mode-averaging method allow us to quantify all systematic uncertainties and perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses for the connected contributions. Our final estimates, in the $\overline{\text{MS}}$ scheme at 2 GeV, of the isovector charges are $g_A^{u-d} = 1.195(33)(20)$, $g_S^{u-d} = 0.97(12)(6) $ and $g_T^{u-d} = 0.987(51)(20)$. The first error includes statistical and all systematic uncertainties except that due to the extrapolation Ansatz, which is given by the second error estimate. Combining our estimate for $g_S^{u-d}$ with the difference of light quarks masses $(m_d-m_u)^{\rm QCD}=2.67(35)$ MeV given by FLAG, we obtain $(M_N-M_P)^{\rm QCD} = 2.59(49)$ MeV. Estimates of the connected part of the flavor-diagonal tensor charges of the proton are $g^{u}_T=0.792(42)$ and $g^{d}_T=-0.194(14)$. Combining our new estimates with precision low-energy experiments, we update constraints on novel scalar and tensor interactions, $\epsilon_{S,T}$, at the TeV scale.

A map of update constraints in inductive inference

We investigate how different learning restrictions reduce learning power and how the different restrictions relate to one another. We give a complete map for nine different restrictions both for the cases of complete information learning and set-driven learning. This completes the picture for these well-studied delayable learning restrictions. A further insight is gained by different characterizations of conservative learning in terms of variants of cautious learning.Our analyses greatly benefit from general theorems we give, for example showing that learners which have to obey only delayable restrictions can always be assumed total.

The gauge-Higgs legacy of the LHC Run I

The effective Lagrangian expansion provides a framework to study effects of new physics at the electroweak scale. To make full use of LHC data in constraining higher-dimensional operators we need to include both the Higgs and the electroweak gauge sector in our study. We first present an analysis of the relevant di-boson production LHC results to update constraints on triple gauge boson couplings. Our bounds are several times stronger than those obtained from LEP data. Next, we show how in combination with Higgs measurements the triple gauge vertices lead to a significant improvement in the entire set of operators, including operators describing Higgs couplings.

On the role of update constraints and text-types in iterative learning

The present work investigates the relationship of iterative learning with other learning criteria such as decisiveness, caution, reliability, non-U-shapedness, monotonicity, strong monotonicity and conservativeness. Building on the result of Case and Moelius that iterative learners can be made non-U-shaped, we show that they also can be made cautious and decisive. Furthermore, we obtain various special results with respect to one-one texts, fat texts and one-one hypothesis spaces.