Absence Of Fine-tuning Research Articles

Probing an ultralight QCD axion with electromagnetic quadratic interaction

The axion-gluon coupling is the defining feature of the QCD axion. This feature induces additional and qualitatively different interactions of the axion with standard model particles—quadratic couplings. Previously, hadronic quadratic couplings have been studied and experimental implications have been explored especially in the context of atomic spectroscopy and interferometry. We investigate additional quadratic couplings to the electromagnetic field and electron mass. These electromagnetic quadratic couplings are generated at the loop level from threshold corrections and are expected to be present in the absence of fine-tuning. While they are generally loop-suppressed compared to the hadronic ones, they open up new ways to search for the QCD axion, for instance via optical atomic clocks. Moreover, due to the velocity spread of the dark matter field, the quadratic nature of the coupling leads to low-frequency stochastic fluctuations. These distinctive low-frequency fluctuations offer a new way to search for heavier axions. We provide an analytic expression for the power spectral density of this low-frequency background and briefly discuss experimental strategies for a low-frequency stochastic background search. Published by the American Physical Society 2024

Natural Explanation for 21cm Absorption Signals via Axion-Induced Cooling.

The EDGES Collaboration has reported an anomalously strong 21cm absorption feature corresponding to the era of first star formation, which may indirectly betray the influence of dark matter during this epoch. We demonstrate that, by virtue of the ability to mediate cooling processes while in the condensed phase, a small amount of axion dark matter can explain these observations within the context of standard models of axions and axionlike particles. The EDGES best-fit result favors an axionlike particle mass in the (10, 450) meV range, which can be compressed for the QCD axion to (100, 450)meV in the absence of fine tuning. Future experiments and large scale surveys, particularly the International Axion Observatory (IAXO) and EUCLID, should have the capability to directly test this scenario.

Improving the effectiveness of training the on-board object detection system for a compact unmanned aerial vehicle

The model of object detector and the criterion of leaning effectiveness of the model were proposed. The model contains 7 first modules of the convolutional Squeezenet network, two convolutional multiscale layers and the information­extreme classifier. The multiplicative convolution of the particular criteria that takes into account the effectiveness of detection of objects in the image and accuracy of the classification analysis was considered as the criterion of learning effectiveness of the model. In this case, additional use of the orthogonal matching pursuit algorithm in calculating high­level features makes it possible to increase the accuracy of the model by 4 %. The training algorithm of object detector under conditions of a small size of labeled training datasets and limited computing resources available on board of a compact unmanned aerial vehicle was developed. The essence of the algorithm is to adapt the high­level layers of the model to the domain application area, based on the algorithms of growing sparse coding neural gas and simulated annealing. Unsupervised learning of high­level layers makes it possible to use effectively the unlabeled datasets from the domain area and determine the required number of neurons. It is shown that in the absence of fine tuning of convolutional layers, 69 % detection of objects in the images of the test dataset Inria Aerial Image was ensured. In this case, after fine tuning based on the simulated annealing algorithm, 95 % detection of the objects in test images is ensured. It was shown that the use of unsupervised pretraining makes it possible to increase the generalizing ability of decision rules and to accelerate the iteration process of finding the global maximum during supervised learning on the dataset of limited size. In this case, the overfitting effect is eliminated by optimal selection of the value of hyperparameter, characterizing the measure of coverage of the input data of by network neurons.

A novel approach to avoiding early stagnation in Ant Colony Optimization algorithms

This paper introduces a novel approach to avoiding early stagnation in Ant Colony Optimization algorithms. The approach involves oscillating the α and β parameters out of phase with each other according to an offline adaptation formula triggered by the online signal of stagnation in improved solutions across iterations. Further, in this paper, we present the ex- perimental results obtained from applying this method to solving the Traveling Salesman Problem across eight fully connected, symmetric maps of sizes ranging from 51 to 1,400 cities, and show that a marginal improvement is achieved even with relatively constrained amounts of computation time and in the absence of fine-tuning of the ACO parameters towards each specific instance of the problem.

Glycemic Variability in Hospitalized Patients: Choosing Metrics While Awaiting the Evidence

Hyperglycemia, hypoglycemia, preexisting diabetes, and glycemic variability each may affect hospital outcomes. Observational findings derived from randomized trials or retrospective studies suggest that independent of hypoglycemia and hyperglycemia, a relationship exists between variability and hospital outcomes. A review of studies conducted in diverse hospital populations is reported here, showing a relationship between measures of variability and nonglycemic outcomes, including ICU and hospital mortality and length of stay. "Glycemic variability" has an intuitive meaning, understood as a propensity of a single patient to develop repeated episodes of excursions of BG over a relatively short period of time that exceed the amplitude expected in normal physiology. It is proposed that each of 3 dimensions of variability should be separately studied: (1) magnitude of glycemic excursions during intervals of relative stability of the moving average of BG, (2) frequency with which a critical magnitude of excursion is exceeded, and (3) presence or absence of fine tuning. Multiple hospital studies have found that the standard deviation (SD) of the data set of blood glucose values (BG) of individual patients predicts outcomes. An appropriate refinement would be to report the "Reverse-transformed group mean of the SD of the logarithmically transformed BG data set of each patient," with confidence intervals. In logarithmic space, group means of the SD of BGs of each patient may be compared, using an appropriate parametric test. Upon reverse transformation, the upper and lower bounds of the confidence intervals become asymmetric about the reverse-transformed group mean of the SD. There is a need to understand what patterns of dispersion of BG over time are captured by SD as a predictor of outcomes. Among the causes of high SD, a subgroup may consist of patients having frequent oscillations of BG. Another subgroup may consist of patients experiencing a major change of overall glycemia during the timeframe of data collection. Appropriate metrics should be developed to recognize both variability in the sense of recurrent large oscillations of BG, and separately to recognize any time-dependent change of overall glycemia during hospitalization. Especially in relation to uncontrolled diabetes, there is a need to know whether rapid correction of chronic hyperglycemia adversely affects hospital outcomes. We have some understanding of how to control or prevent change of overall glycemia, and less understanding of how to control variability. Each may be associated with outcomes, and each may be detected by a high SD, but it remains uncertain whether intervention to prevent either pattern of changing glycemia would affect outcomes.

Neutrino mass implications for muon decay parameters

We use the scale of neutrino mass and naturalness considerations to obtain model-independent expectations for the magnitude of possible contributions to muon decay Michel parameters from new physics above the electroweak symmetry-breaking scale. Focusing on Dirac neutrinos, we obtain a complete basis of dimension four and dimension six effective operators that are invariant under the gauge symmetry of the standard model and that contribute to both muon decay and neutrino mass. We show that---in the absence of fine tuning---the most stringent neutrino-mass naturalness bounds on chirality-changing vector operators relevant to muon decay arise from one-loop operator mixing. The bounds we obtain on their contributions to the Michel parameters are 2 orders of magnitude stronger than bounds previously obtained in the literature. In addition, we analyze the implications of one-loop matching considerations and find that the expectations for the size of various scalar and tensor contributions to the Michel parameters are considerably smaller than derived from previous estimates of two-loop operator mixing. We also show, however, that there exist gauge-invariant operators that generate scalar and tensor contributions to muon decay but whose flavor structure allows them to evade neutrino-mass naturalness bounds. We discuss the implications of our analysis for the interpretation of muon-decay experiments.

Electroweak breaking and supersymmetry breaking

We discuss the clash between the absence of fine tuning in the Higgs potential and a sufficient suppression of flavour changing neutral current transitions in supersymmetric extensions of the standard model. It is pointed out that horizontalU(1) symmetry combined with theD-term supersymmetry breaking provides a realistic framework for solving both problems.

Fine‐tuning Corrective Feedback

Abstract: This paper explores the notion of “fine‐tuning” in connection with the corrective feedback process. The underlying argument is that the absence of fine‐tuning can be a potent source of ineffective feedback. Fine‐tuning is herein defined as a process whereby the provider of corrective feedback tunes in to the causal factors of an error and successfully brings the learner's attention to the learning problem. A longitudinal case study, conducted in the context of Norwegian as a second language, is presented to show how fine‐tuning and lack thereof in the provision of written corrective feedback differentially affects an L2 learner's restructuring of an interlanguage construction.

Soft SUSY breaking terms in stringy scenarios. Computation and phenomenological viability

We calculate the soft SUSY breaking terms arising from a large class of string scenarios, namely symmetric orbifold constructions, and study its phenomenological viability. They exhibit a certain lack of universality, unlike the usual assumptions of the minimal supersymmetric standard model. Assuming gaugino condensation in the hidden sector as the source of SUSY breaking, it turns out that squark and slepton masses tend to be much larger than gaugino masses. Furthermore, we show that these soft breaking terms can be perfectly consistent with both experimental and naturalness constraints (the latter comes from the absence of fine tuning in the SU(2) × U(1) Y → U(1) em breaking process). This is certainly non-trivial and in fact imposes interesting constraints on measurable quantities. More precisely, we find that the gluino mass ( M 3) and the chargino mass ( M χ ±) cannot be much higher than their present experimental lower bounds ( M 3⪅285 GeV; M χ ± ⪅80 GeV), while squark and slepton masses must be much larger ( ⪆1 TeV ). This can be considered as an observational signature of this kind of stringy scenarius. Besides, the top mass is constrained to be within a range (80⪅ m t ⪅165 GeV) remarkably consistent with its present experimental bounds.