Enlightening the CSL model landscape in inflation

We propose a novel realization for the natural extrapolation of the continuous spontaneous localization (CSL) model, in order to account for the origin of primordial inhomogeneities during inflation. This particular model is based on three main elements: (i) the semiclassical gravity framework, (ii) a collapse-generating operator associated to a relativistic invariant scalar of the energy-momentum tensor, and (iii) an extension of the CSL parameter(s) as a function of the spacetime curvature. Furthermore, employing standard cosmological perturbation theory at linear order, and for a reasonable range within the parameter space of the model, we obtain a nearly scale invariant power spectrum consistent with recent observational CMB data. This opens a vast landscape of different options for the application of the CSL model to the cosmological context, and possibly sheds light on searches for a full covariant version of the CSL theory.

Performance Prediction of the Ferrous Metal Smelting and Rolling Processing Industry in Supply-Side Structural Reform in China

Supply-side structural reforms and environmental protection policies have a great impact on the ferrous metal smelting and rolling processing industry. This paper uses a grey model that introduces a fractional-order cumulative generating operator to study the development of ferrous metal smelting and rolling processing enterprises under the influence of supply-side structural reform in order to derive the future development trend of the industry. The forecast results show that from 2018 to 2022, the number of enterprises and substitute enterprises, inventory, finished products, and assets and liabilities decreases; the scale of income of metal smelting and rolling processing industry increases. The results can serve as a reference for policy makers and industry investors.

Discussions about the landscape of possibilities for treatments of cosmic inflation involving continuous spontaneous localization models

In this work we consider a wide variety of alternatives opened when applying the continuous spontaneous localization (CSL) dynamical collapse theory to the inflationary era. The definitive resolution of many of the issues discussed here will have to await, not only for a general relativistic CSL theory, but for a fully workable theory of quantum gravity. Our concern here is to explore these issues, and to warn against premature conclusions. This exploration includes: two different approaches to deal with quantum field theory and gravitation, the identification of the collapse-generating operator and the general nature and values of the parameters of the CSL theory. All the choices connected with these issues have the potential to dramatically alter the conclusions one can draw. We also argue that the incompatibilities found in a recent paper, between the CSL parameter values and the cosmic microwave background observational data, are associated with specific choices made for the extrapolation to the cosmological context of the CSL theory (as it is known to work in non-relativistic laboratory situations) which do not represent the most natural ones.

Metric algebroid and Dirac generating operator in Double Field Theory

We give a formulation of Double Field Theory (DFT) based on a metric algebroid. We derive a covariant completion of the Bianchi identities, i.e. the pre-Bianchi identity in torsion and an improved generalized curvature, and the pre-Bianchi identity including the dilaton contribution. The derived bracket formulation by the Dirac generating operator is applied to the metric algebroid. We propose a generalized Lichnerowicz formula and show that it is equivalent to the pre-Bianchi identities. The dilaton in this setting is included as an ambiguity in the divergence. The projected generalized Lichnerowicz formula gives a new formulation of the DFT action. The closure of the generalized Lie derivative on the spin bundle yields the Bianchi identities as a consistency condition. A relation to the generalized supergravity equations (GSE) is discussed.

PERAMALAN HARGA EMAS BATANGAN MENGGUNAKAN METODE GREY DOUBLE EXPONENTIAL SMOOTHING

Grey Double Exponential Smoothing (GDES) merupakan gabungan dari metode grey dan double exponential smoothing yang digunakan untuk melakukan peramalan data deret waktu yang berpola trend dengan keacakan, ketidakteraturan dan keterbatasan informasi data yang ada. Grey accumulated generating operator (r-AGO) yang dapat memuluskan gangguan acak data dimasukkan ke dalam metode double exponential smoothing sehingga kecenderungan pola data dapat dilihat dengan jelas. Hasil peramalan metode GDES diperoleh dengan cara mentransformasikan balik data transformasi r-AGO menggunakan inverse accumulated generating operator (IAGO). Penelitian ini bertujuan meramalkan harga emas batangan pada bulan Januari sampai Juni tahun 2020 menggunakan metode GDES serta mengukur kesalahan peramalan yang dihasilkan metode tersebut. Keakuratan hasil peramalan yang digunakan adalah mean absolute precentage error (MAPE). Dataset yang digunakan pada penelitian ini adalah rata-rata harga emas batangan per gram dari bulan Januari 2016 sampai Desember 2019. Hasil peramalan harga emas yang diperoleh menggunakan metode GDES menunjukkan trend naik setiap bulannya dengan hasil peramalan terendah adalah Rp.755.340,39 pada bulan Januari 2020 dan hasil peramalan tertinggi adalah Rp.763.833,70 pada bulan Juni 2020. Nilai MAPE yang dihasilkan sebesar 1,53% yang berarti bahwa peramalan GDES untuk harga emas batangan termasuk dalam kategori peramalan yang sangat baik. Kata Kunci : peramalan, exponential smoothing, grey, r-AGO, IAGO, MAPE

A Novel Weighted Fractional GM(1,1) Model and Its Applications

Based on the ideas of the new information priority principle and the fractional-accumulation generating operator, in this paper we propose a novel weighted fractional GM(1,1) (WFGM(1,1)) prediction model. In the new model, the original sequence is first transformed by using the weighted fractional-accumulation generating operator, which involves two parameters. With special choices of these parameters, the proposed WFGM(1,1) model reduces to the classical GM(1,1) model and the fractional GM(1,1) (FGM(1,1)) model, as well as the new information priority GM(1,1) (NIPGM(1,1)) model studied recently. Stability property of the WFGM(1,1) model is studied in detail. In practice, the quantum particle swarm optimization algorithm is adopted to choose the quasi-optimal parameters for the new model so as to get the best fitting accuracy. Finally, four numerical examples from different practical applications are present. Numerical results show that the new proposed prediction model is very efficient and has both the best fitting accuracy and the best prediction accuracy compared with the GM(1,1) and the FGM(1,1) as well as the NIPGM(1,1) prediction models.