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Solving the discrete logarithm problem in a finite prime field is an extremely important computing problem in modern cryptography. The hardness of solving the discrete logarithm problem in a finite prime field is the security foundation of numerous cryptography schemes. In this paper, we propose the double index calculus algorithm to solve the discrete logarithm problem in a finite prime field. Our algorithm is faster than the index calculus algorithm, which is the state-of-the-art algorithm for solving the discrete logarithm problem in a finite prime field. Empirical experiment results indicate that our algorithm could be more than a 30-fold increase in computing speed than the index calculus algorithm when the bit length of the order of prime field is 70 bits. In addition, our algorithm is more general than the index calculus algorithm. Specifically, when the base of the target discrete logarithm problem is not the multiplication generator, the index calculus algorithm may fail to solve the discrete logarithm problem while our algorithm still can work.

In this paper, we introduce a Unet model of deep learning algorithms for reconstructions of the 3D peculiar velocity field, which simplifies the reconstruction process with enhanced precision. We test the adaptability of the Unet model with simulation data under more realistic conditions, including the redshift space distortion (RSD) effect and halo mass threshold. Our results show that the Unet model outperforms the analytical method that runs under ideal conditions, with a 16% improvement in precision, 13% in residuals, 18% in correlation coefficient and 27% in average coherence. The deep learning algorithm exhibits exceptional capacities to capture velocity features in non-linear regions and substantially improve reconstruction precision in boundary regions. We then apply the Unet model trained under SDSS observational conditions to the SDSS DR7 data for observational 3D peculiar velocity reconstructions.

In this investigation, we leverage the combination of Dark Energy Spectroscopic Instrument Legacy imaging Surveys Data Release 9 (DESI LS DR9), Survey Validation 3 (SV3), and Year 1 (Y1) data sets to estimate the conditional luminosity and stellar mass functions (CLFs & CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI Mock Galaxy Redshift Survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low redshift bin at low luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift the faint end slopes of CLFs and CSMFs below $10^{9}h^{-2}L_{\odot}$ (or $h^{-2}M_{\odot}$) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following arXiv:1809.00523, the faint end slopes of the LFs/SMFs turn out to be also in good agreement with the slope of the halo mass function., Comment: 28 pages, 13 figures, Accepted for publication in ApJ

We compare the transport properties of a well-characterized hydrogen plasma for low and high current ion beams. The energy-loss of low current beams can be well understood, within the framework of current stopping power models. However, for high current proton beams, significant energy-loss reduction and collimation is observed in the experiment. We have developed a new particle-in-cell code, which includes both collective electromagnetic effects and collisional interactions. Our simulations indicate that resistive magnetic fields, induced by the transport of an intense proton beam, act to collimate the proton beam and simultaneously deplete the local plasma density along the beam path. This in turn causes the energy-loss reduction detected in the experiment.

We present an improved method for calculating the parallel and perpendicular velocity correlation functions directly from peculiar velocity surveys using weighted maximum-likelihood estimators. A central feature of the new method is the use of position-dependent weighting scheme that reduces the influence of nearby galaxies, which are typically overrepresented relative to the more distant galaxies in most surveys. We demonstrate that the correlation functions calculated this way are less susceptible to biases due to our particular location in the Universe, and thus are more easily comparable to linear theory and between surveys. Our results suggest that the parallel velocity correlation function is a promising cosmological probe, given that it provides a better approximation of a Gaussian distribution than other velocity correlation functions and that its bias is more easily minimized by weighting. Though the position weighted parallel velocity correlation function increases the statistical uncertainty, it decreases the cosmic variance and is expected to provide more stable and tighter cosmological parameter constraints than other correlation methods in conjunction with more precise velocity surveys in the future., Comment: 15 pages, 13 figures

Assume that $M$ is a compact connected unitary 2n-dimensional manifold and admits a non-trivial circle action preserving the given complex structure. If the first Chern class of $M$ equals to $k_0x$ for a certain 2nd integral cohomology class $x$ with $|k_0|\geq n + 2$, and its first integral cohomology group is zero, this short paper shows that the Todd genus and $A_k$-genus of $M$ vanish., Comment: 7 pages

We study the elliptic genera of level $N$ at the cusps of $\Gamma_1(N)$ for any complete intersection. These genera are described as the summations of generalized binomial coefficients, where each generalized binomial coefficient is related to the dimension and multi-degree of complete intersection. For complete intersection $X_n(\underline{d})$, write $c_1(X_n(\underline{d}))=c_1x$, where $x\in H^2(X_n(\underline{d});\mathbb{Z})\cong\mathbb{Z}$ is a generator. We mainly discuss the values of the elliptic genera of level $N$ for $X_n(\underline{d})$ in the case of $c_1>0, =0$ or $<0$. In particular, the values about the Todd genus, $\hat{A}$-genus and $A_k$-genus of $X_n(\underline{d})$ can be derived from the elliptic genera of level $N$., Comment: 18 pages, 1 table

The Sunyaev-Zel'dolvich (SZ) effect is expected to be instrumental in measuring velocities of distant clusters in near future telescope surveys. We simplify the calculation of peculiar velocities of galaxy clusters using deep learning frameworks trained on numerical simulations to avoid the estimation of the optical depth. The image of distorted photon backgrounds are generated for idealized observations using one of the largest cosmological hydrodynamical simulations, the Magneticum simulations. The model is tested to be capable peculiar velocities from future kinetic SZ observations under different noise conditions. The deep learning algorithm displays robustness in estimating peculiar velocities from kinetic SZ effect by an improvement in accuracy of about 17% compared to the analytical approach., Comment: 10 pages, 12 figures, Submitted to MNRAS

In this paper, we give three pairs of complex 3-dim complete intersections and a pair of complex 5-dim complete intersections, and every pair of them is diffeomorphic but with different Hodge numbers. Moreover, the diffeomorphic complex 3-dim complete intersections have different Chern mumbers $c_1^3, c_1c_2$., Comment: 7 pages, 2 tables

Following Brooks's calculation of the $\hat{A}$-genus of complete intersections, a new and more computable formula about the $\hat{A}$-genus and $\alpha$-invariant will be described as polynomials of multi-degree and dimension. We also give an iterated formula of $\hat{A}$-genus and the necessary and sufficient conditions for the vanishing of $\hat{A}$-genus of complex even dimensional spin complete intersections. Finally, we obtain a general formula about the Hirzebruch genus of complete intersections, and calculate some classical Hirzebruch genera as examples., Comment: Revised version: Remarks 3.3 and 3.4 are removed due to an error in 3.4. Some arguments simplified. Comments are welcome!

We present an analysis of the two-point peculiar velocity correlation function using data from the CosmicFlows catalogues. The Millennium and MultiDark Planck 2 N-body simulations are used to estimate cosmic variance and uncertainties due to measurement errors. We compare the velocity correlation function to expectations from linear theory to constrain cosmological parameters. Using the maximum likelihood method, we find values of $\Omega_m= 0.315^{+0.205}_{-0.135}$ and $\sigma_8=0.92^{+0.440}_{-0.295}$, consistent with the Planck and Wilkinson Microwave Anisotropy Probe CMB derived estimates. However, we find that the cosmic variance of the correlation function is large and non-Gaussian distributed, making the peculiar velocity correlation function less than ideal as a probe of large-scale structure., Comment: 12 pages, 13 figures