State Research Center – Institute for High Energy Physics (IHEP) is a research organisation in Protvino (near Moscow, Moscow Oblast), Russia. It was established in 1963.The institute is known for the particle accelerator U-70 synchrotron launched in 1967 with the maximum proton energy of 70 GeV, which had the largest proton energy in the world for five years.The first director of the institute from 1963 to 1974 was Anatoly Logunov. From 1974 to 1993 professor Lev Solovyov (Russian: Лев Дмитриевич Соловьев) served as the director of the institute. A professor, Nikolai E. Tyurin has been the director of the institute since 2003.In 1978, a scientist of the institute, Anatoli Bugorski, was irradiated by an extreme dose of proton beam. His demise was deemed inevitable as the doctors believed he had received a dosage far in excess of what could be considered fatal. However, he survived the accident and continued to work in the institute.
We present galaxy luminosity functions (LFs) for the Dark Energy Spectroscopic Instrument (DESI) DR2 Bright Galaxy Survey (BGS) in the g, r, z, and wl bands over 0.002 < z < 0.6 Our analysis uses updated k-corrections and evolutionary corrections, including new polynomial kcorrection fits derived from BGS Year 1 data that supersede earlier GAMA-based prescriptions. Exploiting the statistical power of DESI, we measure LFs to very faint magnitudes, reaching M-0.1(r)- 5 logh similar to -10. Independent measurements from the North and South survey regions show excellent agreement around the LF knee, but the very small statistical uncertainties reveal that simple analytic forms fail to capture the full LF shape. The bright end departs from a pure exponential decline, while the faint end exhibits complex, non-powerlaw behaviour, including a pronounced upturn at M-0.1(r) - 5 log(h) greater than or similar to - 15, which is stronger for red galaxies than for blue. We show that our LFs are largely complete for galaxies with surface brightness mu(50) < 25 and that an apparent steepening fainter than -13 is driven primarily by local overdensity and fragmentation of large galaxies. A systematic North-South offset at the brightest magnitudes is traced to red galaxies and may reflect shallower North photometry underestimating extended earlytype profiles, although this remains inconclusive. We therefore also provide LFs based on model Petrosian magnitudes. Redshift splitting reveals small but significant residuals, indicating limitations of a simple global evolutionary model. Using the redshift limits of J. Loveday et al. (2012), we find excellent agreement with GAMA, with substantially reduced statistical errors. These measurements provide a precise reference for studies of environmental and population-dependent LFs and for testing galaxy formation models.
Using an up-to-date compilation of σ_tot(e^+e^- → hadrons) data we estimated the LO hadronic contribution to the muon anomalous magnetic moment, a_μ(had,LO). Incompatibilities between σ_tot(e^+e^- → hadrons) measurements by independent experiments are mitigated by extra systematic uncertainties estimated using as a guideline a requirement of uniformity of χ^2 distribution over degrees of freedom in joint fits of σ_tot. Tensions in the e^+e^- input data translate into an expanded uncertainty of the a_μ(had,LO) = (697.7 ±9.8_e^+e^-± 3.6_sys) × 10^-10. Given this, we obtain the SM prediction for the muon anomaly a_μ^SM = 11659185.5(10.6) × 10^-10, below the experimental world average a_μ^exp at 2σ level.
We discuss energy scales in soft hadron scattering and possibility of their separation: the one relevant to the region where the total cross-sections increase begins and another one related to the asymptotic region. The latter scale is most sensitive to the unitarity effects and former one – to the gross features of absorption of the initial wave due to multiparticle production. Transition from the shadow to reflective scattering sets a relation between the two energy scales.
Materials science has traditionally relied on a combination of experimental techniques and theoretical modeling to discover and develop new materials with desired properties. However, these processes can be time‐consuming, resource‐intensive, and often limited by the complexity of material systems. The advent of artificial intelligence (AI), particularly machine learning, has revolutionized materials science by offering powerful tools to accelerate the discovery, design, and characterization of novel materials. AI not only enhances the predictive modeling of material properties but also streamlines data analysis in techniques like X‐Ray diffraction, Raman spectroscopy, scanning probe microscopy, and electron microscopy. By leveraging large datasets, AI algorithms can identify patterns, reduce noise, and predict material behavior with unprecedented accuracy. In this review, recent advancements in AI applications across various domains of materials science, including spectroscopy, synchrotron studies, scanning probe and electron microscopies, metamaterials, atomistic modeling, molecular design, and drug discovery, are highlighted. It is discussed how AI‐driven methods are reshaping the field, making material discovery more efficient, and paving the way for breakthroughs in material design and real‐time experimental analysis.
We survey the opportunities offered by the detection of the forward muons that accompany the creation of neutral effective vector bosons at a muon collider, in different kinematic regimes. Vectors with relatively low energy produce the Higgs boson and the extended muon angular coverage enables studies of the Higgs properties, such as the measurement of the inclusive production cross section and the branching ratio to invisible final states. New heavy particles could be produced by vectors of higher energy, through Higgs portal interactions. If the new particles are invisible, the detection of the forward muons is essential in order to search for this scenario. The angular correlations of the forward muons are sensitive to the quantum interference between the vector-boson helicity amplitudes and can be exploited for the characterization of vector-boson scattering and fusion processes. This is illustrated by analyzing the CP properties of the Higgs coupling to the Z boson. Our findings provide a physics case and a set of benchmarks for the design of a dedicated forward muon detector.
