Results 91 to 100 of about 205,236 (293)
Anomaly detection in the presence of irrelevant features
Experiments at particle colliders are the primary source of insight into physics at microscopic scales. Searches at these facilities often rely on optimization of analyses targeting specific models of new physics. Increasingly, however, data-driven model-
Marat Freytsis +2 more
doaj +1 more source
Adversarially-trained autoencoders for robust unsupervised new physics searches
Machine learning techniques in particle physics are most powerful when they are trained directly on data, to avoid sensitivity to theoretical uncertainties or an underlying bias on the expected signal.
Andrew Blance +2 more
doaj +1 more source
Anthropic solution to the magnetic muon anomaly: the charged see-saw
We present models of new physics that can explain the muon g-2 anomaly in accord with with the assumption that the only scalar existing at the weak scale is the Higgs, as suggested by anthropic selection.
A Czarnecki +34 more
core +1 more source
Possible physics scenarios behind cosmic-ray anomalies [PDF]
16 pages, 4 figures. Highlight talk contribution to the Proceeding of the 34th International Cosmic Ray Conference, The Hague, The ...
openaire +2 more sources
Electrochromic polymer stability under overpotential is improved by inserting an ultrathin, transparent n‐doped poly(benzodifurandione) interlayer between indium tin oxide and a poly(3,4‐propylenedioxythiophene)‐based electrochromic polymer. The interlayer supports rapid switching at operating bias, then becomes resistive near +0.8 V to suppress excess
Priyanka Rout +4 more
wiley +1 more source
High-dimensional and permutation invariant anomaly detection
Methods for anomaly detection of new physics processes are often limited to low-dimensional spaces due to the difficulty of learning high-dimensional probability densities. Particularly at the constituent level, incorporating desirable properties such as
Vinicius Mikuni, Benjamin Nachman
doaj +1 more source
Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection [PDF]
This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from a particle detector.
Grosso Gaia +6 more
doaj +1 more source
We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
These lectures provide a simple introduction to supersymmetry breaking. After presenting the basics of the subject and illustrating them in tree-level examples, we discuss dynamical supersymmetry breaking, emphasizing the role of holomorphy and ...
Affleck +27 more
core +2 more sources
Omnipolar Magnetic Field Detection by Superlattice‐Based Hall Sensor
Magnetic‐field‐induced electronic switching is demonstrated in unit‐cell‐engineered La0.7Sr0.3MnO3–BiFeO3 superlattices. Distinct substrate terminations modify magnetic and transport properties. Hall resistance measurements show omnipolar, hysteretic anomalous Hall switching above the Curie temperature, arising from Fe─Mn interfacial exchange, enabling
Mark Huijben +6 more
wiley +1 more source

