相关论文: Biased rate estimates in bump-hunt searches
The ATLAS, CMS and LHCb experiments will perform extensive searches for physics Beyond the Standard Model (BSM). The investigation of decays of beauty hadrons represents an alternative and complementary approach to the direct BSM searches.…
We explore the physics potential of using precision timing information at the LHC in searches for long-lived particles (LLPs). In comparison with the light Standard Model particles, the decay products of massive LLPs arrive at detectors…
Our predictions for particle physics processes are realized in a chain of complex simulators. They allow us to generate high-fidelity simulated data, but they are not well-suited for inference on the theory parameters with observed data. We…
The use of machine learning algorithms is an attractive way to produce very fast detector simulations for scattering reactions that can otherwise be computationally expensive. Here we develop a factorised approach where we deal with each…
Statistical hypothesis testing serves as statistical evidence for scientific innovation. However, if the reported results are intentionally biased, hypothesis testing no longer controls the rate of false discovery. In particular, we study…
Due to the high energy and luminosity of the LHC, the ATLAS experiment has a huge discovery potential for new physics. A Standard Model Higgs boson can be discovered over the full range of allowed masses, and its mass should be measured…
We present Bayesian Binary Search (BBS), a novel probabilistic variant of the classical binary search/bisection algorithm. BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and…
Physics beyond the Standard Model that is resonant in one or more dimensions has been a longstanding focus of countless searches at colliders and beyond. Recently, many new strategies for resonant anomaly detection have been developed,…
When searching for exoplanets, one wants to count how many planets orbit a given star, and to determine what their characteristics are. If the estimated planet characteristics are too far from those of a planet truly present, this should be…
The search for new significant peaks over a energy spectrum often involves a statistical multiple hypothesis testing problem. Separate tests of hypothesis are conducted at different locations producing an ensemble of local p-values, the…
The bias in the determination of the Hubble parameter and the Hubble constant in the modern Universe is discussed. It could appear due to statistical processing of data on galaxies redshifts and estimated distances based on some statistical…
Different ways of extracting parameters of interest from combined data sets of separate experiments are investigated accounting for the systematic errors. It is shown, that the frequentist approach may yield larger $\chi^2$ values when…
The problem of detecting the presence of a signal that can lead to a disaster is studied. A decision-maker collects data sequentially over time. At some point in time, called the change point, the distribution of data changes. This change…
Systematic uncertainties in the light-element abundances and their evolution make a rigorous statistical assessment difficult. However, using Bayesian methods we show that the following statement is robust: the predicted and measured…
Particle identification using the energy loss in silicon detectors is a powerful technique for probing the Standard Model (SM) as well as searching for new particles beyond the SM. Traditionally, such techniques use the truncated mean of…
Given the lack of evidence for new particle discoveries at the Large Hadron Collider (LHC), it is critical to broaden the search program. A variety of model-independent searches have been proposed, adding sensitivity to unexpected signals.…
In this paper we describe a novel, model-independent technique of "rectangular aggregations" for mining the LHC data for hints of new physics. A typical (CMS) search now has hundreds of signal regions, which can obscure potentially…
Many randomized approximation algorithms operate by giving a procedure for simulating a random variable $X$ which has mean $\mu$ equal to the target answer, and a relative standard deviation bounded above by a known constant $c$. Examples…
To what extent can particulate random media be characterised using direct wave backscattering from a single receiver/source? Here, in a two dimensional setting, we show using a machine learning approach that both the particle radius and…
The discovery of a new type of a heavy long-lived particle (LLP) would be of fundamental significance due to their existence in many beyond the Standard Model scenarios. LLPs are anticipated in a wide range of physics models which extend…