Böcker av Michael Andrews

In the mountain town of Redemption, Wyoming, retired Sheriff John Becket, once renowned as the "Killingest lawman in the Wyoming territory, ' is content to spend his remaining days reading books he's never read before, drinking whiskey in a hammock and courting numerous town widows at once. And then Jamie, a 12-year-old grandson Becket did not know he had, knocks on his door. In Jamie, the hard-tack former sheriff sees some hope to redeem himself for his failure as a father and gradually the ornery old sheriff and the hard-headed boy begin to build trust and affection for one another.What Becket does not know is that Jamie's father, Becket's errant son is a Texas outlaw who ran away from home as a teenager, and has sent Jamie to stay with him for safekeeping after having robbed his partners, the murderous Bill and Frank Blue gang, of the money they stole from a North Texas Bank. Believing that Jamie is the key to finding the stolen money, Bill and Frank Blue hit the trail to find the boy intent to force him to take them to it, triggering what will be a violent and bloody confrontation between the murderous outlaws from Texas and the killingest lawman in Wyoming. But Sheriff Becket has a secret of his own, a recently discovered heart condition that just might just kill him before the outlaws can.

This book describes the first application at CMS of deep learning algorithms trained directly on low-level, ¿raw¿ detector data, or so-called end-to-end physics reconstruction. Growing interest in searches for exotic new physics in the CMS collaboration at the Large Hadron Collider at CERN has highlighted the need for a new generation of particle reconstruction algorithms. For many exotic physics searches, sensitivity is constrained not by the ability to extract information from particle-level data but by inefficiencies in the reconstruction of the particle-level quantities themselves. The technique achieves a breakthrough in the reconstruction of highly merged photon pairs that are completely unresolved in the CMS detector. This newfound ability is used to perform the first direct search for exotic Higgs boson decays to a pair of hypothetical light scalar particles H¿aa, each subsequently decaying to a pair of highly merged photons äyy, an analysis once thought impossible to perform. The book concludes with an outlook on potential new exotic searches made accessible by this new reconstruction paradigm.

People love telling stories. Surely, everyone has made up a story at some time to entertain their children, friends and family, haven't they? The difficult part is finding the courage to get it down on paper and letting a wider audience read it. 'Words Are Sixy' continues the writing journey of three friends, as they encourage each other to fulfil their dreams of becoming published authors. Each month, they meet to discuss their own individual projects and produce a piece of flash fiction based on a theme. This is read aloud and then critiqued by the others. This book contains the next twelve assignments that follow on from the group's previous anthology, 'Words Don't Frive', and charts the continuing growth of each of the authors. It also contains reflective comments at the start of each chapter as they look back over the pieces that they have written over the past twelve months. They hope these will provide insight into the group as authors, and act as inspiration for others to pick up their own pens to write. Maybe, like them, you will find that Words Are Sixy, but discover that with support of others, writing can be a rewarding and enjoyable experience.

This book describes the first application at CMS of deep learning algorithms trained directly on low-level, ¿raw¿ detector data, or so-called end-to-end physics reconstruction. Growing interest in searches for exotic new physics in the CMS collaboration at the Large Hadron Collider at CERN has highlighted the need for a new generation of particle reconstruction algorithms. For many exotic physics searches, sensitivity is constrained not by the ability to extract information from particle-level data but by inefficiencies in the reconstruction of the particle-level quantities themselves. The technique achieves a breakthrough in the reconstruction of highly merged photon pairs that are completely unresolved in the CMS detector. This newfound ability is used to perform the first direct search for exotic Higgs boson decays to a pair of hypothetical light scalar particles H¿aa, each subsequently decaying to a pair of highly merged photons äyy, an analysis once thought impossible to perform. The book concludes with an outlook on potential new exotic searches made accessible by this new reconstruction paradigm.