More than fifty years after his death, Albert Einstein's vital engagement with the world continues to inspire others, spurring conversations, projects, and research, in the sciences as well as the humanities. Einstein for the 21st Century shows us why he remains a figure of fascination.

Examines humankind's changing awareness of its place in the universe and the rich potential of human ventures into the world beyond Earth. In a tour of our solar system, galaxy and beyond, Cornell astronomer Sagan meshes a history of astronomical discovery, a cogent brief for space exploration and an overview of life-from its origins in the oceans to humanity's first emergence to a projected future where humans "terraform" and settle other planets and asteroids, Earth having long been swallowed by the sun. Maintaining that such relocation is inevitable, the author further argues that planetary science is of practical utility, fostering an interdisciplinary approach to looming environmental catastrophes such as "nuclear winter" (lethal cooling of Earth after a nuclear war, a widely accepted prediction first calculated by Sagan in 1982). His exploration of our place in the universe is illustrated with photographs, relief maps and paintings, including high-resolution images made by Voyager 1 and 2, as well as photos taken by the Galileo spacecraft, the Hubble Space Telescope and satellites orbiting Earth, which show our planet as a pale blue dot. A worthy sequel to Sagan's Cosmos.

In this rigorous account the author studies both discrete-time and continuous-time chains. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials, in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and a careful selection of exercises and examples drawn both from theory and practice. This is an ideal text for seminars on random processes or for those that are more oriented towards applications, for advanced undergraduates or graduate students with some background in basic probability theory.