
By Richard Panek
ISBN-10: 0618982442
ISBN-13: 9780618982448
Some time past few years, a handful of scientists were racing to provide an explanation for a hectic point of our universe: in simple terms four percentage of it contains the problem that makes up you, me, our books, and each planet, megastar, and galaxy. The rest—96 percentage of the universe—is thoroughly unknown.
Richard Panek tells the dramatic tale of the way scientists reached this cosmos-shattering end, and what they’re doing to discover this "dark" topic and a fair weirder substance known as darkish power. this is often probably the best secret in all of technology, and fixing it's going to carry repute, investment, and positively a Nobel Prize. in keeping with in-depth, on-site reporting and countless numbers of interviews–with all people from Berkeley’s feisty Saul Perlmutter and Johns Hopkins’s meticulous Adam Riess to the quietly innovative Vera Rubin–the ebook bargains an intimate portrait of the sour rivalries and fruitful collaborations, the eureka moments and blind alleys, that experience fueled their seek, redefined technological know-how, and reinvented the universe.
The stakes couldn’t be better. Our view of the cosmos is profoundly fallacious, and Copernicus was once in simple terms the start: not only Earth, yet all universal topic is a marginal a part of life. Panek’s fast moving narrative, jam-packed with behind-the-scenes information, brings this epic tale to lifestyles for the first actual time.
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Additional info for The 4 Percent Universe: Dark Matter, Dark Energy, and the Race to Discover the Rest of Reality
Sample text
In this case the complexity of a given graph turns into a monotone complexity of monotone boolean functions “representing” this graph in the following sense. Let G = (V, E) be an n-vertex graph, and let z = {zv | v ∈ V } be a set of boolean variables, one for each vertex (not for each subset P ⊆ V , as before). Say that a boolean function (or a circuit) g(z) represents the graph G if, for every input a ∈ {0, 1}n with exactly two 1s in, say, positions u = v, g(a) = 1 iff u and v are adjacent in G.
In this way we reach a sink, and the input a is accepted iff this is the 1-sink. Thus, a deterministic branching program is a nondeterministic branching program with the restriction that each non-sink node has fanout 2, and the two outgoing wires from each such node are labeled by the tests xi = 0 and xi = 1 on the same variable xi . The presence of the 0-sink is just to ensure that each input vector can reach a sink. A decision tree is a deterministic branching program whose underlying graph is a binary tree.
8 A constant factor away from P = NP? F 43 the same circuit! F AND and OR gates AND and OR gates 4m input literals 4m ORs of new variables 2n = 2 m+1 new variables Fig. 12 Having a circuit F computing a boolean function f of 2m variables, we obtain a (monotone) circuit representing the graph Gf by replacing each input literal in F by an appropriate OR of new variables. ) circuit of size nǫ = 2ǫm , which is already exponential in the number of variables of f . 6 to prove truly exponential lower bounds for unbounded-fanin depth-3 circuits with parity gates on the bottom layer.
The 4 Percent Universe: Dark Matter, Dark Energy, and the Race to Discover the Rest of Reality by Richard Panek
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