  Random $k$-SAT is the single most intensely studied example of a random
constraint satisfaction problem. But despite substantial progress over the past
decade, the threshold for the existence of satisfying assignments is not known
precisely for any $k\geq3$. The best current results, based on the second
moment method, yield upper and lower bounds that differ by an additive $k\cdot
\frac{\ln2}2$, a term that is unbounded in $k$ (Achlioptas, Peres: STOC 2003).
The basic reason for this gap is the inherent asymmetry of the Boolean value
`true' and `false' in contrast to the perfect symmetry, e.g., among the various
colors in a graph coloring problem. Here we develop a new asymmetric second
moment method that allows us to tackle this issue head on for the first time in
the theory of random CSPs. This technique enables us to compute the $k$-SAT
threshold up to an additive $\ln2-\frac12+O(1/k)\approx 0.19$. Independently of
the rigorous work, physicists have developed a sophisticated but non-rigorous
technique called the "cavity method" for the study of random CSPs (M\'ezard,
Parisi, Zecchina: Science 2002). Our result matches the best bound that can be
obtained from the so-called "replica symmetric" version of the cavity method,
and indeed our proof directly harnesses parts of the physics calculations.
