We present a simple method based on a variant of Hölder's inequality to lower-bound the trace norm of Boolean matrices. As the main result, we obtain an exponential separation between the randomized decision tree depth and the spectral norm (i.e. the Fourier $L_1$-norm) of a Boolean function. This answers an ... more >>>

We study the relative advantage of classical and quantum distinguishers of bounded query complexity over $n$-bit strings, focusing on the case of a single quantum query. A construction of Aaronson and Ambainis (STOC 2015) yields a pair of distributions that is $\epsilon$-distinguishable by a one-query quantum algorithm, but $O(\epsilon k/\sqrt{n})$-indistinguishable ... more >>>

We study the randomized communication complexity of the following problem. Alice receives the integer coordinates of a point in the plane, and Bob receives the integer parameters of a half-plane, and their goal is to determine whether Alice's point belongs to Bob's half-plane.

This communication task corresponds to determining ... more >>>

In an influential paper, Linial and Shraibman (STOC '07) introduced the factorization norm as a powerful tool for proving lower bounds against randomized and quantum communication complexities. They showed that the logarithm of the approximate $\gamma_2$-factorization norm is a lower bound for these parameters and asked whether a stronger ... more >>>

The sum of the absolute values of the Fourier coefficients of a function $f:\mathbb{F}_2^n \to \mathbb{R}$ is called the spectral norm of $f$. Green and Sanders' quantitative version of Cohen's idempotent theorem states that if the spectral norm of $f:\mathbb{F}_2^n \to \{0,1\}$ is at most $M$, then the support of ... more >>>