On the Complexity of Grid Coloring

This thesis studies problems at the intersection of Ramsey-theoretic mathematics, computational complexity, and communication complexity. The prototypical example of such a problem is Monochromatic-Rectangle-Free Grid Coloring. In an instance of Monochromatic-Rectangle-Free Grid Coloring, we are given a chessboard-like grid graph of dimensions n and m, where the vertices of the graph correspond to squares in the chessboard, and a number of allowed colors, c. The goal is to assign one of the allowed colors to each vertex of the grid graph so that no four vertices arranged in an axis-parallel rectangle are colored monochromatically. Our results include: 1. A conditional, graph-theoretic proof that deciding Monochromatic-Rectangle-Free Grid Coloring requires time superpolynomial in the input size. 2. A natural interpretation of Monochromatic-Rectangle-Free Grid Coloring as a lower bound on the communication complexity of a cluster of related predicates. 3. Original, best-yet, monochromatic-square-free grid colorings: a 2-coloring of the 13 x 13 grid, and a 3-coloring of the 39 x 39 grid. 4. An empirically-validated computational plan to decide a particular instance of Monochromatic-Rectangle-Free Grid Coloring that has been heavily studied by the broader theory community, but remains unsolved: whether the 17 x 17 grid can be 4-colored without monochromatic rectangles. Our plan is based in high-performance computing and is expected to take one year to complete

Complexity Theory

Computational Complexity Theory is the mathematical study of the intrinsic power and limitations of computational resources like time, space, or randomness. The current workshop focused on recent developments in various sub-areas including arithmetic complexity, Boolean complexity, communication complexity, cryptography, probabilistic proof systems, pseudorandomness and randomness extraction. Many of the developments are related to diverse mathematical fields such as algebraic geometry, combinatorial number theory, probability theory, representation theory, and the theory of error-correcting codes

Unconditional Lower Bounds in Complexity Theory

This work investigates the hardness of solving natural computational problems according to different complexity measures. Our results and techniques span several areas in theoretical computer science and discrete mathematics. They have in common the following aspects: (i) the results are unconditional, i.e., they rely on no unproven hardness assumption from complexity theory; (ii) the corresponding lower bounds are essentially optimal. Among our contributions, we highlight the following results. Constraint Satisfaction Problems and Monotone Complexity. We introduce a natural formulation of the satisfiability problem as a monotone function, and prove a near-optimal 2^{Ω (n/log n)} lower bound on the size of monotone formulas solving k-SAT on n-variable instances (for a large enough k ∈ ℕ). More generally, we investigate constraint satisfaction problems according to the geometry of their constraints, i.e., as a function of the hypergraph describing which variables appear in each constraint. Our results show in a certain technical sense that the monotone circuit depth complexity of the satisfiability problem is polynomially related to the tree-width of the corresponding graphs. Interactive Protocols and Communication Complexity. We investigate interactive compression protocols, a hybrid model between computational complexity and communication complexity. We prove that the communication complexity of the Majority function on n-bit inputs with respect to Boolean circuits of size s and depth d extended with modulo p gates is precisely n/log^{ϴ(d)} s, where p is a fixed prime number, and d ∈ ℕ. Further, we establish a strong round-separation theorem for bounded-depth circuits, showing that (r+1)-round protocols can be substantially more efficient than r-round protocols, for every r ∈ ℕ. Negations in Computational Learning Theory. We study the learnability of circuits containing a given number of negation gates, a measure that interpolates between monotone functions, and the class of all functions. Let C^t_n be the class of Boolean functions on n input variables that can be computed by Boolean circuits with at most t negations. We prove that any algorithm that learns every f ∈ C^t_n with membership queries according to the uniform distribution to accuracy ε has query complexity 2^{Ω (2^t sqrt(n)/ε)} (for a large range of these parameters). Moreover, we give an algorithm that learns C^t_n from random examples only, and with a running time that essentially matches this information-theoretic lower bound. Negations in Theory of Cryptography. We investigate the power of negation gates in cryptography and related areas, and prove that many basic cryptographic primitives require essentially the maximum number of negations among all Boolean functions. In other words, cryptography is highly non-monotone. Our results rely on a variety of techniques, and give near-optimal lower bounds for pseudorandom functions, error-correcting codes, hardcore predicates, randomness extractors, and small-bias generators. Algorithms versus Circuit Lower Bounds. We strengthen a few connections between algorithms and circuit lower bounds. We show that the design of faster algorithms in some widely investigated learning models would imply new unconditional lower bounds in complexity theory. In addition, we prove that the existence of non-trivial satisfiability algorithms for certain classes of Boolean circuits of depth d+2 leads to lower bounds for the corresponding class of circuits of depth d. These results show that either there are no faster algorithms for some computational tasks, or certain circuit lower bounds hold

A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms

Parameterization and approximation are two popular ways of coping with NP-hard problems. More recently, the two have also been combined to derive many interesting results. We survey developments in the area both from the algorithmic and hardness perspectives, with emphasis on new techniques and potential future research directions

On Computational Shortcuts for Information-Theoretic PIR

Information-theoretic private information retrieval (PIR) schemes have attractive concrete efficiency features. However, in the standard PIR model, the computational complexity of the servers must scale linearly with the database size. We study the possibility of bypassing this limitation in the case where the database is a truth table of a simple function, such as a union of (multi-dimensional) intervals or convex shapes, a decision tree, or a DNF formula. This question is motivated by the goal of obtaining lightweight homomorphic secret sharing (HSS) schemes and secure multiparty computation (MPC) protocols for the corresponding families. We obtain both positive and negative results. For first-generation PIR schemes based on Reed-Muller codes, we obtain computational shortcuts for the above function families, with the exception of DNF formulas for which we show a (conditional) hardness result. For third-generation PIR schemes based on matching vectors, we obtain stronger hardness results that apply to all of the above families. Our positive results yield new information-theoretic HSS schemes and MPC protocols with attractive efficiency features for simple but useful function families. Our negative results establish new connections between information-theoretic cryptography and fine-grained complexity

Quantum Cryptography Beyond Quantum Key Distribution

Quantum cryptography is the art and science of exploiting quantum mechanical effects in order to perform cryptographic tasks. While the most well-known example of this discipline is quantum key distribution (QKD), there exist many other applications such as quantum money, randomness generation, secure two- and multi-party computation and delegated quantum computation. Quantum cryptography also studies the limitations and challenges resulting from quantum adversaries---including the impossibility of quantum bit commitment, the difficulty of quantum rewinding and the definition of quantum security models for classical primitives. In this review article, aimed primarily at cryptographers unfamiliar with the quantum world, we survey the area of theoretical quantum cryptography, with an emphasis on the constructions and limitations beyond the realm of QKD.Comment: 45 pages, over 245 reference