Proving complexity lower bounds remains a challenging task: currently, we only know how to prove conditional uniform (algorithm) lower bounds and nonuniform (circuit) lower bounds in restricted circuit models. About a decade ago, Williams (STOC 2010) showed how to derive nonuniform lower bounds from uniform upper bounds: roughly, by designing a fast algorithm for checking satisfiability of circuits, one gets a lower bound for this circuit class. Since then, a number of results of this kind have been proved. For example, Jahanjou et al. (ICALP 2015) and Carmosino et al. (ITCS 2016) proved that if NSETH fails, then $E^{NP}$ has series-parallel circuit size $\omega(n)$.

One can also derive nonuniform lower bounds from nondeterministic uniform lower bounds. Perhaps the most well-known example is the Karp--Lipton theorem (STOC 1980): if $\Sigma_2 \neq \Pi_2$, then $NP \not\subset P/poly$. Some recent examples include the following. Nederlof (STOC 2020) proved a lower bound on the matrix multiplication tensor rank under an assumption that TSP cannot be solved faster than in $2^n$ time. Belova et al. (SODA 2024) proved that there exists an explicit polynomial family of arithmetic circuit size $\Omega(n^{\delta})$, for any $\delta > 0$, assuming that MAX-3-SAT cannot be solved faster than in $2^n$ nondeterministic time. Williams (FOCS 2024) proved an exponential lower bound for $ETHR \circ ETHR$ circuits under the Orthogonal Vectors conjecture. Under an assumption that the Set Cover problem cannot be solved faster than in $2^n$, Björklund and Kaski (STOC 2024) and Pratt (STOC 2024) constructed an explicit tensor with superlinear rank. Whereas all of the lower bounds above are proved under strong assumptions that might eventually be refuted, the revealed connections are of great interest and may still give further insights: one may be able to weaken the used assumptions or to construct generators from other fine-grained reductions.

In this paper, we continue developing this line of research and show how uniform nondeterministic lower bounds can be used to construct generators of various types of combinatorial objects that are notoriously hard to analyze: Boolean functions of high circuit size, matrices of high rigidity, and tensors of high rank. Specifically, we prove the following.

- If, for some $\varepsilon$ and $k$, $k$-SAT cannot be solved in input-oblivious co-nondeterministic time $O(2^{(1/2+\varepsilon)n})$, then there exists a monotone Boolean function family in $coNP$ of monotone circuit size $2^{\Omega(n / \log n)}$. Combining this with the result above, we get win-win circuit lower bounds: either $E^{NP}$ requires series-parallel circuits of size $\omega(n)$ or $coNP$ requires monotone circuits of size $2^{\Omega(n / \log n)}$.
- If, for all $\varepsilon>0$, MAX-3-SAT cannot be solved in co-nondeterministic time $O(2^{(1 - \varepsilon)n})$, then there exist small families of matrices with rigidity exceeding the best known constructions as well as small families of three-dimensional tensors of rank $n^{1+\Delta}$, for some $\Delta>0$.

Fix the abstract at ECCC

Proving complexity lower bounds remains a challenging task: currently, we only know how to prove conditional uniform (algorithm) lower bounds and nonuniform (circuit) lower bounds in restricted circuit models. About a decade ago, Williams (STOC 2010) showed how to derive nonuniform lower bounds from uniform upper bounds: roughly, by designing a fast algorithm for checking satisfiability of circuits, one gets a lower bound for this circuit class. Since then, a number of results of this kind have been proved. For example, Jahanjou et al. (ICALP 2015) and Carmosino et al. (ITCS 2016) proved that if NSETH fails, then $\E^{\NP}$ has series-parallel circuit size $\omega(n)$.

One can also derive nonuniform lower bounds from nondeterministic uniform lower bounds. Perhaps the most well-known example is the Karp--Lipton theorem (STOC 1980): if $\Sigma_2 \neq \Pi_2$, then $\NP \not\subset \Ppoly$. Some recent examples include the following. Nederlof (STOC 2020) proved a lower bound on the matrix multiplication tensor rank under an assumption that TSP cannot be solved faster than in $2^n$ time. Belova et al. (SODA 2024) proved that there exists an explicit polynomial family of arithmetic circuit size $\Omega(n^{\delta})$, for any $\delta > 0$, assuming that MAX-3-SAT cannot be solved faster than in $2^n$ nondeterministic time. Williams (FOCS 2024) proved an exponential lower bound for $\ETHR{} \circ \ETHR{}$ circuits under the Orthogonal Vectors conjecture. Under an assumption that the Set Cover problem cannot be solved faster than in $2^n$, Björklund and Kaski (STOC 2024) and Pratt (STOC 2024) constructed an explicit tensor with superlinear rank. Whereas all of the lower bounds above are proved under strong assumptions that might eventually be refuted, the revealed connections are of great interest and may still give further insights: one may be able to weaken the used assumptions or to construct generators from other fine-grained reductions.

In this paper, we continue developing this line of research and show how uniform nondeterministic lower bounds can be used to construct generators of various types of combinatorial objects that are notoriously hard to analyze: Boolean functions of high circuit size, matrices of high rigidity, and tensors of high rank. Specifically, we prove the following.

- If, for some $\varepsilon$ and $k$, $k$-SAT cannot be solved in input-oblivious co-nondeterministic time $O(2^{(1/2+\varepsilon)n})$, then there exists a monotone Boolean function family in $\co\NP$ of monotone circuit size $2^{\Omega(n / \log n)}$. Combining this with the result above, we get win-win circuit lower bounds: either $\E^{\NP}$ requires series-parallel circuits of size $\omega(n)$ or $\coNP$ requires monotone circuits of size $2^{\Omega(n / \log n)}$.
- If, for all $\varepsilon>0$, MAX-3-SAT cannot be solved in co-nondeterministic time $O(2^{(1 - \varepsilon)n})$, then there exist small families of matrices with rigidity exceeding the best known constructions as well as small families of three-dimensional tensors of rank $n^{1+\Delta}$, for some $\Delta>0$.