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Revision #1 to TR24-162 | 11th November 2024 12:51
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#### Computationally Hard Problems Are Hard for QBF Proof Systems Too

**Abstract:**
There has been tremendous progress in the past decade in the field of quantified Boolean formulas (QBF), both in practical solving as well as in creating a theory of corresponding proof systems and their proof complexity analysis. Both for solving and for proof complexity, it is important to have interesting formula families on which we can test solvers and gauge the strength of the proof systems. There are currently few such formula families in the literature.

We initiate a general programme on how to transform computationally hard problems (located in the polynomial hierarchy) into QBFs hard for the main QBF resolution systems Q-Res and QU-Res that relate to core QBF solvers. We illustrate this general approach on three problems from graph theory and logic. This yields QBF families that are provably hard for Q-Res and QU-Res (without any complexity assumptions).

**Changes to previous version:**
Correction of Corollary 11

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TR24-162 | 24th October 2024 16:07
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#### Computationally Hard Problems Are Hard for QBF Proof Systems Too

**Abstract:**
There has been tremendous progress in the past decade in the field of quantified Boolean formulas (QBF), both in practical solving as well as in creating a theory of corresponding proof systems and their proof complexity analysis. Both for solving and for proof complexity, it is important to have interesting formula families on which we can test solvers and gauge the strength of the proof systems. There are currently few such formula families in the literature.

We initiate a general programme on how to transform computationally hard problems (located in the polynomial hierarchy) into QBFs hard for the main QBF resolution systems Q-Res and QU-Res that relate to core QBF solvers. We illustrate this general approach on three problems from graph theory and logic. This yields QBF families that are provably hard for Q-Res and QU-Res (without any complexity assumptions).