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1. Brief Announcement: Relations Between Space-Bounded and Adaptive Massively Parallel Computations

   https://doi.org/10.4230/LIPIcs.DISC.2023.37  

   Chen, Michael; Pavan, A; Vinodchandran, N V (October 2023, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Oshman, Rotem (Ed.)

   In this work, we study the class of problems solvable by (deterministic) Adaptive Massively Parallel Computations in constant rounds from a computational complexity theory perspective. A language L is in the class AMPC⁰ if, for every ε > 0, there is a deterministic AMPC algorithm running in constant rounds with a polynomial number of processors, where the local memory of each machine s = O(N^ε). We prove that the space-bounded complexity class ReachUL is a proper subclass of AMPC⁰. The complexity class ReachUL lies between the well-known space-bounded complexity classes Deterministic Logspace (DLOG) and Nondeterministic Logspace (NLOG). In contrast, we establish that it is unlikely that PSPACE admits AMPC algorithms, even with polynomially many rounds. We also establish that showing PSPACE is a subclass of nonuniform-AMPC with polynomially many rounds leads to a significant separation result in complexity theory, namely PSPACE is a proper subclass of EXP^{Σ₂^{𝖯}}. 

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2. The Complexity of Iterated Reversible Computation

   https://doi.org/10.46298/theoretics.23.10  

   Eppstein, David (December 2023, TheoretiCS)

   We study a class of functional problems reducible to computing $$f^{(n)}(x)$$for inputs $$n$$ and $$x$$, where $$f$$ is a polynomial-time bijection. As we prove,the definition is robust against variations in the type of reduction used inits definition, and in whether we require $$f$$ to have a polynomial-time inverseor to be computible by a reversible logic circuit. These problems arecharacterized by the complexity class $$\mathsf{FP}^{\mathsf{PSPACE}}$$, andinclude natural $$\mathsf{FP}^{\mathsf{PSPACE}}$$-complete problems in circuitcomplexity, cellular automata, graph algorithms, and the dynamical systemsdescribed by piecewise-linear transformations. 

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3. On Basing One-way Permutations on NP-hard Problems under Quantum Reductions

   https://doi.org/10.22331/q-2020-08-27-312  

   Chia, Nai-Hui; Hallgren, Sean; Song, Fang (August 2020, Quantum)

   null (Ed.)

   A fundamental pursuit in complexity theory concerns reducing worst-case problems to average-case problems. There exist complexity classes such as PSPACE that admit worst-case to average-case reductions. However, for many other classes such as NP, the evidence so far is typically negative, in the sense that the existence of such reductions would cause collapses of the polynomial hierarchy(PH). Basing cryptographic primitives, e.g., the average-case hardness of inverting one-way permutations, on NP-completeness is a particularly intriguing instance. As there is evidence showing that classical reductions from NP-hard problems to breaking these primitives result in PH collapses, it seems unlikely to base cryptographic primitives on NP-hard problems. Nevertheless, these results do not rule out the possibilities of the existence of quantum reductions. In this work, we initiate a study of the quantum analogues of these questions. Aside from formalizing basic notions of quantum reductions and demonstrating powers of quantum reductions by examples of separations, our main result shows that if NP-complete problems reduce to inverting one-way permutations using certain types of quantum reductions, then coNP ⊆ QIP ( 2 ) . 

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4. Bosonic Quantum Computational Complexity

   https://doi.org/10.4230/lipics.itcs.2025.33  

   Chabaud, Ulysse; Joseph, Michael; Mehraban, Saeed; Motamedi, Arsalan (January 2025, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Meka, Raghu (Ed.)

   In recent years, quantum computing involving physical systems with continuous degrees of freedom, such as the bosonic quantum states of light, has attracted significant interest. However, a well-defined quantum complexity theory for these bosonic computations over infinite-dimensional Hilbert spaces is missing. In this work, we lay the foundations for such a research program. We introduce natural complexity classes and problems based on bosonic generalizations of BQP, the local Hamiltonian problem, and QMA. We uncover several relationships and subtle differences between standard Boolean classical and discrete-variable quantum complexity classes, and identify outstanding open problems. Our main contributions include the following: 1) Bosonic computations. We show that the power of Gaussian computations up to logspace reductions is equivalent to bounded-error quantum logspace (BQL, characterized by the problem of inverting well-conditioned matrices). More generally, we define classes of continuous-variable quantum polynomial time computations with a bounded probability of error (CVBQP) based on gates generated by polynomial bosonic Hamiltonians and particle-number measurements. Due to the infinite-dimensional Hilbert space, it is not a priori clear whether a decidable upper bound can be obtained for these classes. We identify complete problems for these classes, and we demonstrate a BQP lower bound and an EXPSPACE upper bound by proving bounds on the average energy throughout the computation. We further show that the problem of computing expectation values of polynomial bosonic observables at the output of bosonic quantum circuits using Gaussian and cubic phase gates is in PSPACE. 2) Bosonic ground energy problems. We prove that the problem of deciding whether the spectrum of a bosonic Hamiltonian is bounded from below is co-NP-hard. Furthermore, we show that the problem of finding the minimum energy of a bosonic Hamiltonian critically depends on the non-Gaussian stellar rank of the family of energy-constrained states one optimizes over: for zero stellar rank, i.e., optimizing over Gaussian states, it is NP-complete; for polynomially-bounded stellar rank, it is in QMA; for unbounded stellar rank, it is RE-hard, i.e., undecidable. 

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5. Interactive Distributed Proofs

   Kol, Gillat; Oshman, Rotem; Saxena, Raghuvansh. (January 2018, ACM Symposium on Principles of Distributed Computing)

   Interactive proof systems allow a resource-bounded verifier to decide an intractable language (or compute a hard function) by communicating with a powerful but untrusted prover. Such systems guarantee that the prover can only convince the verifier of true statements. In the context of centralized computation, a celebrated result shows that interactive proofs are extremely powerful, allowing polynomial-time verifiers to decide any language in PSPACE. In this work we initiate the study of interactive distributed proofs: a network of nodes interacts with a single untrusted prover, who sees the entire network graph, to decide whether the graph satisfies some property. We focus on the communication cost of the protocol — the number of bits the nodes must exchange with the prover and each other. Our model can also be viewed as a generalization of the various models of “distributed NP” (proof labeling schemes, etc.) which received significant attention recently: while these models only allow the prover to present each network node with a string of advice, our model allows for back-and-forth interaction. We prove both upper and lower bounds for the new model. We show that for some problems, interaction can exponentially decrease the communication cost compared to a non-interactive prover, but on the other hand, some problems retain non-trivial cost even with interaction. 

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