arXiv:2411.03240 · ACM Symposium on Theory of Computing (STOC)
Distributed Quantum Advantage for Local Problems
Alkida Balliu, Sebastian Brandt, Xavier Coiteux-Roy, Francesco d’Amore, Massimo Equi, François Le Gall, Henrik Lievonen, Augusto Modanese, Dennis Olivetti, Marc-Olivier Renou, Jukka Suomela, Lucas Tendick, Isadora Veeren
We present the first local problem that shows a super-constant separation between the classical randomized LOCAL model of distributed computing and its quantum counterpart. By prior work, such a separation was known only for an artificial graph problem with an inherently global definition [Le Gall et al. 2019]. We present a problem that we call iterated GHZ, which is defined using only local constraints. Formally, it is a family of locally checkable labeling problems [Naor and Stockmeyer 1995]; in particular, solutions can be verified with a constant-round distributed algorithm. We show that in graphs of maximum degree $Δ$, any classical (deterministic or randomized) LOCAL model algorithm will require $Ω(Δ)$ rounds to solve the iterated GHZ problem, while the problem can be solved in $1$ round in quantum-LOCAL. We use the round elimination technique to prove that the iterated GHZ problem requires $Ω(Δ)$ rounds for classical algorithms. This is the first work that shows that round elimination is indeed able to separate the two models, and this also demonstrates that round elimination cannot be used to prove lower bounds for quantum-LOCAL. To apply round elimination, we introduce a new technique that allows us to discover appropriate problem relaxations in a mechanical way; it turns out that this new technique extends beyond the scope of the iterated GHZ problem and can be used to e.g. reproduce prior results on maximal matchings [FOCS 2019, PODC 2020] in a systematic manner.
We present the first local problem that shows a super-constant separation between the classical randomized LOCAL model of distributed computing and its quantum counterpart. By prior work, such a separation was known only for an artificial graph problem with an inherently global definition [Le Gall et al. 2019]. We present a problem that we call iterated GHZ, which is defined using only local constraints. Formally, it is a family of locally checkable labeling problems [Naor and Stockmeyer 1995]; in particular, solutions can be verified with a constant-round distributed algorithm. We show that in graphs of maximum degree Δ, any classical (deterministic or randomized) LOCAL model algorithm will require Ω(Δ) rounds to solve the iterated GHZ problem, while the problem can be solved in 1 round in quantum-LOCAL. We use the round elimination technique to prove that the iterated GHZ problem requires Ω(Δ) rounds for classical algorithms. This is the first work that shows that round elimination is indeed able to separate the two models, and this also demonstrates that round elimination cannot be used to prove lower bounds for quantum-LOCAL. To apply round elimination, we introduce a new technique that allows us to discover appropriate problem relaxations in a mechanical way; it turns out that this new technique extends beyond the scope of the iterated GHZ problem and can be used to e.g. reproduce prior results on maximal matchings [FOCS 2019, PODC 2020] in a systematic manner.
We present the first local problem that shows a super-constant separation between the classical randomized LOCAL model of distributed computing and its quantum counterpart. By prior work, such a separation was known only for an artificial graph problem with an inherently global definition [Le Gall et al. 2019]. We present a problem that we call iterated GHZ, which is defined using only local constraints. Formally, it is a family of locally checkable labeling problems [Naor and Stockmeyer 1995]; in particular, solutions can be verified with a constant-round distributed algorithm. We show that in graphs of maximum degree Δ, any classical (deterministic or randomized) LOCAL model algorithm will require Ω(Δ) rounds to solve the iterated GHZ problem, while the problem can be solved in 1 round in quantum-LOCAL. We use the round elimination technique to prove that the iterated GHZ problem requires Ω(Δ) rounds for classical algorithms. This is the first work that shows that round elimination is indeed able to separate the two models, and this also demonstrates that round elimination cannot be used to prove lower bounds for quantum-LOCAL. To apply round elimination, we introduce a new technique that allows us to discover appropriate problem relaxations in a mechanical way; it turns out that this new technique extends beyond the scope of the iterated GHZ problem and can be used to e.g. reproduce prior results on maximal matchings [FOCS 2019, PODC 2020] in a systematic manner.
We present a distributed quantum algorithm that 3-colors cycles in O(1) rounds, with high probability. It follows that all locally checkable labeling problems (LCLs) that have round complexity O(log∗n) in the classical LOCAL model can be solved in O(1) rounds in the quantum-LOCAL model, with high probability; this includes problems such as maximal independent set and maximal matching in bounded-degree graphs. This presents the first natural examples of graph problems with an asymptotic distributed quantum advantage for the LOCAL model; all prior examples that separate LOCAL and quantum-LOCAL are artificial problems constructed merely for the sake of demonstrating quantum advantage.
In this thesis, I study how quantum computation and quantum communication can help large networks of computers to solve computational problems faster. I also connect the notion of locality between various models, including distributed quantum algorithms and online graph algorithms, and show that locality in online graph algorithms can be used to provide bounds for distributed quantum advantage. Towards proving distributed quantum advantage, I present the first family of LCL problems which shows a quantum advantage for distributed graph algorithms. Here LCLs, or Locally Checkable Labeling problems, are a family of graph problems described by a finite set of local constraints, and I mainly focus on them in this thesis. The models of distributed computing which this result separates are the classical LOCAL model and the quantum-LOCAL model. In both of these models, a network of computers exchanges messages in synchronous rounds, and the running time of the algorithm directly corresponds with locality, that is, how far the computers see in the network. In this thesis, I also introduce new models of computing that capture locality in stronger settings. Most notably, I introduce the online-LOCAL model which captures the locality of online graph algorithms, and show that it is, asymptotically, roughly as strong as the classical LOCAL model for solving LCL problems on rooted regular trees. I provide an online-LOCAL algorithm for finding a 3-coloring of a bipartite graph with lower locality than is possible in the classical LOCAL model, and show that the algorithm is tight. To draw things together, I show that quantum-LOCAL and online-LOCAL are indeed related to each other: any quantum-LOCAL algorithm can be simulated in the randomized online-LOCAL model. The converse does not hold in general, but an online-LOCAL algorithm solving an LCL problem in rooted, possibly non-regular, trees can be simulated in the classical LOCAL model—and thus in the quantum-LOCAL model—with an exponential cost in locality, putting indirectly a bound on the maximum possible attainable quantum advantage. Finally, I consider the sinkless orientation problem, which holds a central role in our understanding of the locality of LCL problems in the classical LOCAL model, and provide a simpler and more direct proof for its hardness using the supported LOCAL model. I also provide a simpler algorithm solving sinkless orientation in the SLOCAL model, which is a sequential version of the LOCAL model.
Distributed Quantum Computing (DQC) offers a promising path toward scalable quantum computation by connecting multiple quantum processors through quantum and classical communication channels, helping overcome the limited qubit counts and noise of individual Noisy Intermediate-Scale Quantum (NISQ) devices. Beyond scaling, DQC has been shown to provide a provable computational advantage: Balliu et al. (STOC 2025) proved that certain locally checkable labeling problems require Ω(Δ) rounds classically in the LOCAL model, where Δ is the maximum degree of the graph, yet only a single round in the quantum-LOCAL model. This separation is unconditional, but a practical demonstration on real hardware had not previously been carried out. This thesis addresses that gap through two contributions. First, it covers the background needed to understand distributed quantum computing: quantum gates, entanglement and the GHZ state, classical distributed models such as LOCAL and CONGEST, locally checkable labeling problems, and the operating principles of superconducting quantum computers, including the practical challenges of connecting them across distances. Second, it presents a practical demonstration of the iterated GHZ game, the locally checkable labeling problem underlying the separation above. The quantum-LOCAL winning strategy is proven correct and implemented as a quantum circuit, executed on IQM’s superconducting quantum computers Garnet and Emerald via the IQM Resonance cloud service. Since physically distributed superconducting hardware is not yet publicly available, a chip-partitioning scheme is used, treating regions of a single chip as independent quantum nodes to emulate a distributed network. The results show that Round 1 games consistently exceed the 75% classical winning bound of the GHZ game, confirming that this win-rate quantum advantage is detectable under NISQ-era noise. In a deeper 3-round demonstration, performance degrades in later rounds, suggesting that demonstrating the advantage consistently across deeper circuits will require longer coherence times, higher gate fidelities, or error correction.
In this work, we give two results that put new limits on distributed quantum advantage in the context of the LOCAL model of distributed computing: 1) We show that there is no distributed quantum advantage for any linear program. Put otherwise, if there is a quantum-LOCAL algorithm 𝒜 that finds an α-approximation of some linear optimization problem Π in T communication rounds, we can construct a classical, deterministic LOCAL algorithm 𝒜' that finds an α-approximation of Π in T rounds. As a corollary, all classical lower bounds for linear programs, including the KMW bound, hold verbatim in quantum-LOCAL. 2) Using the above result, we show that there exists a locally checkable labeling problem (LCL) for which quantum-LOCAL is strictly weaker than the classical deterministic SLOCAL model. Our results extend from quantum-LOCAL to finitely dependent and non-signaling distributions, and one of the corollaries of our work is that the non-signaling model and the SLOCAL model are incomparable in the context of LCL problems: By prior work, there exists an LCL problem for which SLOCAL is strictly weaker than the non-signaling model, and our work provides a separation in the opposite direction.
We connect three distinct lines of research that have recently explored extensions of the classical LOCAL model of distributed computing: A. distributed quantum computing and non-signaling distributions [e.g. STOC 2024], B. finitely-dependent processes [e.g. Forum Math. Pi 2016], and C. locality in online graph algorithms and dynamic graph algorithms [e.g. ICALP 2023]. We prove new results on the capabilities and limitations of all of these models of computing, for locally checkable labeling problems (LCLs). We show that all these settings can be sandwiched between the classical LOCAL model and what we call the randomized online-LOCAL model. Our work implies limitations on the quantum advantage in the distributed setting, and we also exhibit a new barrier for proving tighter bounds. Our main technical results are these: 1. All LCL problems solvable with locality O(log⋆n) in the classical deterministic LOCAL model admit a finitely-dependent distribution with locality O(1). This answers an open question by Holroyd [2024], and also presents a new barrier for proving bounds on distributed quantum advantage using causality-based arguments. 2. In rooted trees, if we can solve an LCL problem with locality o(logloglogn) in the randomized online-LOCAL model (or any of the weaker models, such as quantum-LOCAL), we can solve it with locality O(log⋆n) in the classical deterministic LOCAL model. One of many implications is that in rooted trees, O(log⋆n) locality in quantum-LOCAL is not stronger than O(log⋆n) locality in classical LOCAL.