@inproceedings{19007, abstract = {Learning modular object-centric representations is crucial for systematic generalization. Existing methods show promising object-binding capabilities empirically, but theoretical identifiability guarantees remain relatively underdeveloped. Understanding when object-centric representations can theoretically be identified is crucial for scaling slot-based methods to high-dimensional images with correctness guarantees. To that end, we propose a probabilistic slot-attention algorithm that imposes an aggregate mixture prior over object-centric slot representations, thereby providing slot identifiability guarantees without supervision, up to an equivalence relation. We provide empirical verification of our theoretical identifiability result using both simple 2-dimensional data and high-resolution imaging datasets. }, author = {Kori, Avinash and Locatello, Francesco and Santhirasekaram, Ainkaran and Toni, Francesca and Glocker, Ben and De Sousa Ribeiro, Fabio}, booktitle = {38th Conference on Neural Information Processing Systems}, location = {Vancouver, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Identifiable object-centric representation learning via probabilistic slot attention}}, doi = {10.52202/079017-2960}, volume = {37}, year = {2024}, } @article{15098, abstract = {The paper is devoted to the analysis of the global well-posedness and the interior regularity of the 2D Navier–Stokes equations with inhomogeneous stochastic boundary conditions. The noise, white in time and coloured in space, can be interpreted as the physical law describing the driving mechanism on the atmosphere–ocean interface, i.e. as a balance of the shear stress of the ocean and the horizontal wind force.}, author = {Agresti, Antonio and Luongo, Eliseo}, issn = {1432-1807}, journal = {Mathematische Annalen}, pages = {2727--2766}, publisher = {Springer Nature}, title = {{Global well-posedness and interior regularity of 2D Navier-Stokes equations with stochastic boundary conditions}}, doi = {10.1007/s00208-024-02812-0}, volume = {390}, year = {2024}, } @article{17462, abstract = {We are interested in numerical algorithms for computing the electrical field generated by a charge distribution localized on scale l in an infinite heterogeneous correlated random medium, in a situation where the medium is only known in a box of diameter L >>l around the support of the charge. We show that the algorithm in [J. Lu, F. Otto, and L. Wang, Optimal Artificial Boundary Conditions Based on Second-Order Correctors for Three Dimensional Random Ellilptic Media, preprint, arXiv:2109.01616, 2021], suggesting optimal Dirichlet boundary conditions motivated by the multipole expansion [P. Bella, A. Giunti, and F. Otto, Comm. Partial Differential Equations, 45 (2020), pp. 561–640], still performs well in correlated media. With overwhelming probability, we obtain a convergence rate in terms of l, L, and the size of the correlations for which optimality is supported with numerical simulations. These estimates are provided for ensembles which satisfy a multiscale logarithmic Sobolev inequality, where our main tool is an extension of the semigroup estimates in [N. Clozeau, Stoch. Partial Differ. Equ. Anal. Comput., 11 (2023), pp. 1254–1378]. As part of our strategy, we construct sublinear second-order correctors in this correlated setting, which is of independent interest.}, author = {Clozeau, Nicolas and Wang, Lihan}, issn = {1540-3467}, journal = {Multiscale Modeling and Simulation}, number = {3}, pages = {973--1029}, publisher = {Society for Industrial and Applied Mathematics}, title = {{Artificial boundary conditions for random elliptic systems with correlated coefficient field}}, doi = {10.1137/23M1603819}, volume = {22}, year = {2024}, } @article{15119, abstract = {In this paper we consider an SPDE where the leading term is a second order operator with periodic boundary conditions, coefficients which are measurable in (t,ω) , and Hölder continuous in space. Assuming stochastic parabolicity conditions, we prove Lp((0,T)×Ω,tκdt;Hσ,q(Td)) -estimates. The main novelty is that we do not require p=q . Moreover, we allow arbitrary σ∈R and weights in time. Such mixed regularity estimates play a crucial role in applications to nonlinear SPDEs which is clear from our previous work. To prove our main results we develop a general perturbation theory for SPDEs. Moreover, we prove a new result on pointwise multiplication in spaces with fractional smoothness.}, author = {Agresti, Antonio and Veraar, Mark}, issn = {0246-0203}, journal = {Annales de l'Institut Henri Poincaré, Probabilités et Statistiques}, number = {1}, pages = {413--430}, publisher = {Institute of Mathematical Statistics}, title = {{Stochastic maximal Lp(Lq)-regularity for second order systems with periodic boundary conditions}}, doi = {10.1214/22-AIHP1333}, volume = {60}, year = {2024}, } @article{17481, abstract = {Phase-field models such as the Allen–Cahn equation may give rise to the formation and evolution of geometric shapes, a phenomenon that may be analyzed rigorously in suitable scaling regimes. In its sharp-interface limit, the vectorial Allen–Cahn equation with a potential with N≥3 distinct minima has been conjectured to describe the evolution of branched interfaces by multiphase mean curvature flow. In the present work, we give a rigorous proof for this statement in two and three ambient dimensions and for a suitable class of potentials: as long as a strong solution to multiphase mean curvature flow exists, solutions to the vectorial Allen–Cahn equation with well-prepared initial data converge towards multiphase mean curvature flow in the limit of vanishing interface width parameter ε↘0. We even establish the rate of convergence O(ε 1/2 ). Our approach is based on the gradient-flow structure of the Allen–Cahn equation and its limiting motion: building on the recent concept of “gradient-flow calibrations” for multiphase mean curvature flow, we introduce a notion of relative entropy for the vectorial Allen–Cahn equation with multi-well potential. This enables us to overcome the limitations of other approaches, e.g. avoiding the need for a stability analysis of the Allen–Cahn operator or additional convergence hypotheses for the energy at positive times.}, author = {Fischer, Julian L and Marveggio, Alice}, issn = {1873-1430}, journal = {Annales de l'Institut Henri Poincaré C}, number = {5}, pages = {1117--1178}, publisher = {EMS Press}, title = {{Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase mean curvature flow}}, doi = {10.4171/AIHPC/109}, volume = {41}, year = {2024}, } @inproceedings{17098, abstract = {Turn-based discounted-sum games are two-player zero-sum games played on finite directed graphs. The vertices of the graph are partitioned between player 1 and player 2. Plays are infinite walks on the graph where the next vertex is decided by a player that owns the current vertex. Each edge is assigned an integer weight and the payoff of a play is the discounted-sum of the weights of the play. The goal of player 1 is to maximize the discounted-sum payoff against the adversarial player 2. These games lie in NP ∩ coNP and are among the rare combinatorial problems that belong to this complexity class and the existence of a polynomial-time algorithm is a major open question. Since breaking the general exponential barrier has been a challenging problem, faster parameterized algorithms have been considered. If the discount factor is expressed in unary, then discounted-sum games can be solved in polynomial time. However, if the discount factor is arbitrary (or expressed in binary), but the weights are in unary, none of the existing approaches yield a sub-exponential bound. Our main result is a new analysis technique for a classical algorithm (namely, the strategy iteration algorithm) that present a new runtime bound which is [EQUATION] for game graphs with n vertices and absolute weights of at most W. In particular, our result yields a deterministic sub-exponential bound for games with weights that are constant or represented in unary.}, author = {Asadi, Ali and Chatterjee, Krishnendu and Svoboda, Jakub and Saona Urmeneta, Raimundo J}, booktitle = {39th Annual ACM/IEEE Symposium on Logic in Computer Science}, isbn = {9798400706608}, issn = {1043-6871}, location = {Tallinn, Estonia}, publisher = {Association for Computing Machinery}, title = {{Deterministic sub-exponential algorithm for discounted-sum games with unary weights}}, doi = {10.1145/3661814.3662080}, year = {2024}, } @inproceedings{19510, abstract = {We propose a new variant of the Adam optimizer [Kingma and Ba, 2014] called MICROADAM that specifically minimizes memory overheads, while maintaining theoretical convergence guarantees. We achieve this by compressing the gradient information before it is fed into the optimizer state, thereby reducing its memory footprint significantly. We control the resulting compression error via a novel instance of the classical error feedback mechanism from distributed optimization [Seide et al., 2014, Alistarh et al., 2018, Karimireddy et al., 2019] in which the error correction information is itself compressed to allow for practical memory gains. We prove that the resulting approach maintains theoretical convergence guarantees competitive to those of AMSGrad, while providing good practical performance. Specifically, we show that MICROADAM can be implemented efficiently on GPUs: on both million-scale (BERT) and billion-scale (LLaMA) models, MICROADAM provides practical convergence competitive to that of the uncompressed Adam baseline, with lower memory usage and similar running time. Our code is available at https://github.com/IST-DASLab/MicroAdam.}, author = {Modoranu, Ionut-Vlad and Safaryan, Mher and Malinovsky, Grigory and Kurtic, Eldar and Robert, Thomas and Richtárik, Peter and Alistarh, Dan-Adrian}, booktitle = {38th Conference on Neural Information Processing Systems}, issn = {1049-5258}, publisher = {Neural Information Processing Systems Foundation}, title = {{MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence}}, doi = {10.52202/079017-0001}, volume = {37}, year = {2024}, } @article{18654, abstract = {We compute the rotational anisotropy of the free energy of 𝛼−RuCl3 in an external magnetic field. This quantity, known as the magnetotropic susceptibility, 𝑘, relates to the second derivative of the free energy with respect to the angle of rotation. We have used approximation-free, auxiliary-field quantum Monte Carlo simulations for a realistic model of 𝛼−RuCl3 and optimized the path integral to alleviate the negative sign problem. This allows us to reach temperatures down to 30K—an energy scale below the dominant Kitaev coupling. We demonstrate that the magnetotropic spin susceptibility in this model of 𝛼−RuCl3 displays scaling behavior 𝑘=𝑇⁢𝑓⁡(𝐵/𝑇) at high temperatures. Once the uniform susceptibility departs from the Curie law (i.e., at the energy scale of the exchange interactions), it appears to transition to an emergent scalinglike behavior, characterized by a different function 𝑓 at lower temperatures, stemming from the locality of torque fluctuations. We observe a remarkable numerical match between experiment and simulations and we also find qualitative agreement with the pure Kitaev model. In comparison, for the XXZ Heisenberg Hamiltonian, the scaling 𝑘=𝑇⁢𝑓⁡(𝐵/𝑇) breaks down at a temperature scale where the uniform spin susceptibility deviates from the Curie law and never reemerges at low temperatures.}, author = {Sato, Toshihiro and Ramshaw, B. J. and Modic, Kimberly A and Assaad, Fakher F.}, issn = {2469-9969}, journal = {Physical Review B}, number = {20}, publisher = {American Physical Society}, title = {{Scale-invariant magnetic anisotropy in α-RuCl3: A quantum Monte Carlo study}}, doi = {10.1103/PhysRevB.110.L201114}, volume = {110}, year = {2024}, } @inproceedings{19511, abstract = {We introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits. QuaRot rotates LLMs in a way that removes outliers from the hidden state without changing the output, making quantization easier. This computational invariance is applied to the hidden state (residual) of the LLM, as well as to the activations of the feed-forward components, aspects of the attention mechanism, and to the KV cache. The result is a quantized model where all matrix multiplications are performed in 4 bits, without any channels identified for retention in higher precision. Our 4-bit quantized LLAMA2-70B model has losses of at most 0.47 WikiText-2 perplexity and retains 99% of the zero-shot performance. We also show that QuaRot can provide lossless 6 and 8 bit LLAMA-2 models without any calibration data using round-to-nearest quantization. Code is available at github.com/spcl/QuaRot.}, author = {Ashkboos, Saleh and Mohtashami, Amirkeivan and Croci, Maximilian L. and Li, Bo and Cameron, Pashmina and Jaggi, Martin and Alistarh, Dan-Adrian and Hoefler, Torsten and Hensman, James}, booktitle = {38th Conference on Neural Information Processing Systems}, issn = {1049-5258}, location = {Vancouver, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{QuaRot: Outlier-free 4-bit inference in rotated LLMs}}, doi = {10.52202/079017-3180}, volume = {37}, year = {2024}, } @article{15003, abstract = {Magnetic frustration allows to access novel and intriguing properties of magnetic systems and has been explored mainly in planar triangular-like arrays of magnetic ions. In this work, we describe the phosphide Ce6Ni6P17, where the Ce+3 ions accommodate in a body-centered cubic lattice of Ce6 regular octahedra. From measurements of magnetization, specific heat, and resistivity, we determine a rich phase diagram as a function of temperature and magnetic field in which different magnetic phases are found. Besides clear evidence of magnetic frustration is obtained from entropy analysis. At zero field, a second-order antiferromagnetic transition occurs at TN1≈1 K followed by a first-order transition at TN2≈0.45 K. With magnetic field new magnetic phases appear, including a weakly first-order transition which ends in a classical critical point and a third magnetic phase. We also study the exact solution of the spin-1/2 Heisenberg model in an octahedron which allows us a qualitative understanding of the phase diagram and compare with the experimental results.}, author = {Franco, D. G. and Avalos, R. and Hafner, D. and Modic, Kimberly A and Prots, Yu and Stockert, O. and Hoser, A. and Moll, P. J.W. and Brando, M. and Aligia, A. A. and Geibel, C.}, issn = {2469-9969}, journal = {Physical Review B}, number = {5}, publisher = {American Physical Society}, title = {{Frustrated magnetism in octahedra-based Ce6 Ni6 P17}}, doi = {10.1103/PhysRevB.109.054405}, volume = {109}, year = {2024}, } @article{18926, abstract = {We study weak solutions to mean curvature flow satisfying Young’s angle condition for general contact angles α ∈ (0, π). First, we construct BV solutions by using the Allen-Cahn approximation with boundary contact energy as proposed by Owen and Sternberg. Second, we prove the weak-strong uniqueness and stability for this solution concept. The main ingredient for both results is a relative energy, which can also be interpreted as a tilt excess. }, author = {Hensel, Sebastian and Laux, Tim}, issn = {0022-2518}, journal = {Indiana University Mathematics Journal}, number = {1}, pages = {111--148}, publisher = {Indiana University Mathematics Journal}, title = {{BV solutions for mean curvature flow with constant angle: Allen-Cahn approximation and weak-strong uniqueness}}, doi = {10.1512/iumj.2024.73.9701}, volume = {73}, year = {2024}, } @unpublished{17101, abstract = {This paper considers a class of two-player zero-sum games on directed graphs whose vertices are equipped with random payoffs of bounded support known by both players. Starting from a fixed vertex, players take turns to move a token along the edges of the graph. On the one hand, for acyclic directed graphs of bounded degree and sub-exponential expansion, we show that the value of the game converges almost surely to a constant at an exponential rate dominated in terms of the expansion. On the other hand, for the infinite d-ary tree that does not fall into the previous class of graphs, we show convergence at a double-exponential rate in terms of the expansion.}, author = {Attia, Luc and Lichev, Lyuben and Mitsche, Dieter and Saona Urmeneta, Raimundo J and Ziliotto, Bruno}, booktitle = {arXiv}, title = {{Zero-sum random games on directed graphs}}, doi = {10.48550/arXiv.2401.16252}, year = {2024}, } @inproceedings{15006, abstract = {Graphical games are a useful framework for modeling the interactions of (selfish) agents who are connected via an underlying topology and whose behaviors influence each other. They have wide applications ranging from computer science to economics and biology. Yet, even though an agent’s payoff only depends on the actions of their direct neighbors in graphical games, computing the Nash equilibria and making statements about the convergence time of "natural" local dynamics in particular can be highly challenging. In this work, we present a novel approach for classifying complexity of Nash equilibria in graphical games by establishing a connection to local graph algorithms, a subfield of distributed computing. In particular, we make the observation that the equilibria of graphical games are equivalent to locally verifiable labelings (LVL) in graphs; vertex labelings which are verifiable with constant-round local algorithms. This connection allows us to derive novel lower bounds on the convergence time to equilibrium of best-response dynamics in graphical games. Since we establish that distributed convergence can sometimes be provably slow, we also introduce and give bounds on an intuitive notion of "time-constrained" inefficiency of best responses. We exemplify how our results can be used in the implementation of mechanisms that ensure convergence of best responses to a Nash equilibrium. Our results thus also give insight into the convergence of strategy-proof algorithms for graphical games, which is still not well understood.}, author = {Hirvonen, Juho and Schmid, Laura and Chatterjee, Krishnendu and Schmid, Stefan}, booktitle = {27th International Conference on Principles of Distributed Systems}, isbn = {9783959773089}, issn = {1868-8969}, location = {Tokyo, Japan}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{On the convergence time in graphical games: A locality-sensitive approach}}, doi = {10.4230/LIPIcs.OPODIS.2023.11}, volume = {286}, year = {2024}, } @inproceedings{17402, abstract = {We present version 2.0 of the Partial Exploration Tool (PET), a tool for verification of probabilistic systems. We extend the previous version by adding support for stochastic games, based on a recent unified framework for sound value iteration algorithms. Thereby, PET2 is the first tool implementing a sound and efficient approach for solving stochastic games with objectives of the type reachability/safety and mean payoff. We complement this approach by developing and implementing a partial-exploration based variant for all three objectives. Our experimental evaluation shows that PET2 offers the most efficient partial-exploration based algorithm and is the most viable tool on SGs, even outperforming unsound tools.}, author = {Meggendorfer, Tobias and Weininger, Maximilian}, booktitle = {36th International Conference on Computer Aided Verification}, isbn = {9783031656323}, issn = {1611-3349}, location = {Montreal, Canada}, pages = {359--372}, publisher = {Springer Nature}, title = {{Playing games with your PET: Extending the Partial Exploration Tool to stochastic games}}, doi = {10.1007/978-3-031-65633-0_16}, volume = {14683}, year = {2024}, } @article{17162, abstract = {Cost analysis, also known as resource usage analysis, is the task of finding bounds on the total cost of a program and is a well-studied problem in static analysis. In this work, we consider two classical quantitative problems in cost analysis for probabilistic programs. The first problem is to find a bound on the expected total cost of the program. This is a natural measure for the resource usage of the program and can also be directly applied to average-case runtime analysis. The second problem asks for a tail bound, i.e. ‍given a threshold t the goal is to find a probability bound p such that ℙ[total cost ≥ t] ≤ p. Intuitively, given a threshold t on the resource, the problem is to find the likelihood that the total cost exceeds this threshold. First, for expectation bounds, a major obstacle in previous works on cost analysis is that they can handle only non-negative costs or bounded variable updates. In contrast, we provide a new variant of the standard notion of cost martingales, that allows us to find expectation bounds for a class of programs with general positive or negative costs and no restriction on the variable updates. More specifically, our approach is applicable as long as there is a lower bound on the total cost incurred along every path. Second, for tail bounds, all previous methods are limited to programs in which the expected total cost is finite. In contrast, we present a novel approach, based on a combination of our martingale-based method for expectation bounds with a quantitative safety analysis, to obtain a solution to the tail bound problem that is applicable even to programs with infinite expected cost. Specifically, this allows us to obtain runtime tail bounds for programs that do not terminate almost-surely. In summary, we provide a novel combination of martingale-based cost analysis and quantitative safety analysis that is able to find expectation and tail cost bounds for probabilistic programs, without the restrictions of non-negative costs, bounded updates, or finiteness of the expected total cost. Finally, we provide experimental results showcasing that our approach can solve instances that were beyond the reach of previous methods.}, author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Meggendorfer, Tobias and Zikelic, Dorde}, issn = {2475-1421}, journal = {Proceedings of the ACM on Programming Languages}, number = {OOPSLA1}, publisher = {Association for Computing Machinery}, title = {{Quantitative bounds on resource usage of probabilistic programs}}, doi = {10.1145/3649824}, volume = {8}, year = {2024}, } @inproceedings{19512, abstract = {Differential privacy with gradual expiration models the setting where data items arrive in a stream and at a given time t the privacy loss guaranteed for a data item seen at time (t − d) is εg(d), where g is a monotonically non-decreasing function. We study the fundamental continual (binary) counting problem where each data item consists of a bit, and the algorithm needs to output at each time step the sum of all the bits streamed so far. For a stream of length T and privacy without expiration continual counting is possible with maximum (over all time steps) additive error O(log2 (T)/ε) and the best known lower bound is Ω(log(T)/ε); closing this gap is a challenging open problem. We show that the situation is very different for privacy with gradual expiration by giving upper and lower bounds for a large set of expiration functions g. Specifically, our algorithm achieves an additive error of O(log(T)/ε) for a large set of privacy expiration functions. We also give a lower bound that shows that if C is the additive error of any ε-DP algorithm for this problem, then the product of C and the privacy expiration function after 2C steps must be Ω(log(T)/ε). Our algorithm matches this lower bound as its additive error is O(log(T)/ε), even when g(2C) = O(1). Our empirical evaluation shows that we achieve a slowly growing privacy loss with significantly smaller empirical privacy loss for large values of d than a natural baseline algorithm.}, author = {Andersson, Joel Daniel and Henzinger, Monika H and Pagh, Rasmus and Steiner, Teresa Anna and Upadhyay, Jalaj}, booktitle = {38th Conference on Neural Information Processing Systems}, issn = {1049-5258}, location = {Vancouver, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Continual counting with gradual privacy expiration}}, doi = {10.52202/079017-0299}, volume = {37}, year = {2024}, } @inproceedings{19515, abstract = {Neural models learn data representations that lie on low-dimensional manifolds, yet modeling the relation between these representational spaces is an ongoing challenge. By integrating spectral geometry principles into neural modeling, we show that this problem can be better addressed in the functional domain, mitigating complexity, while enhancing interpretability and performances on downstream tasks. To this end, we introduce a multi-purpose framework to the representation learning community, which allows to: (i) compare different spaces in an interpretable way and measure their intrinsic similarity; (ii) find correspondences between them, both in unsupervised and weakly supervised settings, and (iii) to effectively transfer representations between distinct spaces. We validate our framework on various applications, ranging from stitching to retrieval tasks, and on multiple modalities, demonstrating that Latent Functional Maps can serve as a swiss-army knife for representation alignment}, author = {Fumero, Marco and Pegoraro, Marco and Maiorca, Valentino and Locatello, Francesco and Rodolà, Emanuele}, booktitle = {38th Conference on Neural Information Processing Systems}, issn = {1049-5258}, location = {Vancouver, Canada}, publisher = {Neural Information Processing Systems Foundation}, title = {{Latent functional maps: A spectral framework for representation alignment}}, doi = {10.52202/079017-2115}, volume = {37}, year = {2024}, } @misc{23140, abstract = {The artefact for the OOPSLA 2024 paper "Quantitative Bounds on Resource Usage of Probabilistic Programs". }, author = { Žikelić, Đorđe}, publisher = {Zenodo}, title = {{Artefact for: Quantitative Bounds on Resource Usage of Probabilistic Programs}}, doi = {10.5281/zenodo.10457565}, year = {2024}, } @article{15083, abstract = {Direct reciprocity is a powerful mechanism for cooperation in social dilemmas. The very logic of reciprocity, however, seems to require that individuals are symmetric, and that everyone has the same means to influence each others’ payoffs. Yet in many applications, individuals are asymmetric. Herein, we study the effect of asymmetry in linear public good games. Individuals may differ in their endowments (their ability to contribute to a public good) and in their productivities (how effective their contributions are). Given the individuals’ productivities, we ask which allocation of endowments is optimal for cooperation. To this end, we consider two notions of optimality. The first notion focuses on the resilience of cooperation. The respective endowment distribution ensures that full cooperation is feasible even under the most adverse conditions. The second notion focuses on efficiency. The corresponding endowment distribution maximizes group welfare. Using analytical methods, we fully characterize these two endowment distributions. This analysis reveals that both optimality notions favor some endowment inequality: More productive players ought to get higher endowments. Yet the two notions disagree on how unequal endowments are supposed to be. A focus on resilience results in less inequality. With additional simulations, we show that the optimal endowment allocation needs to account for both the resilience and the efficiency of cooperation.}, author = {Hübner, Valentin and Staab, Manuel and Hilbe, Christian and Chatterjee, Krishnendu and Kleshnina, Maria}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, number = {10}, publisher = {National Academy of Sciences}, title = {{Efficiency and resilience of cooperation in asymmetric social dilemmas}}, doi = {10.1073/pnas.2315558121}, volume = {121}, year = {2024}, } @article{15297, abstract = {Populations evolve by accumulating advantageous mutations. Every population has some spatial structure that can be modeled by an underlying network. The network then influences the probability that new advantageous mutations fixate. Amplifiers of selection are networks that increase the fixation probability of advantageous mutants, as compared to the unstructured fully-connected network. Whether or not a network is an amplifier depends on the choice of the random process that governs the evolutionary dynamics. Two popular choices are Moran process with Birth-death updating and Moran process with death-Birth updating. Interestingly, while some networks are amplifiers under Birth-death updating and other networks are amplifiers under death-Birth updating, so far no spatial structures have been found that function as an amplifier under both types of updating simultaneously. In this work, we identify networks that act as amplifiers of selection under both versions of the Moran process. The amplifiers are robust, modular, and increase fixation probability for any mutant fitness advantage in a range r ∈ (1, 1.2). To complement this positive result, we also prove that for certain quantities closely related to fixation probability, it is impossible to improve them simultaneously for both versions of the Moran process. Together, our results highlight how the two versions of the Moran process differ and what they have in common.}, author = {Svoboda, Jakub and Joshi, Soham Shrikant and Tkadlec, Josef and Chatterjee, Krishnendu}, issn = {1553-7358}, journal = {PLoS Computational Biology}, number = {3}, publisher = {Public Library of Science}, title = {{Amplifiers of selection for the Moran process with both Birth-death and death-Birth updating}}, doi = {10.1371/journal.pcbi.1012008}, volume = {20}, year = {2024}, }