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Related Articles from SNS
Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
Announce Type: new Abstract: Diffusion-based neural solvers have shown strong promise for combinatorial optimization (CO), but existing methods typically rely on supervised training with large collections of near-optimal solutions. In this work, we extend adjoint-based trajectory optimization methods to discrete combinatorial domains. We formulate diffusion-based CO as a stochastic control problem over Continuous-Time Markov Chains and introduce discrete adjoint dynamics for propagating...
A variational formulation of the adjoint Kutta condition in potential flow
arXiv:2606.06937v1 Announce Type: new Abstract: We give a variational formulation of the continuous adjoint Kutta condition for two-dimensional subcritical potential flow, with emphasis on the Kutta condition and the role of the wake. We show that the adjoint Kutta condition can be imposed by a penalty term evaluated at the trailing edge, with the corresponding Lagrange multiplier determined by stationarity of the Lagrangian with respect to circulation, and that a wake treatment is not...
Adjoint-based Perfusion Estimation from Dynamic Contrast-Enhanced Ultrasound: Advection-Diffusion and Two-Compartment Models
Announce Type: new Abstract: Tumor perfusion and vascular properties are important determinants of a cancer's response to therapy. In this paper, we discuss the estimation of spatially varying blood flow velocities and perfusion parameters from time-resolved contrast agent concentration data. We compare a standard parabolic advection-diffusion model against a two-compartment model governed by a coupled system of hyperbolic advection-reaction equations, which is physiologically more sound.
End-to-end optimization of subgrid scale models for discontinuous spectral element schemes based on the discrete adjoint method
Announce Type: new Abstract: In computational fluid dynamics, Large Eddy Simulation (LES) offers a compelling balance between accuracy and computational cost by resolving large-scale flow structures while modeling unresolved subgrid scales. However, its predictive capacity is critically dependent on the choice and calibration of subgrid-scale (SGS) models, which often involve problem-dependent parameters and exhibit intricate interactions with the numerical discretization. In this work, we...
Iterative bounds on effective transport for advection diffusion in periodic flow fields
arXiv:2404.18754v2 Announce Type: replace Abstract: Over three decades ago a Stieltjes integral representation for the effective diffusivity of a tracer in a steady fluid velocity field was developed, involving the spectral measure of a compact self-adjoint operator and the P\'eclet number of the flow. Rigorous bounds on the homogenized diffusivity could then be obtained from knowledge of the moments of the spectral measure. A recent extension to space-time periodic flows involves an...
On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
arXiv:2606.02179v1 Announce Type: new Abstract: Surrogate models for topology optimization (TO) exhibit highly variable out-of-distribution (OOD) generalization under distribution shifts such as changing loads or boundary conditions, yet the source of this variability remains unclear. We hypothesize that OOD performance is governed by how much information the conditioning signal preserves about the adjoint sensitivity (reduced gradient) that drives classical TO. Modeling the TO pipeline as a...
Benchmarking Sequential Feedback Optimization for Wind Farm Power Maximization
arXiv:2606.08315v1 Announce Type: new Abstract: This paper benchmarks sequential feedback optimization (SFO) for wind farm power maximization using a medium-fidelity dynamic flow model. We compare SFO with two well-established approaches, adjoint-based economic model predictive control (AMPC) and extremum seeking control (ESC), under a common nine-turbine layout and identical operating constraints. The comparison focuses on steady-state power production and computational efficiency, both...
On the gap of quiver representations
Announce Type: cross Abstract: The nullcone membership problem, deciding whether an orbit closure contains the origin, is fundamental in computational invariant theory. For self-adjoint groups, B\"urgisser, Franks, Garg, Oliveira, Walter and Wigderson gave a geodesic optimization algorithm whose complexity is controlled by the gap, a condition number of the representation. We study the gap for quiver representations under the action of the special linear group.
Transpose-free linear algebra
arXiv:2606.01335v1 Announce Type: new Abstract: We study the limitations of matrix-free algorithms that access a matrix $A$ only through forward matrix-vector products (matvecs) $x \mapsto Ax$, without access to the transpose $A^\top$ or its action. This setting arises naturally in operator learning, inverse problems, and matrix-free PDE solvers, where adjoint evaluations may be unavailable or prohibitively expensive. We show that the lack of transpose access creates severe and sometimes...
ZOAF: Towards Efficient Zeroth-Order Optimization for Analog/RF Circuit Design
Announce Type: new Abstract: Circuit optimization is an indispensable step in analog/RF IC design. Classical fast gradient-based optimization methods are typically infeasible due to lack of access to simulator source code and the technical barriers to implementing adjoint methods. Therefore, surrogate-based black-box optimization is widely used in practice; however, it can be costly to build and sensitive to hyperparameters, whereas population heuristics often suffer from slow convergence...