11 papers
Directions That Don't Drift: Stiefel Manifold Routing for Transformer Attention
Rubén Darío Guerrero
The query and key projections $\WQ,\WK$ in attention are almost always trained by Euclidean optimizers with no geometric constraint. We constrain them to the Stiefel manifold and o…
Analytic Gradients and Nonadiabatic Couplings for Device-Resident DMRG-QD-NEVPT2 Through Conical Intersections on a Consumer GPU
Rubén Darío Guerrero
Nonadiabatic dynamics through a conical intersection requires both static and dynamic correlation and, at every geometry, an excited-state gradient and interstate nonadiabatic coup…
Spin Rotatory Strength as the Equilibrium Observable for Chiral-Induced Spin Selectivity
Rubén Dar\io Guerrero
We identify the spin rotatory strength---a chirality-odd, finite-frequency spin--dipole cross response---as the equilibrium observable for chiral-induced spin selectivity. Time-rev…
Density-Functional Excited-State Gradients and Nonadiabatic Couplings on a Consumer GPU from a Contraction-DAG
Rubén Darío Guerrero
Nonadiabatic dynamics needs an excited-state gradient and an interstate nonadiabatic coupling matrix element (NACME) at every nuclear geometry, and a double-hybrid functional's acc…
EOM-CC Excited-State Gradients and Nonadiabatic Couplings on a Consumer GPU from a Contraction-DAG with Laplace-Transform J/K Kernels
Rubén Darío Guerrero
We present a unified, memory-bounded GPU realization of equation-of-motion coupled-cluster (EOM-CC) excited-state gradients and interstate nonadiabatic couplings (NACMEs) on a sing…
Bond-dimension scaling of a local-refinement advantage over hyperoptimized tensor-network contraction on Sycamore like topologies
Rubén Darío Guerrero
We identify a missing local-refinement stage in the cotengra tensor-network contraction pipeline and show that its impact grows monotonically with bond dimension on the \emph{conne…
A four-player potential game for barren-plateau-aware quantum ansatz design
Rubén Darío Guerrero
We cast the design of parameterized quantum circuits as a four-player potential game whose state is a circuit directed acyclic graph (DAG) and whose players encode trainability, no…
RECURSUM: Automated Code Generation for Recurrence Relations Exceeds Expert Optimization via LayeredCodegen
Rubén Darío Guerrero
Automated code generation can systematically exceed expert hand-optimization for recurrence relations-computational primitives ubiquitous in orthogonal polynomials, special functio…
Physics-Constrained Adaptive Neural Networks Enable Real-Time Semiconductor Manufacturing Optimization with Minimal Training Data
Rubén Darío Guerrero
The semiconductor industry faces a computational crisis in extreme ultraviolet (EUV) lithography optimization, where traditional methods consume billions of CPU hours while failing…
Game-Theoretic Discovery of Quantum Error-Correcting Codes Through Nash Equilibria
Rubén Darío Guerrero
Quantum error correction code discovery has relied on algebraic constructions with predetermined structure or computational search lacking equilibrium-topology analysis. We introdu…
Bee-yond the Plateau: Training QNNs with Swarm Algorithms
Rubén Darío Guerrero
In the quest to harness the power of quantum computing, training quantum neural networks (QNNs) presents a formidable challenge. This study introduces an innovative approach, integ…