13 papers
Parametrized Exact Hardware-Software Partitioning
Cameron Ibrahim, S M Ferdous, Erdal Mutlu +2
When optimizing computing architecture for specific computationally intensive tasks, such as evaluating or training a neural network, it is important to identify what computational…
The Expressive Power of Constrained QAOA: What You Might Have MISsed
Boris Tsvelikhovskiy, Bao Bach, Ilya Safro
Feasibility-preserving mixer Hamiltonians offer an attractive alternative to penalty encodings for constrained quantum optimization, yet how enforcing constraints alters the state…
Warm-Starting MaxCut Relaxation via Low-Depth Quantum Approximate Optimization Algorithm
Bao G. Bach, Ilya Safro, Filip B. Maciejewski
Quantum optimization has attracted growing interest as quantum hardware continues to improve, yet state-of-the-art classical solvers remain a formidable benchmark for practical uti…
Exponentially many initializations to avoid barren plateaus
Ankit Kulshrestha, Ricard Puig, Diego García-Martín +4
Barren plateaus are stated as an average-case phenomenon: pick an ansatz, initialize it naively, and concentration follows. This has led to the common view that a potential cure fo…
Scaling Quantum Optimization for Unit Commitment via Pauli Correlation Encoding
Kien X. Nguyen, Ilya Safro, Xiaoyuan Liu
Unit commitment is an important optimization problem in power system operations, classified as NP-hard. This paper presents a hybrid quantum-classical method for the unit commitmen…
QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learning
Kien X. Nguyen, Ankit Kulshrestha, Ilya Safro +1
Qubit routing is a fundamental problem in quantum compilation, known to be NP-hard. Its dynamic nature makes local routing decisions propagate and compound over time, making global…
Quantum Hypergraph Partitioning
Cameron Ibrahim, Bao G. Bach, Jad Salem +4
Quantum optimization algorithms are inherently probabilistic, yet they are most often used to search for a single high-quality solution. In this paper, we instead study hypergraph…
Scaling Qubit Mapping and Routing With Position Graph Abstraction and Memoization
Brent Russon, Bao Bach, Ed Younis +1
Scalable qubit mapping and routing remain major bottlenecks in quantum compilation, especially for Trapped-Ion Quantum Charge-Coupled device (TI-QCCD) architectures, where qubit in…
QUACOD: Quantum Optimization via Coordinate Descent for Scalable Drone Scheduling
Van-Quang-Huy Nguyen, Hoang-Quan Nguyen, Samee U. Khan +2
Quantum computing has demonstrated its potential to solve various optimization problems, including drone scheduling, which is important not only for drone delivery but also for log…
Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem
Pratim Ugale, Ilya Tyagin, Karunya Shirali +2
This work introduces Q3SAT-GPT, a generative model for discovering quantum circuits for the Max-E3-SAT problem. Our method learns from high-performing QAOA-style ansätze to directl…
Graph-Conditioned Meta-Optimizer for QAOA Parameter Generation on Multiple Problem Classes
Kien X. Nguyen, Ilya Safro
We study parameter transferability for the Quantum Approximate Optimization Algorithm (QAOA) across multiple combinatorial optimization problem classes from a parameter generation…
Learning Cut Distributions with Quantum Optimization
Bao Bach, Cameron Ibrahim, Reuben Tate +3
Many combinatorial optimization problems admit a maximin fairness variant, where the aim is to find a distribution over possible solutions which maximizes an expected worst-case ou…
UniHetCO: A Unified Heterogeneous Representation for Multi-Problem Learning in Unsupervised Neural Combinatorial Optimization
Kien X. Nguyen, Ilya Safro
Unsupervised neural combinatorial optimization (NCO) offers an appealing alternative to supervised approaches by training learning-based solvers without ground-truth solutions, dir…