RASCqL: Reaction-time-limited Architecture for Space-time-efficient Complex qLDPC Logic
- URL: http://arxiv.org/abs/2602.14273v1
- Date: Sun, 15 Feb 2026 18:52:25 GMT
- Title: RASCqL: Reaction-time-limited Architecture for Space-time-efficient Complex qLDPC Logic
- Authors: Willers Yang, Jason Chadwick, Mariesa H. Teo, Joshua Viszlai, Fred Chong,
- Abstract summary: RASCqL is a Reaction-timelimited Architecture for Space-time-efficient qLDPC Logic.<n>It supports key algorithmic subroutines such as quantum arithmetic, table lookups, and magic-state distillation directly in qLDPC codes.<n>RASCqL implements key algorithmic subroutines at space-time costs comparable to state-of-the-art surface-code architectures.
- Score: 0.39768138694503036
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum low-density parity-check (qLDPC) codes offer a promising route to scalable fault-tolerant quantum computing (FTQC) due to their substantially reduced footprint, but these gains can be diluted at utility scale if we cannot also realize a space-time-efficient instruction-set architecture (ISA) for relevant quantum applications. We present RASCqL, a Reaction-time-limited Architecture for Space-time-efficient Complex qLDPC Logic, introducing a complex-instruction-set quantum computer (CISQ) that supports key algorithmic subroutines such as quantum arithmetic, table lookups, and magic-state distillation directly in co-designed qLDPC codes. Unlike prior constructions for qLDPC logic that aim at versatile ISAs amenable to diverse circuits, RASCqL adopts an application-tailored code-modification scheme that embeds specific complex Clifford instructions useful for functional subroutines as virtually implementable matrix automorphisms. RASCqL further leverages parallel physical operations in reconfigurable neutral-atom array platforms to achieve fast QEC cycles and high-fidelity transversal operations. At the cost of increased design complexity, RASCqL implements key algorithmic subroutines at space-time costs comparable to state-of-the-art transversal surface-code architectures while achieving up to $2\times$ to $7\times$ footprint reduction under realistic physical error rates of $2 \times 10^{-3}$ to $5 \times 10^{-4}$, without additional hardware complexity. RASCqL thus demonstrates a concrete path forward for qLDPC codes as CISQ compute modules, extending their practical utility in fault-tolerant quantum computing architectures.
Related papers
- Explicit construction of low-overhead gadgets for gates on quantum LDPC codes [0.0]
A popular method for performing logical operations is by measuring logical Pauli operators.<n>We present a simple, explicit construction for fixed gadgets that can measure arbitrary logical Pauli operators on QLDPC codes.
arXiv Detail & Related papers (2025-11-20T02:41:31Z) - Batched high-rate logical operations for quantum LDPC codes [2.722479714583866]
High-rate quantum LDPC codes reduce memory overhead by densely packing many logical qubits into a single block of physical qubits.<n>We extend this concept to high-rate computation by constructing emphbatched fault-tolerant operations that apply the same logical gate across many code blocks in parallel.
arXiv Detail & Related papers (2025-10-07T17:26:10Z) - ConQuER: Modular Architectures for Control and Bias Mitigation in IQP Quantum Generative Models [40.972673943861075]
Quantum generative models based on instantaneous quantum (IQP) circuits show great promise in learning complex distributions.<n>Current implementations suffer from lack of controllability over generated outputs and severe generation bias towards certain expected patterns.<n>We present a Controllable Quantum Generative Framework, ConQuER, which addresses both challenges through a modular circuit architecture.
arXiv Detail & Related papers (2025-09-26T16:32:41Z) - Resource Analysis of Low-Overhead Transversal Architectures for Reconfigurable Atom Arrays [38.6948808036416]
We present a low-overhead architecture that supports the layout and resource estimation of large-scale fault-tolerant quantum algorithms.<n>We find that a 2048-bit RSA factoring can be executed with 19 million qubits in 5.6 days, for 1 ms QEC cycle times.
arXiv Detail & Related papers (2025-05-21T18:00:18Z) - Extractors: QLDPC Architectures for Efficient Pauli-Based Computation [39.98920557126034]
We propose a new primitive that can augment any QLDPC memory into a computational block well-suited for Pauli-based computation.<n>In particular, any logical Pauli operator supported on the memory can be fault-tolerantly measured in one logical cycle.<n>Our architecture can implement universal quantum circuits via parallel logical measurements.
arXiv Detail & Related papers (2025-03-13T14:07:40Z) - Fast and Parallelizable Logical Computation with Homological Product Codes [3.4338109681532027]
High-rate quantum low-density-parity-check (qLDPC) codes promise a route to reduce qubit numbers, but performing computation while maintaining low space cost has required serialization of operations and extra time costs.
We design fast and parallelizable logical gates for qLDPC codes, demonstrating their utility for key algorithmic subroutines such as the quantum adder.
arXiv Detail & Related papers (2024-07-26T03:49:59Z) - Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
We develop a reinforcement learning-based quantum compiler for a superconducting processor.
We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths.
Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
arXiv Detail & Related papers (2024-06-18T01:49:48Z) - Compiler for Distributed Quantum Computing: a Reinforcement Learning Approach [6.347685922582191]
We introduce a novel compiler that prioritizes reducing the expected execution time by jointly managing the generation and routing of EPR pairs.
We present a real-time, adaptive approach to compiler design, accounting for the nature of entanglement generation and the operational demands of quantum circuits.
Our contributions are twofold: (i) we model the optimal compiler for DQC using a Markov Decision Process (MDP) formulation, establishing the existence of an optimal algorithm, and (ii) we introduce a constrained Reinforcement Learning (RL) method to approximate this optimal compiler.
arXiv Detail & Related papers (2024-04-25T23:03:20Z) - The Basis of Design Tools for Quantum Computing: Arrays, Decision
Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
Quantum computers promise to efficiently solve important problems classical computers never will.
A fully automated quantum software stack needs to be developed.
This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
arXiv Detail & Related papers (2023-01-10T19:00:00Z) - Optimizing Tensor Network Contraction Using Reinforcement Learning [86.05566365115729]
We propose a Reinforcement Learning (RL) approach combined with Graph Neural Networks (GNN) to address the contraction ordering problem.
The problem is extremely challenging due to the huge search space, the heavy-tailed reward distribution, and the challenging credit assignment.
We show how a carefully implemented RL-agent that uses a GNN as the basic policy construct can address these challenges.
arXiv Detail & Related papers (2022-04-18T21:45:13Z) - Logical blocks for fault-tolerant topological quantum computation [55.41644538483948]
We present a framework for universal fault-tolerant logic motivated by the need for platform-independent logical gate definitions.
We explore novel schemes for universal logic that improve resource overheads.
Motivated by the favorable logical error rates for boundaryless computation, we introduce a novel computational scheme.
arXiv Detail & Related papers (2021-12-22T19:00:03Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.