Quantum information at NIST and the federal research agenda | NIST

David J. Wineland

John Chiaverini, M. D. Barrett, R. B. Blakestad +9 more

A. C. Wilson

Patricia Moloney Figliola

Rocco Ballester, Jesús Cerquides, Luis Artiles

Abstract Federated learning (FL) is a recent technique that emerged to handle the vast amount of training data needed in machine learning algorithms while fulfilling data owners’ privacy challenges in such scenarios. Simultaneously, the field of quantum computing (QC), using quantum properties such as entanglement and superposition to perform computation, has experienced exponential growth, theoretically proving to be more efficient in specific machine learning tasks and creating the discipline known as quantum machine learning (QML). Thus, an emerging body of knowledge has started studying the combination of these two research agendas, giving rise to the field of quantum federated learning (QFL). In this review, we systematically classify the existing literature through a novel taxonomy, identify current trends and challenges, and highlight research gaps and future directions to support the continued development of this emerging field.

Thripurala Renuka Devi

Background: The imminent threat posed by cryptographically relevant quantum computers to classical public-key infrastructure specifically RSA and Elliptic-Curve Cryptography (ECC), whose security rests on the conjectured computational intractability of integer factorisation and the discrete logarithm problem respectively has propelled lattice-based cryptography to the centre of global post-quantum standardisation efforts. On 13 August 2024, the United States National Institute of Standards and Technology (NIST) published three landmark Federal Information Processing Standards (FIPS): FIPS 203 (ML-KEM, derived from CRYSTALS-Kyber), FIPS 204 (ML-DSA, derived from CRYSTALS-Dilithium), and FIPS 205 (SLH-DSA, derived from SPHINCS+), with FIPS 206 (FN-DSA, derived from FALCON) in advanced draft. The first three of these standards rest on algebraic structures intimately connected to classical number theory: polynomial rings over integer quotients, cyclotomic fields, and the algebraic geometry of ideal lattices in rings of integers of number fields. Objectives: This article provides: (1) a rigorous mathematical exposition of the lattice problems underpinning NIST’s post-quantum standards, specifically the Learning With Errors (LWE), Ring-LWE (RLWE), Module-LWE (MLWE), Short Integer Solution (SIS), and NTRU problems, and their connections to algebraic number theory; (2) a comparative performance analysis of NIST-standardised lattice-based algorithms against classical RSA and ECC benchmarks; (3) a security analysis examining known classical and quantum attacks on each hard problem; (4) a comparative evaluation of the four NIST-selected algorithms across key size, signature size, and computational benchmarks; and (5) a strategic assessment of the migration challenges facing deployed cryptographic infrastructure. Methods: The study synthesises peer-reviewed literature, NIST official standards documentation (FIPS 203, 204, 205, and draft FIPS 206), and independently published performance benchmarks published between June 2024 and June 2026. Mathematical security analysis is grounded in the worst-case to average-case reductions established by Regev (2005) for LWE and by Lyubashevsky, Peikert, and Regev (2013) [11, 18] for Ring-LWE. Performance data are drawn from Garani (2024) [8], the ARM Cortex-M0+ benchmarking study of Ratnayaka and Fischer (2026) [4], and the cross-platform evaluation by Alzahrani et al. (2025) [2]. Results: NIST’s three August 2024 standards establish a comprehensive lattice-based post-quantum portfolio. ML-KEM-768 produces a 1,184-byte public key and 1,088-byte ciphertext, achieving IND-CCA2 security under the MLWE assumption at NIST Level 3 (AES-192 equivalent). ML-DSA-65 produces 1,952-byte public keys and 3,309-byte signatures under the Module-LWE and Module-SIS assumptions at Level 3. FN-DSA-512 (FALCON, draft FIPS 206) produces 897-byte public keys and 666-byte signatures under the NTRU assumption, offering the most compact lattice-based signatures. Performance benchmarks on an Intel Core i7-12700K (3.6 GHz) confirm that ML-KEM key generation is orders of magnitude faster than RSA-3072 key generation. The algebraic structure of cyclotomic polynomial rings ∑₂ⁿ = Z[x]/(x^n + 1) is central to the efficiency of all three lattice-based NIST standards. Conclusion: Lattice-based cryptography, grounded in the algebraic number theory of ideal lattices over cyclotomic fields, provides the most comprehensive and mathematically well-founded response to the quantum computational threat. The August 2024 NIST standardisation of ML-KEM, ML-DSA, and SLH-DSA represents a landmark in cryptographic history, and the imminent finalisation of FN-DSA will complete the post-quantum toolbox. Organisations should prioritise immediate migration planning, leveraging hybrid classical-quantum schemes during transition, with full transition to NIST post-quantum standards recommended by 2030 per NSA and CISA guidance.