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Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inference costs. The standard alternative, fine-tuning smaller models, often sacrifices…

Computation and Language · Computer Science 2026-02-25 Sanket Badhe , Deep Shah

Magic states are a scarce resource for two-dimensional qubit stabilizer codes. Magic state cultivation was recently proposed to reduce the cost of magic state preparation by measuring the transversal Clifford operator of the color code.…

Quantum Physics · Physics 2026-05-11 Bence Hetényi , Benjamin J. Brown , Dominic J. Williamson

The asymptotic rates of information-theoretic protocols - including error exponents, compression rates, and channel capacities - are traditionally defined under the idealised assumption that the underlying resource (state or channel) is…

Quantum Physics · Physics 2026-05-19 Filippo Girardi , Nilanjana Datta , Giacomo De Palma , Ludovico Lami

A complementary behavior between local mutual information and average output entanglement is derived for arbitrary bipartite ensembles. This leads to bounds on the yield of entanglement in distillation protocols that involve disinguishing.…

Quantum Physics · Physics 2009-10-31 Michal Horodecki , Jonathan Oppenheim , Aditi Sen De , Ujjwal Sen

We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonrandom and observation occurs in nonsynchronous manner. The problem of nonsynchronous observations is important when we consider the analysis…

Statistics Theory · Mathematics 2022-07-04 Teppei Ogihara

We develop two general approaches to characterising the manipulation of quantum states by means of probabilistic protocols constrained by the limitations of some quantum resource theory. First, we give a general necessary condition for the…

Quantum Physics · Physics 2023-06-23 Bartosz Regula

Masked discrete diffusion is a dominant paradigm for high-quality language modeling where tokens are iteratively corrupted to a mask state, yet its inference efficiency is bottlenecked by the lack of deterministic sampling tools. While…

Machine Learning · Computer Science 2026-02-03 Guinan Chen , Xunpeng Huang , Ying Sun , Shijin Wang , Yanyong Zhang , Chao Wang

Quantum magic resources, or nonstabilizerness, are a central ingredient for universal quantum computation. In noisy many-body systems, the interplay between these resources and errors leads to sharp magic phase transitions. However, the…

Quantum Physics · Physics 2026-03-03 Piotr Sierant , Xhek Turkeshi

A new additive and semidefinite programming (SDP) computable entanglement measure is introduced to upper bound the amount of distillable entanglement in bipartite quantum states by operations completely preserving the positivity of partial…

Quantum Physics · Physics 2016-12-07 Xin Wang , Runyao Duan

Self-distillation (SD) is the process of first training a \enquote{teacher} model and then using its predictions to train a \enquote{student} model with the \textit{same} architecture. Specifically, the student's objective function is…

Machine Learning · Computer Science 2023-02-01 Rudrajit Das , Sujay Sanghavi

On-policy distillation (OPD), which aligns the student with the teacher's logit distribution on student-generated trajectories, has demonstrated strong empirical gains in improving student performance and often outperforms off-policy…

Machine Learning · Computer Science 2026-02-27 Wenkai Yang , Weijie Liu , Ruobing Xie , Kai Yang , Saiyong Yang , Yankai Lin

Recent observational studies of red giant stars have estimated the visibility of their mixed oscillation modes, which is a proxy of the average energy of these modes. Among other things, they demonstrated that although the damping rate of…

Solar and Stellar Astrophysics · Physics 2026-03-04 Jonas Müller , Quentin Coppée , Jordan Van Beeck , Tobias van Lier , Saskia Hekker

We investigate the nonparametric, composite hypothesis testing problem for arbitrary unknown distributions in the asymptotic regime where both the sample size and the number of hypotheses grow exponentially large. Such asymptotic analysis…

Information Theory · Computer Science 2019-01-30 Qunwei Li , Tiexing Wang , Donald J. Bucci , Yingbin Liang , Biao Chen , Pramod K. Varshney

Quantum state discrimination plays a central role in defining the possible and impossible operations through a restricted class of quantum operations. A seminal result by Bennett et al. [Phys. Rev. A 59, 1070 (1999)] demonstrates the…

Quantum Physics · Physics 2025-10-01 Hyukjoon Kwon

The remarkable phenomenon of catalyst tells us that adding a catalyst could help state transformation. In this paper, we consider the problem of catalyst-assisted probabilistic coherence distillation for mixed states under strictly…

Quantum Physics · Physics 2020-01-13 C. L. Liu , D. L. Zhou

We derive a sufficient condition for advantage distillation to be secure against collective attacks in device-independent quantum key distribution (DIQKD), focusing on the repetition-code protocol. In addition, we describe a semidefinite…

Quantum Physics · Physics 2020-05-19 Ernest Y. -Z. Tan , Charles C. -W. Lim , Renato Renner

The concept of knowledge distillation (KD) describes the training of a student model from a teacher model and is a widely adopted technique in deep learning. However, it is still not clear how and why distillation works. Previous studies…

Machine Learning · Computer Science 2025-10-20 Giulia Lanzillotta , Felix Sarnthein , Gil Kur , Thomas Hofmann , Bobby He

Pure states are an important resource in many quantum information processing protocols. However, even making a fixed pure state, say $|0\rangle$, in the laboratory requires a considerable amount of effort. Often one ends up with a mixed…

Quantum Physics · Physics 2024-03-26 Sayantan Chakraborty , Rahul Jain , Pranab Sen

We propose a distillation scaling law that estimates distilled model performance based on a compute budget and its allocation between the student and teacher. Our findings mitigate the risks associated with large-scale distillation by…

Machine Learning · Computer Science 2025-07-28 Dan Busbridge , Amitis Shidani , Floris Weers , Jason Ramapuram , Etai Littwin , Russ Webb

This paper systematically develops the resource theory of asymmetric distinguishability, as initiated roughly a decade ago [K. Matsumoto, arXiv:1010.1030 (2010)]. The key constituents of this resource theory are quantum boxes, consisting of…

Quantum Physics · Physics 2019-12-18 Xin Wang , Mark M. Wilde