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We report on the first experimental demonstration of purification of nonclassical continuous variable states. The protocol uses two copies of phase-diffused states overlapped on a beam splitter and provides Gaussified, less mixed states…

Quantum Physics · Physics 2007-07-03 A. Franzen , B. Hage , J. DiGuglielmo , J. Fiurasek , R. Schnabel

We consider a continuous measurement of a two-level system (double-dot) by weakly coupled detector (tunnel point contact nearby). While usual treatment leads to the gradual system decoherence due to the measurement, we show that the…

Quantum Physics · Physics 2007-05-23 Alexander N. Korotkov

Local pure states are an important resource for quantum computing. The problem of distilling local pure states from mixed ones can be cast in an information theoretic paradigm. The bipartite version of this problem where local purity must…

Quantum Physics · Physics 2009-11-13 Hari Krovi , Igor Devetak

We characterize the distillation of quantum coherence in the one-shot setting, that is, the conversion of general quantum states into maximally coherent states under different classes of quantum operations. We show that the maximally…

Quantum Physics · Physics 2018-07-05 Bartosz Regula , Kun Fang , Xin Wang , Gerardo Adesso

This paper is the first part of a project devoted to studying the interconnection between controllability properties of a dynamical system and the large-time asymptotics of trajectories for the associated stochastic system. It is proved…

Classical Analysis and ODEs · Mathematics 2018-03-07 Armen Shirikyan

It is shown that, if the loss of entanglement along a quantum channel is sufficiently small, then approximate quantum error correction is possible, thereby generalizing what happens for coherent information. Explicit bounds are obtained for…

Quantum Physics · Physics 2008-01-15 Francesco Buscemi

We prove new results on the stability of the absolutely continuous spectrum for perturbed Stark operators with decaying or satisfying certain smoothness assumption perturbation. We show that the absolutely continuous spectrum of the Stark…

Spectral Theory · Mathematics 2016-09-07 Alexander Kiselev

On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this signal is beneficial and under which it is detrimental. Which teacher model should be used,…

In this work, we investigate the implicit regularization induced by teacher-student learning dynamics in self-distillation. To isolate its effect, we describe a simple experiment where we consider teachers at random initialization instead…

Machine Learning · Computer Science 2023-07-06 Felix Sarnthein , Gregor Bachmann , Sotiris Anagnostidis , Thomas Hofmann

We study sequential measurement scenarios where the system is repeatedly subjected to the same measurement process. We first provide examples of such repeated measurements where further repetitions of the measurement do not increase our…

Quantum Physics · Physics 2016-09-14 Erkka Haapasalo , Teiko Heinosaari , Yui Kuramochi

Codistillation has been proposed as a mechanism to share knowledge among concurrently trained models by encouraging them to represent the same function through an auxiliary loss. This contrasts with the more commonly used fully-synchronous…

Machine Learning · Computer Science 2021-07-27 Shagun Sodhani , Olivier Delalleau , Mahmoud Assran , Koustuv Sinha , Nicolas Ballas , Michael Rabbat

For any unitarily invariant convex function F on the states of a composite quantum system which isolates the trace there is a critical constant C such that F(w)<= C for a state w implies that w is not entangled; and for any possible D > C…

Quantum Physics · Physics 2009-11-11 G. A. Raggio

Active learning can be defined as iterations of data labeling, model training, and data acquisition, until sufficient labels are acquired. A traditional view of data acquisition is that, through iterations, knowledge from human labels and…

Machine Learning · Computer Science 2022-01-28 Beong-woo Kwak , Youngwook Kim , Yu Jin Kim , Seung-won Hwang , Jinyoung Yeo

In self-supervised learning, self-distilled methods have shown impressive performance, learning representations useful for downstream tasks and even displaying emergent properties. However, state-of-the-art methods usually rely on ensembles…

Machine Learning · Computer Science 2026-05-01 Esteban Rodríguez-Betancourt , Edgar Casasola-Murillo

Repeated closed-loop control operations acting as piecewise-constant Liouville superoperators conditioned on the outcomes of regularly performed measurements may effectively be described by a fixed-point iteration for the density matrix.…

Quantum Physics · Physics 2012-06-26 Gernot Schaller

We show that a two-level non-Hermitian Hamiltonian with constant off-diagonal exchange elements can be analyzed exactly when the underlying exceptional point is perfectly encircled in the complex plane. The state evolution of this system is…

A general description of entanglement is suggested as an action realized by an arbitrary operator over given disentangled states. The related entanglement measure is defined. Because of its generality, this definition can be employed for…

Quantum Physics · Physics 2009-11-10 V. I. Yukalov

We show that a perfectly genuine tripartite EPR steerable assemblage can be distilled from partially genuine tripartite EPR steerable assemblages. In particular, we consider two types of hybrid scenarios: one-sided device-independent (1SDI)…

Quantum Physics · Physics 2021-08-12 Shashank Gupta , Debarshi Das , A. S. Majumdar

Assume that Alice, Bob, and Charlie share a tripartite pure state $|\psi_{ABC}\rangle$. We prove that if Alice cannot distill entanglement with either Bob or Charlie using $|\psi_{ABC}\rangle$ and local operations with any one of the…

Quantum Physics · Physics 2024-10-24 Satvik Singh , Nilanjana Datta

Knowledge distillation introduced in the deep learning context is a method to transfer knowledge from one architecture to another. In particular, when the architectures are identical, this is called self-distillation. The idea is to feed in…

Machine Learning · Computer Science 2020-10-27 Hossein Mobahi , Mehrdad Farajtabar , Peter L. Bartlett