https://quantumzeitgeist.com/quantum-neural-training-networks-states-efficient-privacy-preserving-utilizes-mixed-data-ensembles/
good summary of the preprint
Posts Tagged ‘gw’
Efficient Privacy-Preserving Training Of Quantum Neural Networks Utilizes Mixed States For Data Ensembles
September 21, 2025Holevo’s theorem
June 29, 2025quantum mechanics – How to understand the Holevo capacity intuitively? – Physics Stack Exchange
https://physics.stackexchange.com/questions/711441/how-to-understand-the-holevo-capacity-intuitively
The Limits of Differential Privacy (and Its Misuse in Data Release and Machine Learning) | July 2021 | Communications of the ACM
June 28, 2025Differential privacy is not a silver bullet for all privacy problems. By Josep Domingo-Ferrer, David Sánchez, and Alberto Blanco-Justicia Posted Jul 1 2021
QT:{{”
The traditional approach to statistical disclosure control (SDC) for privacy protection is utility-first. Since the 1970s, national statistical institutes have been using anonymization methods with heuristic parameter choice and suitable utility preservation properties to protect data before release. Their goal is to publish analytically useful data that cannot be linked to specific respondents or leak confidential information on them.
In the late 1990s, the computer science community took another angle and proposed privacy-first data protection. In this approach a privacy model specifying an ex ante privacy condition is enforced using one or several SDC methods, such as noise addition, generalization, or microaggregation. The parameters of the SDC methods depend on the privacy model parameters, and too strict a choice of the latter may result in poor utility. The first widely accepted privacy model was k-anonymity, whereas differential privacy (DP) is the model that currently attracts the most attention.
…
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lecture note on mixed state and density matrix
May 11, 2025https://www.henryyuen.net/classes/spring2022/
https://www.henryyuen.net/spring2022/lec2-mixed-states.pdf
lecture notes on mixed states and density matrix.
QT:{{”
Frontiers of Quantum Complexity and Cryptography Lecture 2 – Mixed States and Density Matrices
Lecturer: Henry Yuen Spring 2022
Scribes: Melody Hsu
In the third lecture, we wrapped up a review of the foundational concepts we will need to tackle
later topics, and then started our first quantum complexity topic, state tomography. We briefly
discussed several ways to analyze probabilistic mixtures of quantum states; after the conclusion of
the review, we explored lower bounds on complexity of a classic tomography protocol.
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Advances in the Quantum Internet | August 2022 | Communications of the ACM
January 25, 2023https://cacm.acm.org/magazines/2022/8/262904-advances-in-the-quantum-internet/fulltext
another use of quantum in computing
HE library links
May 22, 2022https://www.nature.com/articles/s41586-022-04623-2
Perspective
Published: 11 May 2022
Transitioning organizations to post-quantum cryptography
David Joseph, Rafael Misoczki, Marc Manzano, Joe Tricot, Fernando Dominguez Pinuaga, Olivier Lacombe, Stefan Leichenauer, Jack Hidary, Phil Venables & Royal Hansen
Nature volume 605, pages237–243 (2022)
new paper on post-quantum cryptography (PQC):
Interesting article on NFT and genomics
May 22, 2022https://www.nature.com/articles/d41586-021-01642-3
18 June 2021
How scientists are embracing NFTs
Is a trend of auctioning non-fungible tokens based on scientific data a fascinating art fad, an environmental disaster or the future of monetized genomics?
Nicola Jones
an article discussing combining NFT (a hype which is related to blockchain) and genomics data.
HE library links
May 15, 2022Perspective
Published: 11 May 2022
Transitioning organizations to post-quantum cryptography
David Joseph, Rafael Misoczki, Marc Manzano, Joe Tricot, Fernando Dominguez Pinuaga, Olivier Lacombe, Stefan Leichenauer, Jack Hidary, Phil Venables & Royal Hansen
Nature volume 605, pages237–243 (2022)
new paper on post-quantum cryptography (PQC):
linkstream2 microblog 