Francesco Anna Mele
@francescoannamele.bsky.social
Quantum Information PhD student at Scuola Normale Superiore of Pisa (Italy)
It consists of this cute trophy, $3,500, and a fully funded trip to the Chicago Quantum Summit, an event that brings together academics, companies, and even politicians interested in quantum technologies.
November 5, 2025 at 5:18 AM
It consists of this cute trophy, $3,500, and a fully funded trip to the Chicago Quantum Summit, an event that brings together academics, companies, and even politicians interested in quantum technologies.
A huge thanks to the great team: Filippo, Freek, Lennart, @sfeoliviero.bsky.social, David, and Michael. It was a wonderful collaboration!
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October 9, 2025 at 10:36 AM
A huge thanks to the great team: Filippo, Freek, Lennart, @sfeoliviero.bsky.social, David, and Michael. It was a wonderful collaboration!
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I’m very happy to see that the entire toolbox of CV trace-distance bounds we’ve developed over the past two years finds concrete applications in this fundamental task in CV quantum information.
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October 9, 2025 at 10:36 AM
I’m very happy to see that the entire toolbox of CV trace-distance bounds we’ve developed over the past two years finds concrete applications in this fundamental task in CV quantum information.
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In this paper, we systematically investigate this problem, proving that testing Gaussianity can be done *efficiently* in the *pure-state* setting, but is fundamentally *inefficient* for general *mixed states*.
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October 9, 2025 at 10:36 AM
In this paper, we systematically investigate this problem, proving that testing Gaussianity can be done *efficiently* in the *pure-state* setting, but is fundamentally *inefficient* for general *mixed states*.
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Many thanks to my amazing coauthors: Marco, @vishnu-psiyer.bsky.social, Junseo, @antonioannamele.bsky.social! It was fun meeting at odd hours to sync between Europe, Asia, and the US, with our WhatsApp research group constantly active 🤣
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October 8, 2025 at 10:36 AM
Many thanks to my amazing coauthors: Marco, @vishnu-psiyer.bsky.social, Junseo, @antonioannamele.bsky.social! It was fun meeting at odd hours to sync between Europe, Asia, and the US, with our WhatsApp research group constantly active 🤣
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This result is the symplectic analogue of the polar decomposition for nearly unitary matrices:
given a matrix X that is epsilon-close to an (unknown) unitary, the polar decomposition efficiently outputs an exact unitary matrix U that remains O(epsilon)-close to X.
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given a matrix X that is epsilon-close to an (unknown) unitary, the polar decomposition efficiently outputs an exact unitary matrix U that remains O(epsilon)-close to X.
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October 8, 2025 at 10:36 AM
This result is the symplectic analogue of the polar decomposition for nearly unitary matrices:
given a matrix X that is epsilon-close to an (unknown) unitary, the polar decomposition efficiently outputs an exact unitary matrix U that remains O(epsilon)-close to X.
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given a matrix X that is epsilon-close to an (unknown) unitary, the polar decomposition efficiently outputs an exact unitary matrix U that remains O(epsilon)-close to X.
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We also introduce a method that may be of independent interest:
Given as input a matrix X that is epsilon-close to an (unknown) symplectic matrix, our method efficiently outputs an (exact) symplectic matrix S that remains O(epsilon)-close to X.
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Given as input a matrix X that is epsilon-close to an (unknown) symplectic matrix, our method efficiently outputs an (exact) symplectic matrix S that remains O(epsilon)-close to X.
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October 8, 2025 at 10:36 AM
We also introduce a method that may be of independent interest:
Given as input a matrix X that is epsilon-close to an (unknown) symplectic matrix, our method efficiently outputs an (exact) symplectic matrix S that remains O(epsilon)-close to X.
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Given as input a matrix X that is epsilon-close to an (unknown) symplectic matrix, our method efficiently outputs an (exact) symplectic matrix S that remains O(epsilon)-close to X.
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In our work, we carry out the first rigorous complexity analysis of learning Gaussian unitaries using a physically meaningful distance (the energy-constrained diamond norm), thereby proving that tomography of Gaussian unitary is efficient.
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October 8, 2025 at 10:36 AM
In our work, we carry out the first rigorous complexity analysis of learning Gaussian unitaries using a physically meaningful distance (the energy-constrained diamond norm), thereby proving that tomography of Gaussian unitary is efficient.
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Useful bounds on the energy-constrained diamond distance between Gaussian unitaries were recently proved by Becker, Lami, Datta, and Rouzé (arxiv.org/abs/2006.06659).
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Energy-constrained discrimination of unitaries, quantum speed limits and a Gaussian Solovay-Kitaev theorem
We investigate the energy-constrained (EC) diamond norm distance between unitary channels acting on possibly infinite-dimensional quantum systems, and establish a number of results. Firstly, we prove ...
arxiv.org
October 8, 2025 at 10:36 AM
Useful bounds on the energy-constrained diamond distance between Gaussian unitaries were recently proved by Becker, Lami, Datta, and Rouzé (arxiv.org/abs/2006.06659).
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To address this, Maksim Shirokov (arxiv.org/abs/1706.00361) and Andreas Winter (arxiv.org/pdf/1712.10267) introduced the *energy-constrained diamond norm*, a physically meaningful way to measure distances between CV quantum channels.
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Energy-constrained diamond norms and their use in quantum information theory
We consider the family of energy-constrained diamond norms on the set of Hermitian-preserving linear maps (superoperators) between Banach spaces of trace class operators. We prove that any norm from t...
arxiv.org
October 8, 2025 at 10:36 AM
To address this, Maksim Shirokov (arxiv.org/abs/1706.00361) and Andreas Winter (arxiv.org/pdf/1712.10267) introduced the *energy-constrained diamond norm*, a physically meaningful way to measure distances between CV quantum channels.
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This is so because the definition of diamond norm allows *infinite-energy* input states (which is, of course, unphysical!)
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October 8, 2025 at 10:36 AM
This is so because the definition of diamond norm allows *infinite-energy* input states (which is, of course, unphysical!)
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However, the diamond norm loses its physical meaning for CV systems: e.g., the diamond distance between two different beam splitters is *always* maximal, even if their transmissivities differ by an infinitesimal amount.
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October 8, 2025 at 10:36 AM
However, the diamond norm loses its physical meaning for CV systems: e.g., the diamond distance between two different beam splitters is *always* maximal, even if their transmissivities differ by an infinitesimal amount.
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The first non-trivial question is: how should we quantify the estimation error when learning a CV quantum channel? In DV systems, this is done using the *diamond norm*, a well-motivated metric for DV quantum channels.
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October 8, 2025 at 10:36 AM
The first non-trivial question is: how should we quantify the estimation error when learning a CV quantum channel? In DV systems, this is done using the *diamond norm*, a well-motivated metric for DV quantum channels.
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In our new paper, we answer this question, designing efficient learning algorithms with rigorous performance guarantees.
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October 8, 2025 at 10:36 AM
In our new paper, we answer this question, designing efficient learning algorithms with rigorous performance guarantees.
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While writing up this paper, we became aware of arxiv.org/abs/2502.18656, whose main result is similar to ours. The proof techniques in the two papers, however, are significantly different
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Quantum data-hiding scheme using orthogonal separable states
We consider bipartite quantum state discrimination and present a quantum data-hiding scheme utilizing an orthogonal separable state ensemble. Using a bound on local minimum-error discrimination, we pr...
arxiv.org
October 7, 2025 at 10:16 AM
While writing up this paper, we became aware of arxiv.org/abs/2502.18656, whose main result is similar to ours. The proof techniques in the two papers, however, are significantly different
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Many thanks to Ludovico Lami for this collaboration that lasted two (very busy) years! And a big thanks also to @jenseisert.bsky.social for kindly hosting us in the Berlin group in 2023, where this project began.
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October 7, 2025 at 10:16 AM
Many thanks to Ludovico Lami for this collaboration that lasted two (very busy) years! And a big thanks also to @jenseisert.bsky.social for kindly hosting us in the Berlin group in 2023, where this project began.
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In this work, we find explicit examples of quantum data hiding states that are both separable and perfectly orthogonal, thereby exhibiting the phenomenon of nonlocality without entanglement to the utmost extent.
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October 7, 2025 at 10:16 AM
In this work, we find explicit examples of quantum data hiding states that are both separable and perfectly orthogonal, thereby exhibiting the phenomenon of nonlocality without entanglement to the utmost extent.
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Prior to this research, pairs of quantum data hiding states were known only in two cases: either separable or globally perfectly orthogonal, but not both — separability comes at the price of orthogonality being only approximate.
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October 7, 2025 at 10:16 AM
Prior to this research, pairs of quantum data hiding states were known only in two cases: either separable or globally perfectly orthogonal, but not both — separability comes at the price of orthogonality being only approximate.
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