Giacomo Franceschetto

PhD in quantum info theory

Interested in q info & computation

[Physical Review X @PhysRevX]

While quantum back-action is often considered a hindrance in #quantum reservoir computing, it can actually be leveraged to improve performance, a new study suggests. See how:

🔗 https://t.co/i5nI1BU80H

[Quantiki @quantiki]

More info: https://t.co/gDojcOhYP1

[Giacomo Franceschetto @giacomofrn]

Check the related paper here https://t.co/rKSmSb2LGV

[Giacomo Franceschetto @giacomofrn]

Presenting my work on making decisions with single photons (done with @Quandela_SAS ) in Tenerife at @ICE9_Tenerife !🤩

[ICE-9 Conference Tenerife @ICE9_Tenerife]

The #ICE9 morning session continued with nice talks by Ivan Bocanegra, Giacomo Franceschetto and Carles Roch

[BSC-CNS @BSC_CNS]

✨Considering a PhD at BSC? 👋Join us!

🔸With ”la Caixa” Foundation’s programme for doctoral #INPhINIT fellowships, you can carry out research at one of the best universities or research centres in Spain or Portugal

➡https://t.co/eEPsAjGA1G

#Fellowships #laCaixaFoundFellows

[Giacomo Franceschetto @giacomofrn]

Check the paper for more details! And many thanks to my collaborators at @ICFOnians; @marcinplodzien, Maciej Lewenstein, Antonio Acín and Pere Mujal😊

https://t.co/GrmNQv7Nv0

[Giacomo Franceschetto @giacomofrn]

Is quantum back-action necessarily a bad thing?🧐

https://t.co/GrmNQv8lky

Not always! In our recent work, we explore how the ability to tune the disturbance induced by observing a quantum system can be beneficial for the case of quantum reservoir computing (QRC)! 👇🧵

[Giacomo Franceschetto @giacomofrn]

Moreover, we consider also the practical scenario where only a limited number of shots are available and show the combined effect of better scaling plus back-action enhancement.

[Giacomo Franceschetto @giacomofrn]

Check the paper for more details! Huge thanks to @aricou6 and the amazing team at @Quandela_SAS, especially @AlexiaSalavra & @plussailleurs 🙌🙌

https://t.co/cs7v1IyAVB

[Giacomo Franceschetto @giacomofrn]

Can we use single particles of light to make decisions?🤔

https://t.co/cs7v1IyAVB

In our preprint, we borrowed some photons from @Quandela_SAS to tackle a test bed reinforcement learning (RL) task in which finding the optimal strategy is conditional to using quantum effects. 🧵

[Giacomo Franceschetto @giacomofrn]

In our work, we show this by performing experiments both on (ideal and noisy) simulators and on photonic hardware. 🔧