Adam Frim

PhD student @BerkeleyPhysics working in nonequilibrium thermodynamics and statistical mechanics of small (sometimes biological) systems

[DeWeese Lab @DeWeeseLab]

Very excited to share our new paper out in PRL today (as an Editors’ Suggestion)! We unify thermodynamic geometry 🔥 and optimal transport 🥖 providing a coherent picture for optimal minimal-work protocols for arbitrary driving strengths 💪 and speeds ⏱️ ! https://t.co/FHm69Ts7yv

[Matt Leighton @MattLeighton5]

Out today in @PhysRevLett: “Inferring Subsystem Efficiencies in Bipartite Molecular Machines”, with @DavidASivak @SFUPhysics. Check out the paper: https://t.co/sc0Rgy3b6B, or a synopsis in @PhysicsMagazine by @CSRDay: https://t.co/n9MRetkWY5 (1/7)

[Matt Leighton @MattLeighton5]

Excited to be in Las Vegas for #APSMarch this week! I’ll be in session D08: Molecular Machines on Monday afternoon, presenting work with @DavidASivak on inferring energy and information flows inside of two-component molecular machines like ATP-Synthase. (https://t.co/00EUvASUT6)

[Pedro Harunari @pedroharunari]

Happy to see this paper published!
Great efforts from collaborators and I lead to results I'm really proud of. And everything started in the charming city of Trieste.

[Nivedina Sarma @nivedina]

Really happy to see our analysis of structure-property relationships for polymer-drug self-assembly in @PNASNews this week!
https://t.co/ARQM8LX6ZR

[Tushar Saha @TusharKSaha]

#Bayesian info. engine out in @PhysRevLett! Amazing collaboration with @jnlucero96, @Nikthebigfish from @DavidASivak & Bechhoefer groups @SFUPhysics!
https://t.co/Lqkon8n6aG

[Matt Leighton @MattLeighton5]

Excited to announce a new paper in @PhysRevLett: “Dynamic and Thermodynamic Bounds for Collective Motor-Driven Transport”, with @DavidASivak @SFUPhysics. Check it out at https://t.co/cfIQipleiB. (1/6)

[Christopher W. Lynn @ChrisWLynn]

Breakthroughs in physics now allow us to quantify the arrow of time (irreversibility). But how does it emerge in complex systems like the brain? We build a framework to answer this question.

Out now in @PhysRevLett: https://t.co/187Ebsjatr

[Akira Sone @SoneAkira]

Great collaboration with Naoki Yamamoto, Tharon Holdsworth and Prineha Narang (@NarangLab )! We explored the quantum cross entropy from the integrated fluctuation theorems. Happy reading!!
https://t.co/sU08ElXAlx

@UMassBoston, @keio_st, @AliroQuantum

[Pedro Harunari @pedroharunari]

The *(POST)MODERN THERMODYNAMICS* shool+workshop website is finally here! It will happen between 5-9 Dec in Luxembourg.

Covering fields like stochastic thermo, active matter, quantum thermo, chemical reaction networks, and more.

Please spread the word!

https://t.co/PuOSBLPAca

[Adam Frim @AdamFrim]

Very proud to announce our latest out today in @PhysRevLett as an Editors' Suggestion!

We apply isoperimetric inequalities to derive a novel bound on efficiency for any thermodynamic cycle and construct new, geometrically optimal cycles.

Full story: https://t.co/JfnCAOd6EB

[@HinczewskiLab @hinczewskilab]

Our latest collaboration on control of stochastic biological systems is just out this week at Phys. Rev. X (https://t.co/ZjhvbwXBrY), with: @efephys, Özenç Güngör, @benkuznetsspeck, Joshua Chiel, and @quthermo_comp. (1/8)

[Pradeep Niroula @NiroulaPradeep]

Our paper realizing measurement induced phases is now in Nature Physics @crystalMIT13

https://t.co/4dftI4PZO8

[DeWeese Lab @DeWeeseLab]

Very happy to see @AdamFrim's latest out in @PhysRevE: we apply a geometric approach to derive new, experimentally accessible optimal Carnot and Carnot-like Brownian engines at the nanoscale!

https://t.co/O4IICJxxlE

(and stay tuned for more on this topic shortly...)

[andrew @li_geralde]

New preprint from @DeWeeseLab!

TLDR: experiments show neurons in primary visual cortex are tuned for lower spatial frequencies earlier in development. We show the theory of sparse coding is sufficient to account for this phenomenon.

Read more here: https://t.co/7o8YJFZYSx

[Pradeep Niroula @NiroulaPradeep]

My first thread. On quantum optimization.

I wrote a feature on the theoretical and experimental challenges behind quantum optimization. https://t.co/Qpqmwoav7s

Here are some key insights (1/n)

[Ariel Amir @Ariel_4321]

Very sad to learn that Howard Berg passed away.
His decades-long work on chemotaxis is incredibly beautiful. He developed the elegant phenomenological theory and then tracked down the molecular mechanisms. His book "Random Walks in Biology" is a gem.

[Adam Frim @AdamFrim]

Check this out and ping me with any questions so I can refer them to Ethan Evans(, PhD!) and Ziyi Wang (of Georgia Tech) who actually know what's going on, and who both put in tremendous effort and deserve massive credit (and acclaim)!

[DeWeese Lab @DeWeeseLab]

Very happy to announce our latest, in collaboration with the Theodorou group at Georgia Tech! We develop a general framework for training deep neural networks for closed-loop state feedback control of open quantum systems. https://t.co/TTH495EYLn

Comments+questions appreciated!

[DeWeese Lab @DeWeeseLab]

In our recent paper (https://t.co/ZgjNtZUi1c), we derived a first-principles theory of neural network generalization. We've now distilled the high-level takeaways into a short blog post (https://t.co/msHvqCRFGj). Check it out if you're interested in NN generalization!

[DeWeese Lab @DeWeeseLab]

We’re thrilled to announce our new paper, in which we derive and test a ✨first-principles theory of generalization in deep learning!✨ We affectionately call it the Theory of Eigenlearning. 🧵⤵

https://t.co/ZgjNtZUi1c