Still a couple of weeks left to apply for a tenure-track position @EPFL in theory of condensed matter and interacting quantum matter. Great conditions and environment, take a look:

“Heuristic” built modern computational physics: Monte Carlo, simulated annealing, DMRG, density functionals, neural networks... Pragmatic approaches that advance our understanding of Nature.

Some theoretically minded colleagues call our computational methods “heuristic,” often implying disapproval. I embrace heuristics — from the Greek heuriskein, “to find, to discover” — as the art of pragmatically advancing what can be simulated.

I have a new opening for several funded PHD positions in my group @cqs_lab at @EPFL. If you are a talented, motivated student, please apply here https://t.co/12fJ1P1vhT. I am especially looking to hire in scientific ML applications/NQS; not in quantum computing.

A hybrid quantum-classical 𝘈𝘯𝘴𝘢𝘵𝘻 simulates many-body dynamics by augmenting Trotterized quantum circuits with a trainable classical method, enabling Trotter error mitigation and scalable, SWAP-free execution. @GianGentinetta @frmetz @gppcarleo https://t.co/k0vBFKh7Un

Blog post: "Actually, you can't test if quantum uses complex numbers" https://t.co/YjClN67xcg I doom the concept of that 2021 Nature paper by showing how to compile any distributed quantum protocol into real-only gates while preserving locality.

I am looking for a talented postdoc to join my group @EPFL @cqs_lab. Goal is to develop and apply state-of-the-art neural quantum states for electronic structure and related applications. Position to be filled soon, excellent conditions! Apply:

Fresh in @NaturePhysics from @cqs_lab @epfl! Led by Linda Mauron, Zakari Denis & Jannes Nys: we predict topological ent. entropy in Rydberg simulators via tVMC. Surprisingly, we find RVB-like properties without the expected topological entropy signatures.

A rumbling beneath China is rising—the underground Church is about to erupt. Watch the broadcast with Hank Kunneman

We have an opening @EPFL_en for a Condensed Matter/ Interacting Quantum Matter **theorist**, at our Physics Institute. Appointment is at the level of the tenure track assistant professor, with generous support and excellent conditions. DM for more info. https://t.co/VlHrmTPNJ5

Thrilled to share our latest paper https://t.co/5iLsAHm0p7 where we formalize VMC for multiple wave function optimization building on the excited state framework of @pfau et al. ( https://t.co/I1mPMPyXiA…). With D. Hendry and @gppcarleo.

Excited to share our latest quantum chemistry preprint @cqs_lab, the result of the hard work of Clemens Giuliani, https://t.co/Cnfg8eCrvP. We use a "simple" variational wavefunction composed of a few hundred optimized non-orthogonal Slater determinants and show that it achieves

We provide a classical simulation of DWave quantum "s-word" paper. Here it is https://t.co/IEivJNMnid , great work by Linda Mauron @cqs_lab, check it out! Our findings are in line with the other pre-print from @FlatironInst @MStoudenmire that just came out, but with a very

Check out our new work with A. F. Mello, M. Collura and @gppcarleo on the first scalable method to compute non-stabilizerness/magic with Neural Quantum States (NQS) https://t.co/5JksfPVCfE. 🪄🧠

Most importantly, you can download these models for free and have state-of-the-art pre trained wave functions that work on many problems ! https://t.co/p0NGIofvFN Many thanks to @ll_viteritti of @EPFL_en @cqs_lab and @riccardorende of @Sissaschool for taking this to the finish

In the case of disordered models P(gamma) is naturally the distribution over disorder, however it can be anything meaningful, for example the distribution of couplings in a generalized long-range Heisenberg model or even the lattice structure underlying a given hamiltonian. (4/5)

The general idea is to minimize the ensemble energy over a suitable distribution of Hamiltonian parameters P(gamma). The wave function (a transformer) depends on the Hamiltonian, and generalizes across many instances of different Hamiltonians. We give a version of SR specialized

These models allows for applications that are hard to do with the standard framework, e.g.: 1. Automatic ensemble averages for hamiltonians with disorder 2. Computing fidelity susceptibility for automatic, and from first-principles, detection of phase transitions 3. Fine tuning

Our work on Foundation Neural Quantum States finally out: https://t.co/eXxlLoKcOf. These are generalized NQS that work for many hamiltonians: think of a general solver working for many ground-state problems! Pre-trained models ready for fine tuning are available here

Looking for a talented postdoc to join my group @cqs_lab @EPFL_en! 🇨🇭 Research Topics Include: Neural Quantum States, Many-Body Systems, Ab-Initio & Quantum Chemistry...etc Start: Fall 2025, excellent conditions Apply:

Can’t beat them? Connect your broker to trade like them.

For the french-speaking friends: an article in @lemondefr "AI versus quantum computing : a very physical fight!" also featuring excerpts from an interview I had with David Larousserie https://t.co/hFxnUNc9qq (needs a subscription to Le Monde)