Matt Beach

machine learning, quantum computing, software development

[Christian Weedbrook @_cweedbrook]

New paper from the @XanaduAI and #AWS #Braket teams! @3rdquantization @DWierichs @awscloud #quantum

https://t.co/V9tGvYMSuG

[PennyLane @PennyLaneAI]

Exciting new Quantum Computing Challenge from @BMWGroup and @awscloud, including a QML-focused challenge😃🙌

Great opportunity for PennyLane users to show the world what they can do👩‍💻

[Hsin-Yuan Huang (Robert) @RobertHuangHY]

❓Can classical machine learning models solve challenging problems in physics that no classical algorithms could solve?

We prove the affirmative (for quantum many-body problems) in https://t.co/DqhbpBLdGL
with @RichardKueng, @giactorlai, @victorvalbert, @preskill [🧵1/13]

[Roger Melko @rgmelko]

The best of both words: academia (@Perimeter, @UWaterloo @QuantumIQC ) and industry (@awscloud, @1QB_IT) collaborating together to search for new physics on a trapped ion quantum computer. Made possible by #PIQuIL

[Alejandro Perdomo-Ortiz @aperdomoortiz]

Don’t miss TODAY our panel on "QML in Industry" at #QTML2020 and the opportunity to ask experts your questions Live! We are fortunate to have researchers from major hardware and software companies. YouTube Live or Webinar available. Spread the word! ;) @ZapataComputing @rgmelko

[Timothy Nguyen @IAmTimNguyen]

Understanding deep learning requires rethinking datasets: Train on 1K of these noise images and outperform 1K natural CIFAR-10 images (45.0% vs 35.4% test acc). Find out how, along with how to compress datasets, using our novel meta-learning algorithm KIP: https://t.co/ZzJd2JMpaF

[Giacomo Torlai @giactorlai]

Happy to introduce PastaQ, a Julia package for simulating and benchmarking near-term #quantum computers, using a combination of tensor networks and #MachineLearning algorithms.

https://t.co/LEeoAOUjKQ

Really fun project with Matt Fishman @FlatironCCQ, supported by @SimonsFdn.

[Isaac Kim @Isaac__kim]

I think it's fair to say that we now have a nontrivial solution to the quantum (and classical) marginal problem. The solutions are actually quite physical!
https://t.co/7y4aMO7Eva
https://t.co/4EUuf2VvnQ

[Quantum @quantumjournal]

Fresh in Quantum: Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design by Xiu-Zhe Luo, Jin-Guo Liu, Pan Zhang, and Lei Wang https://t.co/QxyA0zgLwq

[ITensor @ITensorLib]

ITensor power user and developer Katharine Hyatt will speak at JuliaCon tomorrow on "Accelerating Tensor Computations in Julia on the GPU" regarding her work on ITensorsGPU.jl https://t.co/Syd3QBsbx4

[Roger Luo 罗秀哲 @rogerluorl18]

Basic circuit simplification based on ZX calculus is now available in #JuliaLang as our @gsoc project this summer. It will power our compiler as a native implementation of the PyZX in #JuliaLang , check Chen Zhao's blog post: https://t.co/c39MDu7ymw

[Yudong Cao @caoyudong]

New papers on squeezing the most quantum speedup out of a noisy quantum device for amplitude estimation: https://t.co/I9UA0v3fH0
https://t.co/1ISEkURxtP
We will be hosting a live discussion about this next week: https://t.co/G8rfSSjWwm

[Giacomo Torlai @giactorlai]

Just out on @PhysRevResearch, a protocol to lower measurement overhead in #quantum simulations by integrating the hardware with #NeuralNetworks, with applications in quantum chemistry. @gppcarleo @A_Mezzacapo gmazzola, @FlatironCCQ @IBMResearch

https://t.co/NcChK5KBQ3

[Ion busters @Ion_busters]

Universal Quantum (@universalquant) is out of stealth mode today announcing £3.6m in early funding!

Spinning out of @IQT_group, they will use #IonTraps to make scalable #QuantumComputers.

Disclosure - one of the ionbusters is with Universal Quantum.

https://t.co/KkQ4ptFL6H

[ITensor @ITensorLib]

julia> ]
pkg> add ITensors

[ITensor @ITensorLib]

Successful run of the extended Hubbard model with ITensors.jl (Julia port of ITensor). We are getting very close to version 0.1 and officially registering the package.

https://t.co/Z5Jh4EFWiU

[Isaac Tamblyn @itamblyn]

Accepted and to appear in CanadianAI

https://t.co/BGCHr5wTR8

[evolvingstuff @evolvingstuff]

Transformers as Soft Reasoners over Language

"we explore whether transformers can similarly learn to reason (or emulate reasoning), but using rules expressed in language, thus bypassing a formal representation."

https://t.co/5uib4bRPud
Datasets and demo: https://t.co/wKxgdCpHiE

[Roger Melko @rgmelko]

Announcing the @SimonsFdn school on Ultra Quantum Matter, August 4-14 @Perimeter. Apply now
https://t.co/dLQXRpCWqb