# PennyLane v0.10 Released

**URL:** <https://discuss.pennylane.ai/t/pennylane-v0-10-released/440>\
**Category:** PennyLane Development\
**Created:** [June 23, 2020, 5:04pm UTC](https://discuss.pennylane.ai/t/pennylane-v0-10-released/440 "2020-06-23T17:04:10Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![theodor](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/theodor/32/178_2.png) [@theodor](https://discuss.pennylane.ai/u/theodor)\
**Post date:** [June 23, 2020, 5:04pm UTC](https://discuss.pennylane.ai/t/pennylane-v0-10-released/440/1 "2020-06-23T17:04:10Z")

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Hi everyone! We’re very happy to announce the release of PennyLane version 0.10 🎆 🎊

**New and improved simulators** ⚡

- Use the new [default.qubit.tf](https://pennylane.readthedocs.io/en/stable/code/api/pennylane.plugins.default_qubit_tf.DefaultQubitTF.html) device, a quantum simulator written in TensorFlow, allowing simulated circuits to be trained faster via backpropagation

- Experiment with an upgraded [default.tensor plugin](https://pennylane.readthedocs.io/en/stable/code/api/pennylane.beta.plugins.DefaultTensor.html) that now features two different tensor network representations to be used: `"exact"` and `"mps"`

![default_qubit_tf_benchmark](https://canada1.discourse-cdn.com/flex012/uploads/pennylane/original/1X/c795d366e2dae5bcbf55bef442a1248c3c991e4b.png)

**New machine learning functionality and integrations** 🏗

- Convert a PennyLane QNode into a [TorchLayer](https://pennylane.readthedocs.io/en/latest/code/api/pennylane.qnn.TorchLayer.html), allowing for creation of quantum and hybrid models using the `torch.nn`

- Trade off extra computation for enhanced memory efficiency with the new “reversible” differentiation method which can be used in simulators

**New templates using broadcasting** ⚗

- Use the new `UCCSD`, `SingleExcitationUnitary`, and `DoubleExcitationUnitary` templates to create the Unitary Coupled-Cluster Singles and Doubles (UCCSD) ansatz and perform VQE-based quantum chemistry simulations using PennyLane-QChem

- Specify the Squared error loss function for circuits with trainable parameters using the `SquaredErrorLoss` class from the new `pennylane.qnn.cost` module

**Major upgrades to variable handling**

Mark if a variable is differentiable or not by using the new `pennylane.numpy.tensor` class and specifying the `requires_grad` attribute

**New plugin to complement the growing library of devices**

In addition to[@qiskit](https://twitter.com/qiskit),[@rigetti](https://twitter.com/rigetti) Forest,[@GoogleAI](https://twitter.com/GoogleAI) Cirq, etc., you can now access Alpine Quantum Technologies’ online ion-trap platform using PennyLane.

* * *

The full release notes are available at [Release notes — PennyLane 0.27.0 documentation](https://pennylane.readthedocs.io/en/stable/development/release_notes.html)

As always, this release would not have been possible without all the help from our contributors:

@Alain_Delgado_Gran, @antalszava , Jack Ceroni , @Maria_Schuld, Nicola Vitucci, @theodor, @josh, @nathan , @Tom_Bromley .

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**Author:** ![josh](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/josh/32/100_2.png) [@josh](https://discuss.pennylane.ai/u/josh)\
**Post date:** [June 24, 2020, 6:09am UTC](https://discuss.pennylane.ai/t/pennylane-v0-10-released/440/2 "2020-06-24T06:09:14Z")

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**Author:** ![josh](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/josh/32/100_2.png) [@josh](https://discuss.pennylane.ai/u/josh)\
**Post date:** [August 19, 2020, 5:05am UTC](https://discuss.pennylane.ai/t/pennylane-v0-10-released/440/3 "2020-08-19T05:05:43Z")

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