Stable BSgate #248
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Stable BSgate #248
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Additional details and impacted files@@ Coverage Diff @@
## develop #248 +/- ##
===========================================
+ Coverage 77.41% 77.54% +0.13%
===========================================
Files 53 53
Lines 4325 4369 +44
===========================================
+ Hits 3348 3388 +40
- Misses 977 981 +4
... and 1 file with indirect coverage changes Continue to review full report in Codecov by Sentry.
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ryk-wolf
reviewed
Jun 12, 2023
sylviemonet
approved these changes
Jun 13, 2023
|
Note: we need another PR to fix the shape or cutoffs things as well. |
ryk-wolf
reviewed
Jun 14, 2023
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com>
Merged
ziofil
added a commit
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Jul 26, 2023
# Release 0.5.0 ### New features * Optimization callback functionalities has been improved. A dedicated `Callback` class is added which is able to access the optimizer, the cost function, the parameters as well as gradients, during the optimization. In addition, multiple callbacks can be specified. This opens up the endless possiblities of customizing the the optimization progress with schedulers, trackers, heuristics, tricks, etc. [(#219)](#219) * Tensorboard-based optimization tracking is added as a builtin `Callback` class: `TensorboardCallback`. It can automatically track costs as well as all trainable parameters during optimization in realtime. Tensorboard can be most conveniently viewed from VScode. [(#219)](#219) ```python import numpy as np from mrmustard.training import Optimizer, TensorboardCallback def cost_fn(): ... def as_dB(cost): delta = np.sqrt(np.log(1 / (abs(cost) ** 2)) / (2 * np.pi)) cost_dB = -10 * np.log10(delta**2) return cost_dB tb_cb = TensorboardCallback(cost_converter=as_dB, track_grads=True) opt = Optimizer(euclidean_lr = 0.001); opt.minimize(cost_fn, max_steps=200, by_optimizing=[...], callbacks=tb_cb) # Logs will be stored in `tb_cb.logdir` which defaults to `./tb_logdir/...` but can be customized. # VScode can be used to open the Tensorboard frontend for live monitoring. # Or, in command line: `tensorboard --logdir={tb_cb.logdir}` and open link in browser. ``` * Gaussian states support a `bargmann` method for returning the bargmann representation. [(#235)](#235) * The `ket` method of `State` now supports new keyword arguments `max_prob` and `max_photons`. Use them to speed-up the filling of a ket array up to a certain probability or *total* photon number. [(#235)](#235) ```python from mrmustard.lab import Gaussian # Fills the ket array up to 99% probability or up to the |0,3>, |1,2>, |2,1>, |3,0> subspace, whichever is reached first. # The array has the autocutoff shape, unless the cutoffs are specified explicitly. ket = Gaussian(2).ket(max_prob=0.99, max_photons=3) ``` * Gaussian transformations support a `bargmann` method for returning the bargmann representation. [(#239)](#239) * BSGate.U now supports method='vanilla' (default) and 'schwinger' (slower, but stable to any cutoff) [(#248)](#248) ### Breaking Changes * The previous `callback` argument to `Optimizer.minimize` is now `callbacks` since we can now pass multiple callbacks to it. [(#219)](#219) * The `opt_history` attribute of `Optimizer` does not have the placeholder at the beginning anymore. [(#235)](#235) ### Improvements * The math module now has a submodule `lattice` for constructing recurrence relation strategies in the Fock lattice. There are a few predefined strategies in `mrmustard.math.lattice.strategies`. [(#235)](#235) * Gradients in the Fock lattice are now computed using the vector-jacobian product. This saves a lot of memory and speeds up the optimization process by roughly 4x. [(#235)](#235) * Tests of the compact_fock module now use hypothesis. [(#235)](#235) * Faster implementation of the fock representation of `BSgate`, `Sgate` and `SqueezedVacuum`, ranging from 5x to 50x. [(#239)](#239) * More robust implementation of cutoffs for States. [(#239)](#239) * Dependencies and versioning are now managed using Poetry. [(#257)](#257) ### Bug fixes * Fixed a bug that would make two progress bars appear during an optimization [(#235)](#235) * The displacement of the dual of an operation had the wrong sign [(#239)](#239) * When projecting a Gaussian state onto a Fock state, the upper limit of the autocutoff now respect the Fock projection. [(#246)](#246) * Fixed a bug for the algorithms that allow faster PNR sampling from Gaussian circuits using density matrices. When the cutoff of the first detector is equal to 1, the resulting density matrix is now correct. ### Documentation ### Contributors [Filippo Miatto](https://github.com/ziofil), [Zeyue Niu](https://github.com/zeyueN), [Robbe De Prins](https://github.com/rdprins), [Gabriele Gullì](https://github.com/ggulli), [Richard A. Wolf](https://github.com/ryk-wolf)
Merged
sduquemesa
added a commit
that referenced
this pull request
Jul 27, 2023
# Release 0.5.0 ### New features * Optimization callback functionalities has been improved. A dedicated `Callback` class is added which is able to access the optimizer, the cost function, the parameters as well as gradients, during the optimization. In addition, multiple callbacks can be specified. This opens up the endless possiblities of customizing the the optimization progress with schedulers, trackers, heuristics, tricks, etc. [(#219)](#219) * Tensorboard-based optimization tracking is added as a builtin `Callback` class: `TensorboardCallback`. It can automatically track costs as well as all trainable parameters during optimization in realtime. Tensorboard can be most conveniently viewed from VScode. [(#219)](#219) ```python import numpy as np from mrmustard.training import Optimizer, TensorboardCallback def cost_fn(): ... def as_dB(cost): delta = np.sqrt(np.log(1 / (abs(cost) ** 2)) / (2 * np.pi)) cost_dB = -10 * np.log10(delta**2) return cost_dB tb_cb = TensorboardCallback(cost_converter=as_dB, track_grads=True) opt = Optimizer(euclidean_lr = 0.001); opt.minimize(cost_fn, max_steps=200, by_optimizing=[...], callbacks=tb_cb) # Logs will be stored in `tb_cb.logdir` which defaults to `./tb_logdir/...` but can be customized. # VScode can be used to open the Tensorboard frontend for live monitoring. # Or, in command line: `tensorboard --logdir={tb_cb.logdir}` and open link in browser. ``` * Gaussian states support a `bargmann` method for returning the bargmann representation. [(#235)](#235) * The `ket` method of `State` now supports new keyword arguments `max_prob` and `max_photons`. Use them to speed-up the filling of a ket array up to a certain probability or *total* photon number. [(#235)](#235) ```python from mrmustard.lab import Gaussian # Fills the ket array up to 99% probability or up to the |0,3>, |1,2>, |2,1>, |3,0> subspace, whichever is reached first. # The array has the autocutoff shape, unless the cutoffs are specified explicitly. ket = Gaussian(2).ket(max_prob=0.99, max_photons=3) ``` * Gaussian transformations support a `bargmann` method for returning the bargmann representation. [(#239)](#239) * BSGate.U now supports method='vanilla' (default) and 'schwinger' (slower, but stable to any cutoff) [(#248)](#248) ### Breaking Changes * The previous `callback` argument to `Optimizer.minimize` is now `callbacks` since we can now pass multiple callbacks to it. [(#219)](#219) * The `opt_history` attribute of `Optimizer` does not have the placeholder at the beginning anymore. [(#235)](#235) ### Improvements * The math module now has a submodule `lattice` for constructing recurrence relation strategies in the Fock lattice. There are a few predefined strategies in `mrmustard.math.lattice.strategies`. [(#235)](#235) * Gradients in the Fock lattice are now computed using the vector-jacobian product. This saves a lot of memory and speeds up the optimization process by roughly 4x. [(#235)](#235) * Tests of the compact_fock module now use hypothesis. [(#235)](#235) * Faster implementation of the fock representation of `BSgate`, `Sgate` and `SqueezedVacuum`, ranging from 5x to 50x. [(#239)](#239) * More robust implementation of cutoffs for States. [(#239)](#239) * Dependencies and versioning are now managed using Poetry. [(#257)](#257) ### Bug fixes * Fixed a bug that would make two progress bars appear during an optimization [(#235)](#235) * The displacement of the dual of an operation had the wrong sign [(#239)](#239) * When projecting a Gaussian state onto a Fock state, the upper limit of the autocutoff now respect the Fock projection. [(#246)](#246) * Fixed a bug for the algorithms that allow faster PNR sampling from Gaussian circuits using density matrices. When the cutoff of the first detector is equal to 1, the resulting density matrix is now correct. ### Documentation ### Contributors [Filippo Miatto](https://github.com/ziofil), [Zeyue Niu](https://github.com/zeyueN), [Robbe De Prins](https://github.com/rdprins), [Gabriele Gullì](https://github.com/ggulli), [Richard A. Wolf](https://github.com/ryk-wolf) --------- Co-authored-by: Sebastián Duque Mesa <675763+sduquemesa@users.noreply.github.com> Co-authored-by: JacobHast <jacobhastrup@gmail.com> Co-authored-by: elib20 <53090166+elib20@users.noreply.github.com> Co-authored-by: Luke Helt <31250931+heltluke@users.noreply.github.com> Co-authored-by: zeyueN <48225584+zeyueN@users.noreply.github.com> Co-authored-by: Robbe De Prins <52749580+rdprins@users.noreply.github.com> Co-authored-by: Robbe De Prins (UGent-imec) <Robbe.DePrins@UGent.be> Co-authored-by: Yuan <16817699+sylviemonet@users.noreply.github.com> Co-authored-by: Ryk <47638463+ryk-wolf@users.noreply.github.com> Co-authored-by: Gabriele Gullì <120967042+ggulli@users.noreply.github.com>
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Context:
BSgate is unstable for high Fock cutoff.
Description of the Change:
Implements an alternative method to calculate the BS and exposes it like so:
Benefits:
Slower but stable method to compute the BS Fock amplitudes to any cutoff