Abstract
Among the predictive hidden Markov models that describe a given stochastic process, the \(\epsilon \text{-machine }\) is strongly minimal in that it minimizes every Rényi-based memory measure. Quantum models can be smaller still. In contrast with the \(\epsilon \text{-machine }\) ’s unique role in the classical setting, however, among the class of processes described by pure-state hidden quantum Markov models, there are those for which there does not exist any strongly minimal model. Quantum memory optimization then depends on which memory measure best matches a given problem’s circumstance.
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Notes
It is worthwhile to note an ambiguity when comparing distributions defined over different numbers of elements. There are generally two standards for such comparisons that depend on application. In the resource theory of informational nonequilibrium [20], one compares distributions over different numbers of events by “squashing” their Lorenz curves so that the x-axis ranges from 0 to 1. Under this comparison, the distribution \(\mathbf {p}_3 = (1,0,0)\) has more informational nonequilibrium than \(\mathbf {p}_2=(1,0)\). In the following, however, we adopt the standard of simply extending the smaller distribution by adding events of zero probability. In this case, \(\mathbf {p}_3\) and \(\mathbf {p}_2\) are considered equivalent. This choice is driven by our interest in the Rényi entropy costs and not in the overall nonequilibrium. (The latter is more naturally measured by Rényi negentropies\(\bar{H}_\alpha \left( \mathbf {p}\right) = \log n - {H}_\alpha \left( \mathbf {p}\right) \), where n is the number of events.)
The following uses the words machine and model interchangeably. Machine emphasizes the simulative nature of the implementation; model emphasizes the predictive nature.
A process is stationary if it is time-invariant.
The definition here using Kraus operators can be equivalently formulated in terms of a unitary quantum system [34]. While that alternate definition is more obviously physical, our formulation makes the classical parallels explicit.
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Acknowledgements
The authors thank Fabio Anza, John Mahoney, Cina Aghamohammadi, and Ryan James for helpful discussions, as well as Felix Binder for clarifying suggestions. As a faculty member, JPC thanks the Santa Fe Institute and the Telluride Science Research Center for their hospitality during visits. This material is based upon work supported by, or in part by, John Templeton Foundation Grant 52095, Foundational Questions Institute Grant FQXi-RFP-1609, the U.S. Army Research Laboratory and the U. S. Army Research Office under Contract W911NF-13-1-0390 and Grant W911NF-18-1-0028, and via Intel Corporation support of CSC as an Intel Parallel Computing Center.
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SPL and JPC conceived of the project, developed the theory, and wrote the manuscript. SPL performed the calculations. JPC supervised the project.
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Appendix: Weak Minimality of \(\mathbf {D}_3\)
Appendix: Weak Minimality of \(\mathbf {D}_3\)
Here, we prove that \(\mathfrak {D}_3\) is the unique 2D representation of the 3-state MBW process. We show this by considering the entire class of 2D models and applying the completeness constraint.
We note that a pure-state quantum model of the 3-state MBW process must have three states \(\left| \eta _A\right\rangle \), \(\left| \eta _B\right\rangle \), and \(\left| \eta _C\right\rangle \), along with three dual states \(\left\langle \epsilon _A\right| \), \(\left\langle \epsilon _B\right| \), and \(\left\langle \epsilon _C\right| \) such that:
and
We list the available geometric symmetries that leave the final stationary state unchanged:
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1.
Phase transformation on each state, \(\left| \eta _x\right\rangle \mapsto e^{i\phi _x}\left| \eta _x\right\rangle \);
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2.
Phase transformation on each dual state, \(\left| \epsilon _x\right\rangle \mapsto e^{i\phi _x}\left| \epsilon _x\right\rangle \); and
-
3.
Unitary transformation \(\left| \eta _x\right\rangle \mapsto U\left| \eta _x\right\rangle \) and \(\left\langle \epsilon _x\right| \mapsto \left\langle \epsilon _x\right| U^\dagger \).
From these symmetries we can fix gauge in the following ways:
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1.
Set \(\left\langle 0|\eta _x\right\rangle \) to be real and positive for all x.
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2.
Set \(\phi _{AA}=\phi _{BB}=\phi _{CC}=0\).
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3.
Set \(\left\langle 0|\eta _A\right\rangle =0\) and set \(\left\langle 1|\eta _B\right\rangle \) to be real and positive.
These gauge fixings allow us to write:
for \(\alpha _B,\alpha _C\ge 0\), \(\beta _B=\sqrt{1-\alpha _B^2}\) and \(\beta _C=\sqrt{1-\alpha _C^2}\) and a phase \(\theta \).
That these states are embedded in a 2D Hilbert space means there must exist some linear consistency conditions. For some triple of numbers \(\mathbf {c}=(c_A, c_B, c_C)\) we can write:
Up to a constant, this triplet has the form:
Consistency requires that this relationship between vectors is preserved by the Kraus operator dynamic. Consider the matrix \(\mathbf {A}:=(A_{xy}) = \left( \left\langle \epsilon _x|\eta _y\right\rangle \right) \). The vector \(\mathbf {c}\) must be a null vector of \(\mathbf {A}\); i.e. \(\sum _y A_{xy}c_y=0\). This first requires that \(A_{xy}\) be degenerate. One way to enforce this is to check that the characteristic polynomial \(\det (\mathbf {A}-\lambda \mathbf {I}_3)\) has an overall factor of \(\lambda \). For simplicity, we compute the characteristic polynomial of \(\mathbf {A}\sqrt{6}\):
To have an overall factor of \(\lambda \), we need:
Typically, there will be several ways to choose phases to cancel out vectors, but in this case since the sum of the magnitudes of the complex terms is 8, the only way to cancel is at the extreme point where \(\phi _{AB}=-\,\phi _{BA}=\phi _1\), \(\phi _{BC}=-\,\phi _{CB}=\phi _2\), and \(\phi _{CA}=-\,\phi _{AC}=\phi _3\) and:
To recapitulate the results so far, \(\mathbf {A}\) has the form:
We now need to enforce that \(\sum _y A_{xy}c_y=0\). We have the three equations:
It can be checked that these are solved by:
Taking our formulation of the \(\mathbf {c}\) vector, we immediately have \(\beta _B=\beta _C=\beta \) (implying \(\alpha _B=\alpha _C=\alpha \)), \(\phi _2 = \theta \), and:
This means:
where we take \(-\pi \le \theta \le \pi \) and \(\mathrm {sgn}(\theta )\) is the sign of \(\theta \).
Note, however, that for \(-\frac{\pi }{3}< \theta < \frac{\pi }{3}\), we have \(|\csc (\theta )|> 1\), so these values are unphysical.
We see that all parameters in our possible states \(\left| \eta _x\right\rangle \), as well as all the possible transition phases, are dependent on the single parameter \(\theta \). To construct the dual basis, we start with the new forms of the states:
We note directly that we must have:
from how the dual states contract with \(\left| \eta _A\right\rangle \). These can be used with the contractions with \(\left| \eta _B\right\rangle \) to get:
It is quickly checked that these coefficients are consistent with the action on on \(\left| \eta _C\right\rangle \) by making liberal use of \(e^{-i\phi _3} =\alpha (1-e^{i\theta })\).
Recall that with the correct dual states, the Kraus operators take the form:
Completeness requires:
Define the vectors \(u_x = \left\langle \epsilon _x | 0\right\rangle \) and \(v_x = \left\langle \epsilon _x | 1\right\rangle \). One can check that the above relationship implies \(\sum _x u_x^*u_x = \sum _x v_x^*v_x = 1\) and \(\sum _x u_x v^*_x = 0\). However, for our model, it is straightforward (though a bit tedious) to check that:
Using the definitions of \(\alpha \), \(\beta \), and \(\phi _1\), the second equation can be simplified to:
This is unity only when \(\csc ^2\frac{\theta }{2}=1\), which requires that \(\theta = \pi \). This is, indeed, the model \(\mathfrak {D}_3\) that we have already seen.
This establishes that the only two-dimensional pure-state quantum model which reproduces the 3-state MBW process is the one with a nonminimal statistical memory \(S(\rho _\pi )\). This means there cannot exist a quantum representation of the 3-state MBW process that majorizes all other representations of the same. For, if it existed, it must be a two-dimensional model and also minimize \(S(\rho _\pi )\).
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Loomis, S.P., Crutchfield, J.P. Strong and Weak Optimizations in Classical and Quantum Models of Stochastic Processes. J Stat Phys 176, 1317–1342 (2019). https://doi.org/10.1007/s10955-019-02344-x
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DOI: https://doi.org/10.1007/s10955-019-02344-x