Recognition: unknown
Tight Entropic Uncertainty Relations
Pith reviewed 2026-05-10 14:55 UTC · model grok-4.3
The pith
A new parameter s allows a tighter state-independent lower bound on the sum of Shannon entropies for any incompatible quantum observables A and B.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
Entropic uncertainty relations H(A)+H(B)≥γ give a nonzero lower bound γ to the sum of the Shannon entropies H of the outcome probabilities of incompatible observables A and B. They are better than the variance-based uncertainty relations because they only depend on the Born statistics of the outcomes and not on the outcomes themselves, and because bounds γ typically are state independent. Here we provide a state-independent lower bound γ_s that is better than the textbook Maassen-Uffink bound and, in the limit of the parameter s→2, becomes asymptotically tight for all A,B. The bound can be extended to Renyi entropies.
What carries the argument
The parameterized state-independent lower bound γ_s on the entropy sum, constructed to exceed the Maassen-Uffink value while approaching the true minimum as s tends to 2.
If this is right
- For every pair of incompatible observables the sum of Shannon entropies is bounded below by a number strictly larger than the Maassen-Uffink value.
- As the parameter s approaches 2 the bound γ_s converges to the smallest entropy sum that can ever be realized by any state.
- The identical construction supplies improved lower bounds when Rényi entropies replace Shannon entropies.
- The bound remains valid without reference to any particular quantum state or to the explicit form of the observables beyond their incompatibility.
Where Pith is reading between the lines
- Because the bound is asymptotically tight, the value at s=2 may serve as a benchmark against which future exact uncertainty relations can be tested.
- The construction may be applied to any pair of observables once their outcome probability distributions are known, without needing additional state-dependent information.
Load-bearing premise
The tighter bound γ_s follows from the standard definitions of Shannon and Rényi entropies together with the mutual incompatibility of the observables A and B.
What would settle it
Compute the greatest lower bound on H(A) + H(B) over all quantum states for any chosen incompatible pair A and B; if that value lies below γ_s for any such pair, the claimed improvement is false.
Figures
read the original abstract
Entropic uncertainty relations $H(A)+H(B)\geqslant \gamma$ give a nonzero lower bound $\gamma$ to the sum of the Shannon entropies $H$ of the outcome probabilities of incompatible observables $A$ and $B$. They are better than the variance-based uncertainty relations because they only depend on the Born statistics of the outcomes and not on the outcomes themselves, and because bounds $\gamma$ typically are state independent. Here we provide a state-independent lower bound $\gamma_s$ that is better than the textbook Maassen-Uffink bound and, in the limit of the parameter $s\to 2$, becomes asymptotically tight for all $A,B$. The bound can be extended to Renyi entropies.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript claims to derive a state-independent lower bound γ_s on the sum of Shannon entropies H(A) + H(B) for incompatible observables A and B. This bound is asserted to be strictly better than the Maassen-Uffink bound for finite values of the parameter s, and to become asymptotically tight for all pairs of observables as s approaches 2. The result is extended to Rényi entropies as well.
Significance. Should the derivation prove correct, this work offers a meaningful advancement in entropic uncertainty relations by providing a family of improved, state-independent bounds with a desirable asymptotic tightness property. Such bounds are valuable in quantum information science for tasks involving measurement incompatibility, and the extension to Rényi entropies broadens the applicability. The approach relies on standard entropy definitions and observable incompatibility, which is a strength in terms of generality.
minor comments (2)
- The abstract would benefit from a concise statement of the key technical step used to construct γ_s, to help readers immediately grasp how the improvement over Maassen-Uffink is achieved.
- Notation for the family of bounds and the limit s → 2 should be introduced with a short reminder of the relevant entropy definitions in the main text to improve readability for non-specialists.
Simulated Author's Rebuttal
We thank the referee for their positive evaluation of the manuscript and the recommendation for minor revision. We appreciate the recognition that the parameterized bound γ_s provides a strict improvement over the Maassen-Uffink relation for finite s while becoming asymptotically tight for all observable pairs as s approaches 2, together with the extension to Rényi entropies. This is acknowledged as a meaningful contribution to state-independent entropic uncertainty relations in quantum information.
Circularity Check
No significant circularity; derivation is self-contained
full rationale
The paper derives a family of state-independent lower bounds γ_s on H(A) + H(B) that strictly improve the Maassen-Uffink bound for finite s while recovering asymptotic tightness for every pair of observables as s → 2 (with a parallel statement for Rényi entropies). The abstract and available text invoke only the standard definitions of Shannon/Rényi entropy together with the incompatibility of A and B; no fitted parameters are renamed as predictions, no self-citation chain is load-bearing for the central claim, and no ansatz or uniqueness theorem is smuggled in. The explicit construction of γ_s is presented as an independent mathematical improvement, not a re-expression of its own inputs. This is the normal, non-circular case.
Axiom & Free-Parameter Ledger
axioms (2)
- standard math Standard definitions of Shannon and Rényi entropies for discrete probability distributions
- domain assumption Observables A and B are incompatible (non-commuting) quantum measurements
Reference graph
Works this paper leans on
-
[1]
P. J. Coles, M. Berta, M. Tomamichel, S. Wehner, En- tropic uncertainty relations and their applications, Rev. Mod. Phys.89, 015002 (2017)
2017
-
[2]
Wehner, A
S. Wehner, A. Winter Entropic uncertainty relations—a survey, New J. Phys.12, 025009 (2010)
2010
-
[3]
Quantum Uncertainty and Entropy
G. Chesi, L. Maccone, Quantum Uncertainty and En- tropy, Reference Module in Materials Science and Mate- rials Engineering (Elsevier, 2026),https://doi.org/10. 1016/B978-0-443-33965-3.00002-X; arXiv:2604.09384
work page internal anchor Pith review Pith/arXiv arXiv 2026
-
[4]
Heisenberg, The physical content of quantum kine- 4 matics and mechanics, in J
W. Heisenberg, The physical content of quantum kine- 4 matics and mechanics, in J. A. Wheeler, W. H. Zurek, (eds.) Quantum Theory and Measurement, 62–84 (Princeton UP, Princeton, NJ, 1983), originally pub- lished in Z. Phys.,43, 172 (1927)
1983
-
[5]
H. P. Robertson, The Uncertainty Principle, Phys. Rev. 34, 163 (1929)
1929
-
[6]
Hirschmann, A note on entropy
I.I. Hirschmann, A note on entropy. Am. J. Math.79, 152 (1957)
1957
-
[7]
Bialynicki-Birula, J
I. Bialynicki-Birula, J. Miycielski, Uncertainty relations for information entropy in wave mechanics. Commun. Math. Phys.44, 129 (1975)
1975
-
[8]
Deutsch, Uncertainty in quantum measurements, Phys
D. Deutsch, Uncertainty in quantum measurements, Phys. Rev. Lett.50, 631 (1983)
1983
-
[9]
Maassen, J.B.M
H. Maassen, J.B.M. Uffink, Generalized entropic uncer- tainty relations, Phys. Rev. Lett.60, 1103 (1988)
1988
-
[10]
Coles, M
P.J. Coles, M. Piani, Improved entropic uncertainty rela- tions and information exclusion relations, Phys. Rev. A 89, 022112 (2014)
2014
-
[11]
Rudnicki, Z
L. Rudnicki, Z. Puchala, K. ˙Zyczkowski, Strong ma- jorization entropic uncertainty relations, Phys. Rev. A 89, 052115 (2014)
2014
-
[12]
D. W. Boyd, The power method forℓ p norms. Linear Algebra and its Applications,9(2), 95 (1974)
1974
-
[13]
N. J. Higham, Estimating the matrixp-norm. Nu- merische Mathematik,62(1), 539 (1992); N.J. Higham, Estimating the matrixp-norm. Numer. Math.62, 539 (1992)
1992
-
[14]
Zozor, G.M
S. Zozor, G.M. Bosyk, M. Portesi, On a generalized en- tropic uncertainty relation in the case of the qubit, J. Phys. A46, 46530 (2013)
2013
-
[15]
˙Zyczkowski, P
K. ˙Zyczkowski, P. Horodecki, A. Sanpera, M. Lewenstein, Volume of the set of separable states, Phys. Rev. A58, 883 (1998)
1998
-
[16]
Pozniak, K
M. Pozniak, K. ˙Zyczkowski, M. Kus, Composed ensem- bles of random unitary matrices, J. Phys. A: Math. Gen. 311059 (1998)
1998
-
[17]
R´ enyi, On measures of information and entropy, in Proceedings of the fourth Berkeley Symposium on Math- ematics, Statistics and Probability 1960, pg.547 (1961)
A. R´ enyi, On measures of information and entropy, in Proceedings of the fourth Berkeley Symposium on Math- ematics, Statistics and Probability 1960, pg.547 (1961)
1960
-
[18]
Ozawa, N
M. Ozawa, N. Javerzat, Perspective on Physical Interpre- tations of R´ enyi Entropy in Statistical Mechanics, Euro- phys. Lett.147, 11001 (2024)
2024
-
[19]
Dunford, J.T
N. Dunford, J.T. Schwartz, Linear operators, Parts I and II, (Wiley-Interscience, 1958)
1958
-
[20]
Sorkin, Quantum Mechanics as Quantum Measure Theory, Mod
R.D. Sorkin, Quantum Mechanics as Quantum Measure Theory, Mod. Phys. Lett. A9, 3119 (1994)
1994
-
[21]
power method forℓ p norms
U. Sinha, C. Couteau, T. Jennewein, R. Laflamme, G. Weihs, Ruling out multi-order interference in quantum mechanics, Science329, 418 (2010). Appendix A: NONLINEAR POWER ITERA TION METHOD In this appendix we review the nonlinear power itera- tion method, also referred to in the literature as “power method forℓ p norms” or “nonlinear power method” [12, 13]....
2010
-
[22]
Generate a random complex vector (seed)u (k) ∈C d withk= 0
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[23]
Normalize it to create the vectorv (k) =u (k)/∥u(k)∥p
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[24]
Apply the operatorU:w (k) j =P i Ujiv(k) i
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[25]
Calculate the norm for thek-th iteration as∥w (k)∥s′
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[26]
Rescale it asx (k) j =w (k) j |w(k) j |s′−2, wheres ′ −2>0, sinces ′ >2
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[27]
Apply the adjoint to go back:y i =P j U ∗ jixj
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[28]
Rescale it again asz (k) j =y (k) j |y(k) j |s′−2
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[29]
Iterate from step 2, choosingv (k+1) =z (k), and stop when the iteration converges: ∥w(k+1)∥s′ − ∥w(k)∥s′ < ϵ, withϵsome (small) accuracy parameter
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[30]
This is needed because the algorithm converges to alocal maximum and one needs to repeat it multiple times with Nseeds random seeds to find the global maximum
Repeat the whole procedureN seeds times from step 1 and select the largestLof the obtained norms∥w (k)∥s′. This is needed because the algorithm converges to alocal maximum and one needs to repeat it multiple times with Nseeds random seeds to find the global maximum. The final quantityLis the estimated norm∥U∥ s→s′. A good check to see whetherN seeds is su...
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