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ENTROPIC CHARACTERISTICS OF QUANTUM CHANNELS AND THE ADDITIVITY PROBLEM. A. S. Holevo Steklov Mathematical Institute, Moscow. Introduction: quantum information theory The classical capacity of quantum channel Hierarchy of additivity conjectures Global equivalence
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ENTROPIC CHARACTERISTICS OF QUANTUM CHANNELS AND THE ADDITIVITY PROBLEM A. S. Holevo Steklov Mathematical Institute, Moscow
Introduction: quantum information theory • The classical capacity of quantum channel • Hierarchy of additivity conjectures • Global equivalence • Partial results
A brief history of quantum information theory INTRODUCTION
Information Theory • Born: middle of XX century, 1940-1950s (Shannon,…) • Concepts: random source, entropy, typicality, code, channel, capacity: • Tools: probability theory, discrete math, group theory,… • Impact: digital data processing, data compression, error correction,…
Quantum Information Theory • Born: second half of XX century Physics of quantum communication, 1950-60s (Gabor, Gordon, Helstrom,…): FUNDAMENTAL QUANTUM LIMITATIONS ON INFORMATIOM TRANSMISSION ? • Mathematical framework: 1970-80s
Quantum Information Theory The early age (1970-1980s) Understanding quantum limits • Concepts: random source, entropy, channel, capacity, coding theorem, …, entanglement • Tools:noncommutative probability, operator algebra, random matrices (large deviations)… • Implications: …,the upper bound for classical capacity of quantum channel: χ-capacity C ≤ Cχ An overview in the book “Statistical structure of quantum theory” (Springer, 2001)
Quantum Information Theory(“Quantum Shannon theory”) The new age (1990-2000s) From quantum limitations to quantum advantages • Q. data compression (Schumacher-Josza,…) • The quantum coding theorem for c-q channels: C = C χ (Holevo; Schumacher-Westmoreland) • Variety of quantum channel capacities/coding theorems (Shor, Devetak, Winter, Hayden,…) Summarized in recent book by Hayashi (Springer, 2006)
Additivity of channel capacity 11011010 01001011 MEMORYLESS CLASSICAL INFORMATION CLASSICAL INFORMATION encoding decoding ? ?
Quantum channel ρ ρ’ Completely positive (CP) map, Σ(H)→Σ(H’):
The χ-capacity ensemble average conditional output entropy output entropy
Separate encodings/separate decodings . . n . CLASSICAL INFORMATION CLASSICAL INFORMATION separate q. separate q. encodings decodings ACCESSIBLE (SHANNON) INFORMATION
Separate encodings/entangled decodings . . n . CLASSICAL INFORMATION CLASSICAL INFORMATION separate q. entangled encodings decodings HSW-theorem: χ - CAPACITY ! !
Entangled encodings/ entangled decodings . . n . CLASSICAL INFORMATION CLASSICAL INFORMATION entangled entangled encodings decodings The full CLASSICAL CAPACITY ? ?
- minimal output entropy - χ-capacity convex closure/ constrained χ-capacity/EoF HIERARCHY of ADDITIVITYCONJECTURES
The χ-capacity ensemble average conditional output entropy output entropy convex closure
Partial results • Qubit unital channel (King) • Entanglement-breaking channel (Shor) • Depolarizing channel (King) Lieb-Thirring inequality:
Recent work on special channels (2003-…) Alicki-Fannes; Datta-Fukuda-Holevo-Suhov; Giovannetti-Lloyd-Maccone-Shapiro-Yen; Hayashi-Imai-Matsumoto-Ruskai-Shimono; King-Nathanson-Ruskai; King-Koldan; Matsumoto-Yura; Macchiavello-Palma; Wolf-Eisert,… ALL ADDITIVE!
Transpose-depolarizing channel Numerical search for counterexamples
Breakthrough 2007 Multiplicativity breaks: • p>2, large d (Winter); • 1<p<2, large d (Hayden); • p=0, large d (Winter); p close to 0. Method: random unitary (non-constructive) It remains 0<p<1 and p=1 (the additivity!) ... And many other questions
of additivity conjectures (Shor, Audenaert-Braunstein, Matsumoto- Shimono-Winter, Pomeranski, Holevo-Shirokov) GLOBAL EQUIVALENCE
“Global” proofs involving Shor’s channel extensions Discontinuity of In infinite dimensions
THM Proof: Uses Shor’s trick: extension of the original channel which has capacity obtained by the Lagrange method with a linear constraint
Set of states is separable metric space, not • locally compact • Entropy is “almost always” infinite and everywhere discontinuous • BUT • Entropy is lower semicontinuous • Entropy is finite and continuous on “useful” compact subset of states (of bounded “mean energy”)
The χ-capacity ensemble average conditional output entropy output entropy Generalized ensemble (GE)=Borel probability measure on state space
THM In particular, for all Gaussian channels with energy constraints
Gaussian channels Canonical variables (CCR) Gaussian environment Gaussian states Gaussian states Energy constraint PROPFor arbitrary Gaussian channel with energy constraint an optimal generalized ensemble (GE) exists. CONJ Optimal GE is a Gaussian probability measure supported by pure Gaussian states with fixed correlation matrix. (GAUSSIAN CHANNELS HAVE GAUSSIAN OPTIMIZERS?) Holds for c-c, c-q, q-c Gaussian channels ------------------------------------------------------------
Complementary channels(AH, Matsumoto et al.,2005) Observation: additivity holds for very classical channels; for very quantum channels Example: