What can constant- and logarithmic-depth STP compute?
For constant or logarithmic STP depth, characterize decision power and classical sampling complexity under stated restrictions on the classical controller.
Discuss this questionFix polynomially many qubits initially in . A depth- protocol has layers of disjoint pairwise STP measurements; the pairs in a layer may depend on the entire preceding outcome record through uniform polynomial-time classical computation. With no postselection, determine the decision power at and , using completeness and soundness . Separately ask for classical sampling of the full outcome record within inverse-polynomial total variation error.
The main model counts quantum layers and permits polynomial-time classical control. It therefore already contains classical polynomial-time decision procedures. Comparisons with and require the separate total-depth model below. Geometry, input encoding, copy count, postselection, and output decoding must be fixed.
Why this is interesting
The quantum depth, interaction geometry, and amount of classical control are distinct resources. Keeping them separate may reveal useful upper and lower bounds.
Explicit variants
Total depth, including classical control
Define a uniform polynomial-size hybrid circuit with disjoint-pair STP layers and explicit classical AND/OR/NOT gates. Count the entire dependency depth, including feed-forward and final decoding. Compare bounded-fan-in logarithmic depth with unbounded-fan-in constant-depth classical control; do not grant threshold or parity gates without declaring them. No postselection.
A Majority benchmark
For odd , receive one copy of , with unknown , and . Using polynomially many mixed ancillas, decide with error at most . Is constant STP depth together with constant TOTAL classical-control depth sufficient? One STP layer plus logarithmic-depth bounded-fan-in classical decoding is a baseline.
A quantum spin threshold
Given one unknown -qubit state supported either on or on , determine STP depth as a function of and the sector separation. Specify retained output and copy access. A projective measurement that distinguishes only the two promised ranges must preserve coherence within each range. Reading the exact label and forgetting it can destroy that coherence.
Lower bounds native to STP
Develop light-cone, representation-theoretic, subsystem-spin martingale, or communication-cut bounds for an explicit STP task. Relate the chosen progress quantity to success probability and bound its change per layer or crossing measurement, allowing the declared classical feed-forward. Distinguish measurement depth from the total depth of the hybrid computation.
A place to start
Write exact tensor-network descriptions of the first few depth classes and identify a graph parameter that yields efficient classical simulation.
Related work
These works provide context and established results. They need not be the origin of this exact formulation.
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