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Fermi-Hubbard 2D cuprate series, part 6: 6×6 tensor baseline, IBM diagnostics, and Fire Opal Fez

Posted on July 4, 2026 by
English | 2D project page | 1D project page | Previous

The 6x6 step is the first 72-qubit point in this 2D series. It is the same headline lattice size as the external Google/Willow 2D Hubbard context, but it should not be read as the same level of physical validation.

In this series, the 6×6 run is a diagnostic scale test:

  • can the 72-qubit circuit be built and submitted;
  • can the same observables be compared against a tensor baseline;
  • does readout correction repair the main error modes;
  • does the result remain in the right particle sector;
  • is Fire Opal available for the same route?

The current answer is mixed. The IBM run completed and was compared against an MPS circuit baseline. The local baselines agree well with each other. The IBM hardware output is much farther away. A matching 6×6 Fire Opal qelib fallback on ibm_fez has now completed and has been compared against MPS chi32. The separate ibm_marrakesh fallback remains a separate pending route.

Target

The 6×6 diagnostic uses:

item value
lattice 6x6
sites / qubits 36 / 72
holes / doping 4 / 0.111111
expected sector N_up = N_down = 16
parameters U/t = 8, t'/t = -0.25
circuit family number_preserving_t_only
step / dt / time 1 / 0.1 / 0.1
backend ibm_marrakesh

This is still a shallow early-time circuit. It is not a full measurement of off-diagonal d-wave pairing, and it is not a material-level cuprate claim.

MPS tensor baseline

Exact diagonalization is not the right reference route at this size. For this step we use a quimb MPS simulation of the same shallow circuit family. That is important: the MPS baseline is not a different physical experiment. It is the same circuit family evaluated locally.

MPS convergence:

max bond observed max bond elapsed s occupation RMSE vs previous total charge total spin-z mean doublon
16 16 6.630 – 32.000000 0.000000 0.021662
32 32 62.604 0.002741 32.000000 0.000000 0.023625

The chi16 to chi32 difference is small on the measured occupation observables. For this short shallow step, MPS chi32 is a usable local reference.

Local baselines versus MPS

Before interpreting hardware, the local baselines should agree with the tensor reference. They do:

source reference charge RMSE spin-z RMSE doublon RMSE
TDHF mean-field MPS chi32 0.001003 0.001905 0.000682
Gaussian/free MPS chi32 0.001181 0.004429 0.001750
MPS chi16 MPS chi32 0.001034 0.005384 0.002231

This matters because it removes a common ambiguity. The large hardware error is not caused by TDHF, Gaussian/free, and MPS disagreeing wildly at step 1. The local references are close on these diagonal observables.

IBM hardware result

The IBM hardware run completed:

item value
job id d94cogcql68s73c9clg0
backend ibm_marrakesh
shots 1024
best layout seed 26
transpiled depth 759
two-qubit gates 2397
two-qubit depth 317

Summary against MPS chi32:

route profile charge RMSE spin-z RMSE doublon RMSE
IBM raw 0.332687 0.733615 0.167283
IBM readout-corrected 0.330085 0.731364 0.166579
TDHF mean-field 0.001003 0.001905 0.000682
Gaussian/free free-fermion 0.001181 0.004429 0.001750

Readout correction does not fix the main problem. The charge RMSE changes only slightly, and the spin-z RMSE remains very large.

The site-level summary shows the same issue:

profile total charge total spin-z mean abs spin-z mean doublon
MPS chi32 32.000000 0.000000 0.840386 0.023625
IBM raw 31.205078 -0.591797 0.226237 0.171224
IBM readout-corrected 31.153041 -0.455994 0.237755 0.168657

The total charge is not disastrous, but the spin pattern has collapsed and the doublon estimate is much too high. This is hardware noise and sector leakage showing up directly in the observables.

Particle-sector diagnostic

The intended sector is part of the model. For this 6×6 run it is N_up = N_down = 16.

route exact-sector fraction mean abs N_up error mean abs N_down error
IBM 0.018555 2.238281 2.238281
Fire Opal qelib fallback on ibm_fez 0.043945 not reported in summary not reported in summary

Only about 1.9 percent of IBM shots and 4.4 percent of Fez Fire Opal shots remain in the exact expected sector. That is the most important diagnostic number in this chapter. At this scale, the hardware can execute the job, but the measured distribution is not yet a clean physical distribution for the intended particle sector.

Fire Opal status

There are now three 6×6 Fire Opal routes in the local artifacts:

route action ids status note
abstract/native 2331687, 2331688 main failed QASM used reserved rzz gate name from qelib1.inc
qelib fallback on ibm_marrakesh 2331689, 2331690 pending left running
qelib fallback on ibm_fez 2331691, 2331692 success compared against MPS chi32

The qelib fallback was created to avoid the reserved-gate-name problem. Its local QASM check passes:

check value
contains rzz False
contains xx_plus_yy False
two-qubit count 312
two-qubit depth 10
circuit depth 25

This is a much shallower Fire Opal input than the IBM-transpiled hardware circuit. Fire Opal warned that the qelib circuit may already be pre-processed/transpiled, so performance gains may be limited. That is the cost of this fallback route.

Fez Fire Opal result

The Fez Fire Opal result is much better than direct IBM, but it is still far from the local tensor and mean-field baselines.

Summary against MPS chi32:

route profile charge RMSE spin-z RMSE doublon RMSE
Fire Opal Fez raw 0.127246 0.210454 0.116802
Fire Opal Fez readout-corrected 0.127916 0.210285 0.117542
IBM readout-corrected 0.330085 0.731364 0.166579

The site-level summary shows the same pattern:

profile total charge total spin-z mean abs spin-z mean doublon
MPS chi32 32.000000 0.000000 0.840386 0.023625
Fire Opal Fez raw 33.642578 0.447266 0.678385 0.098606
Fire Opal Fez readout-corrected 33.685489 0.456067 0.679056 0.098926
IBM readout-corrected 31.153041 -0.455994 0.237755 0.168657

The Fez result recovers much more spin-z structure than direct IBM. It also has a lower doublon error. But the total charge is high, the mean doublon is still about four times the MPS value, and the exact-sector survival is low.

Sector-conditioned Fez rows:

profile kept fraction charge RMSE spin-z RMSE doublon RMSE
exact sector 0.043945 0.114526 0.195952 0.085595
near sector L1 <= 1 0.187500 0.100592 0.176036 0.086749
near sector L1 <= 2 0.429688 0.102253 0.185340 0.095039

The near-sector rows improve the RMSE, which confirms that particle-sector leakage is a major error source. But the exact-sector row keeps only 45 shots out of 1024, so it is not standalone physical evidence.

Cross-size diagnostic summary

The current step-1 hardware comparison is:

lattice route reference charge RMSE spin-z RMSE doublon RMSE
3×3 IBM readout-corrected ED 0.137934 0.221699 0.045795
3×3 Fire Opal readout-corrected ED 0.044332 0.075335 0.028962
4×4 IBM readout-corrected MPS chi64 0.130838 0.190883 0.056986
4×4 Fire Opal readout-corrected MPS chi64 0.068299 0.097232 0.041630
6×6 IBM readout-corrected MPS chi32 0.330085 0.731364 0.166579
6×6 Fire Opal Fez readout-corrected MPS chi32 0.127916 0.210285 0.117542

The pattern is clear. Fire Opal improves the available 3×3 and 4×4 hardware results. The completed 6×6 Fire Opal Fez point is much better than the direct 6×6 IBM point, especially in spin-z, but it is still not close to the local MPS/TDHF/Gaussian baselines.

Interpretation boundary

The 6×6 result is useful, but only as a diagnostic:

  • the tensor baseline exists and is stable enough for this shallow step;
  • local TDHF, Gaussian/free, and MPS agree on the diagonal observables;
  • IBM hardware completed but is far from the MPS reference;
  • readout correction is not enough;
  • particle-sector survival is too low for a physical claim;
  • Fire Opal Fez improves the 6×6 route, but its exact-sector survival remains

too low for a physical claim.

So the next engineering target is not simply another larger run. It is a shallower 72-qubit route with better sector protection, followed by the same observable comparison against tensor baselines.

Artifacts

  • MPS report:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/mps_shallow_t_only_steps1/cuprate_2d_mps_report.md

  • IBM summary:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/ibm_hardware_steps1_shallow_t_only_best_layout/cuprate_2d_ibm_hardware_summary.md

  • observable comparison:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/observable_comparison_shallow_t_only_steps1_vs_mps_hardware/cuprate_2d_observable_comparison.md

  • Fire Opal qelib fallback status:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/fire_opal_qelib_fallback_status.md

  • Fire Opal qelib fallback Fez status:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/fire_opal_qelib_fallback_ibm_fez_preparation_status.md

  • Fire Opal Fez observable comparison:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/observable_comparison_shallow_t_only_steps1_vs_mps_qelib_fallback_ibm_fez/cuprate_2d_observable_comparison.md

  • Fire Opal Fez sector-conditioned report:

results_cuprate_2d/validation_ladder_steps1/cuprate_6x6_holes4_steps1/sector_conditioned_qelib_fallback_ibm_fez_vs_mps/sector_conditioned_report.md

English | 2D project page | 1D project page | Previous

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